librarian-bots/model_cards_with_metadata · Datasets at Hugging Face

modelId stringlengths 5 139	author stringlengths 2 42	last_modified timestamp[us, tz=UTC]date 2020-02-15 11:33:14 2025-09-06 00:36:47	downloads int64 0 223M	likes int64 0 11.7k	library_name stringclasses 540 values	tags listlengths 1 4.05k	pipeline_tag stringclasses 55 values	createdAt timestamp[us, tz=UTC]date 2022-03-02 23:29:04 2025-09-06 00:36:27	card stringlengths 11 1.01M
nhoxinh/56074fa1-1876-44f5-9e04-4019f008f055	nhoxinh	2025-01-21T12:55:18Z	6	0	peft	[ "peft", "safetensors", "mistral", "axolotl", "generated_from_trainer", "base_model:unsloth/zephyr-sft", "base_model:adapter:unsloth/zephyr-sft", "license:apache-2.0", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-21T11:44:17Z	--- library_name: peft license: apache-2.0 base_model: unsloth/zephyr-sft tags: - axolotl - generated_from_trainer model-index: - name: 56074fa1-1876-44f5-9e04-4019f008f055 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/zephyr-sft bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 6bb273fb8d3c0253_train_data.json ds_type: json format: custom path: /workspace/input_data/6bb273fb8d3c0253_train_data.json type: field_input: condition field_instruction: drugName field_output: review format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: nhoxinh/56074fa1-1876-44f5-9e04-4019f008f055 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/6bb273fb8d3c0253_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: f44a8599-bd2c-4b24-9468-fb17670debf8 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: f44a8599-bd2c-4b24-9468-fb17670debf8 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details><br> # 56074fa1-1876-44f5-9e04-4019f008f055 This model is a fine-tuned version of [unsloth/zephyr-sft](https://huggingface.co/unsloth/zephyr-sft) on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.0659 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 7.8806 \| 0.0078 \| 200 \| 2.0659 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
Best000/601e1c9e-6e78-4c6c-83a7-ce96943576bf	Best000	2025-01-21T12:55:06Z	11	0	peft	[ "peft", "safetensors", "falcon", "axolotl", "generated_from_trainer", "custom_code", "base_model:fxmarty/really-tiny-falcon-testing", "base_model:adapter:fxmarty/really-tiny-falcon-testing", "license:mit", "region:us" ]	null	2025-01-21T12:54:41Z	--- library_name: peft license: mit base_model: fxmarty/really-tiny-falcon-testing tags: - axolotl - generated_from_trainer model-index: - name: 601e1c9e-6e78-4c6c-83a7-ce96943576bf results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: fxmarty/really-tiny-falcon-testing bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 4214a6acaa4ea6d5_train_data.json ds_type: json format: custom path: /workspace/input_data/4214a6acaa4ea6d5_train_data.json type: field_input: tags field_instruction: sentences field_output: NER_TAGS format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: Best000/601e1c9e-6e78-4c6c-83a7-ce96943576bf hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/4214a6acaa4ea6d5_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 7c1cea2e-e61e-4570-af77-6f76e74a258b wandb_project: Birthday-SN56-16-Gradients-On-Demand wandb_run: your_name wandb_runid: 7c1cea2e-e61e-4570-af77-6f76e74a258b warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # 601e1c9e-6e78-4c6c-83a7-ce96943576bf This model is a fine-tuned version of [fxmarty/really-tiny-falcon-testing](https://huggingface.co/fxmarty/really-tiny-falcon-testing) on the None dataset. It achieves the following results on the evaluation set: - Loss: 10.8839 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 43.6855 \| 0.0009 \| 1 \| 10.9245 \| \| 43.7175 \| 0.0028 \| 3 \| 10.9243 \| \| 43.7176 \| 0.0056 \| 6 \| 10.9227 \| \| 43.6932 \| 0.0084 \| 9 \| 10.8839 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
sergioalves/05618dee-ab92-4757-af73-12793dbaba30	sergioalves	2025-01-21T12:55:00Z	6	0	peft	[ "peft", "safetensors", "phi3", "axolotl", "generated_from_trainer", "custom_code", "base_model:microsoft/Phi-3-mini-128k-instruct", "base_model:adapter:microsoft/Phi-3-mini-128k-instruct", "license:mit", "region:us" ]	null	2025-01-21T12:44:20Z	--- library_name: peft license: mit base_model: microsoft/Phi-3-mini-128k-instruct tags: - axolotl - generated_from_trainer model-index: - name: 05618dee-ab92-4757-af73-12793dbaba30 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: microsoft/Phi-3-mini-128k-instruct bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 2285406178062357_train_data.json ds_type: json format: custom path: /workspace/input_data/2285406178062357_train_data.json type: field_input: code_before field_instruction: func_before field_output: code_after format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: 1 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: false hub_model_id: sergioalves/05618dee-ab92-4757-af73-12793dbaba30 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0001 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 75GiB max_steps: 30 micro_batch_size: 2 mlflow_experiment_name: /tmp/2285406178062357_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_hf output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: ad2f2b3d-aa0d-468c-9405-73b96cd163da wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: ad2f2b3d-aa0d-468c-9405-73b96cd163da warmup_steps: 10 weight_decay: 0.01 xformers_attention: true ``` </details><br> # 05618dee-ab92-4757-af73-12793dbaba30 This model is a fine-tuned version of [microsoft/Phi-3-mini-128k-instruct](https://huggingface.co/microsoft/Phi-3-mini-128k-instruct) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.7229 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0001 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_HF with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 30 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| No log \| 0.0020 \| 1 \| 0.7530 \| \| 2.7448 \| 0.0101 \| 5 \| 0.7507 \| \| 3.0068 \| 0.0202 \| 10 \| 0.7387 \| \| 2.7597 \| 0.0302 \| 15 \| 0.7309 \| \| 2.8839 \| 0.0403 \| 20 \| 0.7269 \| \| 2.7014 \| 0.0504 \| 25 \| 0.7234 \| \| 2.6363 \| 0.0605 \| 30 \| 0.7229 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
havinash-ai/5a51f800-f03b-497d-9dc7-c04b99c41fb6	havinash-ai	2025-01-21T12:54:31Z	6	0	peft	[ "peft", "safetensors", "mistral", "axolotl", "generated_from_trainer", "base_model:Artples/L-MChat-7b", "base_model:adapter:Artples/L-MChat-7b", "license:apache-2.0", "region:us" ]	null	2025-01-21T12:53:16Z	--- library_name: peft license: apache-2.0 base_model: Artples/L-MChat-7b tags: - axolotl - generated_from_trainer model-index: - name: 5a51f800-f03b-497d-9dc7-c04b99c41fb6 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: Artples/L-MChat-7b bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - df03514e65800f80_train_data.json ds_type: json format: custom path: /workspace/input_data/df03514e65800f80_train_data.json type: field_instruction: input field_output: response format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: havinash-ai/5a51f800-f03b-497d-9dc7-c04b99c41fb6 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/df03514e65800f80_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 special_tokens: pad_token: <\|end_of_turn\|> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: e3508d62-5471-4cdf-8dba-5844f441931a wandb_project: Mine-SN56-2-Gradients-On-Demand wandb_run: your_name wandb_runid: e3508d62-5471-4cdf-8dba-5844f441931a warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # 5a51f800-f03b-497d-9dc7-c04b99c41fb6 This model is a fine-tuned version of [Artples/L-MChat-7b](https://huggingface.co/Artples/L-MChat-7b) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 0.0 \| 0.0011 \| 1 \| nan \| \| 0.0 \| 0.0034 \| 3 \| nan \| \| 0.0 \| 0.0068 \| 6 \| nan \| \| 0.0 \| 0.0101 \| 9 \| nan \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
Best000/1220e340-6dd5-449f-955a-5c7b981b876f	Best000	2025-01-21T12:54:14Z	6	0	peft	[ "peft", "safetensors", "gemma2", "axolotl", "generated_from_trainer", "base_model:UCLA-AGI/Gemma-2-9B-It-SPPO-Iter2", "base_model:adapter:UCLA-AGI/Gemma-2-9B-It-SPPO-Iter2", "license:gemma", "region:us" ]	null	2025-01-21T11:50:56Z	--- library_name: peft license: gemma base_model: UCLA-AGI/Gemma-2-9B-It-SPPO-Iter2 tags: - axolotl - generated_from_trainer model-index: - name: 1220e340-6dd5-449f-955a-5c7b981b876f results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: UCLA-AGI/Gemma-2-9B-It-SPPO-Iter2 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 7152f650ecb2903c_train_data.json ds_type: json format: custom path: /workspace/input_data/7152f650ecb2903c_train_data.json type: field_instruction: pattern field_output: sentence format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: Best000/1220e340-6dd5-449f-955a-5c7b981b876f hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/7152f650ecb2903c_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 2f783681-0954-497d-858e-f6a9740d789d wandb_project: Birthday-SN56-16-Gradients-On-Demand wandb_run: your_name wandb_runid: 2f783681-0954-497d-858e-f6a9740d789d warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # 1220e340-6dd5-449f-955a-5c7b981b876f This model is a fine-tuned version of [UCLA-AGI/Gemma-2-9B-It-SPPO-Iter2](https://huggingface.co/UCLA-AGI/Gemma-2-9B-It-SPPO-Iter2) on the None dataset. It achieves the following results on the evaluation set: - Loss: 3.5726 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 6.1394 \| 0.0000 \| 1 \| 5.6277 \| \| 5.728 \| 0.0001 \| 3 \| 5.5548 \| \| 5.1083 \| 0.0001 \| 6 \| 4.6567 \| \| 3.2958 \| 0.0002 \| 9 \| 3.5726 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
nhung03/e06908a5-3e83-40a2-971b-3893a66fe938	nhung03	2025-01-21T12:53:53Z	6	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:JackFram/llama-160m", "base_model:adapter:JackFram/llama-160m", "license:apache-2.0", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-21T12:48:12Z	--- library_name: peft license: apache-2.0 base_model: JackFram/llama-160m tags: - axolotl - generated_from_trainer model-index: - name: e06908a5-3e83-40a2-971b-3893a66fe938 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: JackFram/llama-160m bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - a75236d5c65ead30_train_data.json ds_type: json format: custom path: /workspace/input_data/a75236d5c65ead30_train_data.json type: field_input: scene_setting field_instruction: user_setting field_output: assistant_setting format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: nhung03/e06908a5-3e83-40a2-971b-3893a66fe938 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/a75236d5c65ead30_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 special_tokens: pad_token: </s> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: a26c3dbd-260b-429a-b4e4-cbf7b2da5f3d wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: a26c3dbd-260b-429a-b4e4-cbf7b2da5f3d warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details><br> # e06908a5-3e83-40a2-971b-3893a66fe938 This model is a fine-tuned version of [JackFram/llama-160m](https://huggingface.co/JackFram/llama-160m) on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.5639 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 2.404 \| 0.0427 \| 200 \| 2.5639 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
Best000/7cc54379-cd55-4a1a-a934-592749a9aa76	Best000	2025-01-21T12:53:40Z	6	0	peft	[ "peft", "safetensors", "gemma2", "axolotl", "generated_from_trainer", "base_model:unsloth/gemma-2-2b-it", "base_model:adapter:unsloth/gemma-2-2b-it", "license:gemma", "region:us" ]	null	2025-01-21T12:52:58Z	--- library_name: peft license: gemma base_model: unsloth/gemma-2-2b-it tags: - axolotl - generated_from_trainer model-index: - name: 7cc54379-cd55-4a1a-a934-592749a9aa76 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/gemma-2-2b-it bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - ddbeadb543cf2f4e_train_data.json ds_type: json format: custom path: /workspace/input_data/ddbeadb543cf2f4e_train_data.json type: field_instruction: instruction field_output: output format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: Best000/7cc54379-cd55-4a1a-a934-592749a9aa76 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/ddbeadb543cf2f4e_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 42dfa003-a971-4f6d-a499-5d2f92d18baa wandb_project: Birthday-SN56-15-Gradients-On-Demand wandb_run: your_name wandb_runid: 42dfa003-a971-4f6d-a499-5d2f92d18baa warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # 7cc54379-cd55-4a1a-a934-592749a9aa76 This model is a fine-tuned version of [unsloth/gemma-2-2b-it](https://huggingface.co/unsloth/gemma-2-2b-it) on the None dataset. It achieves the following results on the evaluation set: - Loss: 3.4881 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 4.4439 \| 0.0092 \| 1 \| 4.2637 \| \| 3.8856 \| 0.0277 \| 3 \| 4.2370 \| \| 3.7924 \| 0.0554 \| 6 \| 3.9160 \| \| 3.1065 \| 0.0831 \| 9 \| 3.4881 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
thdihan/gemma-2b-finetuned-psych8k-1k	thdihan	2025-01-21T12:51:49Z	38	0	transformers	[ "transformers", "safetensors", "gemma", "text-generation", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2025-01-21T12:44:34Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. 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nhunglaaaaaaa/f773374e-60ef-4fe9-b325-4ce2a455347b	nhunglaaaaaaa	2025-01-21T12:51:49Z	6	0	peft	[ "peft", "safetensors", "gemma2", "axolotl", "generated_from_trainer", "base_model:unsloth/gemma-2-9b-it", "base_model:adapter:unsloth/gemma-2-9b-it", "license:gemma", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-21T12:16:05Z	--- library_name: peft license: gemma base_model: unsloth/gemma-2-9b-it tags: - axolotl - generated_from_trainer model-index: - name: f773374e-60ef-4fe9-b325-4ce2a455347b results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/gemma-2-9b-it bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - baac717caf978860_train_data.json ds_type: json format: custom path: /workspace/input_data/baac717caf978860_train_data.json type: field_input: chosen-r field_instruction: source field_output: chosen-refined format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: nhunglaaaaaaa/f773374e-60ef-4fe9-b325-4ce2a455347b hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/baac717caf978860_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 15392e77-9853-4e00-86aa-ecd75e9c25d7 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 15392e77-9853-4e00-86aa-ecd75e9c25d7 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details><br> # f773374e-60ef-4fe9-b325-4ce2a455347b This model is a fine-tuned version of [unsloth/gemma-2-9b-it](https://huggingface.co/unsloth/gemma-2-9b-it) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.8181 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 0.8422 \| 0.0687 \| 200 \| 0.8181 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
great0001/40731a2d-6e66-4847-9aad-f6c99c65c3c0	great0001	2025-01-21T12:50:20Z	6	0	peft	[ "peft", "safetensors", "gemma2", "axolotl", "generated_from_trainer", "base_model:unsloth/gemma-2-2b-it", "base_model:adapter:unsloth/gemma-2-2b-it", "license:gemma", "region:us" ]	null	2025-01-21T12:48:40Z	--- library_name: peft license: gemma base_model: unsloth/gemma-2-2b-it tags: - axolotl - generated_from_trainer model-index: - name: 40731a2d-6e66-4847-9aad-f6c99c65c3c0 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/gemma-2-2b-it bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - ddbeadb543cf2f4e_train_data.json ds_type: json format: custom path: /workspace/input_data/ddbeadb543cf2f4e_train_data.json type: field_instruction: instruction field_output: output format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: great0001/40731a2d-6e66-4847-9aad-f6c99c65c3c0 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/ddbeadb543cf2f4e_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 42dfa003-a971-4f6d-a499-5d2f92d18baa wandb_project: Birthday-SN56-14-Gradients-On-Demand wandb_run: your_name wandb_runid: 42dfa003-a971-4f6d-a499-5d2f92d18baa warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # 40731a2d-6e66-4847-9aad-f6c99c65c3c0 This model is a fine-tuned version of [unsloth/gemma-2-2b-it](https://huggingface.co/unsloth/gemma-2-2b-it) on the None dataset. It achieves the following results on the evaluation set: - Loss: 3.4869 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 4.4439 \| 0.0092 \| 1 \| 4.2637 \| \| 3.8892 \| 0.0277 \| 3 \| 4.2397 \| \| 3.797 \| 0.0554 \| 6 \| 3.9266 \| \| 3.1095 \| 0.0831 \| 9 \| 3.4869 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
MayBashendy/ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k8_task7_organization	MayBashendy	2025-01-21T12:48:54Z	5	0	transformers	[ "transformers", "safetensors", "bert", "text-classification", "generated_from_trainer", "base_model:aubmindlab/bert-base-arabertv02", "base_model:finetune:aubmindlab/bert-base-arabertv02", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2025-01-21T12:44:58Z	--- library_name: transformers base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k8_task7_organization results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k8_task7_organization This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.9402 - Qwk: 0.2460 - Mse: 0.9402 - Rmse: 0.9697 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 100 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Qwk \| Mse \| Rmse \| \|:-------------:\|:-------:\|:----:\|:---------------:\|:-------:\|:------:\|:------:\| \| No log \| 0.1053 \| 2 \| 2.4641 \| -0.0568 \| 2.4641 \| 1.5697 \| \| No log \| 0.2105 \| 4 \| 1.2791 \| 0.1882 \| 1.2791 \| 1.1310 \| \| No log \| 0.3158 \| 6 \| 1.0031 \| -0.0550 \| 1.0031 \| 1.0015 \| \| No log \| 0.4211 \| 8 \| 1.1737 \| -0.1355 \| 1.1737 \| 1.0834 \| \| No log \| 0.5263 \| 10 \| 1.2532 \| -0.1993 \| 1.2532 \| 1.1195 \| \| No log \| 0.6316 \| 12 \| 0.8472 \| 0.0 \| 0.8472 \| 0.9204 \| \| No log \| 0.7368 \| 14 \| 0.6607 \| 0.1232 \| 0.6607 \| 0.8128 \| \| No log \| 0.8421 \| 16 \| 0.6433 \| 0.2676 \| 0.6433 \| 0.8021 \| \| No log \| 0.9474 \| 18 \| 0.7040 \| 0.3019 \| 0.7040 \| 0.8391 \| \| No log \| 1.0526 \| 20 \| 0.7188 \| 0.3019 \| 0.7188 \| 0.8478 \| \| No log \| 1.1579 \| 22 \| 0.6808 \| 0.2676 \| 0.6808 \| 0.8251 \| \| No log \| 1.2632 \| 24 \| 0.6844 \| 0.2676 \| 0.6844 \| 0.8273 \| \| No log \| 1.3684 \| 26 \| 0.6940 \| 0.2676 \| 0.6940 \| 0.8331 \| \| No log \| 1.4737 \| 28 \| 0.7603 \| 0.3125 \| 0.7603 \| 0.8720 \| \| No log \| 1.5789 \| 30 \| 0.8185 \| 0.1660 \| 0.8185 \| 0.9047 \| \| No log \| 1.6842 \| 32 \| 0.7336 \| 0.2748 \| 0.7336 \| 0.8565 \| \| No log \| 1.7895 \| 34 \| 0.8494 \| 0.2358 \| 0.8494 \| 0.9217 \| \| No log \| 1.8947 \| 36 \| 1.0127 \| 0.1955 \| 1.0127 \| 1.0063 \| \| No log \| 2.0 \| 38 \| 0.8270 \| 0.1459 \| 0.8270 \| 0.9094 \| \| No log \| 2.1053 \| 40 \| 0.7232 \| 0.1277 \| 0.7232 \| 0.8504 \| \| No log \| 2.2105 \| 42 \| 0.7874 \| 0.2156 \| 0.7874 \| 0.8874 \| \| No log \| 2.3158 \| 44 \| 0.7714 \| 0.1365 \| 0.7714 \| 0.8783 \| \| No log \| 2.4211 \| 46 \| 0.7528 \| 0.0717 \| 0.7528 \| 0.8677 \| \| No log \| 2.5263 \| 48 \| 0.8233 \| 0.2407 \| 0.8233 \| 0.9073 \| \| No log \| 2.6316 \| 50 \| 0.8316 \| 0.2652 \| 0.8316 \| 0.9119 \| \| No log \| 2.7368 \| 52 \| 0.7702 \| 0.1863 \| 0.7702 \| 0.8776 \| \| No log \| 2.8421 \| 54 \| 0.7735 \| 0.2884 \| 0.7735 \| 0.8795 \| \| No log \| 2.9474 \| 56 \| 0.7935 \| 0.3238 \| 0.7935 \| 0.8908 \| \| No log \| 3.0526 \| 58 \| 1.0933 \| 0.1241 \| 1.0933 \| 1.0456 \| \| No log \| 3.1579 \| 60 \| 1.2316 \| 0.1839 \| 1.2316 \| 1.1098 \| \| No log \| 3.2632 \| 62 \| 1.0365 \| 0.2460 \| 1.0365 \| 1.0181 \| \| No log \| 3.3684 \| 64 \| 0.9874 \| 0.1692 \| 0.9874 \| 0.9937 \| \| No log \| 3.4737 \| 66 \| 1.1110 \| 0.2209 \| 1.1110 \| 1.0540 \| \| No log \| 3.5789 \| 68 \| 1.4546 \| 0.1067 \| 1.4546 \| 1.2061 \| \| No log \| 3.6842 \| 70 \| 1.6366 \| 0.1555 \| 1.6366 \| 1.2793 \| \| No log \| 3.7895 \| 72 \| 1.3934 \| 0.1093 \| 1.3934 \| 1.1804 \| \| No log \| 3.8947 \| 74 \| 1.3039 \| 0.1175 \| 1.3039 \| 1.1419 \| \| No log \| 4.0 \| 76 \| 1.1431 \| 0.1394 \| 1.1431 \| 1.0692 \| \| No log \| 4.1053 \| 78 \| 1.1404 \| 0.1976 \| 1.1404 \| 1.0679 \| \| No log \| 4.2105 \| 80 \| 1.3409 \| 0.1568 \| 1.3409 \| 1.1580 \| \| No log \| 4.3158 \| 82 \| 1.1559 \| 0.1618 \| 1.1559 \| 1.0751 \| \| No log \| 4.4211 \| 84 \| 1.2002 \| 0.1799 \| 1.2002 \| 1.0955 \| \| No log \| 4.5263 \| 86 \| 1.5611 \| 0.1169 \| 1.5611 \| 1.2495 \| \| No log \| 4.6316 \| 88 \| 1.9707 \| 0.0421 \| 1.9707 \| 1.4038 \| \| No log \| 4.7368 \| 90 \| 1.9777 \| 0.0421 \| 1.9777 \| 1.4063 \| \| No log \| 4.8421 \| 92 \| 1.7506 \| 0.0589 \| 1.7506 \| 1.3231 \| \| No log \| 4.9474 \| 94 \| 1.5731 \| 0.1195 \| 1.5731 \| 1.2542 \| \| No log \| 5.0526 \| 96 \| 1.4243 \| 0.1093 \| 1.4243 \| 1.1934 \| \| No log \| 5.1579 \| 98 \| 1.3725 \| 0.1093 \| 1.3725 \| 1.1716 \| \| No log \| 5.2632 \| 100 \| 1.6731 \| 0.0689 \| 1.6731 \| 1.2935 \| \| No log \| 5.3684 \| 102 \| 1.6296 \| 0.0300 \| 1.6296 \| 1.2766 \| \| No log \| 5.4737 \| 104 \| 1.1849 \| 0.1029 \| 1.1849 \| 1.0885 \| \| No log \| 5.5789 \| 106 \| 0.9579 \| 0.1661 \| 0.9579 \| 0.9787 \| \| No log \| 5.6842 \| 108 \| 0.9987 \| 0.1603 \| 0.9987 \| 0.9994 \| \| No log \| 5.7895 \| 110 \| 1.2834 \| 0.1458 \| 1.2834 \| 1.1329 \| \| No log \| 5.8947 \| 112 \| 1.4733 \| 0.0803 \| 1.4733 \| 1.2138 \| \| No log \| 6.0 \| 114 \| 1.3218 \| 0.1458 \| 1.3218 \| 1.1497 \| \| No log \| 6.1053 \| 116 \| 0.9666 \| 0.1651 \| 0.9666 \| 0.9832 \| \| No log \| 6.2105 \| 118 \| 0.9062 \| 0.2076 \| 0.9062 \| 0.9519 \| \| No log \| 6.3158 \| 120 \| 1.0268 \| 0.1210 \| 1.0268 \| 1.0133 \| \| No log \| 6.4211 \| 122 \| 1.4521 \| 0.0361 \| 1.4521 \| 1.2050 \| \| No log \| 6.5263 \| 124 \| 1.8056 \| 0.0350 \| 1.8056 \| 1.3437 \| \| No log \| 6.6316 \| 126 \| 1.7978 \| 0.0350 \| 1.7978 \| 1.3408 \| \| No log \| 6.7368 \| 128 \| 1.5457 \| 0.0447 \| 1.5457 \| 1.2433 \| \| No log \| 6.8421 \| 130 \| 1.2205 \| 0.1262 \| 1.2205 \| 1.1048 \| \| No log \| 6.9474 \| 132 \| 1.1007 \| 0.1356 \| 1.1007 \| 1.0491 \| \| No log \| 7.0526 \| 134 \| 1.1800 \| 0.1293 \| 1.1800 \| 1.0863 \| \| No log \| 7.1579 \| 136 \| 1.3351 \| 0.1174 \| 1.3351 \| 1.1555 \| \| No log \| 7.2632 \| 138 \| 1.2657 \| 0.1293 \| 1.2657 \| 1.1251 \| \| No log \| 7.3684 \| 140 \| 1.2024 \| 0.1293 \| 1.2024 \| 1.0965 \| \| No log \| 7.4737 \| 142 \| 1.3602 \| 0.1175 \| 1.3602 \| 1.1663 \| \| No log \| 7.5789 \| 144 \| 1.5870 \| 0.0283 \| 1.5870 \| 1.2598 \| \| No log \| 7.6842 \| 146 \| 1.5829 \| 0.0283 \| 1.5829 \| 1.2581 \| \| No log \| 7.7895 \| 148 \| 1.3217 \| 0.1175 \| 1.3217 \| 1.1497 \| \| No log \| 7.8947 \| 150 \| 1.0634 \| 0.2119 \| 1.0634 \| 1.0312 \| \| No log \| 8.0 \| 152 \| 1.0604 \| 0.1787 \| 1.0604 \| 1.0298 \| \| No log \| 8.1053 \| 154 \| 1.1823 \| 0.2412 \| 1.1823 \| 1.0873 \| \| No log \| 8.2105 \| 156 \| 1.3899 \| 0.0873 \| 1.3899 \| 1.1789 \| \| No log \| 8.3158 \| 158 \| 1.3188 \| 0.1464 \| 1.3188 \| 1.1484 \| \| No log \| 8.4211 \| 160 \| 1.0921 \| 0.1709 \| 1.0921 \| 1.0450 \| \| No log \| 8.5263 \| 162 \| 0.9088 \| 0.1777 \| 0.9088 \| 0.9533 \| \| No log \| 8.6316 \| 164 \| 0.8664 \| 0.2692 \| 0.8664 \| 0.9308 \| \| No log \| 8.7368 \| 166 \| 0.9342 \| 0.1955 \| 0.9342 \| 0.9665 \| \| No log \| 8.8421 \| 168 \| 1.2602 \| 0.1458 \| 1.2602 \| 1.1226 \| \| No log \| 8.9474 \| 170 \| 1.4897 \| 0.0745 \| 1.4897 \| 1.2205 \| \| No log \| 9.0526 \| 172 \| 1.3828 \| 0.0829 \| 1.3828 \| 1.1759 \| \| No log \| 9.1579 \| 174 \| 1.0783 \| 0.2782 \| 1.0783 \| 1.0384 \| \| No log \| 9.2632 \| 176 \| 0.8226 \| 0.2352 \| 0.8226 \| 0.9070 \| \| No log \| 9.3684 \| 178 \| 0.7643 \| 0.2407 \| 0.7643 \| 0.8743 \| \| No log \| 9.4737 \| 180 \| 0.7740 \| 0.2718 \| 0.7740 \| 0.8798 \| \| No log \| 9.5789 \| 182 \| 0.9104 \| 0.2000 \| 0.9104 \| 0.9541 \| \| No log \| 9.6842 \| 184 \| 1.2011 \| 0.2045 \| 1.2011 \| 1.0959 \| \| No log \| 9.7895 \| 186 \| 1.3583 \| 0.1427 \| 1.3583 \| 1.1655 \| \| No log \| 9.8947 \| 188 \| 1.3863 \| 0.1275 \| 1.3863 \| 1.1774 \| \| No log \| 10.0 \| 190 \| 1.4604 \| 0.1549 \| 1.4604 \| 1.2085 \| \| No log \| 10.1053 \| 192 \| 1.2898 \| 0.1638 \| 1.2898 \| 1.1357 \| \| No log \| 10.2105 \| 194 \| 1.1966 \| 0.1784 \| 1.1966 \| 1.0939 \| \| No log \| 10.3158 \| 196 \| 1.1865 \| 0.1784 \| 1.1865 \| 1.0893 \| \| No log \| 10.4211 \| 198 \| 1.2104 \| 0.1490 \| 1.2104 \| 1.1002 \| \| No log \| 10.5263 \| 200 \| 1.2296 \| 0.1458 \| 1.2296 \| 1.1089 \| \| No log \| 10.6316 \| 202 \| 1.2308 \| 0.1458 \| 1.2308 \| 1.1094 \| \| No log \| 10.7368 \| 204 \| 1.1178 \| 0.1626 \| 1.1178 \| 1.0573 \| \| No log \| 10.8421 \| 206 \| 0.9721 \| 0.1274 \| 0.9721 \| 0.9859 \| \| No log \| 10.9474 \| 208 \| 0.9787 \| 0.1557 \| 0.9787 \| 0.9893 \| \| No log \| 11.0526 \| 210 \| 1.0491 \| 0.0925 \| 1.0491 \| 1.0242 \| \| No log \| 11.1579 \| 212 \| 1.2200 \| 0.1943 \| 1.2200 \| 1.1046 \| \| No log \| 11.2632 \| 214 \| 1.3621 \| 0.1220 \| 1.3621 \| 1.1671 \| \| No log \| 11.3684 \| 216 \| 1.2789 \| 0.1427 \| 1.2789 \| 1.1309 \| \| No log \| 11.4737 \| 218 \| 1.1262 \| 0.2782 \| 1.1262 \| 1.0612 \| \| No log \| 11.5789 \| 220 \| 1.0803 \| 0.1787 \| 1.0803 \| 1.0394 \| \| No log \| 11.6842 \| 222 \| 1.0540 \| 0.1787 \| 1.0540 \| 1.0266 \| \| No log \| 11.7895 \| 224 \| 1.1171 \| 0.1949 \| 1.1171 \| 1.0569 \| \| No log \| 11.8947 \| 226 \| 1.2800 \| 0.0712 \| 1.2800 \| 1.1314 \| \| No log \| 12.0 \| 228 \| 1.3595 \| 0.0419 \| 1.3595 \| 1.1660 \| \| No log \| 12.1053 \| 230 \| 1.3345 \| 0.0694 \| 1.3345 \| 1.1552 \| \| No log \| 12.2105 \| 232 \| 1.5379 \| 0.0832 \| 1.5379 \| 1.2401 \| \| No log \| 12.3158 \| 234 \| 1.7880 \| 0.0932 \| 1.7880 \| 1.3372 \| \| No log \| 12.4211 \| 236 \| 1.6579 \| 0.1549 \| 1.6579 \| 1.2876 \| \| No log \| 12.5263 \| 238 \| 1.3537 \| 0.0952 \| 1.3537 \| 1.1635 \| \| No log \| 12.6316 \| 240 \| 1.1170 \| 0.0448 \| 1.1170 \| 1.0569 \| \| No log \| 12.7368 \| 242 \| 1.0241 \| 0.0448 \| 1.0241 \| 1.0120 \| \| No log \| 12.8421 \| 244 \| 1.0171 \| 0.0799 \| 1.0171 \| 1.0085 \| \| No log \| 12.9474 \| 246 \| 1.1371 \| 0.0585 \| 1.1371 \| 1.0663 \| \| No log \| 13.0526 \| 248 \| 1.2053 \| 0.1205 \| 1.2053 \| 1.0979 \| \| No log \| 13.1579 \| 250 \| 1.1845 \| 0.0538 \| 1.1845 \| 1.0884 \| \| No log \| 13.2632 \| 252 \| 1.0946 \| 0.0982 \| 1.0946 \| 1.0463 \| \| No log \| 13.3684 \| 254 \| 1.1487 \| 0.0982 \| 1.1487 \| 1.0718 \| \| No log \| 13.4737 \| 256 \| 1.3419 \| 0.0694 \| 1.3419 \| 1.1584 \| \| No log \| 13.5789 \| 258 \| 1.5060 \| 0.0086 \| 1.5060 \| 1.2272 \| \| No log \| 13.6842 \| 260 \| 1.4753 \| 0.0086 \| 1.4753 \| 1.2146 \| \| No log \| 13.7895 \| 262 \| 1.2918 \| 0.0459 \| 1.2918 \| 1.1366 \| \| No log \| 13.8947 \| 264 \| 1.2588 \| 0.0761 \| 1.2588 \| 1.1220 \| \| No log \| 14.0 \| 266 \| 1.1447 \| 0.1147 \| 1.1447 \| 1.0699 \| \| No log \| 14.1053 \| 268 \| 1.0228 \| 0.1385 \| 1.0228 \| 1.0114 \| \| No log \| 14.2105 \| 270 \| 1.0093 \| 0.1734 \| 1.0093 \| 1.0046 \| \| No log \| 14.3158 \| 272 \| 1.1433 \| 0.0561 \| 1.1433 \| 1.0692 \| \| No log \| 14.4211 \| 274 \| 1.3866 \| 0.0584 \| 1.3866 \| 1.1776 \| \| No log \| 14.5263 \| 276 \| 1.5194 \| 0.0465 \| 1.5194 \| 1.2326 \| \| No log \| 14.6316 \| 278 \| 1.4404 \| 0.0531 \| 1.4404 \| 1.2002 \| \| No log \| 14.7368 \| 280 \| 1.3060 \| 0.1458 \| 1.3060 \| 1.1428 \| \| No log \| 14.8421 \| 282 \| 1.2034 \| 0.0546 \| 1.2034 \| 1.0970 \| \| No log \| 14.9474 \| 284 \| 1.1476 \| 0.0315 \| 1.1476 \| 1.0712 \| \| No log \| 15.0526 \| 286 \| 1.2144 \| 0.1262 \| 1.2144 \| 1.1020 \| \| No log \| 15.1579 \| 288 \| 1.3063 \| 0.0648 \| 1.3063 \| 1.1429 \| \| No log \| 15.2632 \| 290 \| 1.3645 \| 0.0921 \| 1.3645 \| 1.1681 \| \| No log \| 15.3684 \| 292 \| 1.2482 \| 0.0921 \| 1.2482 \| 1.1172 \| \| No log \| 15.4737 \| 294 \| 1.0915 \| 0.2183 \| 1.0915 \| 1.0447 \| \| No log \| 15.5789 \| 296 \| 1.0100 \| 0.2032 \| 1.0100 \| 1.0050 \| \| No log \| 15.6842 \| 298 \| 0.9617 \| 0.1651 \| 0.9617 \| 0.9807 \| \| No log \| 15.7895 \| 300 \| 0.9237 \| 0.1822 \| 0.9237 \| 0.9611 \| \| No log \| 15.8947 \| 302 \| 0.9719 \| 0.1651 \| 0.9719 \| 0.9859 \| \| No log \| 16.0 \| 304 \| 1.0726 \| 0.1389 \| 1.0726 \| 1.0357 \| \| No log \| 16.1053 \| 306 \| 1.2458 \| 0.1490 \| 1.2458 \| 1.1162 \| \| No log \| 16.2105 \| 308 \| 1.4795 \| 0.0519 \| 1.4795 \| 1.2164 \| \| No log \| 16.3158 \| 310 \| 1.4706 \| 0.0519 \| 1.4706 \| 1.2127 \| \| No log \| 16.4211 \| 312 \| 1.2663 \| 0.1233 \| 1.2663 \| 1.1253 \| \| No log \| 16.5263 \| 314 \| 1.0773 \| 0.0569 \| 1.0773 \| 1.0379 \| \| No log \| 16.6316 \| 316 \| 1.0396 \| 0.0592 \| 1.0396 \| 1.0196 \| \| No log \| 16.7368 \| 318 \| 1.0507 \| 0.0894 \| 1.0507 \| 1.0251 \| \| No log \| 16.8421 \| 320 \| 1.0997 \| 0.1394 \| 1.0997 \| 1.0487 \| \| No log \| 16.9474 \| 322 \| 1.1279 \| 0.1635 \| 1.1279 \| 1.0620 \| \| No log \| 17.0526 \| 324 \| 1.1312 \| 0.1635 \| 1.1312 \| 1.0636 \| \| No log \| 17.1579 \| 326 \| 1.0328 \| 0.1463 \| 1.0328 \| 1.0163 \| \| No log \| 17.2632 \| 328 \| 0.9286 \| 0.1612 \| 0.9286 \| 0.9636 \| \| No log \| 17.3684 \| 330 \| 0.9605 \| 0.1612 \| 0.9605 \| 0.9800 \| \| No log \| 17.4737 \| 332 \| 1.0802 \| 0.2183 \| 1.0802 \| 1.0393 \| \| No log \| 17.5789 \| 334 \| 1.2681 \| 0.0921 \| 1.2681 \| 1.1261 \| \| No log \| 17.6842 \| 336 \| 1.3526 \| 0.0343 \| 1.3526 \| 1.1630 \| \| No log \| 17.7895 \| 338 \| 1.3346 \| 0.0898 \| 1.3346 \| 1.1553 \| \| No log \| 17.8947 \| 340 \| 1.3625 \| 0.0873 \| 1.3625 \| 1.1673 \| \| No log \| 18.0 \| 342 \| 1.1606 \| 0.1523 \| 1.1606 \| 1.0773 \| \| No log \| 18.1053 \| 344 \| 0.9443 \| 0.1803 \| 0.9443 \| 0.9717 \| \| No log \| 18.2105 \| 346 \| 0.9077 \| 0.2287 \| 0.9077 \| 0.9527 \| \| No log \| 18.3158 \| 348 \| 0.9189 \| 0.2000 \| 0.9189 \| 0.9586 \| \| No log \| 18.4211 \| 350 \| 0.9441 \| 0.2211 \| 0.9441 \| 0.9717 \| \| No log \| 18.5263 \| 352 \| 0.9530 \| 0.2211 \| 0.9530 \| 0.9762 \| \| No log \| 18.6316 \| 354 \| 1.0559 \| 0.2316 \| 1.0559 \| 1.0276 \| \| No log \| 18.7368 \| 356 \| 1.1002 \| 0.2552 \| 1.1002 \| 1.0489 \| \| No log \| 18.8421 \| 358 \| 1.1299 \| 0.1858 \| 1.1299 \| 1.0629 \| \| No log \| 18.9474 \| 360 \| 1.1509 \| 0.1821 \| 1.1509 \| 1.0728 \| \| No log \| 19.0526 \| 362 \| 1.0969 \| 0.1709 \| 1.0969 \| 1.0473 \| \| No log \| 19.1579 \| 364 \| 1.0309 \| 0.1869 \| 1.0309 \| 1.0153 \| \| No log \| 19.2632 \| 366 \| 1.0453 \| 0.1869 \| 1.0453 \| 1.0224 \| \| No log \| 19.3684 \| 368 \| 1.0596 \| 0.2032 \| 1.0596 \| 1.0294 \| \| No log \| 19.4737 \| 370 \| 1.1637 \| 0.1870 \| 1.1637 \| 1.0788 \| \| No log \| 19.5789 \| 372 \| 1.2256 \| 0.1205 \| 1.2256 \| 1.1070 \| \| No log \| 19.6842 \| 374 \| 1.2246 \| 0.1205 \| 1.2246 \| 1.1066 \| \| No log \| 19.7895 \| 376 \| 1.1160 \| 0.2183 \| 1.1160 \| 1.0564 \| \| No log \| 19.8947 \| 378 \| 1.0576 \| 0.1210 \| 1.0576 \| 1.0284 \| \| No log \| 20.0 \| 380 \| 1.0879 \| 0.1463 \| 1.0879 \| 1.0430 \| \| No log \| 20.1053 \| 382 \| 1.1567 \| 0.1463 \| 1.1567 \| 1.0755 \| \| No log \| 20.2105 \| 384 \| 1.2232 \| 0.1262 \| 1.2232 \| 1.1060 \| \| No log \| 20.3158 \| 386 \| 1.2875 \| 0.1233 \| 1.2875 \| 1.1347 \| \| No log \| 20.4211 \| 388 \| 1.3831 \| 0.0343 \| 1.3831 \| 1.1761 \| \| No log \| 20.5263 \| 390 \| 1.4274 \| 0.0708 \| 1.4274 \| 1.1947 \| \| No log \| 20.6316 \| 392 \| 1.3132 \| 0.1233 \| 1.3132 \| 1.1459 \| \| No log \| 20.7368 \| 394 \| 1.1052 \| 0.1747 \| 1.1052 \| 1.0513 \| \| No log \| 20.8421 \| 396 \| 0.9038 \| 0.1651 \| 0.9038 \| 0.9507 \| \| No log \| 20.9474 \| 398 \| 0.8384 \| 0.2632 \| 0.8384 \| 0.9157 \| \| No log \| 21.0526 \| 400 \| 0.8279 \| 0.2063 \| 0.8279 \| 0.9099 \| \| No log \| 21.1579 \| 402 \| 0.8476 \| 0.2297 \| 0.8476 \| 0.9206 \| \| No log \| 21.2632 \| 404 \| 0.9798 \| 0.0616 \| 0.9798 \| 0.9899 \| \| No log \| 21.3684 \| 406 \| 1.2113 \| 0.1591 \| 1.2113 \| 1.1006 \| \| No log \| 21.4737 \| 408 \| 1.4117 \| 0.1093 \| 1.4117 \| 1.1882 \| \| No log \| 21.5789 \| 410 \| 1.5392 \| 0.1285 \| 1.5392 \| 1.2407 \| \| No log \| 21.6842 \| 412 \| 1.4635 \| 0.0766 \| 1.4635 \| 1.2097 \| \| No log \| 21.7895 \| 414 \| 1.1993 \| 0.1324 \| 1.1993 \| 1.0951 \| \| No log \| 21.8947 \| 416 \| 0.9784 \| 0.0896 \| 0.9784 \| 0.9891 \| \| No log \| 22.0 \| 418 \| 0.8859 \| 0.0895 \| 0.8859 \| 0.9412 \| \| No log \| 22.1053 \| 420 \| 0.8847 \| 0.0895 \| 0.8847 \| 0.9406 \| \| No log \| 22.2105 \| 422 \| 0.8522 \| 0.2171 \| 0.8522 \| 0.9232 \| \| No log \| 22.3158 \| 424 \| 0.8241 \| 0.2171 \| 0.8241 \| 0.9078 \| \| No log \| 22.4211 \| 426 \| 0.8996 \| 0.1718 \| 0.8996 \| 0.9485 \| \| No log \| 22.5263 \| 428 \| 1.0471 \| 0.0896 \| 1.0471 \| 1.0233 \| \| No log \| 22.6316 \| 430 \| 1.0850 \| 0.0842 \| 1.0850 \| 1.0416 \| \| No log \| 22.7368 \| 432 \| 1.0406 \| 0.0896 \| 1.0406 \| 1.0201 \| \| No log \| 22.8421 \| 434 \| 0.9429 \| 0.1692 \| 0.9429 \| 0.9711 \| \| No log \| 22.9474 \| 436 \| 0.8892 \| 0.2632 \| 0.8892 \| 0.9430 \| \| No log \| 23.0526 \| 438 \| 0.8751 \| 0.2409 \| 0.8751 \| 0.9355 \| \| No log \| 23.1579 \| 440 \| 0.8877 \| 0.1914 \| 0.8877 \| 0.9422 \| \| No log \| 23.2632 \| 442 \| 0.8993 \| 0.1914 \| 0.8993 \| 0.9483 \| \| No log \| 23.3684 \| 444 \| 0.9416 \| 0.2000 \| 0.9416 \| 0.9703 \| \| No log \| 23.4737 \| 446 \| 0.9549 \| 0.1651 \| 0.9549 \| 0.9772 \| \| No log \| 23.5789 \| 448 \| 0.8887 \| 0.1962 \| 0.8887 \| 0.9427 \| \| No log \| 23.6842 \| 450 \| 0.8707 \| 0.2352 \| 0.8707 \| 0.9331 \| \| No log \| 23.7895 \| 452 \| 0.9281 \| 0.2142 \| 0.9281 \| 0.9634 \| \| No log \| 23.8947 \| 454 \| 0.9651 \| 0.2259 \| 0.9651 \| 0.9824 \| \| No log \| 24.0 \| 456 \| 0.9547 \| 0.2000 \| 0.9547 \| 0.9771 \| \| No log \| 24.1053 \| 458 \| 0.9812 \| 0.2259 \| 0.9812 \| 0.9905 \| \| No log \| 24.2105 \| 460 \| 0.9499 \| 0.2000 \| 0.9499 \| 0.9746 \| \| No log \| 24.3158 \| 462 \| 0.9134 \| 0.1734 \| 0.9134 \| 0.9557 \| \| No log \| 24.4211 \| 464 \| 0.8957 \| 0.1542 \| 0.8957 \| 0.9464 \| \| No log \| 24.5263 \| 466 \| 0.9177 \| 0.1501 \| 0.9177 \| 0.9580 \| \| No log \| 24.6316 \| 468 \| 0.9123 \| 0.1144 \| 0.9123 \| 0.9552 \| \| No log \| 24.7368 \| 470 \| 0.9427 \| 0.0803 \| 0.9427 \| 0.9709 \| \| No log \| 24.8421 \| 472 \| 0.9644 \| 0.1045 \| 0.9644 \| 0.9820 \| \| No log \| 24.9474 \| 474 \| 0.9877 \| 0.0953 \| 0.9877 \| 0.9938 \| \| No log \| 25.0526 \| 476 \| 0.9548 \| 0.0746 \| 0.9548 \| 0.9771 \| \| No log \| 25.1579 \| 478 \| 0.8722 \| 0.1962 \| 0.8722 \| 0.9339 \| \| No log \| 25.2632 \| 480 \| 0.8807 \| 0.1962 \| 0.8807 \| 0.9385 \| \| No log \| 25.3684 \| 482 \| 0.9581 \| 0.1642 \| 0.9581 \| 0.9788 \| \| No log \| 25.4737 \| 484 \| 0.9240 \| 0.1379 \| 0.9240 \| 0.9612 \| \| No log \| 25.5789 \| 486 \| 0.8329 \| 0.2883 \| 0.8329 \| 0.9126 \| \| No log \| 25.6842 \| 488 \| 0.7711 \| 0.3312 \| 0.7711 \| 0.8781 \| \| No log \| 25.7895 \| 490 \| 0.7734 \| 0.2883 \| 0.7734 \| 0.8794 \| \| No log \| 25.8947 \| 492 \| 0.7991 \| 0.3167 \| 0.7991 \| 0.8939 \| \| No log \| 26.0 \| 494 \| 0.8618 \| 0.3359 \| 0.8618 \| 0.9283 \| \| No log \| 26.1053 \| 496 \| 0.8989 \| 0.3231 \| 0.8989 \| 0.9481 \| \| No log \| 26.2105 \| 498 \| 0.8341 \| 0.3294 \| 0.8341 \| 0.9133 \| \| 0.2424 \| 26.3158 \| 500 \| 0.7303 \| 0.3099 \| 0.7303 \| 0.8546 \| \| 0.2424 \| 26.4211 \| 502 \| 0.7038 \| 0.2817 \| 0.7038 \| 0.8389 \| \| 0.2424 \| 26.5263 \| 504 \| 0.7111 \| 0.3099 \| 0.7111 \| 0.8433 \| \| 0.2424 \| 26.6316 \| 506 \| 0.7457 \| 0.3099 \| 0.7457 \| 0.8635 \| \| 0.2424 \| 26.7368 \| 508 \| 0.8348 \| 0.3359 \| 0.8348 \| 0.9137 \| \| 0.2424 \| 26.8421 \| 510 \| 0.9436 \| 0.2460 \| 0.9436 \| 0.9714 \| \| 0.2424 \| 26.9474 \| 512 \| 1.0461 \| 0.2141 \| 1.0461 \| 1.0228 \| \| 0.2424 \| 27.0526 \| 514 \| 1.1003 \| 0.1832 \| 1.1003 \| 1.0490 \| \| 0.2424 \| 27.1579 \| 516 \| 1.0420 \| 0.2227 \| 1.0420 \| 1.0208 \| \| 0.2424 \| 27.2632 \| 518 \| 0.9402 \| 0.2460 \| 0.9402 \| 0.9697 \| ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.0+cu118 - Datasets 2.21.0 - Tokenizers 0.19.1
ClarenceDan/8500479a-7b5d-46f1-9208-c970e58819a2	ClarenceDan	2025-01-21T12:48:49Z	8	0	peft	[ "peft", "safetensors", "mistral", "axolotl", "generated_from_trainer", "base_model:teknium/OpenHermes-2.5-Mistral-7B", "base_model:adapter:teknium/OpenHermes-2.5-Mistral-7B", "license:apache-2.0", "region:us" ]	null	2025-01-21T12:39:14Z	--- library_name: peft license: apache-2.0 base_model: teknium/OpenHermes-2.5-Mistral-7B tags: - axolotl - generated_from_trainer model-index: - name: 8500479a-7b5d-46f1-9208-c970e58819a2 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: teknium/OpenHermes-2.5-Mistral-7B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 1b5fe4b652f9222e_train_data.json ds_type: json format: custom path: /workspace/input_data/1b5fe4b652f9222e_train_data.json type: field_instruction: instruction field_output: output format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: ClarenceDan/8500479a-7b5d-46f1-9208-c970e58819a2 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/1b5fe4b652f9222e_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 special_tokens: pad_token: <\|im_end\|> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 857fa1e7-73d3-440e-a388-76fc6a5b2495 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 857fa1e7-73d3-440e-a388-76fc6a5b2495 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # 8500479a-7b5d-46f1-9208-c970e58819a2 This model is a fine-tuned version of [teknium/OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 0.0 \| 0.0002 \| 1 \| nan \| \| 0.0 \| 0.0006 \| 3 \| nan \| \| 0.0 \| 0.0012 \| 6 \| nan \| \| 0.0 \| 0.0018 \| 9 \| nan \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
ClarenceDan/8d4acffc-77b2-45e7-b2db-56fd18aa1ade	ClarenceDan	2025-01-21T12:48:20Z	6	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:heegyu/WizardVicuna-open-llama-3b-v2", "base_model:adapter:heegyu/WizardVicuna-open-llama-3b-v2", "license:apache-2.0", "region:us" ]	null	2025-01-21T12:33:03Z	--- library_name: peft license: apache-2.0 base_model: heegyu/WizardVicuna-open-llama-3b-v2 tags: - axolotl - generated_from_trainer model-index: - name: 8d4acffc-77b2-45e7-b2db-56fd18aa1ade results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: heegyu/WizardVicuna-open-llama-3b-v2 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 0eba3e80d15355a6_train_data.json ds_type: json format: custom path: /workspace/input_data/0eba3e80d15355a6_train_data.json type: field_input: input field_instruction: instruction field_output: accepted format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: ClarenceDan/8d4acffc-77b2-45e7-b2db-56fd18aa1ade hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/0eba3e80d15355a6_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 special_tokens: pad_token: </s> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 84f8a085-50df-4e7c-9e21-f8d55ac51824 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 84f8a085-50df-4e7c-9e21-f8d55ac51824 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # 8d4acffc-77b2-45e7-b2db-56fd18aa1ade This model is a fine-tuned version of [heegyu/WizardVicuna-open-llama-3b-v2](https://huggingface.co/heegyu/WizardVicuna-open-llama-3b-v2) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.7682 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 0.904 \| 0.0002 \| 1 \| 0.7949 \| \| 0.7439 \| 0.0005 \| 3 \| 0.7944 \| \| 0.7234 \| 0.0009 \| 6 \| 0.7882 \| \| 0.7158 \| 0.0014 \| 9 \| 0.7682 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
Manas32122/whisper_merged_new	Manas32122	2025-01-21T12:48:01Z	6	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2025-01-21T12:42:08Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. 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Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
ryusangwon/ko_en_qe_ppo_0.9_1e-6	ryusangwon	2025-01-21T12:47:12Z	5	0	transformers	[ "transformers", "safetensors", "m2m_100", "text2text-generation", "trl", "reinforcement-learning", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	reinforcement-learning	2025-01-21T12:43:47Z	--- license: apache-2.0 tags: - trl - transformers - reinforcement-learning --- # TRL Model This is a [TRL language model](https://github.com/huggingface/trl) that has been fine-tuned with reinforcement learning to guide the model outputs according to a value, function, or human feedback. The model can be used for text generation. ## Usage To use this model for inference, first install the TRL library: ```bash python -m pip install trl ``` You can then generate text as follows: ```python from transformers import pipeline generator = pipeline("text-generation", model="ryusangwon//tmp/tmpbj0hofua/ryusangwon/ko_en_qe_ppo_0.9_1e-6") outputs = generator("Hello, my llama is cute") ``` If you want to use the model for training or to obtain the outputs from the value head, load the model as follows: ```python from transformers import AutoTokenizer from trl import AutoModelForCausalLMWithValueHead tokenizer = AutoTokenizer.from_pretrained("ryusangwon//tmp/tmpbj0hofua/ryusangwon/ko_en_qe_ppo_0.9_1e-6") model = AutoModelForCausalLMWithValueHead.from_pretrained("ryusangwon//tmp/tmpbj0hofua/ryusangwon/ko_en_qe_ppo_0.9_1e-6") inputs = tokenizer("Hello, my llama is cute", return_tensors="pt") outputs = model(**inputs, labels=inputs["input_ids"]) ```
nhung03/ba28972f-a518-42ba-8b7e-9a76b2c77273	nhung03	2025-01-21T12:45:44Z	6	0	peft	[ "peft", "safetensors", "gemma2", "axolotl", "generated_from_trainer", "base_model:unsloth/gemma-2-2b-it", "base_model:adapter:unsloth/gemma-2-2b-it", "license:gemma", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-21T12:39:33Z	--- library_name: peft license: gemma base_model: unsloth/gemma-2-2b-it tags: - axolotl - generated_from_trainer model-index: - name: ba28972f-a518-42ba-8b7e-9a76b2c77273 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/gemma-2-2b-it bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - ddbeadb543cf2f4e_train_data.json ds_type: json format: custom path: /workspace/input_data/ddbeadb543cf2f4e_train_data.json type: field_instruction: instruction field_output: output format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: nhung03/ba28972f-a518-42ba-8b7e-9a76b2c77273 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/ddbeadb543cf2f4e_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 42dfa003-a971-4f6d-a499-5d2f92d18baa wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 42dfa003-a971-4f6d-a499-5d2f92d18baa warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details><br> # ba28972f-a518-42ba-8b7e-9a76b2c77273 This model is a fine-tuned version of [unsloth/gemma-2-2b-it](https://huggingface.co/unsloth/gemma-2-2b-it) on the None dataset. It achieves the following results on the evaluation set: - Loss: 3.1683 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 109 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 4.3957 \| 0.9977 \| 108 \| 3.1566 \| \| 5.1265 \| 1.0069 \| 109 \| 3.1683 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
havinash-ai/785c4b87-9684-48b5-abf4-93a55427d946	havinash-ai	2025-01-21T12:44:54Z	7	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:lmsys/vicuna-7b-v1.5", "base_model:adapter:lmsys/vicuna-7b-v1.5", "license:llama2", "region:us" ]	null	2025-01-21T12:39:58Z	--- library_name: peft license: llama2 base_model: lmsys/vicuna-7b-v1.5 tags: - axolotl - generated_from_trainer model-index: - name: 785c4b87-9684-48b5-abf4-93a55427d946 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: lmsys/vicuna-7b-v1.5 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 87ecfef6de5c4ae6_train_data.json ds_type: json format: custom path: /workspace/input_data/87ecfef6de5c4ae6_train_data.json type: field_input: input field_instruction: instruction field_output: output format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: havinash-ai/785c4b87-9684-48b5-abf4-93a55427d946 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/87ecfef6de5c4ae6_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 08949a5f-0b74-4dce-877f-c6b2eba8999f wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 08949a5f-0b74-4dce-877f-c6b2eba8999f warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # 785c4b87-9684-48b5-abf4-93a55427d946 This model is a fine-tuned version of [lmsys/vicuna-7b-v1.5](https://huggingface.co/lmsys/vicuna-7b-v1.5) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.0688 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 1.3716 \| 0.0002 \| 1 \| 1.5921 \| \| 1.9101 \| 0.0006 \| 3 \| 1.5875 \| \| 1.8918 \| 0.0011 \| 6 \| 1.4767 \| \| 1.4858 \| 0.0017 \| 9 \| 1.0688 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
Alecardo/Ricardo-Fort-678f930b9d5393dc7e1a8ca9	Alecardo	2025-01-21T12:44:49Z	110	0	diffusers	[ "diffusers", "flux", "lora", "replicate", "text-to-image", "en", "base_model:black-forest-labs/FLUX.1-dev", "base_model:adapter:black-forest-labs/FLUX.1-dev", "license:other", "region:us" ]	text-to-image	2025-01-21T12:29:02Z	--- license: other license_name: flux-1-dev-non-commercial-license license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md language: - en tags: - flux - diffusers - lora - replicate base_model: "black-forest-labs/FLUX.1-dev" pipeline_tag: text-to-image # widget: # - text: >- # prompt # output: # url: https://... instance_prompt: ricmaiamefort --- # Ricardo Fort 678F930B9D5393Dc7E1A8Ca9 <Gallery /> Trained on Replicate using: https://replicate.com/ostris/flux-dev-lora-trainer/train ## Trigger words You should use `ricmaiamefort` to trigger the image generation. ## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers) ```py from diffusers import AutoPipelineForText2Image import torch pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.float16).to('cuda') pipeline.load_lora_weights('Alecardo/Ricardo-Fort-678f930b9d5393dc7e1a8ca9', weight_name='lora.safetensors') image = pipeline('your prompt').images[0] ``` For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)
tarabukinivan/88f3286d-c2d1-4d09-9e58-f6eb64e10140	tarabukinivan	2025-01-21T12:44:37Z	6	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:TinyLlama/TinyLlama-1.1B-Chat-v1.0", "base_model:adapter:TinyLlama/TinyLlama-1.1B-Chat-v1.0", "license:apache-2.0", "region:us" ]	null	2025-01-21T12:30:38Z	--- library_name: peft license: apache-2.0 base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0 tags: - axolotl - generated_from_trainer model-index: - name: 88f3286d-c2d1-4d09-9e58-f6eb64e10140 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 9c321e8cf88f16f0_train_data.json ds_type: json format: custom path: /workspace/input_data/9c321e8cf88f16f0_train_data.json type: field_input: input field_instruction: instruction field_output: output format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: null eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: false hub_model_id: tarabukinivan/88f3286d-c2d1-4d09-9e58-f6eb64e10140 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 75GiB max_steps: 30 micro_batch_size: 2 mlflow_experiment_name: /tmp/9c321e8cf88f16f0_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 1a9527a4-dbed-4d09-b3dc-303d2f7479cd wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 1a9527a4-dbed-4d09-b3dc-303d2f7479cd warmup_steps: 10 weight_decay: 0.01 xformers_attention: true ``` </details><br> # 88f3286d-c2d1-4d09-9e58-f6eb64e10140 This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.4001 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 30 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| No log \| 0.0002 \| 1 \| 1.6017 \| \| 1.4713 \| 0.0008 \| 5 \| 1.5789 \| \| 1.4853 \| 0.0016 \| 10 \| 1.4876 \| \| 1.3148 \| 0.0024 \| 15 \| 1.4307 \| \| 1.3637 \| 0.0033 \| 20 \| 1.4131 \| \| 1.5555 \| 0.0041 \| 25 \| 1.4021 \| \| 1.3646 \| 0.0049 \| 30 \| 1.4001 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
MayBashendy/ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k7_task7_organization	MayBashendy	2025-01-21T12:44:35Z	5	0	transformers	[ "transformers", "safetensors", "bert", "text-classification", "generated_from_trainer", "base_model:aubmindlab/bert-base-arabertv02", "base_model:finetune:aubmindlab/bert-base-arabertv02", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2025-01-21T12:40:22Z	--- library_name: transformers base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k7_task7_organization results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k7_task7_organization This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.7187 - Qwk: 0.3341 - Mse: 0.7187 - Rmse: 0.8478 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 100 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Qwk \| Mse \| Rmse \| \|:-------------:\|:-------:\|:----:\|:---------------:\|:-------:\|:------:\|:------:\| \| No log \| 0.1176 \| 2 \| 2.5757 \| -0.0924 \| 2.5757 \| 1.6049 \| \| No log \| 0.2353 \| 4 \| 1.3587 \| 0.0994 \| 1.3587 \| 1.1656 \| \| No log \| 0.3529 \| 6 \| 1.1844 \| -0.2292 \| 1.1844 \| 1.0883 \| \| No log \| 0.4706 \| 8 \| 0.9977 \| -0.0426 \| 0.9977 \| 0.9988 \| \| No log \| 0.5882 \| 10 \| 0.9364 \| 0.1007 \| 0.9364 \| 0.9677 \| \| No log \| 0.7059 \| 12 \| 0.8715 \| 0.1648 \| 0.8715 \| 0.9335 \| \| No log \| 0.8235 \| 14 \| 0.8307 \| -0.0103 \| 0.8307 \| 0.9114 \| \| No log \| 0.9412 \| 16 \| 0.8269 \| -0.0483 \| 0.8269 \| 0.9094 \| \| No log \| 1.0588 \| 18 \| 0.9257 \| 0.0495 \| 0.9257 \| 0.9621 \| \| No log \| 1.1765 \| 20 \| 0.9539 \| -0.0700 \| 0.9539 \| 0.9767 \| \| No log \| 1.2941 \| 22 \| 0.8720 \| 0.0027 \| 0.8720 \| 0.9338 \| \| No log \| 1.4118 \| 24 \| 0.8314 \| 0.0 \| 0.8314 \| 0.9118 \| \| No log \| 1.5294 \| 26 \| 0.8248 \| 0.0 \| 0.8248 \| 0.9082 \| \| No log \| 1.6471 \| 28 \| 0.8307 \| 0.1236 \| 0.8307 \| 0.9114 \| \| No log \| 1.7647 \| 30 \| 0.7798 \| 0.0 \| 0.7798 \| 0.8831 \| \| No log \| 1.8824 \| 32 \| 0.7549 \| 0.0 \| 0.7549 \| 0.8688 \| \| No log \| 2.0 \| 34 \| 0.7683 \| 0.0 \| 0.7683 \| 0.8765 \| \| No log \| 2.1176 \| 36 \| 0.8061 \| 0.0481 \| 0.8061 \| 0.8978 \| \| No log \| 2.2353 \| 38 \| 0.9177 \| 0.2526 \| 0.9177 \| 0.9579 \| \| No log \| 2.3529 \| 40 \| 0.9241 \| 0.3444 \| 0.9241 \| 0.9613 \| \| No log \| 2.4706 \| 42 \| 0.8782 \| 0.3173 \| 0.8782 \| 0.9371 \| \| No log \| 2.5882 \| 44 \| 0.7992 \| 0.1372 \| 0.7992 \| 0.8940 \| \| No log \| 2.7059 \| 46 \| 0.7477 \| 0.0937 \| 0.7477 \| 0.8647 \| \| No log \| 2.8235 \| 48 \| 0.7057 \| 0.0428 \| 0.7057 \| 0.8400 \| \| No log \| 2.9412 \| 50 \| 0.7487 \| 0.3243 \| 0.7487 \| 0.8653 \| \| No log \| 3.0588 \| 52 \| 0.8144 \| 0.1648 \| 0.8144 \| 0.9025 \| \| No log \| 3.1765 \| 54 \| 0.8334 \| 0.1699 \| 0.8334 \| 0.9129 \| \| No log \| 3.2941 \| 56 \| 0.8386 \| 0.1094 \| 0.8386 \| 0.9157 \| \| No log \| 3.4118 \| 58 \| 0.8747 \| -0.0027 \| 0.8747 \| 0.9353 \| \| No log \| 3.5294 \| 60 \| 0.9345 \| -0.1275 \| 0.9345 \| 0.9667 \| \| No log \| 3.6471 \| 62 \| 0.8860 \| -0.0444 \| 0.8860 \| 0.9413 \| \| No log \| 3.7647 \| 64 \| 0.7937 \| 0.0 \| 0.7937 \| 0.8909 \| \| No log \| 3.8824 \| 66 \| 0.7158 \| 0.0889 \| 0.7158 \| 0.8460 \| \| No log \| 4.0 \| 68 \| 0.7009 \| 0.0393 \| 0.7009 \| 0.8372 \| \| No log \| 4.1176 \| 70 \| 0.7320 \| 0.0359 \| 0.7320 \| 0.8556 \| \| No log \| 4.2353 \| 72 \| 0.7952 \| -0.0051 \| 0.7952 \| 0.8917 \| \| No log \| 4.3529 \| 74 \| 0.8104 \| 0.0265 \| 0.8104 \| 0.9002 \| \| No log \| 4.4706 \| 76 \| 0.8378 \| 0.0927 \| 0.8378 \| 0.9153 \| \| No log \| 4.5882 \| 78 \| 0.8915 \| 0.0966 \| 0.8915 \| 0.9442 \| \| No log \| 4.7059 \| 80 \| 0.9184 \| 0.1699 \| 0.9184 \| 0.9583 \| \| No log \| 4.8235 \| 82 \| 0.9273 \| 0.2171 \| 0.9273 \| 0.9630 \| \| No log \| 4.9412 \| 84 \| 0.9053 \| 0.1972 \| 0.9053 \| 0.9515 \| \| No log \| 5.0588 \| 86 \| 0.9132 \| 0.0245 \| 0.9132 \| 0.9556 \| \| No log \| 5.1765 \| 88 \| 0.8966 \| 0.0968 \| 0.8966 \| 0.9469 \| \| No log \| 5.2941 \| 90 \| 0.9317 \| 0.1303 \| 0.9317 \| 0.9652 \| \| No log \| 5.4118 \| 92 \| 0.9620 \| 0.2063 \| 0.9620 \| 0.9808 \| \| No log \| 5.5294 \| 94 \| 0.9345 \| 0.2632 \| 0.9345 \| 0.9667 \| \| No log \| 5.6471 \| 96 \| 0.8433 \| 0.3238 \| 0.8433 \| 0.9183 \| \| No log \| 5.7647 \| 98 \| 0.8240 \| 0.2007 \| 0.8240 \| 0.9078 \| \| No log \| 5.8824 \| 100 \| 0.8275 \| -0.0070 \| 0.8275 \| 0.9096 \| \| No log \| 6.0 \| 102 \| 0.8620 \| 0.0362 \| 0.8620 \| 0.9284 \| \| No log \| 6.1176 \| 104 \| 0.8316 \| 0.0697 \| 0.8316 \| 0.9119 \| \| No log \| 6.2353 \| 106 \| 0.8263 \| 0.2345 \| 0.8263 \| 0.9090 \| \| No log \| 6.3529 \| 108 \| 0.8755 \| 0.2604 \| 0.8755 \| 0.9357 \| \| No log \| 6.4706 \| 110 \| 0.8392 \| 0.2171 \| 0.8392 \| 0.9161 \| \| No log \| 6.5882 \| 112 \| 0.8389 \| 0.2063 \| 0.8389 \| 0.9159 \| \| No log \| 6.7059 \| 114 \| 0.8407 \| 0.0 \| 0.8407 \| 0.9169 \| \| No log \| 6.8235 \| 116 \| 0.7234 \| 0.1829 \| 0.7234 \| 0.8505 \| \| No log \| 6.9412 \| 118 \| 0.6556 \| 0.2819 \| 0.6556 \| 0.8097 \| \| No log \| 7.0588 \| 120 \| 0.6881 \| 0.3950 \| 0.6881 \| 0.8295 \| \| No log \| 7.1765 \| 122 \| 0.8563 \| 0.3499 \| 0.8563 \| 0.9254 \| \| No log \| 7.2941 \| 124 \| 0.9866 \| 0.2921 \| 0.9866 \| 0.9933 \| \| No log \| 7.4118 \| 126 \| 0.9981 \| 0.2464 \| 0.9981 \| 0.9991 \| \| No log \| 7.5294 \| 128 \| 1.0640 \| 0.1354 \| 1.0640 \| 1.0315 \| \| No log \| 7.6471 \| 130 \| 1.5347 \| 0.1007 \| 1.5347 \| 1.2388 \| \| No log \| 7.7647 \| 132 \| 1.5733 \| 0.0790 \| 1.5733 \| 1.2543 \| \| No log \| 7.8824 \| 134 \| 1.2396 \| 0.1332 \| 1.2396 \| 1.1134 \| \| No log \| 8.0 \| 136 \| 0.9817 \| 0.0801 \| 0.9817 \| 0.9908 \| \| No log \| 8.1176 \| 138 \| 0.9364 \| 0.2832 \| 0.9364 \| 0.9677 \| \| No log \| 8.2353 \| 140 \| 0.8926 \| 0.3183 \| 0.8926 \| 0.9448 \| \| No log \| 8.3529 \| 142 \| 0.8516 \| 0.3221 \| 0.8516 \| 0.9228 \| \| No log \| 8.4706 \| 144 \| 0.8222 \| 0.2414 \| 0.8222 \| 0.9068 \| \| No log \| 8.5882 \| 146 \| 0.8010 \| 0.2813 \| 0.8010 \| 0.8950 \| \| No log \| 8.7059 \| 148 \| 0.7963 \| 0.2784 \| 0.7963 \| 0.8924 \| \| No log \| 8.8235 \| 150 \| 0.8079 \| 0.3372 \| 0.8079 \| 0.8989 \| \| No log \| 8.9412 \| 152 \| 0.8412 \| 0.3699 \| 0.8412 \| 0.9171 \| \| No log \| 9.0588 \| 154 \| 0.7978 \| 0.3637 \| 0.7978 \| 0.8932 \| \| No log \| 9.1765 \| 156 \| 0.7614 \| 0.3099 \| 0.7614 \| 0.8726 \| \| No log \| 9.2941 \| 158 \| 0.7245 \| 0.1699 \| 0.7245 \| 0.8512 \| \| No log \| 9.4118 \| 160 \| 0.7185 \| 0.1807 \| 0.7185 \| 0.8477 \| \| No log \| 9.5294 \| 162 \| 0.7381 \| 0.1268 \| 0.7381 \| 0.8592 \| \| No log \| 9.6471 \| 164 \| 0.7843 \| 0.2171 \| 0.7843 \| 0.8856 \| \| No log \| 9.7647 \| 166 \| 0.8367 \| 0.2328 \| 0.8367 \| 0.9147 \| \| No log \| 9.8824 \| 168 \| 0.8363 \| 0.1995 \| 0.8363 \| 0.9145 \| \| No log \| 10.0 \| 170 \| 0.8047 \| 0.2589 \| 0.8047 \| 0.8970 \| \| No log \| 10.1176 \| 172 \| 0.8180 \| 0.0652 \| 0.8180 \| 0.9044 \| \| No log \| 10.2353 \| 174 \| 0.8233 \| 0.0652 \| 0.8233 \| 0.9074 \| \| No log \| 10.3529 \| 176 \| 0.7997 \| 0.2027 \| 0.7997 \| 0.8942 \| \| No log \| 10.4706 \| 178 \| 0.8016 \| 0.3372 \| 0.8016 \| 0.8953 \| \| No log \| 10.5882 \| 180 \| 0.7845 \| 0.3819 \| 0.7845 \| 0.8857 \| \| No log \| 10.7059 \| 182 \| 0.6968 \| 0.3032 \| 0.6968 \| 0.8347 \| \| No log \| 10.8235 \| 184 \| 0.6736 \| 0.3425 \| 0.6736 \| 0.8208 \| \| No log \| 10.9412 \| 186 \| 0.7071 \| 0.3127 \| 0.7071 \| 0.8409 \| \| No log \| 11.0588 \| 188 \| 0.7794 \| 0.3372 \| 0.7794 \| 0.8828 \| \| No log \| 11.1765 \| 190 \| 0.8896 \| 0.3782 \| 0.8896 \| 0.9432 \| \| No log \| 11.2941 \| 192 \| 0.8603 \| 0.4251 \| 0.8603 \| 0.9275 \| \| No log \| 11.4118 \| 194 \| 0.7622 \| 0.2784 \| 0.7622 \| 0.8730 \| \| No log \| 11.5294 \| 196 \| 0.7462 \| 0.2683 \| 0.7462 \| 0.8638 \| \| No log \| 11.6471 \| 198 \| 0.7544 \| 0.2683 \| 0.7544 \| 0.8686 \| \| No log \| 11.7647 \| 200 \| 0.7524 \| 0.2319 \| 0.7524 \| 0.8674 \| \| No log \| 11.8824 \| 202 \| 0.8204 \| 0.4089 \| 0.8204 \| 0.9058 \| \| No log \| 12.0 \| 204 \| 0.8332 \| 0.3590 \| 0.8332 \| 0.9128 \| \| No log \| 12.1176 \| 206 \| 0.8053 \| 0.1264 \| 0.8053 \| 0.8974 \| \| No log \| 12.2353 \| 208 \| 0.8030 \| 0.2043 \| 0.8030 \| 0.8961 \| \| No log \| 12.3529 \| 210 \| 0.8035 \| 0.1051 \| 0.8035 \| 0.8964 \| \| No log \| 12.4706 \| 212 \| 0.7790 \| 0.2158 \| 0.7790 \| 0.8826 \| \| No log \| 12.5882 \| 214 \| 0.7441 \| 0.2319 \| 0.7441 \| 0.8626 \| \| No log \| 12.7059 \| 216 \| 0.7776 \| 0.3894 \| 0.7776 \| 0.8818 \| \| No log \| 12.8235 \| 218 \| 0.7996 \| 0.4014 \| 0.7996 \| 0.8942 \| \| No log \| 12.9412 \| 220 \| 0.7439 \| 0.4052 \| 0.7439 \| 0.8625 \| \| No log \| 13.0588 \| 222 \| 0.7111 \| 0.3471 \| 0.7111 \| 0.8433 \| \| No log \| 13.1765 \| 224 \| 0.6985 \| 0.3341 \| 0.6985 \| 0.8357 \| \| No log \| 13.2941 \| 226 \| 0.7284 \| 0.3545 \| 0.7284 \| 0.8535 \| \| No log \| 13.4118 \| 228 \| 0.8148 \| 0.3372 \| 0.8148 \| 0.9027 \| \| No log \| 13.5294 \| 230 \| 0.9035 \| 0.3519 \| 0.9035 \| 0.9505 \| \| No log \| 13.6471 \| 232 \| 0.8974 \| 0.2754 \| 0.8974 \| 0.9473 \| \| No log \| 13.7647 \| 234 \| 0.8592 \| 0.2847 \| 0.8592 \| 0.9269 \| \| No log \| 13.8824 \| 236 \| 0.8327 \| 0.3737 \| 0.8327 \| 0.9125 \| \| No log \| 14.0 \| 238 \| 0.8219 \| 0.3918 \| 0.8219 \| 0.9066 \| \| No log \| 14.1176 \| 240 \| 0.7738 \| 0.3032 \| 0.7738 \| 0.8797 \| \| No log \| 14.2353 \| 242 \| 0.7455 \| 0.3712 \| 0.7455 \| 0.8634 \| \| No log \| 14.3529 \| 244 \| 0.7875 \| 0.3302 \| 0.7875 \| 0.8874 \| \| No log \| 14.4706 \| 246 \| 0.8593 \| 0.3869 \| 0.8593 \| 0.9270 \| \| No log \| 14.5882 \| 248 \| 0.9272 \| 0.3825 \| 0.9272 \| 0.9629 \| \| No log \| 14.7059 \| 250 \| 0.8637 \| 0.3538 \| 0.8637 \| 0.9294 \| \| No log \| 14.8235 \| 252 \| 0.7736 \| 0.3894 \| 0.7736 \| 0.8795 \| \| No log \| 14.9412 \| 254 \| 0.7035 \| 0.3594 \| 0.7035 \| 0.8387 \| \| No log \| 15.0588 \| 256 \| 0.6780 \| 0.4001 \| 0.6780 \| 0.8234 \| \| No log \| 15.1765 \| 258 \| 0.6778 \| 0.4291 \| 0.6778 \| 0.8233 \| \| No log \| 15.2941 \| 260 \| 0.6805 \| 0.4001 \| 0.6805 \| 0.8249 \| \| No log \| 15.4118 \| 262 \| 0.7081 \| 0.4158 \| 0.7081 \| 0.8415 \| \| No log \| 15.5294 \| 264 \| 0.7434 \| 0.3868 \| 0.7434 \| 0.8622 \| \| No log \| 15.6471 \| 266 \| 0.8074 \| 0.3746 \| 0.8074 \| 0.8986 \| \| No log \| 15.7647 \| 268 \| 0.8077 \| 0.3699 \| 0.8077 \| 0.8987 \| \| No log \| 15.8824 \| 270 \| 0.8001 \| 0.4014 \| 0.8001 \| 0.8945 \| \| No log \| 16.0 \| 272 \| 0.7637 \| 0.3770 \| 0.7637 \| 0.8739 \| \| No log \| 16.1176 \| 274 \| 0.7132 \| 0.3518 \| 0.7132 \| 0.8445 \| \| No log \| 16.2353 \| 276 \| 0.7116 \| 0.3238 \| 0.7116 \| 0.8436 \| \| No log \| 16.3529 \| 278 \| 0.7267 \| 0.3238 \| 0.7267 \| 0.8525 \| \| No log \| 16.4706 \| 280 \| 0.7366 \| 0.3099 \| 0.7366 \| 0.8583 \| \| No log \| 16.5882 \| 282 \| 0.7447 \| 0.3712 \| 0.7447 \| 0.8630 \| \| No log \| 16.7059 \| 284 \| 0.7767 \| 0.3712 \| 0.7767 \| 0.8813 \| \| No log \| 16.8235 \| 286 \| 0.8651 \| 0.3675 \| 0.8651 \| 0.9301 \| \| No log \| 16.9412 \| 288 \| 0.8676 \| 0.3606 \| 0.8676 \| 0.9315 \| \| No log \| 17.0588 \| 290 \| 0.8148 \| 0.3819 \| 0.8148 \| 0.9027 \| \| No log \| 17.1765 \| 292 \| 0.8137 \| 0.3637 \| 0.8137 \| 0.9021 \| \| No log \| 17.2941 \| 294 \| 0.7826 \| 0.3737 \| 0.7826 \| 0.8847 \| \| No log \| 17.4118 \| 296 \| 0.7781 \| 0.2847 \| 0.7781 \| 0.8821 \| \| No log \| 17.5294 \| 298 \| 0.7970 \| 0.2319 \| 0.7970 \| 0.8927 \| \| No log \| 17.6471 \| 300 \| 0.8518 \| 0.1918 \| 0.8518 \| 0.9230 \| \| No log \| 17.7647 \| 302 \| 0.9251 \| 0.1866 \| 0.9251 \| 0.9618 \| \| No log \| 17.8824 \| 304 \| 0.9407 \| 0.1866 \| 0.9407 \| 0.9699 \| \| No log \| 18.0 \| 306 \| 0.8990 \| 0.1918 \| 0.8990 \| 0.9482 \| \| No log \| 18.1176 \| 308 \| 0.8168 \| 0.2847 \| 0.8168 \| 0.9038 \| \| No log \| 18.2353 \| 310 \| 0.7374 \| 0.3919 \| 0.7374 \| 0.8587 \| \| No log \| 18.3529 \| 312 \| 0.7206 \| 0.3919 \| 0.7206 \| 0.8489 \| \| No log \| 18.4706 \| 314 \| 0.7563 \| 0.4684 \| 0.7563 \| 0.8696 \| \| No log \| 18.5882 \| 316 \| 0.7759 \| 0.4684 \| 0.7759 \| 0.8809 \| \| No log \| 18.7059 \| 318 \| 0.7929 \| 0.4684 \| 0.7929 \| 0.8905 \| \| No log \| 18.8235 \| 320 \| 0.7879 \| 0.3572 \| 0.7879 \| 0.8876 \| \| No log \| 18.9412 \| 322 \| 0.7850 \| 0.3572 \| 0.7850 \| 0.8860 \| \| No log \| 19.0588 \| 324 \| 0.7964 \| 0.4270 \| 0.7964 \| 0.8924 \| \| No log \| 19.1765 \| 326 \| 0.8016 \| 0.3996 \| 0.8016 \| 0.8953 \| \| No log \| 19.2941 \| 328 \| 0.8174 \| 0.3590 \| 0.8174 \| 0.9041 \| \| No log \| 19.4118 \| 330 \| 0.7876 \| 0.4247 \| 0.7876 \| 0.8874 \| \| No log \| 19.5294 \| 332 \| 0.8040 \| 0.3770 \| 0.8040 \| 0.8966 \| \| No log \| 19.6471 \| 334 \| 0.7851 \| 0.3770 \| 0.7851 \| 0.8861 \| \| No log \| 19.7647 \| 336 \| 0.7121 \| 0.4592 \| 0.7121 \| 0.8439 \| \| No log \| 19.8824 \| 338 \| 0.6655 \| 0.2819 \| 0.6655 \| 0.8158 \| \| No log \| 20.0 \| 340 \| 0.6671 \| 0.2819 \| 0.6671 \| 0.8167 \| \| No log \| 20.1176 \| 342 \| 0.6997 \| 0.3782 \| 0.6997 \| 0.8365 \| \| No log \| 20.2353 \| 344 \| 0.7596 \| 0.4076 \| 0.7596 \| 0.8715 \| \| No log \| 20.3529 \| 346 \| 0.8016 \| 0.3372 \| 0.8016 \| 0.8953 \| \| No log \| 20.4706 \| 348 \| 0.8415 \| 0.3372 \| 0.8415 \| 0.9173 \| \| No log \| 20.5882 \| 350 \| 0.8207 \| 0.3519 \| 0.8207 \| 0.9059 \| \| No log \| 20.7059 \| 352 \| 0.8039 \| 0.3519 \| 0.8039 \| 0.8966 \| \| No log \| 20.8235 \| 354 \| 0.7602 \| 0.3544 \| 0.7602 \| 0.8719 \| \| No log \| 20.9412 \| 356 \| 0.7442 \| 0.4190 \| 0.7442 \| 0.8626 \| \| No log \| 21.0588 \| 358 \| 0.7384 \| 0.4167 \| 0.7384 \| 0.8593 \| \| No log \| 21.1765 \| 360 \| 0.7168 \| 0.4479 \| 0.7168 \| 0.8467 \| \| No log \| 21.2941 \| 362 \| 0.7191 \| 0.4479 \| 0.7191 \| 0.8480 \| \| No log \| 21.4118 \| 364 \| 0.7384 \| 0.4576 \| 0.7384 \| 0.8593 \| \| No log \| 21.5294 \| 366 \| 0.7592 \| 0.4167 \| 0.7592 \| 0.8713 \| \| No log \| 21.6471 \| 368 \| 0.7503 \| 0.4576 \| 0.7503 \| 0.8662 \| \| No log \| 21.7647 \| 370 \| 0.7116 \| 0.4576 \| 0.7116 \| 0.8436 \| \| No log \| 21.8824 \| 372 \| 0.6735 \| 0.3755 \| 0.6735 \| 0.8207 \| \| No log \| 22.0 \| 374 \| 0.6573 \| 0.3123 \| 0.6573 \| 0.8107 \| \| No log \| 22.1176 \| 376 \| 0.6633 \| 0.3976 \| 0.6633 \| 0.8144 \| \| No log \| 22.2353 \| 378 \| 0.7019 \| 0.4753 \| 0.7019 \| 0.8378 \| \| No log \| 22.3529 \| 380 \| 0.7806 \| 0.4167 \| 0.7806 \| 0.8835 \| \| No log \| 22.4706 \| 382 \| 0.9162 \| 0.3913 \| 0.9162 \| 0.9572 \| \| No log \| 22.5882 \| 384 \| 0.9838 \| 0.3128 \| 0.9838 \| 0.9919 \| \| No log \| 22.7059 \| 386 \| 0.9348 \| 0.3012 \| 0.9348 \| 0.9668 \| \| No log \| 22.8235 \| 388 \| 0.8444 \| 0.2883 \| 0.8444 \| 0.9189 \| \| No log \| 22.9412 \| 390 \| 0.7869 \| 0.2145 \| 0.7869 \| 0.8871 \| \| No log \| 23.0588 \| 392 \| 0.7715 \| 0.1863 \| 0.7715 \| 0.8783 \| \| No log \| 23.1765 \| 394 \| 0.7584 \| 0.2206 \| 0.7584 \| 0.8709 \| \| No log \| 23.2941 \| 396 \| 0.7867 \| 0.3020 \| 0.7867 \| 0.8870 \| \| No log \| 23.4118 \| 398 \| 0.8898 \| 0.3972 \| 0.8898 \| 0.9433 \| \| No log \| 23.5294 \| 400 \| 0.9919 \| 0.3473 \| 0.9919 \| 0.9960 \| \| No log \| 23.6471 \| 402 \| 1.0320 \| 0.2781 \| 1.0320 \| 1.0159 \| \| No log \| 23.7647 \| 404 \| 1.0073 \| 0.2387 \| 1.0073 \| 1.0036 \| \| No log \| 23.8824 \| 406 \| 0.9323 \| 0.3060 \| 0.9323 \| 0.9656 \| \| No log \| 24.0 \| 408 \| 0.9247 \| 0.2532 \| 0.9247 \| 0.9616 \| \| No log \| 24.1176 \| 410 \| 0.9271 \| 0.2838 \| 0.9271 \| 0.9629 \| \| No log \| 24.2353 \| 412 \| 0.9283 \| 0.3106 \| 0.9283 \| 0.9635 \| \| No log \| 24.3529 \| 414 \| 0.9059 \| 0.2813 \| 0.9059 \| 0.9518 \| \| No log \| 24.4706 \| 416 \| 0.9277 \| 0.3344 \| 0.9277 \| 0.9632 \| \| No log \| 24.5882 \| 418 \| 0.9200 \| 0.3918 \| 0.9200 \| 0.9591 \| \| No log \| 24.7059 \| 420 \| 0.8989 \| 0.3991 \| 0.8989 \| 0.9481 \| \| No log \| 24.8235 \| 422 \| 0.8600 \| 0.3894 \| 0.8600 \| 0.9274 \| \| No log \| 24.9412 \| 424 \| 0.8149 \| 0.4392 \| 0.8149 \| 0.9027 \| \| No log \| 25.0588 \| 426 \| 0.7731 \| 0.4243 \| 0.7731 \| 0.8793 \| \| No log \| 25.1765 \| 428 \| 0.7624 \| 0.3976 \| 0.7624 \| 0.8731 \| \| No log \| 25.2941 \| 430 \| 0.7936 \| 0.4243 \| 0.7936 \| 0.8909 \| \| No log \| 25.4118 \| 432 \| 0.8036 \| 0.3622 \| 0.8036 \| 0.8964 \| \| No log \| 25.5294 \| 434 \| 0.8172 \| 0.3224 \| 0.8172 \| 0.9040 \| \| No log \| 25.6471 \| 436 \| 0.7936 \| 0.3224 \| 0.7936 \| 0.8908 \| \| No log \| 25.7647 \| 438 \| 0.7833 \| 0.3498 \| 0.7833 \| 0.8851 \| \| No log \| 25.8824 \| 440 \| 0.7797 \| 0.4663 \| 0.7797 \| 0.8830 \| \| No log \| 26.0 \| 442 \| 0.8268 \| 0.3843 \| 0.8268 \| 0.9093 \| \| No log \| 26.1176 \| 444 \| 0.8310 \| 0.3843 \| 0.8310 \| 0.9116 \| \| No log \| 26.2353 \| 446 \| 0.7962 \| 0.4753 \| 0.7962 \| 0.8923 \| \| No log \| 26.3529 \| 448 \| 0.7693 \| 0.4753 \| 0.7693 \| 0.8771 \| \| No log \| 26.4706 \| 450 \| 0.7771 \| 0.4479 \| 0.7771 \| 0.8816 \| \| No log \| 26.5882 \| 452 \| 0.8233 \| 0.4052 \| 0.8233 \| 0.9074 \| \| No log \| 26.7059 \| 454 \| 0.8303 \| 0.3637 \| 0.8303 \| 0.9112 \| \| No log \| 26.8235 \| 456 \| 0.7922 \| 0.4479 \| 0.7922 \| 0.8901 \| \| No log \| 26.9412 \| 458 \| 0.7423 \| 0.3622 \| 0.7423 \| 0.8616 \| \| No log \| 27.0588 \| 460 \| 0.7357 \| 0.2981 \| 0.7357 \| 0.8577 \| \| No log \| 27.1765 \| 462 \| 0.7645 \| 0.3594 \| 0.7645 \| 0.8744 \| \| No log \| 27.2941 \| 464 \| 0.8427 \| 0.3972 \| 0.8427 \| 0.9180 \| \| No log \| 27.4118 \| 466 \| 0.9057 \| 0.3675 \| 0.9057 \| 0.9517 \| \| No log \| 27.5294 \| 468 \| 0.9028 \| 0.3675 \| 0.9028 \| 0.9501 \| \| No log \| 27.6471 \| 470 \| 0.8554 \| 0.3894 \| 0.8554 \| 0.9249 \| \| No log \| 27.7647 \| 472 \| 0.8067 \| 0.4247 \| 0.8067 \| 0.8982 \| \| No log \| 27.8824 \| 474 \| 0.8030 \| 0.4247 \| 0.8030 \| 0.8961 \| \| No log \| 28.0 \| 476 \| 0.7978 \| 0.4247 \| 0.7978 \| 0.8932 \| \| No log \| 28.1176 \| 478 \| 0.8022 \| 0.4052 \| 0.8022 \| 0.8957 \| \| No log \| 28.2353 \| 480 \| 0.8193 \| 0.3972 \| 0.8193 \| 0.9051 \| \| No log \| 28.3529 \| 482 \| 0.8121 \| 0.4479 \| 0.8121 \| 0.9012 \| \| No log \| 28.4706 \| 484 \| 0.8070 \| 0.4479 \| 0.8070 \| 0.8984 \| \| No log \| 28.5882 \| 486 \| 0.7850 \| 0.4219 \| 0.7850 \| 0.8860 \| \| No log \| 28.7059 \| 488 \| 0.7744 \| 0.4502 \| 0.7744 \| 0.8800 \| \| No log \| 28.8235 \| 490 \| 0.7633 \| 0.4502 \| 0.7633 \| 0.8737 \| \| No log \| 28.9412 \| 492 \| 0.7753 \| 0.4774 \| 0.7753 \| 0.8805 \| \| No log \| 29.0588 \| 494 \| 0.8084 \| 0.4076 \| 0.8084 \| 0.8991 \| \| No log \| 29.1765 \| 496 \| 0.8381 \| 0.4330 \| 0.8381 \| 0.9155 \| \| No log \| 29.2941 \| 498 \| 0.8586 \| 0.4409 \| 0.8586 \| 0.9266 \| \| 0.3134 \| 29.4118 \| 500 \| 0.8490 \| 0.4224 \| 0.8490 \| 0.9214 \| \| 0.3134 \| 29.5294 \| 502 \| 0.8322 \| 0.3972 \| 0.8322 \| 0.9123 \| \| 0.3134 \| 29.6471 \| 504 \| 0.7995 \| 0.4479 \| 0.7995 \| 0.8942 \| \| 0.3134 \| 29.7647 \| 506 \| 0.7992 \| 0.4845 \| 0.7992 \| 0.8940 \| \| 0.3134 \| 29.8824 \| 508 \| 0.8180 \| 0.4414 \| 0.8180 \| 0.9044 \| \| 0.3134 \| 30.0 \| 510 \| 0.8297 \| 0.4414 \| 0.8297 \| 0.9109 \| \| 0.3134 \| 30.1176 \| 512 \| 0.8231 \| 0.3649 \| 0.8231 \| 0.9072 \| \| 0.3134 \| 30.2353 \| 514 \| 0.8386 \| 0.3737 \| 0.8386 \| 0.9158 \| \| 0.3134 \| 30.3529 \| 516 \| 0.8447 \| 0.3737 \| 0.8447 \| 0.9191 \| \| 0.3134 \| 30.4706 \| 518 \| 0.8344 \| 0.3471 \| 0.8344 \| 0.9135 \| \| 0.3134 \| 30.5882 \| 520 \| 0.7964 \| 0.4330 \| 0.7964 \| 0.8924 \| \| 0.3134 \| 30.7059 \| 522 \| 0.7581 \| 0.3782 \| 0.7581 \| 0.8707 \| \| 0.3134 \| 30.8235 \| 524 \| 0.7483 \| 0.3782 \| 0.7483 \| 0.8651 \| \| 0.3134 \| 30.9412 \| 526 \| 0.7706 \| 0.4414 \| 0.7706 \| 0.8779 \| \| 0.3134 \| 31.0588 \| 528 \| 0.8221 \| 0.3972 \| 0.8221 \| 0.9067 \| \| 0.3134 \| 31.1765 \| 530 \| 0.8522 \| 0.3972 \| 0.8522 \| 0.9231 \| \| 0.3134 \| 31.2941 \| 532 \| 0.8332 \| 0.4392 \| 0.8332 \| 0.9128 \| \| 0.3134 \| 31.4118 \| 534 \| 0.7971 \| 0.4219 \| 0.7971 \| 0.8928 \| \| 0.3134 \| 31.5294 \| 536 \| 0.7689 \| 0.3950 \| 0.7689 \| 0.8768 \| \| 0.3134 \| 31.6471 \| 538 \| 0.7299 \| 0.3976 \| 0.7299 \| 0.8543 \| \| 0.3134 \| 31.7647 \| 540 \| 0.7136 \| 0.3976 \| 0.7136 \| 0.8447 \| \| 0.3134 \| 31.8824 \| 542 \| 0.7187 \| 0.3341 \| 0.7187 \| 0.8478 \| ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.0+cu118 - Datasets 2.21.0 - Tokenizers 0.19.1
kostiantynk1205/2dd26e7f-9d61-472b-959a-69573b14c63f	kostiantynk1205	2025-01-21T12:44:12Z	6	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:openlm-research/open_llama_3b", "base_model:adapter:openlm-research/open_llama_3b", "license:apache-2.0", "region:us" ]	null	2025-01-21T12:32:47Z	--- library_name: peft license: apache-2.0 base_model: openlm-research/open_llama_3b tags: - axolotl - generated_from_trainer model-index: - name: 2dd26e7f-9d61-472b-959a-69573b14c63f results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: openlm-research/open_llama_3b bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 88305afcc505bc32_train_data.json ds_type: json format: custom path: /workspace/input_data/88305afcc505bc32_train_data.json type: field_input: context field_instruction: question field_output: answer format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: kostiantynk1205/2dd26e7f-9d61-472b-959a-69573b14c63f hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/88305afcc505bc32_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 special_tokens: pad_token: </s> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 3c103d36-11cb-4530-bc3a-9d1b166132e7 wandb_project: Birthday-SN56-6-Gradients-On-Demand wandb_run: your_name wandb_runid: 3c103d36-11cb-4530-bc3a-9d1b166132e7 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # 2dd26e7f-9d61-472b-959a-69573b14c63f This model is a fine-tuned version of [openlm-research/open_llama_3b](https://huggingface.co/openlm-research/open_llama_3b) on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.0551 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 2.8039 \| 0.0001 \| 1 \| 3.1952 \| \| 4.0102 \| 0.0002 \| 3 \| 3.1831 \| \| 2.2182 \| 0.0004 \| 6 \| 2.9729 \| \| 1.3269 \| 0.0006 \| 9 \| 2.0551 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
thalllsssss/0f03e4cb-bf5c-44f3-871d-201307142e82	thalllsssss	2025-01-21T12:42:58Z	7	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:TinyLlama/TinyLlama-1.1B-Chat-v1.0", "base_model:adapter:TinyLlama/TinyLlama-1.1B-Chat-v1.0", "license:apache-2.0", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-21T12:30:41Z	--- library_name: peft license: apache-2.0 base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0 tags: - axolotl - generated_from_trainer model-index: - name: 0f03e4cb-bf5c-44f3-871d-201307142e82 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 9c321e8cf88f16f0_train_data.json ds_type: json format: custom path: /workspace/input_data/9c321e8cf88f16f0_train_data.json type: field_input: input field_instruction: instruction field_output: output format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: thalllsssss/0f03e4cb-bf5c-44f3-871d-201307142e82 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/9c321e8cf88f16f0_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 1a9527a4-dbed-4d09-b3dc-303d2f7479cd wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 1a9527a4-dbed-4d09-b3dc-303d2f7479cd warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details><br> # 0f03e4cb-bf5c-44f3-871d-201307142e82 This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.1885 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 1.2752 \| 0.0326 \| 200 \| 1.1885 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
fedovtt/8fc9f7fb-2a88-4444-a575-f1294e1b3b5d	fedovtt	2025-01-21T12:41:57Z	7	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "custom_code", "base_model:NousResearch/Yarn-Llama-2-13b-64k", "base_model:adapter:NousResearch/Yarn-Llama-2-13b-64k", "region:us" ]	null	2025-01-21T11:48:38Z	--- library_name: peft base_model: NousResearch/Yarn-Llama-2-13b-64k tags: - axolotl - generated_from_trainer model-index: - name: 8fc9f7fb-2a88-4444-a575-f1294e1b3b5d results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: NousResearch/Yarn-Llama-2-13b-64k bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 9eb6b8bdf2350702_train_data.json ds_type: json format: custom path: /workspace/input_data/9eb6b8bdf2350702_train_data.json type: field_input: '' field_instruction: Text field_output: Clean_Text format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: 1 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: false hub_model_id: fedovtt/8fc9f7fb-2a88-4444-a575-f1294e1b3b5d hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 78GiB max_steps: 30 micro_batch_size: 2 mlflow_experiment_name: /tmp/9eb6b8bdf2350702_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 2d1a479d-63b0-4baa-834e-801f81f8def7 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 2d1a479d-63b0-4baa-834e-801f81f8def7 warmup_steps: 10 weight_decay: 0.01 xformers_attention: true ``` </details><br> # 8fc9f7fb-2a88-4444-a575-f1294e1b3b5d This model is a fine-tuned version of [NousResearch/Yarn-Llama-2-13b-64k](https://huggingface.co/NousResearch/Yarn-Llama-2-13b-64k) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.1936 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 30 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| No log \| 0.0002 \| 1 \| 1.5564 \| \| 6.24 \| 0.0012 \| 5 \| 1.4933 \| \| 5.5815 \| 0.0024 \| 10 \| 1.3498 \| \| 4.9161 \| 0.0036 \| 15 \| 1.2571 \| \| 4.7732 \| 0.0048 \| 20 \| 1.2136 \| \| 4.7155 \| 0.0061 \| 25 \| 1.1968 \| \| 4.8142 \| 0.0073 \| 30 \| 1.1936 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
nadejdatarabukina/2328ba71-018b-406a-9616-710264e1f406	nadejdatarabukina	2025-01-21T12:41:54Z	6	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:TinyLlama/TinyLlama-1.1B-Chat-v1.0", "base_model:adapter:TinyLlama/TinyLlama-1.1B-Chat-v1.0", "license:apache-2.0", "region:us" ]	null	2025-01-21T12:30:40Z	--- library_name: peft license: apache-2.0 base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0 tags: - axolotl - generated_from_trainer model-index: - name: 2328ba71-018b-406a-9616-710264e1f406 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 9c321e8cf88f16f0_train_data.json ds_type: json format: custom path: /workspace/input_data/9c321e8cf88f16f0_train_data.json type: field_input: input field_instruction: instruction field_output: output format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: null eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: false hub_model_id: nadejdatarabukina/2328ba71-018b-406a-9616-710264e1f406 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 75GiB max_steps: 30 micro_batch_size: 2 mlflow_experiment_name: /tmp/9c321e8cf88f16f0_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 1a9527a4-dbed-4d09-b3dc-303d2f7479cd wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 1a9527a4-dbed-4d09-b3dc-303d2f7479cd warmup_steps: 10 weight_decay: 0.01 xformers_attention: true ``` </details><br> # 2328ba71-018b-406a-9616-710264e1f406 This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.4001 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 30 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| No log \| 0.0002 \| 1 \| 1.6018 \| \| 1.4712 \| 0.0008 \| 5 \| 1.5746 \| \| 1.485 \| 0.0016 \| 10 \| 1.4882 \| \| 1.3159 \| 0.0024 \| 15 \| 1.4275 \| \| 1.3649 \| 0.0033 \| 20 \| 1.4139 \| \| 1.5573 \| 0.0041 \| 25 \| 1.4024 \| \| 1.3646 \| 0.0049 \| 30 \| 1.4001 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
datlaaaaaaa/daac2d22-2b87-4368-98d4-0bc82576b148	datlaaaaaaa	2025-01-21T12:41:26Z	6	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:NousResearch/Nous-Hermes-llama-2-7b", "base_model:adapter:NousResearch/Nous-Hermes-llama-2-7b", "license:mit", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-21T11:41:30Z	--- library_name: peft license: mit base_model: NousResearch/Nous-Hermes-llama-2-7b tags: - axolotl - generated_from_trainer model-index: - name: daac2d22-2b87-4368-98d4-0bc82576b148 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: NousResearch/Nous-Hermes-llama-2-7b bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - db35a4b2827972f9_train_data.json ds_type: json format: custom path: /workspace/input_data/db35a4b2827972f9_train_data.json type: field_input: rejected field_instruction: context field_output: chosen format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: datlaaaaaaa/daac2d22-2b87-4368-98d4-0bc82576b148 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/db35a4b2827972f9_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 881827a9-7bb9-4a3a-bfa5-bc8cbc8f588f wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 881827a9-7bb9-4a3a-bfa5-bc8cbc8f588f warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details><br> # daac2d22-2b87-4368-98d4-0bc82576b148 This model is a fine-tuned version of [NousResearch/Nous-Hermes-llama-2-7b](https://huggingface.co/NousResearch/Nous-Hermes-llama-2-7b) on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.1089 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 1.879 \| 0.0294 \| 200 \| 2.1089 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
great0001/b6c1df64-4838-486b-8a93-fee44f12a3b9	great0001	2025-01-21T12:38:03Z	6	0	peft	[ "peft", "safetensors", "mistral", "axolotl", "generated_from_trainer", "base_model:unsloth/zephyr-sft", "base_model:adapter:unsloth/zephyr-sft", "license:apache-2.0", "region:us" ]	null	2025-01-21T12:16:00Z	--- library_name: peft license: apache-2.0 base_model: unsloth/zephyr-sft tags: - axolotl - generated_from_trainer model-index: - name: b6c1df64-4838-486b-8a93-fee44f12a3b9 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/zephyr-sft bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 6bb273fb8d3c0253_train_data.json ds_type: json format: custom path: /workspace/input_data/6bb273fb8d3c0253_train_data.json type: field_input: condition field_instruction: drugName field_output: review format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: great0001/b6c1df64-4838-486b-8a93-fee44f12a3b9 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/6bb273fb8d3c0253_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: f44a8599-bd2c-4b24-9468-fb17670debf8 wandb_project: Mine-SN56-20-Gradients-On-Demand wandb_run: your_name wandb_runid: f44a8599-bd2c-4b24-9468-fb17670debf8 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # b6c1df64-4838-486b-8a93-fee44f12a3b9 This model is a fine-tuned version of [unsloth/zephyr-sft](https://huggingface.co/unsloth/zephyr-sft) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 0.0 \| 0.0000 \| 1 \| nan \| \| 0.0 \| 0.0001 \| 3 \| nan \| \| 0.0 \| 0.0002 \| 6 \| nan \| \| 0.0 \| 0.0004 \| 9 \| nan \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
lesso04/41f6379f-db9e-4d10-acc0-68151277842e	lesso04	2025-01-21T12:35:42Z	6	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:NousResearch/Nous-Hermes-llama-2-7b", "base_model:adapter:NousResearch/Nous-Hermes-llama-2-7b", "license:mit", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-21T11:42:25Z	--- library_name: peft license: mit base_model: NousResearch/Nous-Hermes-llama-2-7b tags: - axolotl - generated_from_trainer model-index: - name: 41f6379f-db9e-4d10-acc0-68151277842e results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: NousResearch/Nous-Hermes-llama-2-7b bf16: true chat_template: llama3 datasets: - data_files: - db35a4b2827972f9_train_data.json ds_type: json format: custom path: /workspace/input_data/db35a4b2827972f9_train_data.json type: field_input: rejected field_instruction: context field_output: chosen format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: 2 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null flash_attention: false fp16: false fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: lesso04/41f6379f-db9e-4d10-acc0-68151277842e hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 25 micro_batch_size: 2 mlflow_experiment_name: /tmp/db35a4b2827972f9_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 881827a9-7bb9-4a3a-bfa5-bc8cbc8f588f wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 881827a9-7bb9-4a3a-bfa5-bc8cbc8f588f warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # 41f6379f-db9e-4d10-acc0-68151277842e This model is a fine-tuned version of [NousResearch/Nous-Hermes-llama-2-7b](https://huggingface.co/NousResearch/Nous-Hermes-llama-2-7b) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 25 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 0.0 \| 0.0001 \| 1 \| nan \| \| 0.0 \| 0.0007 \| 5 \| nan \| \| 0.0 \| 0.0015 \| 10 \| nan \| \| 0.0 \| 0.0022 \| 15 \| nan \| \| 0.0 \| 0.0029 \| 20 \| nan \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
nhung02/6e52b841-35b7-4d2f-867b-4cc3b62567c5	nhung02	2025-01-21T12:34:55Z	6	0	peft	[ "peft", "safetensors", "qwen2", "axolotl", "generated_from_trainer", "base_model:Qwen/Qwen1.5-0.5B", "base_model:adapter:Qwen/Qwen1.5-0.5B", "license:other", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-21T12:23:30Z	--- library_name: peft license: other base_model: Qwen/Qwen1.5-0.5B tags: - axolotl - generated_from_trainer model-index: - name: 6e52b841-35b7-4d2f-867b-4cc3b62567c5 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: Qwen/Qwen1.5-0.5B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 1de821793308c2b7_train_data.json ds_type: json format: custom path: /workspace/input_data/1de821793308c2b7_train_data.json type: field_input: context field_instruction: question field_output: answer format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: nhung02/6e52b841-35b7-4d2f-867b-4cc3b62567c5 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/1de821793308c2b7_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 7a0563f4-7af4-494e-9dbf-8003b312e74d wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 7a0563f4-7af4-494e-9dbf-8003b312e74d warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details><br> # 6e52b841-35b7-4d2f-867b-4cc3b62567c5 This model is a fine-tuned version of [Qwen/Qwen1.5-0.5B](https://huggingface.co/Qwen/Qwen1.5-0.5B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.5976 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 0.5455 \| 0.1792 \| 200 \| 0.5976 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
visdata/kw5	visdata	2025-01-21T12:34:36Z	16	0	transformers	[ "transformers", "safetensors", "llama", "text-generation", "conversational", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2025-01-21T12:29:51Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. 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visdata/kw6	visdata	2025-01-21T12:33:35Z	31	0	transformers	[ "transformers", "safetensors", "llama", "text-generation", "conversational", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2025-01-21T12:29:21Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. 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VenkataRanjith/llama-3-8b-Instruct-bnb-4bit-Ranjith-coderTrainer	VenkataRanjith	2025-01-21T12:33:24Z	20	0	transformers	[ "transformers", "gguf", "llama", "text-generation-inference", "unsloth", "en", "base_model:unsloth/llama-3-8b-Instruct-bnb-4bit", "base_model:quantized:unsloth/llama-3-8b-Instruct-bnb-4bit", "license:apache-2.0", "endpoints_compatible", "region:us", "conversational" ]	null	2025-01-21T12:29:29Z	--- base_model: unsloth/llama-3-8b-Instruct-bnb-4bit tags: - text-generation-inference - transformers - unsloth - llama - gguf license: apache-2.0 language: - en --- # Uploaded model - Developed by: VenkataRanjith - License: apache-2.0 - Finetuned from model : unsloth/llama-3-8b-Instruct-bnb-4bit This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
ClarenceDan/7848bbb3-caf9-490d-953b-ec68eb34e4ba	ClarenceDan	2025-01-21T12:31:38Z	6	0	peft	[ "peft", "safetensors", "falcon", "axolotl", "generated_from_trainer", "custom_code", "base_model:tiiuae/falcon-rw-1b", "base_model:adapter:tiiuae/falcon-rw-1b", "license:apache-2.0", "region:us" ]	null	2025-01-21T12:22:55Z	--- library_name: peft license: apache-2.0 base_model: tiiuae/falcon-rw-1b tags: - axolotl - generated_from_trainer model-index: - name: 7848bbb3-caf9-490d-953b-ec68eb34e4ba results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: tiiuae/falcon-rw-1b bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 8848939c923ff5a3_train_data.json ds_type: json format: custom path: /workspace/input_data/8848939c923ff5a3_train_data.json type: field_instruction: query field_output: answer format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: ClarenceDan/7848bbb3-caf9-490d-953b-ec68eb34e4ba hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/8848939c923ff5a3_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 special_tokens: pad_token: <\|endoftext\|> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 5acc14af-26c3-48ba-a29c-137d3b312a22 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 5acc14af-26c3-48ba-a29c-137d3b312a22 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # 7848bbb3-caf9-490d-953b-ec68eb34e4ba This model is a fine-tuned version of [tiiuae/falcon-rw-1b](https://huggingface.co/tiiuae/falcon-rw-1b) on the None dataset. It achieves the following results on the evaluation set: - Loss: 4.1183 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 22.7759 \| 0.0001 \| 1 \| 4.7796 \| \| 19.6007 \| 0.0002 \| 3 \| 4.7656 \| \| 16.7883 \| 0.0004 \| 6 \| 4.6233 \| \| 17.1448 \| 0.0006 \| 9 \| 4.1183 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
MayBashendy/ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k4_task7_organization	MayBashendy	2025-01-21T12:31:01Z	5	0	transformers	[ "transformers", "safetensors", "bert", "text-classification", "generated_from_trainer", "base_model:aubmindlab/bert-base-arabertv02", "base_model:finetune:aubmindlab/bert-base-arabertv02", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2025-01-21T12:27:04Z	--- library_name: transformers base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k4_task7_organization results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k4_task7_organization This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.7467 - Qwk: 0.0697 - Mse: 0.7467 - Rmse: 0.8641 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 100 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Qwk \| Mse \| Rmse \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:-------:\|:------:\|:------:\| \| No log \| 0.2 \| 2 \| 2.4280 \| -0.0646 \| 2.4280 \| 1.5582 \| \| No log \| 0.4 \| 4 \| 1.0881 \| 0.2875 \| 1.0881 \| 1.0431 \| \| No log \| 0.6 \| 6 \| 1.0474 \| -0.1517 \| 1.0474 \| 1.0234 \| \| No log \| 0.8 \| 8 \| 1.3691 \| -0.1706 \| 1.3691 \| 1.1701 \| \| No log \| 1.0 \| 10 \| 1.2737 \| -0.1706 \| 1.2737 \| 1.1286 \| \| No log \| 1.2 \| 12 \| 1.0007 \| 0.0283 \| 1.0007 \| 1.0003 \| \| No log \| 1.4 \| 14 \| 0.9275 \| 0.1183 \| 0.9275 \| 0.9630 \| \| No log \| 1.6 \| 16 \| 0.8221 \| 0.0428 \| 0.8221 \| 0.9067 \| \| No log \| 1.8 \| 18 \| 0.8087 \| 0.0 \| 0.8087 \| 0.8993 \| \| No log \| 2.0 \| 20 \| 0.7870 \| 0.0 \| 0.7870 \| 0.8871 \| \| No log \| 2.2 \| 22 \| 0.7671 \| 0.0 \| 0.7671 \| 0.8758 \| \| No log \| 2.4 \| 24 \| 0.7781 \| 0.0 \| 0.7781 \| 0.8821 \| \| No log \| 2.6 \| 26 \| 0.8770 \| -0.0320 \| 0.8770 \| 0.9365 \| \| No log \| 2.8 \| 28 \| 1.0144 \| -0.0076 \| 1.0144 \| 1.0072 \| \| No log \| 3.0 \| 30 \| 0.8925 \| -0.0700 \| 0.8925 \| 0.9447 \| \| No log \| 3.2 \| 32 \| 0.7964 \| 0.0481 \| 0.7964 \| 0.8924 \| \| No log \| 3.4 \| 34 \| 0.7693 \| 0.1674 \| 0.7693 \| 0.8771 \| \| No log \| 3.6 \| 36 \| 0.8324 \| 0.2285 \| 0.8324 \| 0.9123 \| \| No log \| 3.8 \| 38 \| 0.8665 \| 0.2319 \| 0.8665 \| 0.9309 \| \| No log \| 4.0 \| 40 \| 0.9179 \| -0.0045 \| 0.9179 \| 0.9581 \| \| No log \| 4.2 \| 42 \| 1.2147 \| 0.0367 \| 1.2147 \| 1.1021 \| \| No log \| 4.4 \| 44 \| 1.0913 \| -0.0033 \| 1.0913 \| 1.0446 \| \| No log \| 4.6 \| 46 \| 0.8643 \| 0.2063 \| 0.8643 \| 0.9297 \| \| No log \| 4.8 \| 48 \| 0.8581 \| 0.1550 \| 0.8581 \| 0.9263 \| \| No log \| 5.0 \| 50 \| 0.8888 \| 0.1815 \| 0.8888 \| 0.9428 \| \| No log \| 5.2 \| 52 \| 0.8949 \| 0.1766 \| 0.8949 \| 0.9460 \| \| No log \| 5.4 \| 54 \| 0.8389 \| 0.1699 \| 0.8389 \| 0.9159 \| \| No log \| 5.6 \| 56 \| 0.8780 \| 0.0410 \| 0.8780 \| 0.9370 \| \| No log \| 5.8 \| 58 \| 1.0235 \| 0.0975 \| 1.0235 \| 1.0117 \| \| No log \| 6.0 \| 60 \| 1.0118 \| 0.1259 \| 1.0118 \| 1.0059 \| \| No log \| 6.2 \| 62 \| 0.8937 \| 0.1498 \| 0.8937 \| 0.9454 \| \| No log \| 6.4 \| 64 \| 0.8858 \| 0.1541 \| 0.8858 \| 0.9412 \| \| No log \| 6.6 \| 66 \| 0.8867 \| 0.1541 \| 0.8867 \| 0.9416 \| \| No log \| 6.8 \| 68 \| 0.8969 \| 0.0930 \| 0.8969 \| 0.9471 \| \| No log \| 7.0 \| 70 \| 0.8899 \| 0.1760 \| 0.8899 \| 0.9434 \| \| No log \| 7.2 \| 72 \| 0.9062 \| 0.1866 \| 0.9062 \| 0.9519 \| \| No log \| 7.4 \| 74 \| 1.0502 \| 0.1271 \| 1.0502 \| 1.0248 \| \| No log \| 7.6 \| 76 \| 0.9760 \| 0.1712 \| 0.9760 \| 0.9879 \| \| No log \| 7.8 \| 78 \| 0.8485 \| 0.1303 \| 0.8485 \| 0.9211 \| \| No log \| 8.0 \| 80 \| 0.8510 \| 0.1379 \| 0.8510 \| 0.9225 \| \| No log \| 8.2 \| 82 \| 0.8621 \| 0.1969 \| 0.8621 \| 0.9285 \| \| No log \| 8.4 \| 84 \| 0.8653 \| 0.2747 \| 0.8653 \| 0.9302 \| \| No log \| 8.6 \| 86 \| 0.8761 \| 0.2987 \| 0.8761 \| 0.9360 \| \| No log \| 8.8 \| 88 \| 0.9020 \| 0.2593 \| 0.9020 \| 0.9498 \| \| No log \| 9.0 \| 90 \| 0.8735 \| 0.2888 \| 0.8735 \| 0.9346 \| \| No log \| 9.2 \| 92 \| 0.8758 \| 0.2256 \| 0.8758 \| 0.9359 \| \| No log \| 9.4 \| 94 \| 0.8433 \| 0.2936 \| 0.8433 \| 0.9183 \| \| No log \| 9.6 \| 96 \| 0.8244 \| 0.3296 \| 0.8244 \| 0.9080 \| \| No log \| 9.8 \| 98 \| 0.8399 \| 0.3060 \| 0.8399 \| 0.9165 \| \| No log \| 10.0 \| 100 \| 0.8450 \| 0.3060 \| 0.8450 \| 0.9192 \| \| No log \| 10.2 \| 102 \| 0.8358 \| 0.3478 \| 0.8358 \| 0.9142 \| \| No log \| 10.4 \| 104 \| 0.9045 \| 0.0678 \| 0.9045 \| 0.9511 \| \| No log \| 10.6 \| 106 \| 0.8931 \| 0.0702 \| 0.8931 \| 0.9450 \| \| No log \| 10.8 \| 108 \| 0.8382 \| 0.1379 \| 0.8382 \| 0.9155 \| \| No log \| 11.0 \| 110 \| 0.8312 \| 0.2475 \| 0.8312 \| 0.9117 \| \| No log \| 11.2 \| 112 \| 0.8191 \| 0.2360 \| 0.8191 \| 0.9050 \| \| No log \| 11.4 \| 114 \| 0.8313 \| 0.1797 \| 0.8313 \| 0.9118 \| \| No log \| 11.6 \| 116 \| 0.8490 \| 0.1179 \| 0.8490 \| 0.9214 \| \| No log \| 11.8 \| 118 \| 0.8143 \| 0.1179 \| 0.8143 \| 0.9024 \| \| No log \| 12.0 \| 120 \| 0.7943 \| 0.3002 \| 0.7943 \| 0.8912 \| \| No log \| 12.2 \| 122 \| 0.7994 \| 0.2973 \| 0.7994 \| 0.8941 \| \| No log \| 12.4 \| 124 \| 0.8554 \| 0.2633 \| 0.8554 \| 0.9249 \| \| No log \| 12.6 \| 126 \| 0.8489 \| 0.2633 \| 0.8489 \| 0.9213 \| \| No log \| 12.8 \| 128 \| 0.8310 \| 0.2561 \| 0.8310 \| 0.9116 \| \| No log \| 13.0 \| 130 \| 0.8112 \| 0.1471 \| 0.8112 \| 0.9006 \| \| No log \| 13.2 \| 132 \| 0.8178 \| 0.1697 \| 0.8178 \| 0.9043 \| \| No log \| 13.4 \| 134 \| 0.9047 \| 0.2899 \| 0.9047 \| 0.9511 \| \| No log \| 13.6 \| 136 \| 1.0909 \| 0.1142 \| 1.0909 \| 1.0445 \| \| No log \| 13.8 \| 138 \| 1.0766 \| 0.1743 \| 1.0766 \| 1.0376 \| \| No log \| 14.0 \| 140 \| 0.9207 \| 0.2495 \| 0.9207 \| 0.9595 \| \| No log \| 14.2 \| 142 \| 0.8547 \| 0.2072 \| 0.8547 \| 0.9245 \| \| No log \| 14.4 \| 144 \| 0.9249 \| 0.1156 \| 0.9249 \| 0.9617 \| \| No log \| 14.6 \| 146 \| 0.8786 \| 0.1494 \| 0.8786 \| 0.9373 \| \| No log \| 14.8 \| 148 \| 0.8118 \| 0.1760 \| 0.8118 \| 0.9010 \| \| No log \| 15.0 \| 150 \| 0.8315 \| 0.2261 \| 0.8315 \| 0.9119 \| \| No log \| 15.2 \| 152 \| 0.8498 \| 0.1740 \| 0.8498 \| 0.9218 \| \| No log \| 15.4 \| 154 \| 0.8157 \| 0.2590 \| 0.8157 \| 0.9031 \| \| No log \| 15.6 \| 156 \| 0.8095 \| 0.2424 \| 0.8095 \| 0.8997 \| \| No log \| 15.8 \| 158 \| 0.8147 \| 0.1870 \| 0.8147 \| 0.9026 \| \| No log \| 16.0 \| 160 \| 0.7790 \| 0.0741 \| 0.7790 \| 0.8826 \| \| No log \| 16.2 \| 162 \| 0.7751 \| 0.2353 \| 0.7751 \| 0.8804 \| \| No log \| 16.4 \| 164 \| 0.8274 \| 0.2995 \| 0.8274 \| 0.9096 \| \| No log \| 16.6 \| 166 \| 0.8519 \| 0.2521 \| 0.8519 \| 0.9230 \| \| No log \| 16.8 \| 168 \| 0.7997 \| 0.2558 \| 0.7997 \| 0.8943 \| \| No log \| 17.0 \| 170 \| 0.7449 \| 0.1386 \| 0.7449 \| 0.8631 \| \| No log \| 17.2 \| 172 \| 0.7760 \| 0.1873 \| 0.7760 \| 0.8809 \| \| No log \| 17.4 \| 174 \| 0.7825 \| 0.2926 \| 0.7825 \| 0.8846 \| \| No log \| 17.6 \| 176 \| 0.7185 \| 0.1133 \| 0.7185 \| 0.8477 \| \| No log \| 17.8 \| 178 \| 0.6876 \| 0.1456 \| 0.6876 \| 0.8292 \| \| No log \| 18.0 \| 180 \| 0.7060 \| 0.2685 \| 0.7060 \| 0.8402 \| \| No log \| 18.2 \| 182 \| 0.7141 \| 0.2471 \| 0.7141 \| 0.8450 \| \| No log \| 18.4 \| 184 \| 0.7117 \| 0.2652 \| 0.7117 \| 0.8436 \| \| No log \| 18.6 \| 186 \| 0.7238 \| 0.2287 \| 0.7238 \| 0.8508 \| \| No log \| 18.8 \| 188 \| 0.7424 \| 0.2182 \| 0.7424 \| 0.8617 \| \| No log \| 19.0 \| 190 \| 0.7592 \| 0.2132 \| 0.7592 \| 0.8713 \| \| No log \| 19.2 \| 192 \| 0.7723 \| 0.2772 \| 0.7723 \| 0.8788 \| \| No log \| 19.4 \| 194 \| 0.7658 \| 0.2458 \| 0.7658 \| 0.8751 \| \| No log \| 19.6 \| 196 \| 0.7629 \| 0.2405 \| 0.7629 \| 0.8735 \| \| No log \| 19.8 \| 198 \| 0.7542 \| 0.2749 \| 0.7542 \| 0.8684 \| \| No log \| 20.0 \| 200 \| 0.8205 \| 0.2995 \| 0.8205 \| 0.9058 \| \| No log \| 20.2 \| 202 \| 0.8206 \| 0.3399 \| 0.8206 \| 0.9059 \| \| No log \| 20.4 \| 204 \| 0.7879 \| 0.2784 \| 0.7879 \| 0.8876 \| \| No log \| 20.6 \| 206 \| 0.7408 \| 0.2589 \| 0.7408 \| 0.8607 \| \| No log \| 20.8 \| 208 \| 0.7042 \| 0.1407 \| 0.7042 \| 0.8392 \| \| No log \| 21.0 \| 210 \| 0.7484 \| 0.1528 \| 0.7484 \| 0.8651 \| \| No log \| 21.2 \| 212 \| 0.8096 \| 0.2068 \| 0.8096 \| 0.8998 \| \| No log \| 21.4 \| 214 \| 0.7809 \| 0.1716 \| 0.7809 \| 0.8837 \| \| No log \| 21.6 \| 216 \| 0.7705 \| 0.2475 \| 0.7705 \| 0.8778 \| \| No log \| 21.8 \| 218 \| 0.8606 \| 0.3586 \| 0.8606 \| 0.9277 \| \| No log \| 22.0 \| 220 \| 0.9064 \| 0.3586 \| 0.9064 \| 0.9521 \| \| No log \| 22.2 \| 222 \| 0.8311 \| 0.3590 \| 0.8311 \| 0.9116 \| \| No log \| 22.4 \| 224 \| 0.7556 \| 0.1353 \| 0.7556 \| 0.8693 \| \| No log \| 22.6 \| 226 \| 0.7622 \| -0.0023 \| 0.7622 \| 0.8731 \| \| No log \| 22.8 \| 228 \| 0.7908 \| 0.1716 \| 0.7908 \| 0.8893 \| \| No log \| 23.0 \| 230 \| 0.7844 \| 0.2349 \| 0.7844 \| 0.8857 \| \| No log \| 23.2 \| 232 \| 0.7792 \| 0.2379 \| 0.7792 \| 0.8827 \| \| No log \| 23.4 \| 234 \| 0.7998 \| 0.2784 \| 0.7998 \| 0.8943 \| \| No log \| 23.6 \| 236 \| 0.8093 \| 0.2899 \| 0.8093 \| 0.8996 \| \| No log \| 23.8 \| 238 \| 0.7995 \| 0.3127 \| 0.7995 \| 0.8942 \| \| No log \| 24.0 \| 240 \| 0.7712 \| 0.1835 \| 0.7712 \| 0.8782 \| \| No log \| 24.2 \| 242 \| 0.7589 \| 0.1813 \| 0.7589 \| 0.8711 \| \| No log \| 24.4 \| 244 \| 0.7670 \| 0.1133 \| 0.7670 \| 0.8758 \| \| No log \| 24.6 \| 246 \| 0.7585 \| 0.1850 \| 0.7585 \| 0.8709 \| \| No log \| 24.8 \| 248 \| 0.7605 \| 0.2590 \| 0.7605 \| 0.8721 \| \| No log \| 25.0 \| 250 \| 0.7949 \| 0.3121 \| 0.7949 \| 0.8916 \| \| No log \| 25.2 \| 252 \| 0.8086 \| 0.3121 \| 0.8086 \| 0.8992 \| \| No log \| 25.4 \| 254 \| 0.7797 \| 0.2161 \| 0.7797 \| 0.8830 \| \| No log \| 25.6 \| 256 \| 0.7776 \| 0.2713 \| 0.7776 \| 0.8818 \| \| No log \| 25.8 \| 258 \| 0.8006 \| 0.1775 \| 0.8006 \| 0.8948 \| \| No log \| 26.0 \| 260 \| 0.7976 \| 0.2683 \| 0.7976 \| 0.8931 \| \| No log \| 26.2 \| 262 \| 0.8170 \| 0.2445 \| 0.8170 \| 0.9039 \| \| No log \| 26.4 \| 264 \| 0.8895 \| 0.3320 \| 0.8895 \| 0.9432 \| \| No log \| 26.6 \| 266 \| 0.9028 \| 0.3320 \| 0.9028 \| 0.9501 \| \| No log \| 26.8 \| 268 \| 0.8500 \| 0.3723 \| 0.8500 \| 0.9220 \| \| No log \| 27.0 \| 270 \| 0.7773 \| 0.2237 \| 0.7773 \| 0.8816 \| \| No log \| 27.2 \| 272 \| 0.7466 \| 0.1432 \| 0.7466 \| 0.8640 \| \| No log \| 27.4 \| 274 \| 0.7358 \| 0.1432 \| 0.7358 \| 0.8578 \| \| No log \| 27.6 \| 276 \| 0.7184 \| 0.1400 \| 0.7184 \| 0.8476 \| \| No log \| 27.8 \| 278 \| 0.7469 \| 0.2913 \| 0.7469 \| 0.8642 \| \| No log \| 28.0 \| 280 \| 0.8341 \| 0.4167 \| 0.8341 \| 0.9133 \| \| No log \| 28.2 \| 282 \| 0.9025 \| 0.3480 \| 0.9025 \| 0.9500 \| \| No log \| 28.4 \| 284 \| 0.8798 \| 0.3480 \| 0.8798 \| 0.9380 \| \| No log \| 28.6 \| 286 \| 0.7983 \| 0.3305 \| 0.7983 \| 0.8935 \| \| No log \| 28.8 \| 288 \| 0.7546 \| 0.2530 \| 0.7546 \| 0.8687 \| \| No log \| 29.0 \| 290 \| 0.7365 \| 0.3198 \| 0.7365 \| 0.8582 \| \| No log \| 29.2 \| 292 \| 0.7642 \| 0.3369 \| 0.7642 \| 0.8742 \| \| No log \| 29.4 \| 294 \| 0.7576 \| 0.3369 \| 0.7576 \| 0.8704 \| \| No log \| 29.6 \| 296 \| 0.7301 \| 0.3603 \| 0.7301 \| 0.8545 \| \| No log \| 29.8 \| 298 \| 0.7250 \| 0.2182 \| 0.7250 \| 0.8515 \| \| No log \| 30.0 \| 300 \| 0.7324 \| 0.2471 \| 0.7324 \| 0.8558 \| \| No log \| 30.2 \| 302 \| 0.7285 \| 0.2471 \| 0.7285 \| 0.8535 \| \| No log \| 30.4 \| 304 \| 0.7248 \| 0.2973 \| 0.7248 \| 0.8514 \| \| No log \| 30.6 \| 306 \| 0.7439 \| 0.3859 \| 0.7439 \| 0.8625 \| \| No log \| 30.8 \| 308 \| 0.7629 \| 0.3716 \| 0.7629 \| 0.8734 \| \| No log \| 31.0 \| 310 \| 0.7752 \| 0.3093 \| 0.7752 \| 0.8804 \| \| No log \| 31.2 \| 312 \| 0.7833 \| 0.3433 \| 0.7833 \| 0.8850 \| \| No log \| 31.4 \| 314 \| 0.7665 \| 0.2535 \| 0.7665 \| 0.8755 \| \| No log \| 31.6 \| 316 \| 0.7582 \| 0.2862 \| 0.7582 \| 0.8707 \| \| No log \| 31.8 \| 318 \| 0.7551 \| 0.4081 \| 0.7551 \| 0.8690 \| \| No log \| 32.0 \| 320 \| 0.7494 \| 0.4081 \| 0.7494 \| 0.8657 \| \| No log \| 32.2 \| 322 \| 0.7288 \| 0.3144 \| 0.7288 \| 0.8537 \| \| No log \| 32.4 \| 324 \| 0.7226 \| 0.2360 \| 0.7226 \| 0.8500 \| \| No log \| 32.6 \| 326 \| 0.7280 \| 0.2392 \| 0.7280 \| 0.8532 \| \| No log \| 32.8 \| 328 \| 0.7445 \| 0.2092 \| 0.7445 \| 0.8628 \| \| No log \| 33.0 \| 330 \| 0.7433 \| 0.2092 \| 0.7433 \| 0.8622 \| \| No log \| 33.2 \| 332 \| 0.7497 \| 0.3144 \| 0.7497 \| 0.8658 \| \| No log \| 33.4 \| 334 \| 0.7552 \| 0.3088 \| 0.7552 \| 0.8690 \| \| No log \| 33.6 \| 336 \| 0.7637 \| 0.3355 \| 0.7637 \| 0.8739 \| \| No log \| 33.8 \| 338 \| 0.7622 \| 0.2751 \| 0.7622 \| 0.8730 \| \| No log \| 34.0 \| 340 \| 0.7537 \| 0.3253 \| 0.7537 \| 0.8681 \| \| No log \| 34.2 \| 342 \| 0.7522 \| 0.2621 \| 0.7522 \| 0.8673 \| \| No log \| 34.4 \| 344 \| 0.7579 \| 0.2530 \| 0.7579 \| 0.8706 \| \| No log \| 34.6 \| 346 \| 0.7845 \| 0.3399 \| 0.7845 \| 0.8857 \| \| No log \| 34.8 \| 348 \| 0.8104 \| 0.3918 \| 0.8104 \| 0.9002 \| \| No log \| 35.0 \| 350 \| 0.8344 \| 0.4167 \| 0.8344 \| 0.9135 \| \| No log \| 35.2 \| 352 \| 0.8210 \| 0.4167 \| 0.8210 \| 0.9061 \| \| No log \| 35.4 \| 354 \| 0.7846 \| 0.3662 \| 0.7846 \| 0.8858 \| \| No log \| 35.6 \| 356 \| 0.7560 \| 0.2813 \| 0.7560 \| 0.8695 \| \| No log \| 35.8 \| 358 \| 0.7321 \| 0.3551 \| 0.7321 \| 0.8556 \| \| No log \| 36.0 \| 360 \| 0.7285 \| 0.2113 \| 0.7285 \| 0.8535 \| \| No log \| 36.2 \| 362 \| 0.7275 \| 0.1760 \| 0.7275 \| 0.8529 \| \| No log \| 36.4 \| 364 \| 0.7351 \| 0.2973 \| 0.7351 \| 0.8574 \| \| No log \| 36.6 \| 366 \| 0.7917 \| 0.3121 \| 0.7917 \| 0.8898 \| \| No log \| 36.8 \| 368 \| 0.8597 \| 0.3092 \| 0.8597 \| 0.9272 \| \| No log \| 37.0 \| 370 \| 0.8741 \| 0.3320 \| 0.8741 \| 0.9349 \| \| No log \| 37.2 \| 372 \| 0.8339 \| 0.3092 \| 0.8339 \| 0.9132 \| \| No log \| 37.4 \| 374 \| 0.7728 \| 0.3088 \| 0.7728 \| 0.8791 \| \| No log \| 37.6 \| 376 \| 0.7437 \| 0.2684 \| 0.7437 \| 0.8624 \| \| No log \| 37.8 \| 378 \| 0.7441 \| 0.0741 \| 0.7441 \| 0.8626 \| \| No log \| 38.0 \| 380 \| 0.7444 \| 0.1133 \| 0.7444 \| 0.8628 \| \| No log \| 38.2 \| 382 \| 0.7398 \| 0.0330 \| 0.7398 \| 0.8601 \| \| No log \| 38.4 \| 384 \| 0.7364 \| 0.1050 \| 0.7364 \| 0.8581 \| \| No log \| 38.6 \| 386 \| 0.7439 \| 0.1988 \| 0.7439 \| 0.8625 \| \| No log \| 38.8 \| 388 \| 0.7504 \| 0.2652 \| 0.7504 \| 0.8663 \| \| No log \| 39.0 \| 390 \| 0.7610 \| 0.2590 \| 0.7610 \| 0.8724 \| \| No log \| 39.2 \| 392 \| 0.7666 \| 0.2877 \| 0.7666 \| 0.8755 \| \| No log \| 39.4 \| 394 \| 0.7729 \| 0.2877 \| 0.7729 \| 0.8791 \| \| No log \| 39.6 \| 396 \| 0.7772 \| 0.2943 \| 0.7772 \| 0.8816 \| \| No log \| 39.8 \| 398 \| 0.7828 \| 0.2327 \| 0.7828 \| 0.8848 \| \| No log \| 40.0 \| 400 \| 0.7829 \| 0.2327 \| 0.7829 \| 0.8848 \| \| No log \| 40.2 \| 402 \| 0.7780 \| 0.2270 \| 0.7780 \| 0.8820 \| \| No log \| 40.4 \| 404 \| 0.7750 \| 0.2590 \| 0.7750 \| 0.8804 \| \| No log \| 40.6 \| 406 \| 0.7717 \| 0.3224 \| 0.7717 \| 0.8785 \| \| No log \| 40.8 \| 408 \| 0.7689 \| 0.3224 \| 0.7689 \| 0.8769 \| \| No log \| 41.0 \| 410 \| 0.7627 \| 0.1935 \| 0.7627 \| 0.8733 \| \| No log \| 41.2 \| 412 \| 0.7545 \| 0.1303 \| 0.7545 \| 0.8686 \| \| No log \| 41.4 \| 414 \| 0.7458 \| 0.0652 \| 0.7458 \| 0.8636 \| \| No log \| 41.6 \| 416 \| 0.7394 \| 0.0652 \| 0.7394 \| 0.8599 \| \| No log \| 41.8 \| 418 \| 0.7392 \| 0.0652 \| 0.7392 \| 0.8598 \| \| No log \| 42.0 \| 420 \| 0.7425 \| 0.1432 \| 0.7425 \| 0.8617 \| \| No log \| 42.2 \| 422 \| 0.7477 \| 0.1697 \| 0.7477 \| 0.8647 \| \| No log \| 42.4 \| 424 \| 0.7587 \| 0.1341 \| 0.7587 \| 0.8710 \| \| No log \| 42.6 \| 426 \| 0.7674 \| 0.1673 \| 0.7674 \| 0.8760 \| \| No log \| 42.8 \| 428 \| 0.7715 \| 0.1673 \| 0.7715 \| 0.8783 \| \| No log \| 43.0 \| 430 \| 0.7743 \| 0.2023 \| 0.7743 \| 0.8800 \| \| No log \| 43.2 \| 432 \| 0.7788 \| 0.1697 \| 0.7788 \| 0.8825 \| \| No log \| 43.4 \| 434 \| 0.7774 \| 0.2004 \| 0.7774 \| 0.8817 \| \| No log \| 43.6 \| 436 \| 0.7802 \| 0.1672 \| 0.7802 \| 0.8833 \| \| No log \| 43.8 \| 438 \| 0.7689 \| 0.1697 \| 0.7689 \| 0.8769 \| \| No log \| 44.0 \| 440 \| 0.7487 \| 0.1393 \| 0.7487 \| 0.8653 \| \| No log \| 44.2 \| 442 \| 0.7407 \| 0.1009 \| 0.7407 \| 0.8607 \| \| No log \| 44.4 \| 444 \| 0.7507 \| 0.1686 \| 0.7507 \| 0.8664 \| \| No log \| 44.6 \| 446 \| 0.7712 \| 0.3471 \| 0.7712 \| 0.8782 \| \| No log \| 44.8 \| 448 \| 0.8306 \| 0.3918 \| 0.8306 \| 0.9114 \| \| No log \| 45.0 \| 450 \| 0.8624 \| 0.3243 \| 0.8624 \| 0.9286 \| \| No log \| 45.2 \| 452 \| 0.8467 \| 0.3918 \| 0.8467 \| 0.9202 \| \| No log \| 45.4 \| 454 \| 0.8022 \| 0.3996 \| 0.8022 \| 0.8956 \| \| No log \| 45.6 \| 456 \| 0.7728 \| 0.3545 \| 0.7728 \| 0.8791 \| \| No log \| 45.8 \| 458 \| 0.7627 \| 0.2621 \| 0.7627 \| 0.8733 \| \| No log \| 46.0 \| 460 \| 0.7581 \| 0.1341 \| 0.7581 \| 0.8707 \| \| No log \| 46.2 \| 462 \| 0.7569 \| 0.1341 \| 0.7569 \| 0.8700 \| \| No log \| 46.4 \| 464 \| 0.7586 \| 0.1341 \| 0.7586 \| 0.8710 \| \| No log \| 46.6 \| 466 \| 0.7676 \| 0.2023 \| 0.7676 \| 0.8761 \| \| No log \| 46.8 \| 468 \| 0.7907 \| 0.3050 \| 0.7907 \| 0.8892 \| \| No log \| 47.0 \| 470 \| 0.8157 \| 0.3196 \| 0.8157 \| 0.9031 \| \| No log \| 47.2 \| 472 \| 0.8223 \| 0.2261 \| 0.8223 \| 0.9068 \| \| No log \| 47.4 \| 474 \| 0.8078 \| 0.2063 \| 0.8078 \| 0.8988 \| \| No log \| 47.6 \| 476 \| 0.7929 \| 0.2063 \| 0.7929 \| 0.8904 \| \| No log \| 47.8 \| 478 \| 0.7951 \| 0.2063 \| 0.7951 \| 0.8917 \| \| No log \| 48.0 \| 480 \| 0.8073 \| 0.2379 \| 0.8073 \| 0.8985 \| \| No log \| 48.2 \| 482 \| 0.8317 \| 0.2981 \| 0.8317 \| 0.9120 \| \| No log \| 48.4 \| 484 \| 0.8679 \| 0.3737 \| 0.8679 \| 0.9316 \| \| No log \| 48.6 \| 486 \| 0.8842 \| 0.3544 \| 0.8842 \| 0.9403 \| \| No log \| 48.8 \| 488 \| 0.8807 \| 0.3737 \| 0.8807 \| 0.9384 \| \| No log \| 49.0 \| 490 \| 0.8616 \| 0.3737 \| 0.8616 \| 0.9282 \| \| No log \| 49.2 \| 492 \| 0.8484 \| 0.3471 \| 0.8484 \| 0.9211 \| \| No log \| 49.4 \| 494 \| 0.8225 \| 0.2319 \| 0.8225 \| 0.9069 \| \| No log \| 49.6 \| 496 \| 0.8099 \| 0.2379 \| 0.8099 \| 0.9000 \| \| No log \| 49.8 \| 498 \| 0.8027 \| 0.2379 \| 0.8027 \| 0.8960 \| \| 0.2553 \| 50.0 \| 500 \| 0.8057 \| 0.2379 \| 0.8057 \| 0.8976 \| \| 0.2553 \| 50.2 \| 502 \| 0.8048 \| 0.2379 \| 0.8048 \| 0.8971 \| \| 0.2553 \| 50.4 \| 504 \| 0.7961 \| 0.1988 \| 0.7961 \| 0.8922 \| \| 0.2553 \| 50.6 \| 506 \| 0.7901 \| 0.2685 \| 0.7901 \| 0.8889 \| \| 0.2553 \| 50.8 \| 508 \| 0.7940 \| 0.2685 \| 0.7940 \| 0.8911 \| \| 0.2553 \| 51.0 \| 510 \| 0.8051 \| 0.2847 \| 0.8051 \| 0.8973 \| \| 0.2553 \| 51.2 \| 512 \| 0.8122 \| 0.2847 \| 0.8122 \| 0.9012 \| \| 0.2553 \| 51.4 \| 514 \| 0.8100 \| 0.2847 \| 0.8100 \| 0.9000 \| \| 0.2553 \| 51.6 \| 516 \| 0.8060 \| 0.2847 \| 0.8060 \| 0.8978 \| \| 0.2553 \| 51.8 \| 518 \| 0.8079 \| 0.2847 \| 0.8079 \| 0.8988 \| \| 0.2553 \| 52.0 \| 520 \| 0.7941 \| 0.2621 \| 0.7941 \| 0.8911 \| \| 0.2553 \| 52.2 \| 522 \| 0.7804 \| 0.2685 \| 0.7804 \| 0.8834 \| \| 0.2553 \| 52.4 \| 524 \| 0.7663 \| 0.2685 \| 0.7663 \| 0.8754 \| \| 0.2553 \| 52.6 \| 526 \| 0.7580 \| 0.1737 \| 0.7580 \| 0.8706 \| \| 0.2553 \| 52.8 \| 528 \| 0.7571 \| 0.1737 \| 0.7571 \| 0.8701 \| \| 0.2553 \| 53.0 \| 530 \| 0.7622 \| 0.2294 \| 0.7622 \| 0.8730 \| \| 0.2553 \| 53.2 \| 532 \| 0.7758 \| 0.2685 \| 0.7758 \| 0.8808 \| \| 0.2553 \| 53.4 \| 534 \| 0.8022 \| 0.3088 \| 0.8022 \| 0.8957 \| \| 0.2553 \| 53.6 \| 536 \| 0.8215 \| 0.3287 \| 0.8215 \| 0.9064 \| \| 0.2553 \| 53.8 \| 538 \| 0.8320 \| 0.3287 \| 0.8320 \| 0.9121 \| \| 0.2553 \| 54.0 \| 540 \| 0.8215 \| 0.3287 \| 0.8215 \| 0.9063 \| \| 0.2553 \| 54.2 \| 542 \| 0.7971 \| 0.3688 \| 0.7971 \| 0.8928 \| \| 0.2553 \| 54.4 \| 544 \| 0.7801 \| 0.2652 \| 0.7801 \| 0.8832 \| \| 0.2553 \| 54.6 \| 546 \| 0.7654 \| 0.1673 \| 0.7654 \| 0.8749 \| \| 0.2553 \| 54.8 \| 548 \| 0.7574 \| 0.0971 \| 0.7574 \| 0.8703 \| \| 0.2553 \| 55.0 \| 550 \| 0.7524 \| 0.0971 \| 0.7524 \| 0.8674 \| \| 0.2553 \| 55.2 \| 552 \| 0.7489 \| 0.0283 \| 0.7489 \| 0.8654 \| \| 0.2553 \| 55.4 \| 554 \| 0.7467 \| 0.0697 \| 0.7467 \| 0.8641 \| ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.0+cu118 - Datasets 2.21.0 - Tokenizers 0.19.1
kostiantynk/19c4fa41-fdff-4798-a49e-259eac91f176	kostiantynk	2025-01-21T12:31:01Z	6	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:oopsung/llama2-7b-n-ox-test-v1", "base_model:adapter:oopsung/llama2-7b-n-ox-test-v1", "region:us" ]	null	2025-01-21T12:24:58Z	--- library_name: peft base_model: oopsung/llama2-7b-n-ox-test-v1 tags: - axolotl - generated_from_trainer model-index: - name: 19c4fa41-fdff-4798-a49e-259eac91f176 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: oopsung/llama2-7b-n-ox-test-v1 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - dddb0489dc663e1a_train_data.json ds_type: json format: custom path: /workspace/input_data/dddb0489dc663e1a_train_data.json type: field_input: Context field_instruction: Question field_output: Answers format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: kostiantynk/19c4fa41-fdff-4798-a49e-259eac91f176 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/dddb0489dc663e1a_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: bbd202cf-ffeb-42f5-82b2-0c60d893aeab wandb_project: Birthday-SN56-7-Gradients-On-Demand wandb_run: your_name wandb_runid: bbd202cf-ffeb-42f5-82b2-0c60d893aeab warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # 19c4fa41-fdff-4798-a49e-259eac91f176 This model is a fine-tuned version of [oopsung/llama2-7b-n-ox-test-v1](https://huggingface.co/oopsung/llama2-7b-n-ox-test-v1) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 0.0 \| 0.0003 \| 1 \| nan \| \| 0.0 \| 0.0008 \| 3 \| nan \| \| 0.0 \| 0.0017 \| 6 \| nan \| \| 0.0 \| 0.0025 \| 9 \| nan \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
akh99/DeepSeek-R1-Distill-Qwen-7B_AWQ-tok-norm	akh99	2025-01-21T12:30:25Z	141	0	transformers	[ "transformers", "safetensors", "qwen2", "text-generation", "conversational", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "4-bit", "awq", "region:us" ]	text-generation	2025-01-21T12:29:31Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. 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Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. 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nhung01/37ee035e-1e50-44b7-aa8a-1086267f8630	nhung01	2025-01-21T12:29:49Z	6	0	peft	[ "peft", "safetensors", "gpt_neox", "axolotl", "generated_from_trainer", "base_model:EleutherAI/pythia-1b", "base_model:adapter:EleutherAI/pythia-1b", "license:apache-2.0", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-21T12:17:26Z	--- library_name: peft license: apache-2.0 base_model: EleutherAI/pythia-1b tags: - axolotl - generated_from_trainer model-index: - name: 37ee035e-1e50-44b7-aa8a-1086267f8630 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: EleutherAI/pythia-1b bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - b88fbb911025d0a2_train_data.json ds_type: json format: custom path: /workspace/input_data/b88fbb911025d0a2_train_data.json type: field_input: Primary Keyword field_instruction: Long Description field_output: Position format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: nhung01/37ee035e-1e50-44b7-aa8a-1086267f8630 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/b88fbb911025d0a2_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 special_tokens: pad_token: <\|endoftext\|> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 9ff18266-1053-4343-a163-393cb535b12c wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 9ff18266-1053-4343-a163-393cb535b12c warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details><br> # 37ee035e-1e50-44b7-aa8a-1086267f8630 This model is a fine-tuned version of [EleutherAI/pythia-1b](https://huggingface.co/EleutherAI/pythia-1b) on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.0207 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 10.0779 \| 0.0119 \| 200 \| 2.0207 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
josty11/roberta-optimized	josty11	2025-01-21T12:29:35Z	23	0	transformers	[ "transformers", "safetensors", "distilbert", "text-classification", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2025-01-21T12:29:09Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
lesso11/d853c065-1f63-4c2f-99c9-18ee9227719f	lesso11	2025-01-21T12:29:00Z	6	0	peft	[ "peft", "safetensors", "phi3", "axolotl", "generated_from_trainer", "custom_code", "base_model:migtissera/Tess-v2.5-Phi-3-medium-128k-14B", "base_model:adapter:migtissera/Tess-v2.5-Phi-3-medium-128k-14B", "license:mit", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-21T12:20:37Z	--- library_name: peft license: mit base_model: migtissera/Tess-v2.5-Phi-3-medium-128k-14B tags: - axolotl - generated_from_trainer model-index: - name: d853c065-1f63-4c2f-99c9-18ee9227719f results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: migtissera/Tess-v2.5-Phi-3-medium-128k-14B bf16: true chat_template: llama3 datasets: - data_files: - 5fe705ae677c52cd_train_data.json ds_type: json format: custom path: /workspace/input_data/5fe705ae677c52cd_train_data.json type: field_input: code_before field_instruction: func_before field_output: code_after format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: 2 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null flash_attention: false fp16: false fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: lesso11/d853c065-1f63-4c2f-99c9-18ee9227719f hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 25 micro_batch_size: 2 mlflow_experiment_name: /tmp/5fe705ae677c52cd_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: c9913a62-6036-4cc0-92bf-1f189dbde5c4 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: c9913a62-6036-4cc0-92bf-1f189dbde5c4 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # d853c065-1f63-4c2f-99c9-18ee9227719f This model is a fine-tuned version of [migtissera/Tess-v2.5-Phi-3-medium-128k-14B](https://huggingface.co/migtissera/Tess-v2.5-Phi-3-medium-128k-14B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.6170 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 25 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 2.286 \| 0.0020 \| 1 \| 0.6638 \| \| 2.5694 \| 0.0101 \| 5 \| 0.6637 \| \| 2.2073 \| 0.0202 \| 10 \| 0.6503 \| \| 2.4329 \| 0.0302 \| 15 \| 0.6293 \| \| 1.1466 \| 0.0403 \| 20 \| 0.6194 \| \| 2.8759 \| 0.0504 \| 25 \| 0.6170 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
cvoffer/ddc7dbca-7bbb-4a64-9065-11f4e2616878	cvoffer	2025-01-21T12:27:43Z	6	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:unsloth/llama-2-7b-chat", "base_model:adapter:unsloth/llama-2-7b-chat", "license:apache-2.0", "region:us" ]	null	2025-01-21T08:34:57Z	--- library_name: peft license: apache-2.0 base_model: unsloth/llama-2-7b-chat tags: - axolotl - generated_from_trainer model-index: - name: ddc7dbca-7bbb-4a64-9065-11f4e2616878 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/llama-2-7b-chat bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 124bc05ddbf5ee81_train_data.json ds_type: json format: custom path: /workspace/input_data/124bc05ddbf5ee81_train_data.json type: field_instruction: docstring field_output: summary format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: 1 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: true hub_model_id: cvoffer/ddc7dbca-7bbb-4a64-9065-11f4e2616878 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 78GiB max_steps: 30 micro_batch_size: 2 mlflow_experiment_name: /tmp/124bc05ddbf5ee81_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 5fe9995d-0a95-46fa-b89c-25f97cbb6eb6 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 5fe9995d-0a95-46fa-b89c-25f97cbb6eb6 warmup_steps: 5 weight_decay: 0.001 xformers_attention: true ``` </details><br> # ddc7dbca-7bbb-4a64-9065-11f4e2616878 This model is a fine-tuned version of [unsloth/llama-2-7b-chat](https://huggingface.co/unsloth/llama-2-7b-chat) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 30 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| No log \| 0.0000 \| 1 \| nan \| \| 0.0 \| 0.0001 \| 5 \| nan \| \| 0.0 \| 0.0002 \| 10 \| nan \| \| 0.0 \| 0.0003 \| 15 \| nan \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
thaffggg/c0a3ae1e-da6c-43d4-9442-7848c0ffddeb	thaffggg	2025-01-21T12:27:07Z	6	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:TinyLlama/TinyLlama-1.1B-Chat-v1.0", "base_model:adapter:TinyLlama/TinyLlama-1.1B-Chat-v1.0", "license:apache-2.0", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-21T12:13:58Z	--- library_name: peft license: apache-2.0 base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0 tags: - axolotl - generated_from_trainer model-index: - name: c0a3ae1e-da6c-43d4-9442-7848c0ffddeb results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - b73b66c21220caaf_train_data.json ds_type: json format: custom path: /workspace/input_data/b73b66c21220caaf_train_data.json type: field_input: categories field_instruction: title field_output: markdown format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: thaffggg/c0a3ae1e-da6c-43d4-9442-7848c0ffddeb hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/b73b66c21220caaf_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: fc2a71fc-f606-4cf6-887a-e73c961e3be1 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: fc2a71fc-f606-4cf6-887a-e73c961e3be1 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details><br> # c0a3ae1e-da6c-43d4-9442-7848c0ffddeb This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.8160 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 1.9254 \| 0.0378 \| 200 \| 1.8160 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
nadejdatarabukina/c663e43a-fce1-4aed-aabb-ac7bc046445f	nadejdatarabukina	2025-01-21T12:27:02Z	6	0	peft	[ "peft", "safetensors", "mistral", "axolotl", "generated_from_trainer", "base_model:teknium/OpenHermes-2.5-Mistral-7B", "base_model:adapter:teknium/OpenHermes-2.5-Mistral-7B", "license:apache-2.0", "region:us" ]	null	2025-01-21T11:55:46Z	--- library_name: peft license: apache-2.0 base_model: teknium/OpenHermes-2.5-Mistral-7B tags: - axolotl - generated_from_trainer model-index: - name: c663e43a-fce1-4aed-aabb-ac7bc046445f results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: teknium/OpenHermes-2.5-Mistral-7B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 1b5fe4b652f9222e_train_data.json ds_type: json format: custom path: /workspace/input_data/1b5fe4b652f9222e_train_data.json type: field_instruction: instruction field_output: output format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: null eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: false hub_model_id: nadejdatarabukina/c663e43a-fce1-4aed-aabb-ac7bc046445f hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 75GiB max_steps: 30 micro_batch_size: 2 mlflow_experiment_name: /tmp/1b5fe4b652f9222e_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 special_tokens: pad_token: <\|im_end\|> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 857fa1e7-73d3-440e-a388-76fc6a5b2495 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 857fa1e7-73d3-440e-a388-76fc6a5b2495 warmup_steps: 10 weight_decay: 0.01 xformers_attention: true ``` </details><br> # c663e43a-fce1-4aed-aabb-ac7bc046445f This model is a fine-tuned version of [teknium/OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 30 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| No log \| 0.0002 \| 1 \| nan \| \| 0.0 \| 0.0010 \| 5 \| nan \| \| 0.0 \| 0.0019 \| 10 \| nan \| \| 0.0 \| 0.0029 \| 15 \| nan \| \| 0.0 \| 0.0039 \| 20 \| nan \| \| 0.0 \| 0.0049 \| 25 \| nan \| \| 0.0 \| 0.0058 \| 30 \| nan \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
filipesantoscv11/87dd10c7-f67d-4031-94e7-cba82e9cbe5a	filipesantoscv11	2025-01-21T12:26:56Z	6	0	peft	[ "peft", "safetensors", "gemma", "axolotl", "generated_from_trainer", "base_model:fxmarty/tiny-random-GemmaForCausalLM", "base_model:adapter:fxmarty/tiny-random-GemmaForCausalLM", "license:mit", "region:us" ]	null	2025-01-21T12:18:45Z	--- library_name: peft license: mit base_model: fxmarty/tiny-random-GemmaForCausalLM tags: - axolotl - generated_from_trainer model-index: - name: 87dd10c7-f67d-4031-94e7-cba82e9cbe5a results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: fxmarty/tiny-random-GemmaForCausalLM bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - dabeeced6597d53e_train_data.json ds_type: json format: custom path: /workspace/input_data/dabeeced6597d53e_train_data.json type: field_instruction: sentence1_en field_output: sentence2_en format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: 1 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: true hub_model_id: filipesantoscv11/87dd10c7-f67d-4031-94e7-cba82e9cbe5a hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 79GiB max_steps: 30 micro_batch_size: 4 mlflow_experiment_name: /tmp/dabeeced6597d53e_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optim_args: adam_beta1: 0.9 adam_beta2: 0.95 adam_epsilon: 1e-5 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 8140ab10-5da7-47df-b106-2846f0a02738 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 8140ab10-5da7-47df-b106-2846f0a02738 warmup_steps: 5 weight_decay: 0.001 xformers_attention: true ``` </details><br> # 87dd10c7-f67d-4031-94e7-cba82e9cbe5a This model is a fine-tuned version of [fxmarty/tiny-random-GemmaForCausalLM](https://huggingface.co/fxmarty/tiny-random-GemmaForCausalLM) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 16 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.95,adam_epsilon=1e-5 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 30 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| No log \| 0.0000 \| 1 \| nan \| \| 0.0 \| 0.0002 \| 5 \| nan \| \| 0.0 \| 0.0004 \| 10 \| nan \| \| 0.0 \| 0.0006 \| 15 \| nan \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
dimasik87/6effa428-7d2c-4d09-8936-920f11f80aa1	dimasik87	2025-01-21T12:25:55Z	6	0	peft	[ "peft", "safetensors", "gemma", "axolotl", "generated_from_trainer", "base_model:fxmarty/tiny-random-GemmaForCausalLM", "base_model:adapter:fxmarty/tiny-random-GemmaForCausalLM", "license:mit", "region:us" ]	null	2025-01-21T12:17:08Z	--- library_name: peft license: mit base_model: fxmarty/tiny-random-GemmaForCausalLM tags: - axolotl - generated_from_trainer model-index: - name: 6effa428-7d2c-4d09-8936-920f11f80aa1 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: fxmarty/tiny-random-GemmaForCausalLM bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - dabeeced6597d53e_train_data.json ds_type: json format: custom path: /workspace/input_data/dabeeced6597d53e_train_data.json type: field_instruction: sentence1_en field_output: sentence2_en format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: 1 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: true hub_model_id: dimasik87/6effa428-7d2c-4d09-8936-920f11f80aa1 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 79GiB max_steps: 30 micro_batch_size: 4 mlflow_experiment_name: /tmp/dabeeced6597d53e_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optim_args: adam_beta1: 0.9 adam_beta2: 0.95 adam_epsilon: 1e-5 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 8140ab10-5da7-47df-b106-2846f0a02738 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 8140ab10-5da7-47df-b106-2846f0a02738 warmup_steps: 5 weight_decay: 0.001 xformers_attention: true ``` </details><br> # 6effa428-7d2c-4d09-8936-920f11f80aa1 This model is a fine-tuned version of [fxmarty/tiny-random-GemmaForCausalLM](https://huggingface.co/fxmarty/tiny-random-GemmaForCausalLM) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 16 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.95,adam_epsilon=1e-5 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 30 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| No log \| 0.0000 \| 1 \| nan \| \| 0.0 \| 0.0002 \| 5 \| nan \| \| 0.0 \| 0.0004 \| 10 \| nan \| \| 0.0 \| 0.0006 \| 15 \| nan \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
mrHungddddh/ee0ee47e-2d5b-4367-8e93-9087d184a92e	mrHungddddh	2025-01-21T12:25:51Z	6	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:unsloth/tinyllama", "base_model:adapter:unsloth/tinyllama", "license:apache-2.0", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-21T12:17:08Z	--- library_name: peft license: apache-2.0 base_model: unsloth/tinyllama tags: - axolotl - generated_from_trainer model-index: - name: ee0ee47e-2d5b-4367-8e93-9087d184a92e results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/tinyllama bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 487571a5edd806c1_train_data.json ds_type: json format: custom path: /workspace/input_data/487571a5edd806c1_train_data.json type: field_input: strategy field_instruction: original_text field_output: reframed_text format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: mrHungddddh/ee0ee47e-2d5b-4367-8e93-9087d184a92e hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/487571a5edd806c1_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 37054b4e-d0d5-4aaa-9839-6cdc15c24dbf wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 37054b4e-d0d5-4aaa-9839-6cdc15c24dbf warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details><br> # ee0ee47e-2d5b-4367-8e93-9087d184a92e This model is a fine-tuned version of [unsloth/tinyllama](https://huggingface.co/unsloth/tinyllama) on the None dataset. It achieves the following results on the evaluation set: - Loss: 3.6298 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 3.7227 \| 0.2042 \| 200 \| 3.6298 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
tarabukinivan/1066e8a2-3893-4cd1-8fd8-e1b505b5a1b3	tarabukinivan	2025-01-21T12:25:00Z	6	0	peft	[ "peft", "safetensors", "opt", "axolotl", "generated_from_trainer", "base_model:facebook/opt-125m", "base_model:adapter:facebook/opt-125m", "license:other", "region:us" ]	null	2025-01-21T12:20:06Z	--- library_name: peft license: other base_model: facebook/opt-125m tags: - axolotl - generated_from_trainer model-index: - name: 1066e8a2-3893-4cd1-8fd8-e1b505b5a1b3 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: facebook/opt-125m bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 807edbe01d3143fb_train_data.json ds_type: json format: custom path: /workspace/input_data/807edbe01d3143fb_train_data.json type: field_input: question field_instruction: answer field_output: context field_system: distractors format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: null eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: false hub_model_id: tarabukinivan/1066e8a2-3893-4cd1-8fd8-e1b505b5a1b3 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 75GiB max_steps: 30 micro_batch_size: 2 mlflow_experiment_name: /tmp/807edbe01d3143fb_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 87d40317-ca50-4c35-ad9f-1a82b7dfae06 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 87d40317-ca50-4c35-ad9f-1a82b7dfae06 warmup_steps: 10 weight_decay: 0.01 xformers_attention: true ``` </details><br> # 1066e8a2-3893-4cd1-8fd8-e1b505b5a1b3 This model is a fine-tuned version of [facebook/opt-125m](https://huggingface.co/facebook/opt-125m) on the None dataset. It achieves the following results on the evaluation set: - Loss: 3.2501 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 30 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| No log \| 0.0001 \| 1 \| 3.4432 \| \| 14.4001 \| 0.0007 \| 5 \| 3.4202 \| \| 13.9917 \| 0.0014 \| 10 \| 3.3622 \| \| 13.5667 \| 0.0021 \| 15 \| 3.3026 \| \| 13.4465 \| 0.0028 \| 20 \| 3.2633 \| \| 13.4339 \| 0.0035 \| 25 \| 3.2522 \| \| 13.0761 \| 0.0042 \| 30 \| 3.2501 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
Ancastal/mistral-7b-literary-creamt-ita-v2	Ancastal	2025-01-21T12:24:44Z	18	0	transformers	[ "transformers", "safetensors", "mistral", "text-generation", "trl", "sft", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "4-bit", "bitsandbytes", "region:us" ]	text-generation	2025-01-21T12:22:09Z	--- library_name: transformers tags: - trl - sft --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. 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kokovova/a68a6605-dbd4-4a06-94e6-cf4a93ba65b4	kokovova	2025-01-21T12:22:52Z	5	0	peft	[ "peft", "safetensors", "opt", "axolotl", "generated_from_trainer", "base_model:facebook/opt-125m", "base_model:adapter:facebook/opt-125m", "license:other", "region:us" ]	null	2025-01-21T12:20:06Z	--- library_name: peft license: other base_model: facebook/opt-125m tags: - axolotl - generated_from_trainer model-index: - name: a68a6605-dbd4-4a06-94e6-cf4a93ba65b4 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: facebook/opt-125m bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 807edbe01d3143fb_train_data.json ds_type: json format: custom path: /workspace/input_data/807edbe01d3143fb_train_data.json type: field_input: question field_instruction: answer field_output: context field_system: distractors format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: 1 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: true hub_model_id: kokovova/a68a6605-dbd4-4a06-94e6-cf4a93ba65b4 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 79GiB max_steps: 30 micro_batch_size: 4 mlflow_experiment_name: /tmp/807edbe01d3143fb_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optim_args: adam_beta1: 0.9 adam_beta2: 0.95 adam_epsilon: 1e-5 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 87d40317-ca50-4c35-ad9f-1a82b7dfae06 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 87d40317-ca50-4c35-ad9f-1a82b7dfae06 warmup_steps: 5 weight_decay: 0.001 xformers_attention: true ``` </details><br> # a68a6605-dbd4-4a06-94e6-cf4a93ba65b4 This model is a fine-tuned version of [facebook/opt-125m](https://huggingface.co/facebook/opt-125m) on the None dataset. It achieves the following results on the evaluation set: - Loss: 3.3495 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 16 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.95,adam_epsilon=1e-5 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 30 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| No log \| 0.0003 \| 1 \| 3.5459 \| \| 12.8135 \| 0.0014 \| 5 \| 3.5057 \| \| 13.1425 \| 0.0028 \| 10 \| 3.4401 \| \| 13.0512 \| 0.0042 \| 15 \| 3.3813 \| \| 12.9854 \| 0.0056 \| 20 \| 3.3556 \| \| 13.2067 \| 0.0070 \| 25 \| 3.3501 \| \| 12.8119 \| 0.0084 \| 30 \| 3.3495 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
ClarenceDan/55ee309d-0518-4ff9-9817-91bd856ea2b9	ClarenceDan	2025-01-21T12:21:37Z	6	0	peft	[ "peft", "safetensors", "qwen2", "axolotl", "generated_from_trainer", "base_model:Qwen/Qwen1.5-14B-Chat", "base_model:adapter:Qwen/Qwen1.5-14B-Chat", "license:other", "region:us" ]	null	2025-01-21T12:19:59Z	--- library_name: peft license: other base_model: Qwen/Qwen1.5-14B-Chat tags: - axolotl - generated_from_trainer model-index: - name: 55ee309d-0518-4ff9-9817-91bd856ea2b9 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: Qwen/Qwen1.5-14B-Chat bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - a6fd907479ec4d1c_train_data.json ds_type: json format: custom path: /workspace/input_data/a6fd907479ec4d1c_train_data.json type: field_instruction: text field_output: title format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: ClarenceDan/55ee309d-0518-4ff9-9817-91bd856ea2b9 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/a6fd907479ec4d1c_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: fded3919-5ba0-4f07-810d-e0ea78b083dd wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: fded3919-5ba0-4f07-810d-e0ea78b083dd warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # 55ee309d-0518-4ff9-9817-91bd856ea2b9 This model is a fine-tuned version of [Qwen/Qwen1.5-14B-Chat](https://huggingface.co/Qwen/Qwen1.5-14B-Chat) on the None dataset. It achieves the following results on the evaluation set: - Loss: 3.5376 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 3.8175 \| 0.0028 \| 1 \| 3.9889 \| \| 3.7012 \| 0.0085 \| 3 \| 3.9837 \| \| 4.6257 \| 0.0171 \| 6 \| 3.9136 \| \| 3.7991 \| 0.0256 \| 9 \| 3.5376 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
lesso15/c922ade5-6e42-482f-8b7f-f2fb56073597	lesso15	2025-01-21T12:21:27Z	6	0	peft	[ "peft", "safetensors", "gpt_neox", "axolotl", "generated_from_trainer", "base_model:EleutherAI/pythia-14m", "base_model:adapter:EleutherAI/pythia-14m", "4-bit", "bitsandbytes", "region:us" ]	null	2025-01-21T12:20:52Z	--- library_name: peft base_model: EleutherAI/pythia-14m tags: - axolotl - generated_from_trainer model-index: - name: c922ade5-6e42-482f-8b7f-f2fb56073597 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: EleutherAI/pythia-14m bf16: auto chat_template: llama3 datasets: - data_files: - eb2c9ecdcfd4c8a6_train_data.json ds_type: json format: custom path: /workspace/input_data/eb2c9ecdcfd4c8a6_train_data.json type: field_instruction: image field_output: description format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: 2 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: true gradient_checkpointing: false group_by_length: false hub_model_id: lesso15/c922ade5-6e42-482f-8b7f-f2fb56073597 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: true load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_steps: 25 micro_batch_size: 2 mlflow_experiment_name: /tmp/eb2c9ecdcfd4c8a6_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 special_tokens: pad_token: <\|endoftext\|> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 99d526df-9766-4d1f-80b3-c918100a230c wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 99d526df-9766-4d1f-80b3-c918100a230c warmup_steps: 10 weight_decay: 0.01 xformers_attention: null ``` </details><br> # c922ade5-6e42-482f-8b7f-f2fb56073597 This model is a fine-tuned version of [EleutherAI/pythia-14m](https://huggingface.co/EleutherAI/pythia-14m) on the None dataset. It achieves the following results on the evaluation set: - Loss: 3.0091 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 25 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| No log \| 0.0012 \| 1 \| 5.6256 \| \| 5.6383 \| 0.0058 \| 5 \| 5.3829 \| \| 4.8286 \| 0.0117 \| 10 \| 4.4874 \| \| 3.6903 \| 0.0175 \| 15 \| 3.6561 \| \| 3.5467 \| 0.0234 \| 20 \| 3.1049 \| \| 2.657 \| 0.0292 \| 25 \| 3.0091 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
demohong/b7c5fd23-cbe4-469e-bdc5-e977a9051452	demohong	2025-01-21T12:21:27Z	6	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:codellama/CodeLlama-7b-Instruct-hf", "base_model:adapter:codellama/CodeLlama-7b-Instruct-hf", "license:llama2", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-21T11:54:20Z	--- library_name: peft license: llama2 base_model: codellama/CodeLlama-7b-Instruct-hf tags: - axolotl - generated_from_trainer model-index: - name: b7c5fd23-cbe4-469e-bdc5-e977a9051452 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: codellama/CodeLlama-7b-Instruct-hf bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - e61b15027cdb8f0f_train_data.json ds_type: json format: custom path: /workspace/input_data/e61b15027cdb8f0f_train_data.json type: field_instruction: text_description field_output: text format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: demohong/b7c5fd23-cbe4-469e-bdc5-e977a9051452 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/e61b15027cdb8f0f_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 special_tokens: pad_token: </s> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 52dcb611-f58d-420b-a954-552a3249dfec wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 52dcb611-f58d-420b-a954-552a3249dfec warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details><br> # b7c5fd23-cbe4-469e-bdc5-e977a9051452 This model is a fine-tuned version of [codellama/CodeLlama-7b-Instruct-hf](https://huggingface.co/codellama/CodeLlama-7b-Instruct-hf) on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.1081 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 1.9469 \| 0.0800 \| 200 \| 2.1081 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
minsangK/20250120-bge-m3-8192-bs-4-1-epoch-5e-6-hn-2	minsangK	2025-01-21T12:21:19Z	7	0	transformers	[ "transformers", "safetensors", "xlm-roberta", "feature-extraction", "generated_from_trainer", "text-embeddings-inference", "endpoints_compatible", "region:us" ]	feature-extraction	2025-01-21T05:05:07Z	--- library_name: transformers tags: - generated_from_trainer model-index: - name: 20250120-bge-m3-8192-bs-4-1-epoch-5e-6-hn-2 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # 20250120-bge-m3-8192-bs-4-1-epoch-5e-6-hn-2 This model was trained from scratch on an unknown dataset. ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-06 - train_batch_size: 4 - eval_batch_size: 8 - seed: 42 - distributed_type: multi-GPU - num_devices: 4 - total_train_batch_size: 16 - total_eval_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 1.0 - mixed_precision_training: Native AMP ### Training results ### Framework versions - Transformers 4.44.2 - Pytorch 2.2.2 - Datasets 2.19.0 - Tokenizers 0.19.1
MayBashendy/ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k2_task7_organization	MayBashendy	2025-01-21T12:21:14Z	5	0	transformers	[ "transformers", "safetensors", "bert", "text-classification", "generated_from_trainer", "base_model:aubmindlab/bert-base-arabertv02", "base_model:finetune:aubmindlab/bert-base-arabertv02", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2025-01-21T12:17:18Z	--- library_name: transformers base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k2_task7_organization results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k2_task7_organization This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.0238 - Qwk: 0.2898 - Mse: 1.0238 - Rmse: 1.0119 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 100 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Qwk \| Mse \| Rmse \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:-------:\|:------:\|:------:\| \| No log \| 0.4 \| 2 \| 2.5043 \| -0.0788 \| 2.5043 \| 1.5825 \| \| No log \| 0.8 \| 4 \| 1.1496 \| 0.1284 \| 1.1496 \| 1.0722 \| \| No log \| 1.2 \| 6 \| 0.8398 \| 0.0535 \| 0.8398 \| 0.9164 \| \| No log \| 1.6 \| 8 \| 0.8665 \| 0.0313 \| 0.8665 \| 0.9309 \| \| No log \| 2.0 \| 10 \| 0.9418 \| 0.1181 \| 0.9418 \| 0.9705 \| \| No log \| 2.4 \| 12 \| 0.8754 \| 0.1268 \| 0.8754 \| 0.9356 \| \| No log \| 2.8 \| 14 \| 0.7780 \| 0.0804 \| 0.7780 \| 0.8821 \| \| No log \| 3.2 \| 16 \| 0.7806 \| 0.0444 \| 0.7806 \| 0.8835 \| \| No log \| 3.6 \| 18 \| 0.7911 \| 0.0444 \| 0.7911 \| 0.8895 \| \| No log \| 4.0 \| 20 \| 0.8116 \| 0.0481 \| 0.8116 \| 0.9009 \| \| No log \| 4.4 \| 22 \| 0.7852 \| 0.0444 \| 0.7852 \| 0.8861 \| \| No log \| 4.8 \| 24 \| 0.7556 \| 0.1187 \| 0.7556 \| 0.8693 \| \| No log \| 5.2 \| 26 \| 0.7550 \| 0.1094 \| 0.7550 \| 0.8689 \| \| No log \| 5.6 \| 28 \| 0.7873 \| 0.2285 \| 0.7873 \| 0.8873 \| \| No log \| 6.0 \| 30 \| 0.8195 \| 0.1867 \| 0.8195 \| 0.9053 \| \| No log \| 6.4 \| 32 \| 0.7905 \| 0.1584 \| 0.7905 \| 0.8891 \| \| No log \| 6.8 \| 34 \| 0.8006 \| 0.1542 \| 0.8006 \| 0.8947 \| \| No log \| 7.2 \| 36 \| 0.8280 \| 0.1946 \| 0.8280 \| 0.9100 \| \| No log \| 7.6 \| 38 \| 1.0096 \| 0.1501 \| 1.0096 \| 1.0048 \| \| No log \| 8.0 \| 40 \| 1.0556 \| 0.1867 \| 1.0556 \| 1.0274 \| \| No log \| 8.4 \| 42 \| 0.9515 \| 0.0241 \| 0.9515 \| 0.9754 \| \| No log \| 8.8 \| 44 \| 0.8984 \| 0.1289 \| 0.8984 \| 0.9478 \| \| No log \| 9.2 \| 46 \| 0.9670 \| 0.1385 \| 0.9670 \| 0.9834 \| \| No log \| 9.6 \| 48 \| 1.0413 \| 0.2119 \| 1.0413 \| 1.0204 \| \| No log \| 10.0 \| 50 \| 1.1556 \| 0.1115 \| 1.1556 \| 1.0750 \| \| No log \| 10.4 \| 52 \| 1.1839 \| 0.0845 \| 1.1839 \| 1.0881 \| \| No log \| 10.8 \| 54 \| 1.2097 \| 0.0686 \| 1.2097 \| 1.0998 \| \| No log \| 11.2 \| 56 \| 1.2016 \| 0.0686 \| 1.2016 \| 1.0962 \| \| No log \| 11.6 \| 58 \| 1.1247 \| 0.0713 \| 1.1247 \| 1.0605 \| \| No log \| 12.0 \| 60 \| 1.0039 \| 0.1775 \| 1.0039 \| 1.0020 \| \| No log \| 12.4 \| 62 \| 0.9073 \| 0.2239 \| 0.9073 \| 0.9525 \| \| No log \| 12.8 \| 64 \| 1.0174 \| 0.1014 \| 1.0174 \| 1.0087 \| \| No log \| 13.2 \| 66 \| 1.2606 \| 0.1176 \| 1.2606 \| 1.1228 \| \| No log \| 13.6 \| 68 \| 1.3323 \| 0.1479 \| 1.3323 \| 1.1542 \| \| No log \| 14.0 \| 70 \| 1.3229 \| 0.0704 \| 1.3229 \| 1.1502 \| \| No log \| 14.4 \| 72 \| 1.0368 \| 0.1843 \| 1.0368 \| 1.0182 \| \| No log \| 14.8 \| 74 \| 0.9368 \| 0.2124 \| 0.9368 \| 0.9679 \| \| No log \| 15.2 \| 76 \| 0.9609 \| 0.2076 \| 0.9609 \| 0.9803 \| \| No log \| 15.6 \| 78 \| 1.1684 \| 0.1086 \| 1.1684 \| 1.0809 \| \| No log \| 16.0 \| 80 \| 1.2916 \| 0.1417 \| 1.2916 \| 1.1365 \| \| No log \| 16.4 \| 82 \| 1.2723 \| 0.1145 \| 1.2723 \| 1.1279 \| \| No log \| 16.8 \| 84 \| 1.1180 \| 0.2070 \| 1.1180 \| 1.0573 \| \| No log \| 17.2 \| 86 \| 0.9465 \| 0.3134 \| 0.9465 \| 0.9729 \| \| No log \| 17.6 \| 88 \| 0.9163 \| 0.3194 \| 0.9163 \| 0.9572 \| \| No log \| 18.0 \| 90 \| 1.0376 \| 0.2209 \| 1.0376 \| 1.0186 \| \| No log \| 18.4 \| 92 \| 1.2168 \| 0.2070 \| 1.2168 \| 1.1031 \| \| No log \| 18.8 \| 94 \| 1.2754 \| 0.0727 \| 1.2754 \| 1.1293 \| \| No log \| 19.2 \| 96 \| 1.2909 \| 0.1200 \| 1.2909 \| 1.1362 \| \| No log \| 19.6 \| 98 \| 1.2740 \| 0.2138 \| 1.2740 \| 1.1287 \| \| No log \| 20.0 \| 100 \| 1.0757 \| 0.2354 \| 1.0757 \| 1.0372 \| \| No log \| 20.4 \| 102 \| 0.9648 \| 0.3134 \| 0.9648 \| 0.9823 \| \| No log \| 20.8 \| 104 \| 0.9900 \| 0.2537 \| 0.9900 \| 0.9950 \| \| No log \| 21.2 \| 106 \| 1.0386 \| 0.1549 \| 1.0386 \| 1.0191 \| \| No log \| 21.6 \| 108 \| 1.1480 \| 0.1206 \| 1.1480 \| 1.0714 \| \| No log \| 22.0 \| 110 \| 1.2393 \| 0.1254 \| 1.2393 \| 1.1133 \| \| No log \| 22.4 \| 112 \| 1.3027 \| 0.1198 \| 1.3027 \| 1.1414 \| \| No log \| 22.8 \| 114 \| 1.2327 \| 0.1473 \| 1.2327 \| 1.1102 \| \| No log \| 23.2 \| 116 \| 1.0803 \| 0.1176 \| 1.0803 \| 1.0394 \| \| No log \| 23.6 \| 118 \| 1.0485 \| 0.2330 \| 1.0485 \| 1.0240 \| \| No log \| 24.0 \| 120 \| 1.0691 \| 0.2545 \| 1.0691 \| 1.0340 \| \| No log \| 24.4 \| 122 \| 1.1256 \| 0.2580 \| 1.1256 \| 1.0610 \| \| No log \| 24.8 \| 124 \| 1.1114 \| 0.1764 \| 1.1114 \| 1.0542 \| \| No log \| 25.2 \| 126 \| 1.0668 \| 0.1576 \| 1.0668 \| 1.0328 \| \| No log \| 25.6 \| 128 \| 0.9976 \| 0.1726 \| 0.9976 \| 0.9988 \| \| No log \| 26.0 \| 130 \| 0.9405 \| 0.2389 \| 0.9405 \| 0.9698 \| \| No log \| 26.4 \| 132 \| 0.9616 \| 0.2507 \| 0.9616 \| 0.9806 \| \| No log \| 26.8 \| 134 \| 0.9992 \| 0.2872 \| 0.9992 \| 0.9996 \| \| No log \| 27.2 \| 136 \| 0.9222 \| 0.3022 \| 0.9222 \| 0.9603 \| \| No log \| 27.6 \| 138 \| 0.8651 \| 0.3319 \| 0.8651 \| 0.9301 \| \| No log \| 28.0 \| 140 \| 0.8733 \| 0.2328 \| 0.8733 \| 0.9345 \| \| No log \| 28.4 \| 142 \| 0.8902 \| 0.2440 \| 0.8902 \| 0.9435 \| \| No log \| 28.8 \| 144 \| 0.9273 \| 0.2116 \| 0.9273 \| 0.9629 \| \| No log \| 29.2 \| 146 \| 0.9950 \| 0.1672 \| 0.9950 \| 0.9975 \| \| No log \| 29.6 \| 148 \| 1.0746 \| 0.1238 \| 1.0746 \| 1.0366 \| \| No log \| 30.0 \| 150 \| 1.2142 \| 0.1583 \| 1.2142 \| 1.1019 \| \| No log \| 30.4 \| 152 \| 1.2794 \| 0.1174 \| 1.2794 \| 1.1311 \| \| No log \| 30.8 \| 154 \| 1.2352 \| 0.1956 \| 1.2352 \| 1.1114 \| \| No log \| 31.2 \| 156 \| 1.1476 \| 0.1884 \| 1.1476 \| 1.0712 \| \| No log \| 31.6 \| 158 \| 1.0861 \| 0.1451 \| 1.0861 \| 1.0422 \| \| No log \| 32.0 \| 160 \| 1.0964 \| 0.0648 \| 1.0964 \| 1.0471 \| \| No log \| 32.4 \| 162 \| 1.1565 \| 0.0872 \| 1.1565 \| 1.0754 \| \| No log \| 32.8 \| 164 \| 1.1985 \| 0.1320 \| 1.1985 \| 1.0948 \| \| No log \| 33.2 \| 166 \| 1.1957 \| 0.1550 \| 1.1957 \| 1.0935 \| \| No log \| 33.6 \| 168 \| 1.1242 \| 0.1774 \| 1.1242 \| 1.0603 \| \| No log \| 34.0 \| 170 \| 1.0184 \| 0.2166 \| 1.0184 \| 1.0092 \| \| No log \| 34.4 \| 172 \| 1.0672 \| 0.2031 \| 1.0672 \| 1.0330 \| \| No log \| 34.8 \| 174 \| 1.0674 \| 0.2961 \| 1.0674 \| 1.0332 \| \| No log \| 35.2 \| 176 \| 1.0550 \| 0.2288 \| 1.0550 \| 1.0272 \| \| No log \| 35.6 \| 178 \| 1.0939 \| 0.1618 \| 1.0939 \| 1.0459 \| \| No log \| 36.0 \| 180 \| 1.1366 \| 0.0953 \| 1.1366 \| 1.0661 \| \| No log \| 36.4 \| 182 \| 1.1833 \| 0.1618 \| 1.1833 \| 1.0878 \| \| No log \| 36.8 \| 184 \| 1.2085 \| 0.2247 \| 1.2085 \| 1.0993 \| \| No log \| 37.2 \| 186 \| 1.1489 \| 0.2330 \| 1.1489 \| 1.0719 \| \| No log \| 37.6 \| 188 \| 1.0133 \| 0.3059 \| 1.0133 \| 1.0066 \| \| No log \| 38.0 \| 190 \| 0.9738 \| 0.3110 \| 0.9738 \| 0.9868 \| \| No log \| 38.4 \| 192 \| 0.9567 \| 0.2554 \| 0.9567 \| 0.9781 \| \| No log \| 38.8 \| 194 \| 1.0198 \| 0.2554 \| 1.0198 \| 1.0099 \| \| No log \| 39.2 \| 196 \| 1.0940 \| 0.2192 \| 1.0940 \| 1.0459 \| \| No log \| 39.6 \| 198 \| 1.0901 \| 0.1726 \| 1.0901 \| 1.0441 \| \| No log \| 40.0 \| 200 \| 1.0486 \| 0.2323 \| 1.0486 \| 1.0240 \| \| No log \| 40.4 \| 202 \| 1.0287 \| 0.2507 \| 1.0287 \| 1.0142 \| \| No log \| 40.8 \| 204 \| 1.0958 \| 0.2330 \| 1.0958 \| 1.0468 \| \| No log \| 41.2 \| 206 \| 1.1211 \| 0.2330 \| 1.1211 \| 1.0588 \| \| No log \| 41.6 \| 208 \| 1.1175 \| 0.2330 \| 1.1175 \| 1.0571 \| \| No log \| 42.0 \| 210 \| 1.0222 \| 0.2461 \| 1.0222 \| 1.0110 \| \| No log \| 42.4 \| 212 \| 0.9571 \| 0.2934 \| 0.9571 \| 0.9783 \| \| No log \| 42.8 \| 214 \| 0.9372 \| 0.2934 \| 0.9372 \| 0.9681 \| \| No log \| 43.2 \| 216 \| 0.9523 \| 0.2830 \| 0.9523 \| 0.9759 \| \| No log \| 43.6 \| 218 \| 0.9940 \| 0.2682 \| 0.9940 \| 0.9970 \| \| No log \| 44.0 \| 220 \| 1.0150 \| 0.2682 \| 1.0150 \| 1.0075 \| \| No log \| 44.4 \| 222 \| 0.9591 \| 0.2898 \| 0.9591 \| 0.9793 \| \| No log \| 44.8 \| 224 \| 0.9037 \| 0.3579 \| 0.9037 \| 0.9506 \| \| No log \| 45.2 \| 226 \| 0.8545 \| 0.3777 \| 0.8545 \| 0.9244 \| \| No log \| 45.6 \| 228 \| 0.8533 \| 0.3777 \| 0.8533 \| 0.9237 \| \| No log \| 46.0 \| 230 \| 0.8554 \| 0.3409 \| 0.8554 \| 0.9249 \| \| No log \| 46.4 \| 232 \| 0.7829 \| 0.3494 \| 0.7829 \| 0.8848 \| \| No log \| 46.8 \| 234 \| 0.7568 \| 0.3737 \| 0.7568 \| 0.8700 \| \| No log \| 47.2 \| 236 \| 0.7869 \| 0.3425 \| 0.7869 \| 0.8871 \| \| No log \| 47.6 \| 238 \| 0.8789 \| 0.3579 \| 0.8789 \| 0.9375 \| \| No log \| 48.0 \| 240 \| 0.9512 \| 0.3161 \| 0.9512 \| 0.9753 \| \| No log \| 48.4 \| 242 \| 0.9939 \| 0.2982 \| 0.9939 \| 0.9969 \| \| No log \| 48.8 \| 244 \| 0.9759 \| 0.2982 \| 0.9759 \| 0.9879 \| \| No log \| 49.2 \| 246 \| 0.9258 \| 0.3161 \| 0.9258 \| 0.9622 \| \| No log \| 49.6 \| 248 \| 0.8924 \| 0.3269 \| 0.8924 \| 0.9447 \| \| No log \| 50.0 \| 250 \| 0.8939 \| 0.3269 \| 0.8939 \| 0.9455 \| \| No log \| 50.4 \| 252 \| 0.8985 \| 0.3214 \| 0.8985 \| 0.9479 \| \| No log \| 50.8 \| 254 \| 0.9009 \| 0.3359 \| 0.9009 \| 0.9492 \| \| No log \| 51.2 \| 256 \| 0.9503 \| 0.3302 \| 0.9503 \| 0.9748 \| \| No log \| 51.6 \| 258 \| 1.0464 \| 0.2643 \| 1.0464 \| 1.0229 \| \| No log \| 52.0 \| 260 \| 1.1513 \| 0.2518 \| 1.1513 \| 1.0730 \| \| No log \| 52.4 \| 262 \| 1.1727 \| 0.2518 \| 1.1727 \| 1.0829 \| \| No log \| 52.8 \| 264 \| 1.1205 \| 0.2843 \| 1.1205 \| 1.0585 \| \| No log \| 53.2 \| 266 \| 1.0426 \| 0.3010 \| 1.0426 \| 1.0211 \| \| No log \| 53.6 \| 268 \| 0.9458 \| 0.3110 \| 0.9458 \| 0.9725 \| \| No log \| 54.0 \| 270 \| 0.9039 \| 0.3110 \| 0.9039 \| 0.9507 \| \| No log \| 54.4 \| 272 \| 0.8963 \| 0.3214 \| 0.8963 \| 0.9467 \| \| No log \| 54.8 \| 274 \| 0.9164 \| 0.2682 \| 0.9164 \| 0.9573 \| \| No log \| 55.2 \| 276 \| 0.9534 \| 0.2682 \| 0.9534 \| 0.9764 \| \| No log \| 55.6 \| 278 \| 1.0053 \| 0.2682 \| 1.0053 \| 1.0026 \| \| No log \| 56.0 \| 280 \| 1.0373 \| 0.2682 \| 1.0373 \| 1.0185 \| \| No log \| 56.4 \| 282 \| 1.0683 \| 0.2682 \| 1.0683 \| 1.0336 \| \| No log \| 56.8 \| 284 \| 1.0886 \| 0.2850 \| 1.0886 \| 1.0433 \| \| No log \| 57.2 \| 286 \| 1.1172 \| 0.2687 \| 1.1172 \| 1.0570 \| \| No log \| 57.6 \| 288 \| 1.1151 \| 0.2687 \| 1.1151 \| 1.0560 \| \| No log \| 58.0 \| 290 \| 1.0486 \| 0.2682 \| 1.0486 \| 1.0240 \| \| No log \| 58.4 \| 292 \| 0.9765 \| 0.2934 \| 0.9765 \| 0.9882 \| \| No log \| 58.8 \| 294 \| 0.9303 \| 0.2754 \| 0.9303 \| 0.9645 \| \| No log \| 59.2 \| 296 \| 0.8948 \| 0.2807 \| 0.8948 \| 0.9459 \| \| No log \| 59.6 \| 298 \| 0.9041 \| 0.2754 \| 0.9041 \| 0.9508 \| \| No log \| 60.0 \| 300 \| 0.9135 \| 0.3217 \| 0.9135 \| 0.9558 \| \| No log \| 60.4 \| 302 \| 0.9702 \| 0.2999 \| 0.9702 \| 0.9850 \| \| No log \| 60.8 \| 304 \| 1.0872 \| 0.2732 \| 1.0872 \| 1.0427 \| \| No log \| 61.2 \| 306 \| 1.1963 \| 0.2601 \| 1.1963 \| 1.0937 \| \| No log \| 61.6 \| 308 \| 1.2333 \| 0.2319 \| 1.2333 \| 1.1105 \| \| No log \| 62.0 \| 310 \| 1.2058 \| 0.2319 \| 1.2058 \| 1.0981 \| \| No log \| 62.4 \| 312 \| 1.1687 \| 0.2643 \| 1.1687 \| 1.0811 \| \| No log \| 62.8 \| 314 \| 1.1065 \| 0.2330 \| 1.1065 \| 1.0519 \| \| No log \| 63.2 \| 316 \| 1.0488 \| 0.2416 \| 1.0488 \| 1.0241 \| \| No log \| 63.6 \| 318 \| 1.0236 \| 0.2461 \| 1.0236 \| 1.0117 \| \| No log \| 64.0 \| 320 \| 1.0416 \| 0.2461 \| 1.0416 \| 1.0206 \| \| No log \| 64.4 \| 322 \| 1.0806 \| 0.2312 \| 1.0806 \| 1.0395 \| \| No log \| 64.8 \| 324 \| 1.0938 \| 0.2312 \| 1.0938 \| 1.0458 \| \| No log \| 65.2 \| 326 \| 1.0957 \| 0.2312 \| 1.0957 \| 1.0468 \| \| No log \| 65.6 \| 328 \| 1.1094 \| 0.2231 \| 1.1094 \| 1.0533 \| \| No log \| 66.0 \| 330 \| 1.0897 \| 0.2372 \| 1.0897 \| 1.0439 \| \| No log \| 66.4 \| 332 \| 1.0418 \| 0.2507 \| 1.0418 \| 1.0207 \| \| No log \| 66.8 \| 334 \| 1.0109 \| 0.2554 \| 1.0109 \| 1.0054 \| \| No log \| 67.2 \| 336 \| 0.9840 \| 0.2537 \| 0.9840 \| 0.9919 \| \| No log \| 67.6 \| 338 \| 0.9836 \| 0.2728 \| 0.9836 \| 0.9918 \| \| No log \| 68.0 \| 340 \| 1.0211 \| 0.2507 \| 1.0211 \| 1.0105 \| \| No log \| 68.4 \| 342 \| 1.0395 \| 0.2461 \| 1.0395 \| 1.0196 \| \| No log \| 68.8 \| 344 \| 1.0772 \| 0.2635 \| 1.0772 \| 1.0379 \| \| No log \| 69.2 \| 346 \| 1.1149 \| 0.2590 \| 1.1149 \| 1.0559 \| \| No log \| 69.6 \| 348 \| 1.1039 \| 0.2590 \| 1.1039 \| 1.0507 \| \| No log \| 70.0 \| 350 \| 1.0739 \| 0.2372 \| 1.0739 \| 1.0363 \| \| No log \| 70.4 \| 352 \| 1.0404 \| 0.2507 \| 1.0404 \| 1.0200 \| \| No log \| 70.8 \| 354 \| 0.9935 \| 0.2881 \| 0.9935 \| 0.9968 \| \| No log \| 71.2 \| 356 \| 0.9676 \| 0.2781 \| 0.9676 \| 0.9837 \| \| No log \| 71.6 \| 358 \| 0.9752 \| 0.3052 \| 0.9752 \| 0.9875 \| \| No log \| 72.0 \| 360 \| 0.9769 \| 0.3052 \| 0.9769 \| 0.9884 \| \| No log \| 72.4 \| 362 \| 1.0081 \| 0.3052 \| 1.0081 \| 1.0041 \| \| No log \| 72.8 \| 364 \| 1.0776 \| 0.2524 \| 1.0776 \| 1.0381 \| \| No log \| 73.2 \| 366 \| 1.1453 \| 0.1943 \| 1.1453 \| 1.0702 \| \| No log \| 73.6 \| 368 \| 1.1644 \| 0.1873 \| 1.1644 \| 1.0791 \| \| No log \| 74.0 \| 370 \| 1.1727 \| 0.1873 \| 1.1727 \| 1.0829 \| \| No log \| 74.4 \| 372 \| 1.1770 \| 0.1873 \| 1.1770 \| 1.0849 \| \| No log \| 74.8 \| 374 \| 1.1415 \| 0.1873 \| 1.1415 \| 1.0684 \| \| No log \| 75.2 \| 376 \| 1.1092 \| 0.2115 \| 1.1092 \| 1.0532 \| \| No log \| 75.6 \| 378 \| 1.0808 \| 0.2898 \| 1.0808 \| 1.0396 \| \| No log \| 76.0 \| 380 \| 1.0451 \| 0.2948 \| 1.0451 \| 1.0223 \| \| No log \| 76.4 \| 382 \| 1.0226 \| 0.2806 \| 1.0226 \| 1.0112 \| \| No log \| 76.8 \| 384 \| 1.0140 \| 0.3029 \| 1.0140 \| 1.0070 \| \| No log \| 77.2 \| 386 \| 1.0344 \| 0.3161 \| 1.0344 \| 1.0171 \| \| No log \| 77.6 \| 388 \| 1.0730 \| 0.2802 \| 1.0730 \| 1.0359 \| \| No log \| 78.0 \| 390 \| 1.0829 \| 0.2687 \| 1.0829 \| 1.0406 \| \| No log \| 78.4 \| 392 \| 1.0565 \| 0.2802 \| 1.0565 \| 1.0279 \| \| No log \| 78.8 \| 394 \| 1.0195 \| 0.3110 \| 1.0195 \| 1.0097 \| \| No log \| 79.2 \| 396 \| 0.9883 \| 0.3082 \| 0.9883 \| 0.9941 \| \| No log \| 79.6 \| 398 \| 0.9735 \| 0.3082 \| 0.9735 \| 0.9867 \| \| No log \| 80.0 \| 400 \| 0.9817 \| 0.3082 \| 0.9817 \| 0.9908 \| \| No log \| 80.4 \| 402 \| 0.9895 \| 0.3082 \| 0.9895 \| 0.9947 \| \| No log \| 80.8 \| 404 \| 1.0064 \| 0.3082 \| 1.0064 \| 1.0032 \| \| No log \| 81.2 \| 406 \| 1.0443 \| 0.3110 \| 1.0443 \| 1.0219 \| \| No log \| 81.6 \| 408 \| 1.0929 \| 0.2601 \| 1.0929 \| 1.0454 \| \| No log \| 82.0 \| 410 \| 1.1361 \| 0.2319 \| 1.1361 \| 1.0659 \| \| No log \| 82.4 \| 412 \| 1.1534 \| 0.2280 \| 1.1534 \| 1.0740 \| \| No log \| 82.8 \| 414 \| 1.1552 \| 0.2280 \| 1.1552 \| 1.0748 \| \| No log \| 83.2 \| 416 \| 1.1361 \| 0.2280 \| 1.1361 \| 1.0659 \| \| No log \| 83.6 \| 418 \| 1.1090 \| 0.2319 \| 1.1090 \| 1.0531 \| \| No log \| 84.0 \| 420 \| 1.0682 \| 0.2643 \| 1.0682 \| 1.0335 \| \| No log \| 84.4 \| 422 \| 1.0314 \| 0.2898 \| 1.0314 \| 1.0156 \| \| No log \| 84.8 \| 424 \| 1.0096 \| 0.2577 \| 1.0096 \| 1.0048 \| \| No log \| 85.2 \| 426 \| 1.0108 \| 0.2806 \| 1.0108 \| 1.0054 \| \| No log \| 85.6 \| 428 \| 1.0292 \| 0.2948 \| 1.0292 \| 1.0145 \| \| No log \| 86.0 \| 430 \| 1.0497 \| 0.2850 \| 1.0497 \| 1.0245 \| \| No log \| 86.4 \| 432 \| 1.0606 \| 0.2545 \| 1.0606 \| 1.0298 \| \| No log \| 86.8 \| 434 \| 1.0645 \| 0.2590 \| 1.0645 \| 1.0317 \| \| No log \| 87.2 \| 436 \| 1.0567 \| 0.2590 \| 1.0567 \| 1.0279 \| \| No log \| 87.6 \| 438 \| 1.0379 \| 0.2590 \| 1.0379 \| 1.0188 \| \| No log \| 88.0 \| 440 \| 1.0118 \| 0.2756 \| 1.0118 \| 1.0059 \| \| No log \| 88.4 \| 442 \| 0.9808 \| 0.3029 \| 0.9808 \| 0.9903 \| \| No log \| 88.8 \| 444 \| 0.9686 \| 0.3029 \| 0.9686 \| 0.9842 \| \| No log \| 89.2 \| 446 \| 0.9716 \| 0.3029 \| 0.9716 \| 0.9857 \| \| No log \| 89.6 \| 448 \| 0.9889 \| 0.3029 \| 0.9889 \| 0.9944 \| \| No log \| 90.0 \| 450 \| 1.0088 \| 0.2977 \| 1.0088 \| 1.0044 \| \| No log \| 90.4 \| 452 \| 1.0223 \| 0.2898 \| 1.0223 \| 1.0111 \| \| No log \| 90.8 \| 454 \| 1.0382 \| 0.2898 \| 1.0382 \| 1.0189 \| \| No log \| 91.2 \| 456 \| 1.0432 \| 0.2590 \| 1.0432 \| 1.0214 \| \| No log \| 91.6 \| 458 \| 1.0437 \| 0.2898 \| 1.0437 \| 1.0216 \| \| No log \| 92.0 \| 460 \| 1.0541 \| 0.2590 \| 1.0541 \| 1.0267 \| \| No log \| 92.4 \| 462 \| 1.0675 \| 0.2590 \| 1.0675 \| 1.0332 \| \| No log \| 92.8 \| 464 \| 1.0758 \| 0.2590 \| 1.0758 \| 1.0372 \| \| No log \| 93.2 \| 466 \| 1.0764 \| 0.2481 \| 1.0764 \| 1.0375 \| \| No log \| 93.6 \| 468 \| 1.0694 \| 0.2590 \| 1.0694 \| 1.0341 \| \| No log \| 94.0 \| 470 \| 1.0591 \| 0.2898 \| 1.0591 \| 1.0291 \| \| No log \| 94.4 \| 472 \| 1.0470 \| 0.2898 \| 1.0470 \| 1.0232 \| \| No log \| 94.8 \| 474 \| 1.0427 \| 0.2898 \| 1.0427 \| 1.0211 \| \| No log \| 95.2 \| 476 \| 1.0401 \| 0.2898 \| 1.0401 \| 1.0199 \| \| No log \| 95.6 \| 478 \| 1.0364 \| 0.2898 \| 1.0364 \| 1.0180 \| \| No log \| 96.0 \| 480 \| 1.0309 \| 0.2898 \| 1.0309 \| 1.0153 \| \| No log \| 96.4 \| 482 \| 1.0296 \| 0.2898 \| 1.0296 \| 1.0147 \| \| No log \| 96.8 \| 484 \| 1.0257 \| 0.2898 \| 1.0257 \| 1.0128 \| \| No log \| 97.2 \| 486 \| 1.0236 \| 0.2898 \| 1.0236 \| 1.0117 \| \| No log \| 97.6 \| 488 \| 1.0233 \| 0.2898 \| 1.0233 \| 1.0116 \| \| No log \| 98.0 \| 490 \| 1.0236 \| 0.2898 \| 1.0236 \| 1.0117 \| \| No log \| 98.4 \| 492 \| 1.0240 \| 0.2898 \| 1.0240 \| 1.0119 \| \| No log \| 98.8 \| 494 \| 1.0237 \| 0.2898 \| 1.0237 \| 1.0118 \| \| No log \| 99.2 \| 496 \| 1.0235 \| 0.2898 \| 1.0235 \| 1.0117 \| \| No log \| 99.6 \| 498 \| 1.0237 \| 0.2898 \| 1.0237 \| 1.0118 \| \| 0.1613 \| 100.0 \| 500 \| 1.0238 \| 0.2898 \| 1.0238 \| 1.0119 \| ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.0+cu118 - Datasets 2.21.0 - Tokenizers 0.19.1
mamung/345fef6a-8237-4ee7-82b7-ba614660cdd1	mamung	2025-01-21T12:20:18Z	14	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:trl-internal-testing/tiny-random-LlamaForCausalLM", "base_model:adapter:trl-internal-testing/tiny-random-LlamaForCausalLM", "region:us" ]	null	2025-01-21T12:18:20Z	--- library_name: peft base_model: trl-internal-testing/tiny-random-LlamaForCausalLM tags: - axolotl - generated_from_trainer model-index: - name: 345fef6a-8237-4ee7-82b7-ba614660cdd1 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: trl-internal-testing/tiny-random-LlamaForCausalLM bf16: true chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 570f06fa330a02a8_train_data.json ds_type: json format: custom path: /workspace/input_data/570f06fa330a02a8_train_data.json type: field_input: starter_code field_instruction: question_content field_output: test format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 256 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 32 gradient_checkpointing: true group_by_length: false hub_model_id: mamung/345fef6a-8237-4ee7-82b7-ba614660cdd1 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 64 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 32 lora_target_linear: true lora_target_modules: - q_proj - k_proj - v_proj - o_proj lr_scheduler: cosine max_grad_norm: 2 max_steps: 100 micro_batch_size: 2 mlflow_experiment_name: /tmp/570f06fa330a02a8_train_data.json model_type: AutoModelForCausalLM num_epochs: 3 optim_args: adam_beta1: 0.9 adam_beta2: 0.95 adam_epsilon: 1.0e-05 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 2048 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: eddysang wandb_mode: online wandb_name: 835a7d05-70b3-4946-9a54-04ee779c4f19 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 835a7d05-70b3-4946-9a54-04ee779c4f19 warmup_steps: 20 weight_decay: 0.02 xformers_attention: false ``` </details><br> # 345fef6a-8237-4ee7-82b7-ba614660cdd1 This model is a fine-tuned version of [trl-internal-testing/tiny-random-LlamaForCausalLM](https://huggingface.co/trl-internal-testing/tiny-random-LlamaForCausalLM) on the None dataset. It achieves the following results on the evaluation set: - Loss: 10.2883 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 32 - total_train_batch_size: 64 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.95,adam_epsilon=1e-05 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 20 - training_steps: 86 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| No log \| 0.0350 \| 1 \| 10.3792 \| \| 10.3758 \| 0.2801 \| 8 \| 10.3774 \| \| 10.3712 \| 0.5602 \| 16 \| 10.3714 \| \| 10.3635 \| 0.8403 \| 24 \| 10.3584 \| \| 13.5544 \| 1.1368 \| 32 \| 10.3373 \| \| 10.2418 \| 1.4168 \| 40 \| 10.3136 \| \| 10.2948 \| 1.6969 \| 48 \| 10.2994 \| \| 10.258 \| 1.9770 \| 56 \| 10.2935 \| \| 10.1202 \| 2.2735 \| 64 \| 10.2904 \| \| 10.3454 \| 2.5536 \| 72 \| 10.2889 \| \| 10.0236 \| 2.8337 \| 80 \| 10.2883 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
tolgaakar/Mistral-Small-Instruct-2409-FP8-Dynamic	tolgaakar	2025-01-21T12:20:13Z	28	0	null	[ "safetensors", "mistral", "base_model:mistralai/Mistral-Small-Instruct-2409", "base_model:quantized:mistralai/Mistral-Small-Instruct-2409", "license:other", "compressed-tensors", "region:us" ]	null	2025-01-21T11:40:26Z	--- license: other license_name: mrl license_link: https://mistral.ai/licenses/MRL-0.1.md base_model: - mistralai/Mistral-Small-Instruct-2409 --- This model was converted to FP8 format from mistralai/Mistral-Small-Instruct-2409 using the llmcompressor library by vLLM. Refer to the [original model card](https://huggingface.co/mistralai/Mistral-Small-Instruct-2409) for more details on the model.
chauhoang/e3c40096-d899-4c00-83fe-a263498a511e	chauhoang	2025-01-21T12:20:02Z	6	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:TinyLlama/TinyLlama-1.1B-Chat-v0.6", "base_model:adapter:TinyLlama/TinyLlama-1.1B-Chat-v0.6", "license:apache-2.0", "region:us" ]	null	2025-01-21T12:16:49Z	--- library_name: peft license: apache-2.0 base_model: TinyLlama/TinyLlama-1.1B-Chat-v0.6 tags: - axolotl - generated_from_trainer model-index: - name: e3c40096-d899-4c00-83fe-a263498a511e results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: TinyLlama/TinyLlama-1.1B-Chat-v0.6 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 5b44368ea0d7d142_train_data.json ds_type: json format: custom path: /workspace/input_data/5b44368ea0d7d142_train_data.json type: field_input: aspect field_instruction: document field_output: summary format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 5 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: chauhoang/e3c40096-d899-4c00-83fe-a263498a511e hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0001 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 5 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 50 micro_batch_size: 2 mlflow_experiment_name: /tmp/5b44368ea0d7d142_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 074be582-c2ba-4209-b6c2-0d56b0df9cdc wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 074be582-c2ba-4209-b6c2-0d56b0df9cdc warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # e3c40096-d899-4c00-83fe-a263498a511e This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-Chat-v0.6](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v0.6) on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.2210 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0001 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 50 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| No log \| 0.0047 \| 1 \| 2.4446 \| \| 2.5709 \| 0.0468 \| 10 \| 2.4348 \| \| 2.3494 \| 0.0936 \| 20 \| 2.3377 \| \| 2.227 \| 0.1404 \| 30 \| 2.2550 \| \| 2.2299 \| 0.1871 \| 40 \| 2.2244 \| \| 2.3316 \| 0.2339 \| 50 \| 2.2210 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
trenden/51365222-6e8d-44e5-b9fb-c99768921c36	trenden	2025-01-21T12:18:36Z	6	0	peft	[ "peft", "safetensors", "phi3", "axolotl", "generated_from_trainer", "custom_code", "base_model:microsoft/Phi-3-mini-128k-instruct", "base_model:adapter:microsoft/Phi-3-mini-128k-instruct", "license:mit", "region:us" ]	null	2025-01-21T12:05:23Z	--- library_name: peft license: mit base_model: microsoft/Phi-3-mini-128k-instruct tags: - axolotl - generated_from_trainer model-index: - name: 51365222-6e8d-44e5-b9fb-c99768921c36 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: microsoft/Phi-3-mini-128k-instruct bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - d23a80b910821333_train_data.json ds_type: json format: custom path: /workspace/input_data/d23a80b910821333_train_data.json type: field_input: input field_instruction: instruction field_output: output format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: trenden/51365222-6e8d-44e5-b9fb-c99768921c36 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/d23a80b910821333_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: c7400a48-f57f-4a5f-8c57-bf09a3ce88d3 wandb_project: Birthday-SN56-3-Gradients-On-Demand wandb_run: your_name wandb_runid: c7400a48-f57f-4a5f-8c57-bf09a3ce88d3 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # 51365222-6e8d-44e5-b9fb-c99768921c36 This model is a fine-tuned version of [microsoft/Phi-3-mini-128k-instruct](https://huggingface.co/microsoft/Phi-3-mini-128k-instruct) on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.4281 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 10.658 \| 0.0001 \| 1 \| 2.5837 \| \| 10.4572 \| 0.0002 \| 3 \| 2.5780 \| \| 9.8738 \| 0.0004 \| 6 \| 2.5291 \| \| 8.7801 \| 0.0006 \| 9 \| 2.4281 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
MayBashendy/ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k1_task7_organization	MayBashendy	2025-01-21T12:16:56Z	5	0	transformers	[ "transformers", "safetensors", "bert", "text-classification", "generated_from_trainer", "base_model:aubmindlab/bert-base-arabertv02", "base_model:finetune:aubmindlab/bert-base-arabertv02", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2025-01-21T12:14:27Z	--- library_name: transformers base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k1_task7_organization results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k1_task7_organization This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.7404 - Qwk: 0.3238 - Mse: 0.7404 - Rmse: 0.8605 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 100 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Qwk \| Mse \| Rmse \| \|:-------------:\|:-------:\|:----:\|:---------------:\|:-------:\|:------:\|:------:\| \| No log \| 0.6667 \| 2 \| 2.6632 \| -0.1213 \| 2.6632 \| 1.6319 \| \| No log \| 1.3333 \| 4 \| 1.3882 \| 0.1265 \| 1.3882 \| 1.1782 \| \| No log \| 2.0 \| 6 \| 1.1319 \| -0.0970 \| 1.1319 \| 1.0639 \| \| No log \| 2.6667 \| 8 \| 1.0927 \| -0.0810 \| 1.0927 \| 1.0453 \| \| No log \| 3.3333 \| 10 \| 0.9247 \| 0.0058 \| 0.9247 \| 0.9616 \| \| No log \| 4.0 \| 12 \| 0.8601 \| 0.0236 \| 0.8601 \| 0.9274 \| \| No log \| 4.6667 \| 14 \| 0.8247 \| 0.0393 \| 0.8247 \| 0.9081 \| \| No log \| 5.3333 \| 16 \| 0.7599 \| 0.0 \| 0.7599 \| 0.8717 \| \| No log \| 6.0 \| 18 \| 0.7561 \| 0.0481 \| 0.7561 \| 0.8696 \| \| No log \| 6.6667 \| 20 \| 0.7398 \| 0.0937 \| 0.7398 \| 0.8601 \| \| No log \| 7.3333 \| 22 \| 0.6974 \| 0.0889 \| 0.6974 \| 0.8351 \| \| No log \| 8.0 \| 24 \| 0.7067 \| 0.0840 \| 0.7067 \| 0.8407 \| \| No log \| 8.6667 \| 26 \| 0.7288 \| 0.1139 \| 0.7288 \| 0.8537 \| \| No log \| 9.3333 \| 28 \| 0.7213 \| 0.0327 \| 0.7213 \| 0.8493 \| \| No log \| 10.0 \| 30 \| 0.6967 \| 0.0393 \| 0.6967 \| 0.8347 \| \| No log \| 10.6667 \| 32 \| 0.6970 \| 0.0846 \| 0.6970 \| 0.8349 \| \| No log \| 11.3333 \| 34 \| 0.6807 \| 0.1327 \| 0.6807 \| 0.8251 \| \| No log \| 12.0 \| 36 \| 0.6864 \| 0.2783 \| 0.6864 \| 0.8285 \| \| No log \| 12.6667 \| 38 \| 0.7758 \| 0.1341 \| 0.7758 \| 0.8808 \| \| No log \| 13.3333 \| 40 \| 1.0549 \| 0.1650 \| 1.0549 \| 1.0271 \| \| No log \| 14.0 \| 42 \| 1.0926 \| 0.1753 \| 1.0926 \| 1.0453 \| \| No log \| 14.6667 \| 44 \| 0.9507 \| 0.1323 \| 0.9507 \| 0.9750 \| \| No log \| 15.3333 \| 46 \| 0.9933 \| 0.2153 \| 0.9933 \| 0.9966 \| \| No log \| 16.0 \| 48 \| 1.0836 \| 0.1926 \| 1.0836 \| 1.0410 \| \| No log \| 16.6667 \| 50 \| 1.1782 \| 0.1077 \| 1.1782 \| 1.0854 \| \| No log \| 17.3333 \| 52 \| 1.0397 \| 0.1339 \| 1.0397 \| 1.0196 \| \| No log \| 18.0 \| 54 \| 0.8137 \| 0.2715 \| 0.8137 \| 0.9021 \| \| No log \| 18.6667 \| 56 \| 0.7808 \| 0.3541 \| 0.7808 \| 0.8836 \| \| No log \| 19.3333 \| 58 \| 0.7654 \| 0.3622 \| 0.7654 \| 0.8749 \| \| No log \| 20.0 \| 60 \| 0.9714 \| 0.2239 \| 0.9714 \| 0.9856 \| \| No log \| 20.6667 \| 62 \| 1.0619 \| 0.2507 \| 1.0619 \| 1.0305 \| \| No log \| 21.3333 \| 64 \| 1.0113 \| 0.1856 \| 1.0113 \| 1.0056 \| \| No log \| 22.0 \| 66 \| 0.8359 \| 0.2662 \| 0.8359 \| 0.9143 \| \| No log \| 22.6667 \| 68 \| 0.7538 \| 0.2414 \| 0.7538 \| 0.8682 \| \| No log \| 23.3333 \| 70 \| 0.7411 \| 0.2237 \| 0.7411 \| 0.8609 \| \| No log \| 24.0 \| 72 \| 0.8121 \| 0.2096 \| 0.8121 \| 0.9012 \| \| No log \| 24.6667 \| 74 \| 0.9212 \| 0.2253 \| 0.9212 \| 0.9598 \| \| No log \| 25.3333 \| 76 \| 0.9368 \| 0.3586 \| 0.9368 \| 0.9679 \| \| No log \| 26.0 \| 78 \| 0.8852 \| 0.3344 \| 0.8852 \| 0.9409 \| \| No log \| 26.6667 \| 80 \| 0.8121 \| 0.3261 \| 0.8121 \| 0.9012 \| \| No log \| 27.3333 \| 82 \| 0.8265 \| 0.3918 \| 0.8265 \| 0.9091 \| \| No log \| 28.0 \| 84 \| 0.8877 \| 0.3234 \| 0.8877 \| 0.9422 \| \| No log \| 28.6667 \| 86 \| 0.8820 \| 0.3099 \| 0.8820 \| 0.9392 \| \| No log \| 29.3333 \| 88 \| 0.8031 \| 0.3196 \| 0.8031 \| 0.8962 \| \| No log \| 30.0 \| 90 \| 0.8070 \| 0.3127 \| 0.8070 \| 0.8983 \| \| No log \| 30.6667 \| 92 \| 0.9023 \| 0.2967 \| 0.9023 \| 0.9499 \| \| No log \| 31.3333 \| 94 \| 0.9381 \| 0.2692 \| 0.9381 \| 0.9686 \| \| No log \| 32.0 \| 96 \| 0.8218 \| 0.2967 \| 0.8218 \| 0.9066 \| \| No log \| 32.6667 \| 98 \| 0.6896 \| 0.2099 \| 0.6896 \| 0.8304 \| \| No log \| 33.3333 \| 100 \| 0.6649 \| 0.2317 \| 0.6649 \| 0.8154 \| \| No log \| 34.0 \| 102 \| 0.6654 \| 0.2476 \| 0.6654 \| 0.8157 \| \| No log \| 34.6667 \| 104 \| 0.7198 \| 0.3840 \| 0.7198 \| 0.8484 \| \| No log \| 35.3333 \| 106 \| 0.7595 \| 0.4020 \| 0.7595 \| 0.8715 \| \| No log \| 36.0 \| 108 \| 0.7477 \| 0.3498 \| 0.7477 \| 0.8647 \| \| No log \| 36.6667 \| 110 \| 0.7214 \| 0.3572 \| 0.7214 \| 0.8494 \| \| No log \| 37.3333 \| 112 \| 0.7180 \| 0.2379 \| 0.7180 \| 0.8474 \| \| No log \| 38.0 \| 114 \| 0.7629 \| 0.1972 \| 0.7629 \| 0.8735 \| \| No log \| 38.6667 \| 116 \| 0.7824 \| 0.1972 \| 0.7824 \| 0.8845 \| \| No log \| 39.3333 \| 118 \| 0.7750 \| 0.1972 \| 0.7750 \| 0.8804 \| \| No log \| 40.0 \| 120 \| 0.7531 \| 0.2652 \| 0.7531 \| 0.8678 \| \| No log \| 40.6667 \| 122 \| 0.7773 \| 0.2171 \| 0.7773 \| 0.8817 \| \| No log \| 41.3333 \| 124 \| 0.8507 \| 0.2692 \| 0.8507 \| 0.9223 \| \| No log \| 42.0 \| 126 \| 0.9124 \| 0.3234 \| 0.9124 \| 0.9552 \| \| No log \| 42.6667 \| 128 \| 0.8637 \| 0.2967 \| 0.8637 \| 0.9293 \| \| No log \| 43.3333 \| 130 \| 0.8389 \| 0.2967 \| 0.8389 \| 0.9159 \| \| No log \| 44.0 \| 132 \| 0.7617 \| 0.2498 \| 0.7617 \| 0.8727 \| \| No log \| 44.6667 \| 134 \| 0.7038 \| 0.3341 \| 0.7038 \| 0.8390 \| \| No log \| 45.3333 \| 136 \| 0.6932 \| 0.2981 \| 0.6932 \| 0.8326 \| \| No log \| 46.0 \| 138 \| 0.6988 \| 0.3894 \| 0.6988 \| 0.8359 \| \| No log \| 46.6667 \| 140 \| 0.7067 \| 0.3894 \| 0.7067 \| 0.8406 \| \| No log \| 47.3333 \| 142 \| 0.7387 \| 0.3399 \| 0.7387 \| 0.8595 \| \| No log \| 48.0 \| 144 \| 0.7523 \| 0.3590 \| 0.7523 \| 0.8673 \| \| No log \| 48.6667 \| 146 \| 0.7570 \| 0.3590 \| 0.7570 \| 0.8701 \| \| No log \| 49.3333 \| 148 \| 0.8021 \| 0.3940 \| 0.8021 \| 0.8956 \| \| No log \| 50.0 \| 150 \| 0.7996 \| 0.4329 \| 0.7996 \| 0.8942 \| \| No log \| 50.6667 \| 152 \| 0.7466 \| 0.3590 \| 0.7466 \| 0.8640 \| \| No log \| 51.3333 \| 154 \| 0.6695 \| 0.3788 \| 0.6695 \| 0.8182 \| \| No log \| 52.0 \| 156 \| 0.6423 \| 0.3070 \| 0.6423 \| 0.8015 \| \| No log \| 52.6667 \| 158 \| 0.6455 \| 0.3336 \| 0.6455 \| 0.8034 \| \| No log \| 53.3333 \| 160 \| 0.6411 \| 0.3070 \| 0.6411 \| 0.8007 \| \| No log \| 54.0 \| 162 \| 0.6462 \| 0.3599 \| 0.6462 \| 0.8039 \| \| No log \| 54.6667 \| 164 \| 0.6690 \| 0.3524 \| 0.6690 \| 0.8179 \| \| No log \| 55.3333 \| 166 \| 0.6858 \| 0.3267 \| 0.6858 \| 0.8281 \| \| No log \| 56.0 \| 168 \| 0.7004 \| 0.3545 \| 0.7004 \| 0.8369 \| \| No log \| 56.6667 \| 170 \| 0.7119 \| 0.3545 \| 0.7119 \| 0.8437 \| \| No log \| 57.3333 \| 172 \| 0.7268 \| 0.3060 \| 0.7268 \| 0.8525 \| \| No log \| 58.0 \| 174 \| 0.7169 \| 0.3127 \| 0.7169 \| 0.8467 \| \| No log \| 58.6667 \| 176 \| 0.6937 \| 0.3498 \| 0.6937 \| 0.8329 \| \| No log \| 59.3333 \| 178 \| 0.6644 \| 0.3524 \| 0.6644 \| 0.8151 \| \| No log \| 60.0 \| 180 \| 0.6653 \| 0.3170 \| 0.6653 \| 0.8157 \| \| No log \| 60.6667 \| 182 \| 0.6667 \| 0.3481 \| 0.6667 \| 0.8165 \| \| No log \| 61.3333 \| 184 \| 0.6775 \| 0.3860 \| 0.6775 \| 0.8231 \| \| No log \| 62.0 \| 186 \| 0.6774 \| 0.3806 \| 0.6774 \| 0.8230 \| \| No log \| 62.6667 \| 188 \| 0.6643 \| 0.2652 \| 0.6643 \| 0.8150 \| \| No log \| 63.3333 \| 190 \| 0.6663 \| 0.3280 \| 0.6663 \| 0.8163 \| \| No log \| 64.0 \| 192 \| 0.6705 \| 0.3280 \| 0.6705 \| 0.8188 \| \| No log \| 64.6667 \| 194 \| 0.6854 \| 0.2973 \| 0.6854 \| 0.8279 \| \| No log \| 65.3333 \| 196 \| 0.6973 \| 0.3524 \| 0.6973 \| 0.8350 \| \| No log \| 66.0 \| 198 \| 0.7181 \| 0.3840 \| 0.7181 \| 0.8474 \| \| No log \| 66.6667 \| 200 \| 0.7369 \| 0.3425 \| 0.7369 \| 0.8584 \| \| No log \| 67.3333 \| 202 \| 0.7561 \| 0.3060 \| 0.7561 \| 0.8695 \| \| No log \| 68.0 \| 204 \| 0.7591 \| 0.2754 \| 0.7591 \| 0.8712 \| \| No log \| 68.6667 \| 206 \| 0.7362 \| 0.3060 \| 0.7362 \| 0.8580 \| \| No log \| 69.3333 \| 208 \| 0.7107 \| 0.2558 \| 0.7107 \| 0.8430 \| \| No log \| 70.0 \| 210 \| 0.7025 \| 0.3267 \| 0.7025 \| 0.8382 \| \| No log \| 70.6667 \| 212 \| 0.6982 \| 0.3267 \| 0.6982 \| 0.8356 \| \| No log \| 71.3333 \| 214 \| 0.7089 \| 0.3267 \| 0.7089 \| 0.8420 \| \| No log \| 72.0 \| 216 \| 0.7317 \| 0.3545 \| 0.7317 \| 0.8554 \| \| No log \| 72.6667 \| 218 \| 0.7634 \| 0.2754 \| 0.7634 \| 0.8737 \| \| No log \| 73.3333 \| 220 \| 0.8069 \| 0.3169 \| 0.8069 \| 0.8983 \| \| No log \| 74.0 \| 222 \| 0.8195 \| 0.3675 \| 0.8195 \| 0.9053 \| \| No log \| 74.6667 \| 224 \| 0.8127 \| 0.3564 \| 0.8127 \| 0.9015 \| \| No log \| 75.3333 \| 226 \| 0.8149 \| 0.3564 \| 0.8149 \| 0.9027 \| \| No log \| 76.0 \| 228 \| 0.7888 \| 0.3032 \| 0.7888 \| 0.8881 \| \| No log \| 76.6667 \| 230 \| 0.7572 \| 0.3518 \| 0.7572 \| 0.8702 \| \| No log \| 77.3333 \| 232 \| 0.7508 \| 0.3518 \| 0.7508 \| 0.8665 \| \| No log \| 78.0 \| 234 \| 0.7350 \| 0.3312 \| 0.7350 \| 0.8573 \| \| No log \| 78.6667 \| 236 \| 0.7308 \| 0.3312 \| 0.7308 \| 0.8549 \| \| No log \| 79.3333 \| 238 \| 0.7419 \| 0.3594 \| 0.7419 \| 0.8613 \| \| No log \| 80.0 \| 240 \| 0.7610 \| 0.3518 \| 0.7610 \| 0.8724 \| \| No log \| 80.6667 \| 242 \| 0.7882 \| 0.3302 \| 0.7882 \| 0.8878 \| \| No log \| 81.3333 \| 244 \| 0.8140 \| 0.3564 \| 0.8140 \| 0.9022 \| \| No log \| 82.0 \| 246 \| 0.8316 \| 0.3819 \| 0.8316 \| 0.9119 \| \| No log \| 82.6667 \| 248 \| 0.8344 \| 0.3819 \| 0.8344 \| 0.9135 \| \| No log \| 83.3333 \| 250 \| 0.8211 \| 0.3819 \| 0.8211 \| 0.9062 \| \| No log \| 84.0 \| 252 \| 0.7963 \| 0.3564 \| 0.7963 \| 0.8924 \| \| No log \| 84.6667 \| 254 \| 0.7777 \| 0.3302 \| 0.7777 \| 0.8819 \| \| No log \| 85.3333 \| 256 \| 0.7631 \| 0.3444 \| 0.7631 \| 0.8736 \| \| No log \| 86.0 \| 258 \| 0.7530 \| 0.3444 \| 0.7530 \| 0.8678 \| \| No log \| 86.6667 \| 260 \| 0.7475 \| 0.3444 \| 0.7475 \| 0.8646 \| \| No log \| 87.3333 \| 262 \| 0.7487 \| 0.3444 \| 0.7487 \| 0.8652 \| \| No log \| 88.0 \| 264 \| 0.7545 \| 0.3032 \| 0.7545 \| 0.8686 \| \| No log \| 88.6667 \| 266 \| 0.7650 \| 0.3032 \| 0.7650 \| 0.8747 \| \| No log \| 89.3333 \| 268 \| 0.7701 \| 0.3032 \| 0.7701 \| 0.8776 \| \| No log \| 90.0 \| 270 \| 0.7715 \| 0.3032 \| 0.7715 \| 0.8783 \| \| No log \| 90.6667 \| 272 \| 0.7700 \| 0.3032 \| 0.7700 \| 0.8775 \| \| No log \| 91.3333 \| 274 \| 0.7710 \| 0.3032 \| 0.7710 \| 0.8781 \| \| No log \| 92.0 \| 276 \| 0.7701 \| 0.3032 \| 0.7701 \| 0.8775 \| \| No log \| 92.6667 \| 278 \| 0.7653 \| 0.3032 \| 0.7653 \| 0.8748 \| \| No log \| 93.3333 \| 280 \| 0.7617 \| 0.3032 \| 0.7617 \| 0.8727 \| \| No log \| 94.0 \| 282 \| 0.7548 \| 0.3444 \| 0.7548 \| 0.8688 \| \| No log \| 94.6667 \| 284 \| 0.7498 \| 0.3167 \| 0.7498 \| 0.8659 \| \| No log \| 95.3333 \| 286 \| 0.7451 \| 0.3238 \| 0.7451 \| 0.8632 \| \| No log \| 96.0 \| 288 \| 0.7421 \| 0.3238 \| 0.7421 \| 0.8615 \| \| No log \| 96.6667 \| 290 \| 0.7399 \| 0.3238 \| 0.7399 \| 0.8602 \| \| No log \| 97.3333 \| 292 \| 0.7388 \| 0.3238 \| 0.7388 \| 0.8595 \| \| No log \| 98.0 \| 294 \| 0.7384 \| 0.3238 \| 0.7384 \| 0.8593 \| \| No log \| 98.6667 \| 296 \| 0.7393 \| 0.3238 \| 0.7393 \| 0.8598 \| \| No log \| 99.3333 \| 298 \| 0.7400 \| 0.3238 \| 0.7400 \| 0.8603 \| \| No log \| 100.0 \| 300 \| 0.7404 \| 0.3238 \| 0.7404 \| 0.8605 \| ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.0+cu118 - Datasets 2.21.0 - Tokenizers 0.19.1
nhung02/909af27c-2380-46a2-abbd-cd15fe4d4de0	nhung02	2025-01-21T12:16:53Z	8	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:heegyu/WizardVicuna-open-llama-3b-v2", "base_model:adapter:heegyu/WizardVicuna-open-llama-3b-v2", "license:apache-2.0", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-21T11:51:36Z	--- library_name: peft license: apache-2.0 base_model: heegyu/WizardVicuna-open-llama-3b-v2 tags: - axolotl - generated_from_trainer model-index: - name: 909af27c-2380-46a2-abbd-cd15fe4d4de0 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: heegyu/WizardVicuna-open-llama-3b-v2 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 0eba3e80d15355a6_train_data.json ds_type: json format: custom path: /workspace/input_data/0eba3e80d15355a6_train_data.json type: field_input: input field_instruction: instruction field_output: accepted format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: nhung02/909af27c-2380-46a2-abbd-cd15fe4d4de0 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/0eba3e80d15355a6_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 special_tokens: pad_token: </s> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 84f8a085-50df-4e7c-9e21-f8d55ac51824 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 84f8a085-50df-4e7c-9e21-f8d55ac51824 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details><br> # 909af27c-2380-46a2-abbd-cd15fe4d4de0 This model is a fine-tuned version of [heegyu/WizardVicuna-open-llama-3b-v2](https://huggingface.co/heegyu/WizardVicuna-open-llama-3b-v2) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.7229 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 0.6899 \| 0.0313 \| 200 \| 0.7229 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
ivangrapher/744e6875-2fc5-49e8-9a0e-2975ca5870ac	ivangrapher	2025-01-21T12:15:54Z	6	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:unsloth/llama-2-7b-chat", "base_model:adapter:unsloth/llama-2-7b-chat", "license:apache-2.0", "region:us" ]	null	2025-01-21T08:34:31Z	--- library_name: peft license: apache-2.0 base_model: unsloth/llama-2-7b-chat tags: - axolotl - generated_from_trainer model-index: - name: 744e6875-2fc5-49e8-9a0e-2975ca5870ac results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/llama-2-7b-chat bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 124bc05ddbf5ee81_train_data.json ds_type: json format: custom path: /workspace/input_data/124bc05ddbf5ee81_train_data.json type: field_instruction: docstring field_output: summary format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: null eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: false hub_model_id: ivangrapher/744e6875-2fc5-49e8-9a0e-2975ca5870ac hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 75GiB max_steps: 30 micro_batch_size: 2 mlflow_experiment_name: /tmp/124bc05ddbf5ee81_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 15 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 5fe9995d-0a95-46fa-b89c-25f97cbb6eb6 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 5fe9995d-0a95-46fa-b89c-25f97cbb6eb6 warmup_steps: 15 weight_decay: 0.01 xformers_attention: true ``` </details><br> # 744e6875-2fc5-49e8-9a0e-2975ca5870ac This model is a fine-tuned version of [unsloth/llama-2-7b-chat](https://huggingface.co/unsloth/llama-2-7b-chat) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 15 - training_steps: 30 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| No log \| 0.0000 \| 1 \| nan \| \| 0.0 \| 0.0001 \| 5 \| nan \| \| 0.0 \| 0.0002 \| 10 \| nan \| \| 0.0 \| 0.0003 \| 15 \| nan \| \| 0.0 \| 0.0003 \| 20 \| nan \| \| 0.0 \| 0.0004 \| 25 \| nan \| \| 0.0 \| 0.0005 \| 30 \| nan \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
kokovova/28cfc357-be2e-4eb7-87e6-ede5f44cf913	kokovova	2025-01-21T12:15:28Z	5	0	peft	[ "peft", "safetensors", "gpt_neox", "axolotl", "generated_from_trainer", "base_model:databricks/dolly-v2-3b", "base_model:adapter:databricks/dolly-v2-3b", "license:mit", "region:us" ]	null	2025-01-21T11:32:50Z	--- library_name: peft license: mit base_model: databricks/dolly-v2-3b tags: - axolotl - generated_from_trainer model-index: - name: 28cfc357-be2e-4eb7-87e6-ede5f44cf913 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: databricks/dolly-v2-3b bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - d4ad1f4ec6a1fae0_train_data.json ds_type: json format: custom path: /workspace/input_data/d4ad1f4ec6a1fae0_train_data.json type: field_instruction: Patient field_output: Description format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: 1 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: true hub_model_id: kokovova/28cfc357-be2e-4eb7-87e6-ede5f44cf913 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 79GiB max_steps: 30 micro_batch_size: 4 mlflow_experiment_name: /tmp/d4ad1f4ec6a1fae0_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optim_args: adam_beta1: 0.9 adam_beta2: 0.95 adam_epsilon: 1e-5 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 6874924e-0eae-4909-b19a-0c7087adfd79 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 6874924e-0eae-4909-b19a-0c7087adfd79 warmup_steps: 5 weight_decay: 0.001 xformers_attention: true ``` </details><br> # 28cfc357-be2e-4eb7-87e6-ede5f44cf913 This model is a fine-tuned version of [databricks/dolly-v2-3b](https://huggingface.co/databricks/dolly-v2-3b) on the None dataset. It achieves the following results on the evaluation set: - Loss: 3.0565 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 16 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.95,adam_epsilon=1e-5 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 30 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| No log \| 0.0001 \| 1 \| 3.7270 \| \| 13.4442 \| 0.0003 \| 5 \| 3.4392 \| \| 12.3538 \| 0.0007 \| 10 \| 3.1945 \| \| 11.8357 \| 0.0010 \| 15 \| 3.1070 \| \| 11.9725 \| 0.0013 \| 20 \| 3.0723 \| \| 12.3078 \| 0.0016 \| 25 \| 3.0603 \| \| 12.0133 \| 0.0020 \| 30 \| 3.0565 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
ClarenceDan/7a6c4aff-60cf-4296-906d-a04240417885	ClarenceDan	2025-01-21T12:14:35Z	8	0	peft	[ "peft", "safetensors", "bloom", "axolotl", "generated_from_trainer", "base_model:bigscience/bloom-560m", "base_model:adapter:bigscience/bloom-560m", "license:bigscience-bloom-rail-1.0", "region:us" ]	null	2025-01-21T12:14:06Z	--- library_name: peft license: bigscience-bloom-rail-1.0 base_model: bigscience/bloom-560m tags: - axolotl - generated_from_trainer model-index: - name: 7a6c4aff-60cf-4296-906d-a04240417885 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: bigscience/bloom-560m bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 5c4eef0d51e921ea_train_data.json ds_type: json format: custom path: /workspace/input_data/5c4eef0d51e921ea_train_data.json type: field_input: world_literals field_instruction: logical_form_pretty field_output: question format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: ClarenceDan/7a6c4aff-60cf-4296-906d-a04240417885 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/5c4eef0d51e921ea_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 847dcfd1-dbaf-4b00-af61-47e0ea3d66d1 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 847dcfd1-dbaf-4b00-af61-47e0ea3d66d1 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # 7a6c4aff-60cf-4296-906d-a04240417885 This model is a fine-tuned version of [bigscience/bloom-560m](https://huggingface.co/bigscience/bloom-560m) on the None dataset. It achieves the following results on the evaluation set: - Loss: 3.1212 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 14.3622 \| 0.0033 \| 1 \| 3.6128 \| \| 14.3937 \| 0.0098 \| 3 \| 3.5999 \| \| 14.6205 \| 0.0197 \| 6 \| 3.4420 \| \| 12.5179 \| 0.0295 \| 9 \| 3.1212 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
mrHungddddh/fbb70a8d-5819-43ab-ad46-15fd560412cd	mrHungddddh	2025-01-21T12:13:42Z	6	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:unsloth/Llama-3.1-Storm-8B", "base_model:adapter:unsloth/Llama-3.1-Storm-8B", "license:llama3.1", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-21T11:41:48Z	--- library_name: peft license: llama3.1 base_model: unsloth/Llama-3.1-Storm-8B tags: - axolotl - generated_from_trainer model-index: - name: fbb70a8d-5819-43ab-ad46-15fd560412cd results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/Llama-3.1-Storm-8B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - dc5c201d257f4800_train_data.json ds_type: json format: custom path: /workspace/input_data/dc5c201d257f4800_train_data.json type: field_instruction: instruction field_output: output format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: mrHungddddh/fbb70a8d-5819-43ab-ad46-15fd560412cd hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/dc5c201d257f4800_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 1fb620f4-588e-4556-8dd0-8ed7c42fd6cc wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 1fb620f4-588e-4556-8dd0-8ed7c42fd6cc warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details><br> # fbb70a8d-5819-43ab-ad46-15fd560412cd This model is a fine-tuned version of [unsloth/Llama-3.1-Storm-8B](https://huggingface.co/unsloth/Llama-3.1-Storm-8B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.6449 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 0.39 \| 0.0681 \| 200 \| 0.6449 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
vertings6/46326f04-0a71-4c3b-a8ef-4c0ff1144789	vertings6	2025-01-21T12:13:16Z	6	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "custom_code", "base_model:NousResearch/Yarn-Llama-2-7b-64k", "base_model:adapter:NousResearch/Yarn-Llama-2-7b-64k", "region:us" ]	null	2025-01-21T12:12:14Z	--- library_name: peft base_model: NousResearch/Yarn-Llama-2-7b-64k tags: - axolotl - generated_from_trainer model-index: - name: 46326f04-0a71-4c3b-a8ef-4c0ff1144789 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: NousResearch/Yarn-Llama-2-7b-64k bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 6f632f47d3ee06ff_train_data.json ds_type: json format: custom path: /workspace/input_data/6f632f47d3ee06ff_train_data.json type: field_input: choices field_instruction: question field_output: answer format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: 1 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: true hub_model_id: vertings6/46326f04-0a71-4c3b-a8ef-4c0ff1144789 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 79GiB max_steps: 30 micro_batch_size: 4 mlflow_experiment_name: /tmp/6f632f47d3ee06ff_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optim_args: adam_beta1: 0.9 adam_beta2: 0.95 adam_epsilon: 1e-5 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: a2153675-d455-4bd4-a862-69a06baed90a wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: a2153675-d455-4bd4-a862-69a06baed90a warmup_steps: 5 weight_decay: 0.001 xformers_attention: true ``` </details><br> # 46326f04-0a71-4c3b-a8ef-4c0ff1144789 This model is a fine-tuned version of [NousResearch/Yarn-Llama-2-7b-64k](https://huggingface.co/NousResearch/Yarn-Llama-2-7b-64k) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.2940 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 16 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.95,adam_epsilon=1e-5 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 7 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| No log \| 0.1538 \| 1 \| 1.5155 \| \| 6.176 \| 0.7692 \| 5 \| 1.2940 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
nhung01/eaf0f1fd-8467-470a-aa52-e26bbce9c105	nhung01	2025-01-21T12:11:02Z	6	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:codellama/CodeLlama-7b-Instruct-hf", "base_model:adapter:codellama/CodeLlama-7b-Instruct-hf", "license:llama2", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-21T11:54:14Z	--- library_name: peft license: llama2 base_model: codellama/CodeLlama-7b-Instruct-hf tags: - axolotl - generated_from_trainer model-index: - name: eaf0f1fd-8467-470a-aa52-e26bbce9c105 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: codellama/CodeLlama-7b-Instruct-hf bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - e61b15027cdb8f0f_train_data.json ds_type: json format: custom path: /workspace/input_data/e61b15027cdb8f0f_train_data.json type: field_instruction: text_description field_output: text format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: nhung01/eaf0f1fd-8467-470a-aa52-e26bbce9c105 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/e61b15027cdb8f0f_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 special_tokens: pad_token: </s> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 52dcb611-f58d-420b-a954-552a3249dfec wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 52dcb611-f58d-420b-a954-552a3249dfec warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details><br> # eaf0f1fd-8467-470a-aa52-e26bbce9c105 This model is a fine-tuned version of [codellama/CodeLlama-7b-Instruct-hf](https://huggingface.co/codellama/CodeLlama-7b-Instruct-hf) on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.1119 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 1.9689 \| 0.0800 \| 200 \| 2.1119 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
thaffggg/91ed7274-5dc1-4bef-99e1-48c9fd775ff6	thaffggg	2025-01-21T12:09:40Z	6	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:heegyu/WizardVicuna-open-llama-3b-v2", "base_model:adapter:heegyu/WizardVicuna-open-llama-3b-v2", "license:apache-2.0", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-21T11:51:42Z	--- library_name: peft license: apache-2.0 base_model: heegyu/WizardVicuna-open-llama-3b-v2 tags: - axolotl - generated_from_trainer model-index: - name: 91ed7274-5dc1-4bef-99e1-48c9fd775ff6 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: heegyu/WizardVicuna-open-llama-3b-v2 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 0eba3e80d15355a6_train_data.json ds_type: json format: custom path: /workspace/input_data/0eba3e80d15355a6_train_data.json type: field_input: input field_instruction: instruction field_output: accepted format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: thaffggg/91ed7274-5dc1-4bef-99e1-48c9fd775ff6 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/0eba3e80d15355a6_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 special_tokens: pad_token: </s> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 84f8a085-50df-4e7c-9e21-f8d55ac51824 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 84f8a085-50df-4e7c-9e21-f8d55ac51824 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details><br> # 91ed7274-5dc1-4bef-99e1-48c9fd775ff6 This model is a fine-tuned version of [heegyu/WizardVicuna-open-llama-3b-v2](https://huggingface.co/heegyu/WizardVicuna-open-llama-3b-v2) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.7231 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 0.6918 \| 0.0313 \| 200 \| 0.7231 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
philip-hightech/9312526f-695d-4bea-b99b-212790fd97bb	philip-hightech	2025-01-21T12:09:21Z	6	0	peft	[ "peft", "safetensors", "mistral", "axolotl", "generated_from_trainer", "base_model:Intel/neural-chat-7b-v3-3", "base_model:adapter:Intel/neural-chat-7b-v3-3", "license:apache-2.0", "region:us" ]	null	2025-01-21T12:07:17Z	--- library_name: peft license: apache-2.0 base_model: Intel/neural-chat-7b-v3-3 tags: - axolotl - generated_from_trainer model-index: - name: 9312526f-695d-4bea-b99b-212790fd97bb results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: Intel/neural-chat-7b-v3-3 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - b5e06bf0e602bd38_train_data.json ds_type: json format: custom path: /workspace/input_data/b5e06bf0e602bd38_train_data.json type: field_instruction: section field_output: text format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: philip-hightech/9312526f-695d-4bea-b99b-212790fd97bb hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/b5e06bf0e602bd38_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 special_tokens: pad_token: </s> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 5312563a-16b4-452e-84f7-611f95b514ff wandb_project: Mine-SN56-21-Gradients-On-Demand wandb_run: your_name wandb_runid: 5312563a-16b4-452e-84f7-611f95b514ff warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # 9312526f-695d-4bea-b99b-212790fd97bb This model is a fine-tuned version of [Intel/neural-chat-7b-v3-3](https://huggingface.co/Intel/neural-chat-7b-v3-3) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 0.0 \| 0.0010 \| 1 \| nan \| \| 0.0 \| 0.0030 \| 3 \| nan \| \| 0.0 \| 0.0059 \| 6 \| nan \| \| 0.0 \| 0.0089 \| 9 \| nan \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
kostiantynk1205/96658c36-8901-4700-8dc4-7caa48990751	kostiantynk1205	2025-01-21T12:09:11Z	6	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:oopsung/llama2-7b-n-ox-test-v1", "base_model:adapter:oopsung/llama2-7b-n-ox-test-v1", "region:us" ]	null	2025-01-21T12:03:08Z	--- library_name: peft base_model: oopsung/llama2-7b-n-ox-test-v1 tags: - axolotl - generated_from_trainer model-index: - name: 96658c36-8901-4700-8dc4-7caa48990751 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: oopsung/llama2-7b-n-ox-test-v1 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - dddb0489dc663e1a_train_data.json ds_type: json format: custom path: /workspace/input_data/dddb0489dc663e1a_train_data.json type: field_input: Context field_instruction: Question field_output: Answers format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: kostiantynk1205/96658c36-8901-4700-8dc4-7caa48990751 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/dddb0489dc663e1a_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: bbd202cf-ffeb-42f5-82b2-0c60d893aeab wandb_project: Birthday-SN56-23-Gradients-On-Demand wandb_run: your_name wandb_runid: bbd202cf-ffeb-42f5-82b2-0c60d893aeab warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # 96658c36-8901-4700-8dc4-7caa48990751 This model is a fine-tuned version of [oopsung/llama2-7b-n-ox-test-v1](https://huggingface.co/oopsung/llama2-7b-n-ox-test-v1) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 0.0 \| 0.0003 \| 1 \| nan \| \| 0.0 \| 0.0008 \| 3 \| nan \| \| 0.0 \| 0.0017 \| 6 \| nan \| \| 0.0 \| 0.0025 \| 9 \| nan \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
ClarenceDan/fd941b3a-7d6d-4a90-a386-08b3ed99ba71	ClarenceDan	2025-01-21T12:08:08Z	6	0	peft	[ "peft", "safetensors", "mistral", "axolotl", "generated_from_trainer", "base_model:Artples/L-MChat-7b", "base_model:adapter:Artples/L-MChat-7b", "license:apache-2.0", "region:us" ]	null	2025-01-21T12:06:27Z	--- library_name: peft license: apache-2.0 base_model: Artples/L-MChat-7b tags: - axolotl - generated_from_trainer model-index: - name: fd941b3a-7d6d-4a90-a386-08b3ed99ba71 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: Artples/L-MChat-7b bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - df03514e65800f80_train_data.json ds_type: json format: custom path: /workspace/input_data/df03514e65800f80_train_data.json type: field_instruction: input field_output: response format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: ClarenceDan/fd941b3a-7d6d-4a90-a386-08b3ed99ba71 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/df03514e65800f80_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 special_tokens: pad_token: <\|end_of_turn\|> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: e3508d62-5471-4cdf-8dba-5844f441931a wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: e3508d62-5471-4cdf-8dba-5844f441931a warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # fd941b3a-7d6d-4a90-a386-08b3ed99ba71 This model is a fine-tuned version of [Artples/L-MChat-7b](https://huggingface.co/Artples/L-MChat-7b) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 0.0 \| 0.0011 \| 1 \| nan \| \| 0.0 \| 0.0034 \| 3 \| nan \| \| 0.0 \| 0.0068 \| 6 \| nan \| \| 0.0 \| 0.0101 \| 9 \| nan \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
havinash-ai/0c7eaea0-bf84-47bb-838e-c5ec19a67fe9	havinash-ai	2025-01-21T12:08:02Z	5	0	peft	[ "peft", "safetensors", "gpt_neox", "axolotl", "generated_from_trainer", "base_model:databricks/dolly-v2-3b", "base_model:adapter:databricks/dolly-v2-3b", "license:mit", "region:us" ]	null	2025-01-21T11:50:34Z	--- library_name: peft license: mit base_model: databricks/dolly-v2-3b tags: - axolotl - generated_from_trainer model-index: - name: 0c7eaea0-bf84-47bb-838e-c5ec19a67fe9 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: databricks/dolly-v2-3b bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - d4ad1f4ec6a1fae0_train_data.json ds_type: json format: custom path: /workspace/input_data/d4ad1f4ec6a1fae0_train_data.json type: field_instruction: Patient field_output: Description format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: havinash-ai/0c7eaea0-bf84-47bb-838e-c5ec19a67fe9 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/d4ad1f4ec6a1fae0_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 6874924e-0eae-4909-b19a-0c7087adfd79 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 6874924e-0eae-4909-b19a-0c7087adfd79 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # 0c7eaea0-bf84-47bb-838e-c5ec19a67fe9 This model is a fine-tuned version of [databricks/dolly-v2-3b](https://huggingface.co/databricks/dolly-v2-3b) on the None dataset. It achieves the following results on the evaluation set: - Loss: 3.1139 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 14.3662 \| 0.0000 \| 1 \| 4.0295 \| \| 13.6342 \| 0.0001 \| 3 \| 4.0051 \| \| 18.6691 \| 0.0002 \| 6 \| 3.7901 \| \| 13.7199 \| 0.0003 \| 9 \| 3.1139 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
nhungphammmmm/a916d37c-5230-43a3-ad27-5b9669db8192	nhungphammmmm	2025-01-21T12:07:53Z	6	0	peft	[ "peft", "safetensors", "phi3", "axolotl", "generated_from_trainer", "custom_code", "base_model:microsoft/Phi-3-mini-128k-instruct", "base_model:adapter:microsoft/Phi-3-mini-128k-instruct", "license:mit", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-21T11:49:16Z	--- library_name: peft license: mit base_model: microsoft/Phi-3-mini-128k-instruct tags: - axolotl - generated_from_trainer model-index: - name: a916d37c-5230-43a3-ad27-5b9669db8192 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: microsoft/Phi-3-mini-128k-instruct bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - d23a80b910821333_train_data.json ds_type: json format: custom path: /workspace/input_data/d23a80b910821333_train_data.json type: field_input: input field_instruction: instruction field_output: output format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: nhungphammmmm/a916d37c-5230-43a3-ad27-5b9669db8192 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/d23a80b910821333_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: c7400a48-f57f-4a5f-8c57-bf09a3ce88d3 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: c7400a48-f57f-4a5f-8c57-bf09a3ce88d3 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details><br> # a916d37c-5230-43a3-ad27-5b9669db8192 This model is a fine-tuned version of [microsoft/Phi-3-mini-128k-instruct](https://huggingface.co/microsoft/Phi-3-mini-128k-instruct) on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.1734 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 8.2072 \| 0.0143 \| 200 \| 2.1734 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
hongngo/d131082f-bd87-4d91-b9ee-d2089181769a	hongngo	2025-01-21T12:04:36Z	6	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:unsloth/Llama-3.1-Storm-8B", "base_model:adapter:unsloth/Llama-3.1-Storm-8B", "license:llama3.1", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-21T11:41:40Z	--- library_name: peft license: llama3.1 base_model: unsloth/Llama-3.1-Storm-8B tags: - axolotl - generated_from_trainer model-index: - name: d131082f-bd87-4d91-b9ee-d2089181769a results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/Llama-3.1-Storm-8B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - dc5c201d257f4800_train_data.json ds_type: json format: custom path: /workspace/input_data/dc5c201d257f4800_train_data.json type: field_instruction: instruction field_output: output format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: hongngo/d131082f-bd87-4d91-b9ee-d2089181769a hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/dc5c201d257f4800_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 1fb620f4-588e-4556-8dd0-8ed7c42fd6cc wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 1fb620f4-588e-4556-8dd0-8ed7c42fd6cc warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details><br> # d131082f-bd87-4d91-b9ee-d2089181769a This model is a fine-tuned version of [unsloth/Llama-3.1-Storm-8B](https://huggingface.co/unsloth/Llama-3.1-Storm-8B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.6455 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 0.3866 \| 0.0681 \| 200 \| 0.6455 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
trangtrannnnn/91e46b57-4c5a-411c-9cd3-585cb158ce5e	trangtrannnnn	2025-01-21T12:03:49Z	5	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:NousResearch/Nous-Hermes-llama-2-7b", "base_model:adapter:NousResearch/Nous-Hermes-llama-2-7b", "license:mit", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-21T11:41:25Z	--- library_name: peft license: mit base_model: NousResearch/Nous-Hermes-llama-2-7b tags: - axolotl - generated_from_trainer model-index: - name: 91e46b57-4c5a-411c-9cd3-585cb158ce5e results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: NousResearch/Nous-Hermes-llama-2-7b bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - db35a4b2827972f9_train_data.json ds_type: json format: custom path: /workspace/input_data/db35a4b2827972f9_train_data.json type: field_input: rejected field_instruction: context field_output: chosen format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: trangtrannnnn/91e46b57-4c5a-411c-9cd3-585cb158ce5e hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/db35a4b2827972f9_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 881827a9-7bb9-4a3a-bfa5-bc8cbc8f588f wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 881827a9-7bb9-4a3a-bfa5-bc8cbc8f588f warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details><br> # 91e46b57-4c5a-411c-9cd3-585cb158ce5e This model is a fine-tuned version of [NousResearch/Nous-Hermes-llama-2-7b](https://huggingface.co/NousResearch/Nous-Hermes-llama-2-7b) on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.1095 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 1.8807 \| 0.0294 \| 200 \| 2.1095 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
lesso02/afd91423-4ee5-4fb8-a211-976981cf01f6	lesso02	2025-01-21T12:03:00Z	6	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:oopsung/llama2-7b-n-ox-test-v1", "base_model:adapter:oopsung/llama2-7b-n-ox-test-v1", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-21T11:38:23Z	--- library_name: peft base_model: oopsung/llama2-7b-n-ox-test-v1 tags: - axolotl - generated_from_trainer model-index: - name: afd91423-4ee5-4fb8-a211-976981cf01f6 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: oopsung/llama2-7b-n-ox-test-v1 bf16: true chat_template: llama3 datasets: - data_files: - dddb0489dc663e1a_train_data.json ds_type: json format: custom path: /workspace/input_data/dddb0489dc663e1a_train_data.json type: field_input: Context field_instruction: Question field_output: Answers format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: 2 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null flash_attention: false fp16: false fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: lesso02/afd91423-4ee5-4fb8-a211-976981cf01f6 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 25 micro_batch_size: 2 mlflow_experiment_name: /tmp/dddb0489dc663e1a_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: bbd202cf-ffeb-42f5-82b2-0c60d893aeab wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: bbd202cf-ffeb-42f5-82b2-0c60d893aeab warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # afd91423-4ee5-4fb8-a211-976981cf01f6 This model is a fine-tuned version of [oopsung/llama2-7b-n-ox-test-v1](https://huggingface.co/oopsung/llama2-7b-n-ox-test-v1) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 25 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 0.0 \| 0.0003 \| 1 \| nan \| \| 0.0 \| 0.0014 \| 5 \| nan \| \| 0.0 \| 0.0028 \| 10 \| nan \| \| 0.0 \| 0.0042 \| 15 \| nan \| \| 0.0 \| 0.0056 \| 20 \| nan \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
kostiantynk1205/524eee36-38c7-4c32-811d-314e799d4341	kostiantynk1205	2025-01-21T12:01:21Z	5	0	peft	[ "peft", "safetensors", "gpt_neox", "axolotl", "generated_from_trainer", "base_model:databricks/dolly-v2-3b", "base_model:adapter:databricks/dolly-v2-3b", "license:mit", "region:us" ]	null	2025-01-21T11:44:21Z	--- library_name: peft license: mit base_model: databricks/dolly-v2-3b tags: - axolotl - generated_from_trainer model-index: - name: 524eee36-38c7-4c32-811d-314e799d4341 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: databricks/dolly-v2-3b bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - d4ad1f4ec6a1fae0_train_data.json ds_type: json format: custom path: /workspace/input_data/d4ad1f4ec6a1fae0_train_data.json type: field_instruction: Patient field_output: Description format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: kostiantynk1205/524eee36-38c7-4c32-811d-314e799d4341 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/d4ad1f4ec6a1fae0_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 6874924e-0eae-4909-b19a-0c7087adfd79 wandb_project: Birthday-SN56-6-Gradients-On-Demand wandb_run: your_name wandb_runid: 6874924e-0eae-4909-b19a-0c7087adfd79 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # 524eee36-38c7-4c32-811d-314e799d4341 This model is a fine-tuned version of [databricks/dolly-v2-3b](https://huggingface.co/databricks/dolly-v2-3b) on the None dataset. It achieves the following results on the evaluation set: - Loss: 3.1108 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 14.3662 \| 0.0000 \| 1 \| 4.0295 \| \| 13.7001 \| 0.0001 \| 3 \| 4.0041 \| \| 18.6084 \| 0.0002 \| 6 \| 3.7846 \| \| 13.6494 \| 0.0003 \| 9 \| 3.1108 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
nblinh/7f6d68fe-a293-4c30-b25c-143527739229	nblinh	2025-01-21T12:00:24Z	6	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:defog/sqlcoder-7b-2", "base_model:adapter:defog/sqlcoder-7b-2", "license:cc-by-sa-4.0", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-21T11:35:38Z	--- library_name: peft license: cc-by-sa-4.0 base_model: defog/sqlcoder-7b-2 tags: - axolotl - generated_from_trainer model-index: - name: 7f6d68fe-a293-4c30-b25c-143527739229 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: defog/sqlcoder-7b-2 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - fdd56d09ce656747_train_data.json ds_type: json format: custom path: /workspace/input_data/fdd56d09ce656747_train_data.json type: field_instruction: INSTRUCTION field_output: RESPONSE format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: nblinh/7f6d68fe-a293-4c30-b25c-143527739229 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/fdd56d09ce656747_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 special_tokens: pad_token: </s> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: fecef9ac-e0fb-4174-87a6-ec0f3fcd1777 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: fecef9ac-e0fb-4174-87a6-ec0f3fcd1777 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details><br> # 7f6d68fe-a293-4c30-b25c-143527739229 This model is a fine-tuned version of [defog/sqlcoder-7b-2](https://huggingface.co/defog/sqlcoder-7b-2) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.5545 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 0.59 \| 0.1960 \| 200 \| 0.5545 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
ClarenceDan/1b016248-9d07-4011-a03a-975b03b2ce03	ClarenceDan	2025-01-21T12:00:14Z	6	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:unsloth/Llama-3.1-Storm-8B", "base_model:adapter:unsloth/Llama-3.1-Storm-8B", "license:llama3.1", "region:us" ]	null	2025-01-21T11:56:03Z	--- library_name: peft license: llama3.1 base_model: unsloth/Llama-3.1-Storm-8B tags: - axolotl - generated_from_trainer model-index: - name: 1b016248-9d07-4011-a03a-975b03b2ce03 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/Llama-3.1-Storm-8B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - dc5c201d257f4800_train_data.json ds_type: json format: custom path: /workspace/input_data/dc5c201d257f4800_train_data.json type: field_instruction: instruction field_output: output format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: ClarenceDan/1b016248-9d07-4011-a03a-975b03b2ce03 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/dc5c201d257f4800_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 1fb620f4-588e-4556-8dd0-8ed7c42fd6cc wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 1fb620f4-588e-4556-8dd0-8ed7c42fd6cc warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # 1b016248-9d07-4011-a03a-975b03b2ce03 This model is a fine-tuned version of [unsloth/Llama-3.1-Storm-8B](https://huggingface.co/unsloth/Llama-3.1-Storm-8B) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 0.0 \| 0.0003 \| 1 \| nan \| \| 0.0 \| 0.0010 \| 3 \| nan \| \| 0.0 \| 0.0020 \| 6 \| nan \| \| 0.0 \| 0.0031 \| 9 \| nan \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
havinash-ai/c0a35a3f-01eb-453e-b74f-a4f270d22a82	havinash-ai	2025-01-21T11:59:58Z	6	0	peft	[ "peft", "safetensors", "mistral", "axolotl", "generated_from_trainer", "base_model:Intel/neural-chat-7b-v3-3", "base_model:adapter:Intel/neural-chat-7b-v3-3", "license:apache-2.0", "region:us" ]	null	2025-01-21T11:57:56Z	--- library_name: peft license: apache-2.0 base_model: Intel/neural-chat-7b-v3-3 tags: - axolotl - generated_from_trainer model-index: - name: c0a35a3f-01eb-453e-b74f-a4f270d22a82 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: Intel/neural-chat-7b-v3-3 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - b5e06bf0e602bd38_train_data.json ds_type: json format: custom path: /workspace/input_data/b5e06bf0e602bd38_train_data.json type: field_instruction: section field_output: text format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: havinash-ai/c0a35a3f-01eb-453e-b74f-a4f270d22a82 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/b5e06bf0e602bd38_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 special_tokens: pad_token: </s> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 5312563a-16b4-452e-84f7-611f95b514ff wandb_project: Mine-SN56-2-Gradients-On-Demand wandb_run: your_name wandb_runid: 5312563a-16b4-452e-84f7-611f95b514ff warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # c0a35a3f-01eb-453e-b74f-a4f270d22a82 This model is a fine-tuned version of [Intel/neural-chat-7b-v3-3](https://huggingface.co/Intel/neural-chat-7b-v3-3) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 0.0 \| 0.0010 \| 1 \| nan \| \| 0.0 \| 0.0030 \| 3 \| nan \| \| 0.0 \| 0.0059 \| 6 \| nan \| \| 0.0 \| 0.0089 \| 9 \| nan \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
JetBrains-Research/deepseek-coder-1.3b-instruct-comment-resolution	JetBrains-Research	2025-01-21T11:59:54Z	63	0	transformers	[ "transformers", "safetensors", "text-generation", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-generation	2024-12-02T17:35:56Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. 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Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
MayBashendy/ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k17_task7_organization	MayBashendy	2025-01-21T11:59:01Z	5	0	transformers	[ "transformers", "safetensors", "bert", "text-classification", "generated_from_trainer", "base_model:aubmindlab/bert-base-arabertv02", "base_model:finetune:aubmindlab/bert-base-arabertv02", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2025-01-21T11:55:01Z	--- library_name: transformers base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k17_task7_organization results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k17_task7_organization This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.0676 - Qwk: 0.2683 - Mse: 1.0676 - Rmse: 1.0333 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 100 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Qwk \| Mse \| Rmse \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:-------:\|:------:\|:------:\| \| No log \| 0.05 \| 2 \| 2.7815 \| -0.0481 \| 2.7815 \| 1.6678 \| \| No log \| 0.1 \| 4 \| 1.7927 \| 0.0061 \| 1.7927 \| 1.3389 \| \| No log \| 0.15 \| 6 \| 2.0211 \| -0.1653 \| 2.0211 \| 1.4217 \| \| No log \| 0.2 \| 8 \| 1.3569 \| -0.1328 \| 1.3569 \| 1.1648 \| \| No log \| 0.25 \| 10 \| 1.0144 \| 0.0054 \| 1.0144 \| 1.0072 \| \| No log \| 0.3 \| 12 \| 0.9010 \| 0.1461 \| 0.9010 \| 0.9492 \| \| No log \| 0.35 \| 14 \| 0.9014 \| 0.1534 \| 0.9014 \| 0.9494 \| \| No log \| 0.4 \| 16 \| 0.8922 \| 0.1636 \| 0.8922 \| 0.9445 \| \| No log \| 0.45 \| 18 \| 0.8487 \| 0.0679 \| 0.8487 \| 0.9212 \| \| No log \| 0.5 \| 20 \| 0.9147 \| 0.1511 \| 0.9147 \| 0.9564 \| \| No log \| 0.55 \| 22 \| 1.0285 \| 0.1259 \| 1.0285 \| 1.0141 \| \| No log \| 0.6 \| 24 \| 1.0813 \| 0.0986 \| 1.0813 \| 1.0398 \| \| No log \| 0.65 \| 26 \| 0.8837 \| 0.2132 \| 0.8837 \| 0.9401 \| \| No log \| 0.7 \| 28 \| 0.7961 \| 0.0937 \| 0.7961 \| 0.8922 \| \| No log \| 0.75 \| 30 \| 0.7689 \| 0.0481 \| 0.7689 \| 0.8769 \| \| No log \| 0.8 \| 32 \| 0.7462 \| 0.0481 \| 0.7462 \| 0.8638 \| \| No log \| 0.85 \| 34 \| 0.7381 \| 0.0884 \| 0.7381 \| 0.8591 \| \| No log \| 0.9 \| 36 \| 0.7520 \| 0.0 \| 0.7520 \| 0.8672 \| \| No log \| 0.95 \| 38 \| 0.7783 \| 0.0481 \| 0.7783 \| 0.8822 \| \| No log \| 1.0 \| 40 \| 0.7709 \| 0.0 \| 0.7709 \| 0.8780 \| \| No log \| 1.05 \| 42 \| 0.7433 \| 0.0 \| 0.7433 \| 0.8622 \| \| No log \| 1.1 \| 44 \| 0.7383 \| 0.0 \| 0.7383 \| 0.8592 \| \| No log \| 1.15 \| 46 \| 0.7397 \| 0.0 \| 0.7397 \| 0.8601 \| \| No log \| 1.2 \| 48 \| 0.7337 \| 0.0884 \| 0.7337 \| 0.8566 \| \| No log \| 1.25 \| 50 \| 0.7301 \| 0.1236 \| 0.7301 \| 0.8544 \| \| No log \| 1.3 \| 52 \| 0.7242 \| 0.1456 \| 0.7242 \| 0.8510 \| \| No log \| 1.35 \| 54 \| 0.7434 \| 0.1807 \| 0.7434 \| 0.8622 \| \| No log \| 1.4 \| 56 \| 0.7364 \| 0.1508 \| 0.7364 \| 0.8581 \| \| No log \| 1.45 \| 58 \| 0.7273 \| 0.1187 \| 0.7273 \| 0.8528 \| \| No log \| 1.5 \| 60 \| 0.7258 \| 0.0840 \| 0.7258 \| 0.8520 \| \| No log \| 1.55 \| 62 \| 0.7335 \| 0.0444 \| 0.7335 \| 0.8564 \| \| No log \| 1.6 \| 64 \| 0.7513 \| 0.0937 \| 0.7513 \| 0.8668 \| \| No log \| 1.65 \| 66 \| 0.7398 \| 0.0481 \| 0.7398 \| 0.8601 \| \| No log \| 1.7 \| 68 \| 0.7442 \| 0.0 \| 0.7442 \| 0.8627 \| \| No log \| 1.75 \| 70 \| 0.7480 \| 0.0 \| 0.7480 \| 0.8649 \| \| No log \| 1.8 \| 72 \| 0.7431 \| -0.0027 \| 0.7431 \| 0.8620 \| \| No log \| 1.85 \| 74 \| 0.7483 \| 0.0893 \| 0.7483 \| 0.8651 \| \| No log \| 1.9 \| 76 \| 0.7506 \| 0.0026 \| 0.7506 \| 0.8664 \| \| No log \| 1.95 \| 78 \| 0.7455 \| 0.0026 \| 0.7455 \| 0.8634 \| \| No log \| 2.0 \| 80 \| 0.7296 \| 0.0764 \| 0.7296 \| 0.8542 \| \| No log \| 2.05 \| 82 \| 0.7244 \| 0.0410 \| 0.7244 \| 0.8511 \| \| No log \| 2.1 \| 84 \| 0.7185 \| 0.0481 \| 0.7185 \| 0.8476 \| \| No log \| 2.15 \| 86 \| 0.7201 \| 0.0481 \| 0.7201 \| 0.8486 \| \| No log \| 2.2 \| 88 \| 0.7684 \| 0.0688 \| 0.7684 \| 0.8766 \| \| No log \| 2.25 \| 90 \| 0.8471 \| -0.0047 \| 0.8471 \| 0.9204 \| \| No log \| 2.3 \| 92 \| 0.9219 \| 0.0336 \| 0.9219 \| 0.9602 \| \| No log \| 2.35 \| 94 \| 0.8593 \| 0.0661 \| 0.8593 \| 0.9270 \| \| No log \| 2.4 \| 96 \| 0.7927 \| 0.1448 \| 0.7927 \| 0.8903 \| \| No log \| 2.45 \| 98 \| 0.7396 \| 0.2158 \| 0.7396 \| 0.8600 \| \| No log \| 2.5 \| 100 \| 0.7441 \| 0.2158 \| 0.7441 \| 0.8626 \| \| No log \| 2.55 \| 102 \| 0.7275 \| 0.1867 \| 0.7275 \| 0.8530 \| \| No log \| 2.6 \| 104 \| 0.7325 \| 0.2509 \| 0.7325 \| 0.8559 \| \| No log \| 2.65 \| 106 \| 0.7702 \| 0.2218 \| 0.7702 \| 0.8776 \| \| No log \| 2.7 \| 108 \| 0.7711 \| 0.2158 \| 0.7711 \| 0.8781 \| \| No log \| 2.75 \| 110 \| 0.7585 \| 0.2158 \| 0.7585 \| 0.8709 \| \| No log \| 2.8 \| 112 \| 0.7625 \| 0.2158 \| 0.7625 \| 0.8732 \| \| No log \| 2.85 \| 114 \| 0.7762 \| 0.2413 \| 0.7762 \| 0.8810 \| \| No log \| 2.9 \| 116 \| 0.7775 \| 0.1901 \| 0.7775 \| 0.8818 \| \| No log \| 2.95 \| 118 \| 0.7895 \| 0.2847 \| 0.7895 \| 0.8886 \| \| No log \| 3.0 \| 120 \| 0.7612 \| 0.1624 \| 0.7612 \| 0.8724 \| \| No log \| 3.05 \| 122 \| 0.7445 \| 0.2158 \| 0.7445 \| 0.8629 \| \| No log \| 3.1 \| 124 \| 0.7593 \| 0.1010 \| 0.7593 \| 0.8714 \| \| No log \| 3.15 \| 126 \| 0.8076 \| 0.0971 \| 0.8076 \| 0.8986 \| \| No log \| 3.2 \| 128 \| 0.7975 \| 0.0971 \| 0.7975 \| 0.8930 \| \| No log \| 3.25 \| 130 \| 0.7766 \| 0.0697 \| 0.7766 \| 0.8812 \| \| No log \| 3.3 \| 132 \| 0.7984 \| 0.1051 \| 0.7984 \| 0.8935 \| \| No log \| 3.35 \| 134 \| 0.9101 \| 0.2149 \| 0.9101 \| 0.9540 \| \| No log \| 3.4 \| 136 \| 1.0361 \| 0.2521 \| 1.0361 \| 1.0179 \| \| No log \| 3.45 \| 138 \| 1.0476 \| 0.2364 \| 1.0476 \| 1.0235 \| \| No log \| 3.5 \| 140 \| 0.9632 \| 0.1995 \| 0.9632 \| 0.9814 \| \| No log \| 3.55 \| 142 \| 0.9064 \| 0.0584 \| 0.9064 \| 0.9521 \| \| No log \| 3.6 \| 144 \| 0.8631 \| 0.0697 \| 0.8631 \| 0.9290 \| \| No log \| 3.65 \| 146 \| 0.9331 \| 0.0975 \| 0.9331 \| 0.9660 \| \| No log \| 3.7 \| 148 \| 0.9420 \| 0.0856 \| 0.9420 \| 0.9706 \| \| No log \| 3.75 \| 150 \| 0.9851 \| 0.2193 \| 0.9851 \| 0.9925 \| \| No log \| 3.8 \| 152 \| 0.9770 \| 0.2892 \| 0.9770 \| 0.9885 \| \| No log \| 3.85 \| 154 \| 0.9237 \| 0.2439 \| 0.9237 \| 0.9611 \| \| No log \| 3.9 \| 156 \| 0.8649 \| 0.2943 \| 0.8649 \| 0.9300 \| \| No log \| 3.95 \| 158 \| 0.8627 \| 0.3369 \| 0.8627 \| 0.9288 \| \| No log \| 4.0 \| 160 \| 0.9110 \| 0.2912 \| 0.9110 \| 0.9544 \| \| No log \| 4.05 \| 162 \| 0.8747 \| 0.3115 \| 0.8747 \| 0.9353 \| \| No log \| 4.1 \| 164 \| 0.8485 \| 0.3157 \| 0.8485 \| 0.9211 \| \| No log \| 4.15 \| 166 \| 0.8876 \| 0.2059 \| 0.8876 \| 0.9421 \| \| No log \| 4.2 \| 168 \| 0.8396 \| 0.2662 \| 0.8396 \| 0.9163 \| \| No log \| 4.25 \| 170 \| 0.7145 \| 0.3020 \| 0.7145 \| 0.8453 \| \| No log \| 4.3 \| 172 \| 0.6763 \| 0.1829 \| 0.6763 \| 0.8224 \| \| No log \| 4.35 \| 174 \| 0.6848 \| 0.2181 \| 0.6848 \| 0.8275 \| \| No log \| 4.4 \| 176 \| 0.7393 \| 0.4052 \| 0.7393 \| 0.8598 \| \| No log \| 4.45 \| 178 \| 0.8544 \| 0.4251 \| 0.8544 \| 0.9243 \| \| No log \| 4.5 \| 180 \| 0.8607 \| 0.3754 \| 0.8607 \| 0.9277 \| \| No log \| 4.55 \| 182 \| 0.8286 \| 0.4251 \| 0.8286 \| 0.9103 \| \| No log \| 4.6 \| 184 \| 0.7767 \| 0.3167 \| 0.7767 \| 0.8813 \| \| No log \| 4.65 \| 186 \| 0.7748 \| 0.3167 \| 0.7748 \| 0.8802 \| \| No log \| 4.7 \| 188 \| 0.7632 \| 0.3622 \| 0.7632 \| 0.8736 \| \| No log \| 4.75 \| 190 \| 0.7500 \| 0.3341 \| 0.7500 \| 0.8660 \| \| No log \| 4.8 \| 192 \| 0.7483 \| 0.2950 \| 0.7483 \| 0.8651 \| \| No log \| 4.85 \| 194 \| 0.7769 \| 0.4642 \| 0.7769 \| 0.8814 \| \| No log \| 4.9 \| 196 \| 0.7819 \| 0.5120 \| 0.7819 \| 0.8843 \| \| No log \| 4.95 \| 198 \| 0.8057 \| 0.3789 \| 0.8057 \| 0.8976 \| \| No log \| 5.0 \| 200 \| 0.8061 \| 0.2950 \| 0.8061 \| 0.8978 \| \| No log \| 5.05 \| 202 \| 0.8570 \| 0.2967 \| 0.8570 \| 0.9257 \| \| No log \| 5.1 \| 204 \| 0.8946 \| 0.4462 \| 0.8946 \| 0.9458 \| \| No log \| 5.15 \| 206 \| 0.8111 \| 0.3372 \| 0.8111 \| 0.9006 \| \| No log \| 5.2 \| 208 \| 0.7667 \| 0.2847 \| 0.7667 \| 0.8756 \| \| No log \| 5.25 \| 210 \| 0.8306 \| 0.4247 \| 0.8306 \| 0.9114 \| \| No log \| 5.3 \| 212 \| 0.9020 \| 0.3333 \| 0.9020 \| 0.9498 \| \| No log \| 5.35 \| 214 \| 0.9648 \| 0.3727 \| 0.9648 \| 0.9822 \| \| No log \| 5.4 \| 216 \| 0.9330 \| 0.3012 \| 0.9330 \| 0.9659 \| \| No log \| 5.45 \| 218 \| 0.9431 \| 0.2779 \| 0.9431 \| 0.9712 \| \| No log \| 5.5 \| 220 \| 0.8969 \| 0.1029 \| 0.8969 \| 0.9471 \| \| No log \| 5.55 \| 222 \| 0.8776 \| 0.1918 \| 0.8776 \| 0.9368 \| \| No log \| 5.6 \| 224 \| 0.8238 \| 0.1935 \| 0.8238 \| 0.9076 \| \| No log \| 5.65 \| 226 \| 0.7614 \| 0.3127 \| 0.7614 \| 0.8726 \| \| No log \| 5.7 \| 228 \| 0.7729 \| 0.3399 \| 0.7729 \| 0.8791 \| \| No log \| 5.75 \| 230 \| 0.8301 \| 0.3425 \| 0.8301 \| 0.9111 \| \| No log \| 5.8 \| 232 \| 0.9000 \| 0.3579 \| 0.9000 \| 0.9487 \| \| No log \| 5.85 \| 234 \| 0.9826 \| 0.2886 \| 0.9826 \| 0.9913 \| \| No log \| 5.9 \| 236 \| 1.0048 \| 0.3059 \| 1.0048 \| 1.0024 \| \| No log \| 5.95 \| 238 \| 0.9560 \| 0.2886 \| 0.9560 \| 0.9778 \| \| No log \| 6.0 \| 240 \| 0.9846 \| 0.2886 \| 0.9846 \| 0.9923 \| \| No log \| 6.05 \| 242 \| 1.0053 \| 0.3247 \| 1.0053 \| 1.0026 \| \| No log \| 6.1 \| 244 \| 0.8946 \| 0.2923 \| 0.8946 \| 0.9458 \| \| No log \| 6.15 \| 246 \| 0.8653 \| 0.2518 \| 0.8653 \| 0.9302 \| \| No log \| 6.2 \| 248 \| 0.8387 \| 0.3127 \| 0.8387 \| 0.9158 \| \| No log \| 6.25 \| 250 \| 0.8439 \| 0.3060 \| 0.8439 \| 0.9187 \| \| No log \| 6.3 \| 252 \| 0.8582 \| 0.2632 \| 0.8582 \| 0.9264 \| \| No log \| 6.35 \| 254 \| 0.9131 \| 0.4113 \| 0.9131 \| 0.9556 \| \| No log \| 6.4 \| 256 \| 0.9065 \| 0.4113 \| 0.9065 \| 0.9521 \| \| No log \| 6.45 \| 258 \| 0.8590 \| 0.4462 \| 0.8590 \| 0.9268 \| \| No log \| 6.5 \| 260 \| 0.8227 \| 0.3169 \| 0.8227 \| 0.9070 \| \| No log \| 6.55 \| 262 \| 0.8932 \| 0.3371 \| 0.8932 \| 0.9451 \| \| No log \| 6.6 \| 264 \| 1.0092 \| 0.2802 \| 1.0092 \| 1.0046 \| \| No log \| 6.65 \| 266 \| 1.0151 \| 0.2926 \| 1.0151 \| 1.0075 \| \| No log \| 6.7 \| 268 \| 0.9591 \| 0.3417 \| 0.9591 \| 0.9794 \| \| No log \| 6.75 \| 270 \| 0.9389 \| 0.3579 \| 0.9389 \| 0.9690 \| \| No log \| 6.8 \| 272 \| 0.9699 \| 0.3302 \| 0.9699 \| 0.9848 \| \| No log \| 6.85 \| 274 \| 1.0013 \| 0.2501 \| 1.0013 \| 1.0007 \| \| No log \| 6.9 \| 276 \| 1.0755 \| 0.2264 \| 1.0755 \| 1.0371 \| \| No log \| 6.95 \| 278 \| 1.1285 \| 0.2264 \| 1.1285 \| 1.0623 \| \| No log \| 7.0 \| 280 \| 1.0357 \| 0.2796 \| 1.0357 \| 1.0177 \| \| No log \| 7.05 \| 282 \| 0.9956 \| 0.3608 \| 0.9956 \| 0.9978 \| \| No log \| 7.1 \| 284 \| 0.9900 \| 0.3557 \| 0.9900 \| 0.9950 \| \| No log \| 7.15 \| 286 \| 0.9507 \| 0.3557 \| 0.9507 \| 0.9751 \| \| No log \| 7.2 \| 288 \| 0.8655 \| 0.4862 \| 0.8655 \| 0.9303 \| \| No log \| 7.25 \| 290 \| 0.8401 \| 0.4144 \| 0.8401 \| 0.9166 \| \| No log \| 7.3 \| 292 \| 0.8795 \| 0.4462 \| 0.8795 \| 0.9378 \| \| No log \| 7.35 \| 294 \| 1.0027 \| 0.2732 \| 1.0027 \| 1.0014 \| \| No log \| 7.4 \| 296 \| 1.0642 \| 0.1981 \| 1.0642 \| 1.0316 \| \| No log \| 7.45 \| 298 \| 1.0066 \| 0.3114 \| 1.0066 \| 1.0033 \| \| No log \| 7.5 \| 300 \| 0.8917 \| 0.4541 \| 0.8917 \| 0.9443 \| \| No log \| 7.55 \| 302 \| 0.8794 \| 0.5077 \| 0.8794 \| 0.9378 \| \| No log \| 7.6 \| 304 \| 0.9474 \| 0.4044 \| 0.9474 \| 0.9733 \| \| No log \| 7.65 \| 306 \| 0.9984 \| 0.3031 \| 0.9984 \| 0.9992 \| \| No log \| 7.7 \| 308 \| 0.9133 \| 0.4114 \| 0.9133 \| 0.9557 \| \| No log \| 7.75 \| 310 \| 0.7844 \| 0.2605 \| 0.7844 \| 0.8857 \| \| No log \| 7.8 \| 312 \| 0.7335 \| 0.2809 \| 0.7335 \| 0.8564 \| \| No log \| 7.85 \| 314 \| 0.7312 \| 0.2809 \| 0.7312 \| 0.8551 \| \| No log \| 7.9 \| 316 \| 0.7909 \| 0.3121 \| 0.7909 \| 0.8893 \| \| No log \| 7.95 \| 318 \| 1.0015 \| 0.2389 \| 1.0015 \| 1.0007 \| \| No log \| 8.0 \| 320 \| 1.2296 \| 0.1391 \| 1.2296 \| 1.1089 \| \| No log \| 8.05 \| 322 \| 1.4373 \| 0.1122 \| 1.4373 \| 1.1989 \| \| No log \| 8.1 \| 324 \| 1.4303 \| 0.1122 \| 1.4303 \| 1.1960 \| \| No log \| 8.15 \| 326 \| 1.2038 \| 0.1654 \| 1.2038 \| 1.0972 \| \| No log \| 8.2 \| 328 \| 0.9614 \| 0.2075 \| 0.9614 \| 0.9805 \| \| No log \| 8.25 \| 330 \| 0.8355 \| 0.3564 \| 0.8355 \| 0.9141 \| \| No log \| 8.3 \| 332 \| 0.8083 \| 0.4329 \| 0.8083 \| 0.8991 \| \| No log \| 8.35 \| 334 \| 0.8333 \| 0.4644 \| 0.8333 \| 0.9129 \| \| No log \| 8.4 \| 336 \| 0.8453 \| 0.4627 \| 0.8453 \| 0.9194 \| \| No log \| 8.45 \| 338 \| 0.8036 \| 0.4167 \| 0.8036 \| 0.8965 \| \| No log \| 8.5 \| 340 \| 0.7977 \| 0.3399 \| 0.7977 \| 0.8931 \| \| No log \| 8.55 \| 342 \| 0.8403 \| 0.3544 \| 0.8403 \| 0.9167 \| \| No log \| 8.6 \| 344 \| 0.8785 \| 0.3121 \| 0.8785 \| 0.9373 \| \| No log \| 8.65 \| 346 \| 0.9207 \| 0.3207 \| 0.9207 \| 0.9595 \| \| No log \| 8.7 \| 348 \| 0.9339 \| 0.2669 \| 0.9339 \| 0.9664 \| \| No log \| 8.75 \| 350 \| 0.8966 \| 0.3677 \| 0.8966 \| 0.9469 \| \| No log \| 8.8 \| 352 \| 0.8942 \| 0.3329 \| 0.8942 \| 0.9456 \| \| No log \| 8.85 \| 354 \| 0.9491 \| 0.3560 \| 0.9491 \| 0.9742 \| \| No log \| 8.9 \| 356 \| 1.1092 \| 0.2520 \| 1.1092 \| 1.0532 \| \| No log \| 8.95 \| 358 \| 1.2857 \| 0.2197 \| 1.2857 \| 1.1339 \| \| No log \| 9.0 \| 360 \| 1.3019 \| 0.1793 \| 1.3019 \| 1.1410 \| \| No log \| 9.05 \| 362 \| 1.1466 \| 0.2191 \| 1.1466 \| 1.0708 \| \| No log \| 9.1 \| 364 \| 0.9258 \| 0.4113 \| 0.9258 \| 0.9622 \| \| No log \| 9.15 \| 366 \| 0.8345 \| 0.3746 \| 0.8345 \| 0.9135 \| \| No log \| 9.2 \| 368 \| 0.8240 \| 0.3972 \| 0.8240 \| 0.9077 \| \| No log \| 9.25 \| 370 \| 0.8596 \| 0.4462 \| 0.8596 \| 0.9271 \| \| No log \| 9.3 \| 372 \| 0.9124 \| 0.4008 \| 0.9124 \| 0.9552 \| \| No log \| 9.35 \| 374 \| 0.9869 \| 0.3359 \| 0.9869 \| 0.9934 \| \| No log \| 9.4 \| 376 \| 1.0105 \| 0.2926 \| 1.0105 \| 1.0052 \| \| No log \| 9.45 \| 378 \| 0.9363 \| 0.4328 \| 0.9363 \| 0.9676 \| \| No log \| 9.5 \| 380 \| 0.8247 \| 0.3564 \| 0.8247 \| 0.9081 \| \| No log \| 9.55 \| 382 \| 0.7809 \| 0.2589 \| 0.7809 \| 0.8837 \| \| No log \| 9.6 \| 384 \| 0.7887 \| 0.2589 \| 0.7887 \| 0.8881 \| \| No log \| 9.65 \| 386 \| 0.8558 \| 0.3564 \| 0.8558 \| 0.9251 \| \| No log \| 9.7 \| 388 \| 1.0092 \| 0.2659 \| 1.0092 \| 1.0046 \| \| No log \| 9.75 \| 390 \| 1.1964 \| 0.1805 \| 1.1964 \| 1.0938 \| \| No log \| 9.8 \| 392 \| 1.2204 \| 0.1479 \| 1.2204 \| 1.1047 \| \| No log \| 9.85 \| 394 \| 1.1127 \| 0.2264 \| 1.1127 \| 1.0548 \| \| No log \| 9.9 \| 396 \| 0.9637 \| 0.3516 \| 0.9637 \| 0.9817 \| \| No log \| 9.95 \| 398 \| 0.8570 \| 0.4144 \| 0.8570 \| 0.9257 \| \| No log \| 10.0 \| 400 \| 0.8032 \| 0.3099 \| 0.8032 \| 0.8962 \| \| No log \| 10.05 \| 402 \| 0.8018 \| 0.2527 \| 0.8018 \| 0.8954 \| \| No log \| 10.1 \| 404 \| 0.8452 \| 0.3564 \| 0.8452 \| 0.9193 \| \| No log \| 10.15 \| 406 \| 0.9750 \| 0.2651 \| 0.9750 \| 0.9874 \| \| No log \| 10.2 \| 408 \| 1.1752 \| 0.1508 \| 1.1752 \| 1.0841 \| \| No log \| 10.25 \| 410 \| 1.2968 \| 0.1522 \| 1.2968 \| 1.1388 \| \| No log \| 10.3 \| 412 \| 1.3569 \| 0.1414 \| 1.3569 \| 1.1649 \| \| No log \| 10.35 \| 414 \| 1.2820 \| 0.1549 \| 1.2820 \| 1.1323 \| \| No log \| 10.4 \| 416 \| 1.1277 \| 0.1568 \| 1.1277 \| 1.0619 \| \| No log \| 10.45 \| 418 \| 0.9659 \| 0.3761 \| 0.9659 \| 0.9828 \| \| No log \| 10.5 \| 420 \| 0.8109 \| 0.4247 \| 0.8109 \| 0.9005 \| \| No log \| 10.55 \| 422 \| 0.7443 \| 0.2558 \| 0.7443 \| 0.8628 \| \| No log \| 10.6 \| 424 \| 0.7236 \| 0.2261 \| 0.7236 \| 0.8506 \| \| No log \| 10.65 \| 426 \| 0.7324 \| 0.2261 \| 0.7324 \| 0.8558 \| \| No log \| 10.7 \| 428 \| 0.7808 \| 0.3399 \| 0.7808 \| 0.8836 \| \| No log \| 10.75 \| 430 \| 0.8909 \| 0.4404 \| 0.8909 \| 0.9439 \| \| No log \| 10.8 \| 432 \| 1.0132 \| 0.4044 \| 1.0132 \| 1.0066 \| \| No log \| 10.85 \| 434 \| 1.0463 \| 0.2264 \| 1.0463 \| 1.0229 \| \| No log \| 10.9 \| 436 \| 1.0307 \| 0.1858 \| 1.0307 \| 1.0152 \| \| No log \| 10.95 \| 438 \| 0.9524 \| 0.2510 \| 0.9524 \| 0.9759 \| \| No log \| 11.0 \| 440 \| 0.9381 \| 0.2866 \| 0.9381 \| 0.9686 \| \| No log \| 11.05 \| 442 \| 0.9587 \| 0.2460 \| 0.9587 \| 0.9791 \| \| No log \| 11.1 \| 444 \| 0.9440 \| 0.2510 \| 0.9440 \| 0.9716 \| \| No log \| 11.15 \| 446 \| 0.9761 \| 0.1747 \| 0.9761 \| 0.9880 \| \| No log \| 11.2 \| 448 \| 1.1083 \| 0.1870 \| 1.1083 \| 1.0527 \| \| No log \| 11.25 \| 450 \| 1.1684 \| 0.1203 \| 1.1684 \| 1.0809 \| \| No log \| 11.3 \| 452 \| 1.1929 \| 0.1530 \| 1.1929 \| 1.0922 \| \| No log \| 11.35 \| 454 \| 1.1310 \| 0.1671 \| 1.1310 \| 1.0635 \| \| No log \| 11.4 \| 456 \| 1.0862 \| 0.0922 \| 1.0862 \| 1.0422 \| \| No log \| 11.45 \| 458 \| 1.0900 \| 0.1463 \| 1.0900 \| 1.0440 \| \| No log \| 11.5 \| 460 \| 1.0844 \| 0.1671 \| 1.0844 \| 1.0414 \| \| No log \| 11.55 \| 462 \| 1.0999 \| 0.1909 \| 1.0999 \| 1.0488 \| \| No log \| 11.6 \| 464 \| 1.1240 \| 0.2020 \| 1.1240 \| 1.0602 \| \| No log \| 11.65 \| 466 \| 1.0884 \| 0.2020 \| 1.0884 \| 1.0433 \| \| No log \| 11.7 \| 468 \| 1.0469 \| 0.2732 \| 1.0469 \| 1.0232 \| \| No log \| 11.75 \| 470 \| 1.0083 \| 0.2271 \| 1.0083 \| 1.0041 \| \| No log \| 11.8 \| 472 \| 0.9795 \| 0.2119 \| 0.9795 \| 0.9897 \| \| No log \| 11.85 \| 474 \| 0.9908 \| 0.2703 \| 0.9908 \| 0.9954 \| \| No log \| 11.9 \| 476 \| 1.0087 \| 0.2886 \| 1.0087 \| 1.0044 \| \| No log \| 11.95 \| 478 \| 1.0151 \| 0.2552 \| 1.0151 \| 1.0075 \| \| No log \| 12.0 \| 480 \| 1.0537 \| 0.2045 \| 1.0537 \| 1.0265 \| \| No log \| 12.05 \| 482 \| 1.0959 \| 0.2006 \| 1.0959 \| 1.0468 \| \| No log \| 12.1 \| 484 \| 1.0750 \| 0.2006 \| 1.0750 \| 1.0368 \| \| No log \| 12.15 \| 486 \| 1.0557 \| 0.2833 \| 1.0557 \| 1.0275 \| \| No log \| 12.2 \| 488 \| 1.0304 \| 0.2886 \| 1.0304 \| 1.0151 \| \| No log \| 12.25 \| 490 \| 1.0110 \| 0.2995 \| 1.0110 \| 1.0055 \| \| No log \| 12.3 \| 492 \| 0.9812 \| 0.3110 \| 0.9812 \| 0.9906 \| \| No log \| 12.35 \| 494 \| 0.9318 \| 0.3606 \| 0.9318 \| 0.9653 \| \| No log \| 12.4 \| 496 \| 0.9165 \| 0.3359 \| 0.9165 \| 0.9573 \| \| No log \| 12.45 \| 498 \| 0.9682 \| 0.2487 \| 0.9682 \| 0.9840 \| \| 0.3594 \| 12.5 \| 500 \| 1.0243 \| 0.3193 \| 1.0243 \| 1.0121 \| \| 0.3594 \| 12.55 \| 502 \| 0.9971 \| 0.3193 \| 0.9971 \| 0.9985 \| \| 0.3594 \| 12.6 \| 504 \| 0.9262 \| 0.3846 \| 0.9262 \| 0.9624 \| \| 0.3594 \| 12.65 \| 506 \| 0.9074 \| 0.3918 \| 0.9074 \| 0.9526 \| \| 0.3594 \| 12.7 \| 508 \| 0.9062 \| 0.3991 \| 0.9062 \| 0.9520 \| \| 0.3594 \| 12.75 \| 510 \| 0.9505 \| 0.2703 \| 0.9505 \| 0.9750 \| \| 0.3594 \| 12.8 \| 512 \| 1.0398 \| 0.2683 \| 1.0398 \| 1.0197 \| \| 0.3594 \| 12.85 \| 514 \| 1.1322 \| 0.2059 \| 1.1322 \| 1.0640 \| \| 0.3594 \| 12.9 \| 516 \| 1.1282 \| 0.2059 \| 1.1282 \| 1.0622 \| \| 0.3594 \| 12.95 \| 518 \| 1.0676 \| 0.2683 \| 1.0676 \| 1.0333 \| ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.0+cu118 - Datasets 2.21.0 - Tokenizers 0.19.1
trenden/1c28c7f4-a783-47ef-8d8c-acd4814f8fca	trenden	2025-01-21T11:56:54Z	5	0	peft	[ "peft", "safetensors", "gpt_neox", "axolotl", "generated_from_trainer", "base_model:databricks/dolly-v2-3b", "base_model:adapter:databricks/dolly-v2-3b", "license:mit", "region:us" ]	null	2025-01-21T11:41:06Z	--- library_name: peft license: mit base_model: databricks/dolly-v2-3b tags: - axolotl - generated_from_trainer model-index: - name: 1c28c7f4-a783-47ef-8d8c-acd4814f8fca results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: databricks/dolly-v2-3b bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - d4ad1f4ec6a1fae0_train_data.json ds_type: json format: custom path: /workspace/input_data/d4ad1f4ec6a1fae0_train_data.json type: field_instruction: Patient field_output: Description format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: trenden/1c28c7f4-a783-47ef-8d8c-acd4814f8fca hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/d4ad1f4ec6a1fae0_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 6874924e-0eae-4909-b19a-0c7087adfd79 wandb_project: Birthday-SN56-26-Gradients-On-Demand wandb_run: your_name wandb_runid: 6874924e-0eae-4909-b19a-0c7087adfd79 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # 1c28c7f4-a783-47ef-8d8c-acd4814f8fca This model is a fine-tuned version of [databricks/dolly-v2-3b](https://huggingface.co/databricks/dolly-v2-3b) on the None dataset. It achieves the following results on the evaluation set: - Loss: 3.1110 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 14.3662 \| 0.0000 \| 1 \| 4.0295 \| \| 13.7863 \| 0.0001 \| 3 \| 4.0044 \| \| 18.6008 \| 0.0002 \| 6 \| 3.7874 \| \| 13.7364 \| 0.0003 \| 9 \| 3.1110 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
JuniperChinenye/wakeupvalis8	JuniperChinenye	2025-01-21T11:56:08Z	30	0	transformers	[ "transformers", "safetensors", "llama", "text-generation", "conversational", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2025-01-21T11:53:32Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. 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Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
lesso14/66972514-8697-43de-9112-4681ac299b37	lesso14	2025-01-21T11:55:37Z	6	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:unsloth/Phi-3.5-mini-instruct", "base_model:adapter:unsloth/Phi-3.5-mini-instruct", "license:mit", "region:us" ]	null	2025-01-21T11:50:52Z	--- library_name: peft license: mit base_model: unsloth/Phi-3.5-mini-instruct tags: - axolotl - generated_from_trainer model-index: - name: 66972514-8697-43de-9112-4681ac299b37 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/Phi-3.5-mini-instruct bf16: true chat_template: llama3 datasets: - data_files: - 223b73ed5c333b1a_train_data.json ds_type: json format: custom path: /workspace/input_data/223b73ed5c333b1a_train_data.json type: field_instruction: category field_output: prompt format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: 2 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null flash_attention: false fp16: false fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: lesso14/66972514-8697-43de-9112-4681ac299b37 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0001 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 25 micro_batch_size: 2 mlflow_experiment_name: /tmp/223b73ed5c333b1a_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_hf output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: a7378db3-707d-4698-9a3f-5c035ca3db01 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: a7378db3-707d-4698-9a3f-5c035ca3db01 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # 66972514-8697-43de-9112-4681ac299b37 This model is a fine-tuned version of [unsloth/Phi-3.5-mini-instruct](https://huggingface.co/unsloth/Phi-3.5-mini-instruct) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0001 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_HF with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 25 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 0.0 \| 0.0009 \| 1 \| nan \| \| 0.0 \| 0.0043 \| 5 \| nan \| \| 0.0 \| 0.0086 \| 10 \| nan \| \| 0.0 \| 0.0129 \| 15 \| nan \| \| 0.0 \| 0.0172 \| 20 \| nan \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
lesso09/31427da4-2cde-4f4b-abb3-2871ae1631e1	lesso09	2025-01-21T11:55:15Z	11	0	peft	[ "peft", "safetensors", "opt", "axolotl", "generated_from_trainer", "base_model:facebook/opt-125m", "base_model:adapter:facebook/opt-125m", "license:other", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-21T11:53:11Z	--- library_name: peft license: other base_model: facebook/opt-125m tags: - axolotl - generated_from_trainer model-index: - name: 31427da4-2cde-4f4b-abb3-2871ae1631e1 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: facebook/opt-125m bf16: true chat_template: llama3 datasets: - data_files: - ac24df8c526e3c85_train_data.json ds_type: json format: custom path: /workspace/input_data/ac24df8c526e3c85_train_data.json type: field_input: vw_text field_instruction: id field_output: raw_text format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: 2 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null flash_attention: false fp16: false fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: lesso09/31427da4-2cde-4f4b-abb3-2871ae1631e1 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 25 micro_batch_size: 2 mlflow_experiment_name: /tmp/ac24df8c526e3c85_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 722a0b59-9cc9-4456-b05d-e688625587ce wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 722a0b59-9cc9-4456-b05d-e688625587ce warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # 31427da4-2cde-4f4b-abb3-2871ae1631e1 This model is a fine-tuned version of [facebook/opt-125m](https://huggingface.co/facebook/opt-125m) on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.7460 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 25 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 13.0725 \| 0.0011 \| 1 \| 3.1971 \| \| 12.7422 \| 0.0055 \| 5 \| 3.1474 \| \| 12.8721 \| 0.0110 \| 10 \| 2.9925 \| \| 11.728 \| 0.0165 \| 15 \| 2.8301 \| \| 11.6738 \| 0.0221 \| 20 \| 2.7617 \| \| 11.938 \| 0.0276 \| 25 \| 2.7460 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
simshelper/task-1-google-gemma-7b	simshelper	2025-01-21T11:55:11Z	412	0	peft	[ "peft", "safetensors", "arxiv:1910.09700", "base_model:google/gemma-7b", "base_model:adapter:google/gemma-7b", "region:us" ]	null	2025-01-12T21:23:12Z	--- base_model: google/gemma-7b library_name: peft --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed] ### Framework versions - PEFT 0.13.2
mrcuddle/Ministral-Instruct-2410-8B-DPO-RP	mrcuddle	2025-01-21T11:54:32Z	173	1	transformers	[ "transformers", "tensorboard", "safetensors", "mistral", "text-generation", "autotrain", "text-generation-inference", "conversational", "en", "dataset:athirdpath/DPO_Pairs-Roleplay-Alpaca-NSFW", "base_model:mistralai/Ministral-8B-Instruct-2410", "base_model:finetune:mistralai/Ministral-8B-Instruct-2410", "license:other", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-generation	2025-01-21T02:03:02Z	--- tags: - autotrain - text-generation-inference - text-generation library_name: transformers base_model: mistralai/Ministral-8B-Instruct-2410 widget: - messages: - role: user content: What is your favorite condiment? license: other datasets: - athirdpath/DPO_Pairs-Roleplay-Alpaca-NSFW language: - en --- # Model Trained Using AutoTrain This model was trained using AutoTrain. For more information, please visit [AutoTrain](https://hf.co/docs/autotrain). # Usage ```python from transformers import AutoModelForCausalLM, AutoTokenizer model_path = "mrcuddle/Ministral-Instruct-2410-8B-DPO-RP" tokenizer = AutoTokenizer.from_pretrained(model_path) model = AutoModelForCausalLM.from_pretrained( model_path, device_map="auto", torch_dtype='auto' ).eval() # Prompt content: "hi" messages = [ {"role": "user", "content": "hi"} ] input_ids = tokenizer.apply_chat_template(conversation=messages, tokenize=True, add_generation_prompt=True, return_tensors='pt') output_ids = model.generate(input_ids.to('cuda')) response = tokenizer.decode(output_ids[0][input_ids.shape[1]:], skip_special_tokens=True) # Model response: "Hello! How can I assist you today?" print(response) ```
AmberYifan/Llama-2-7b-sft-peers-pool	AmberYifan	2025-01-21T11:54:06Z	7	0	transformers	[ "transformers", "safetensors", "llama", "text-generation", "generated_from_trainer", "trl", "dpo", "conversational", "arxiv:2305.18290", "base_model:AmberYifan/llama2-7b-sft-ultrachat-safeRLHF", "base_model:finetune:AmberYifan/llama2-7b-sft-ultrachat-safeRLHF", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2025-01-17T09:20:27Z	--- base_model: AmberYifan/llama2-7b-sft-ultrachat-safeRLHF library_name: transformers model_name: Llama-2-7b-sft-peers-pool tags: - generated_from_trainer - trl - dpo licence: license --- # Model Card for Llama-2-7b-sft-peers-pool This model is a fine-tuned version of [AmberYifan/llama2-7b-sft-ultrachat-safeRLHF](https://huggingface.co/AmberYifan/llama2-7b-sft-ultrachat-safeRLHF). It has been trained using [TRL](https://github.com/huggingface/trl). ## Quick start ```python from transformers import pipeline question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?" generator = pipeline("text-generation", model="AmberYifan/Llama-2-7b-sft-peers-pool", device="cuda") output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0] print(output["generated_text"]) ``` ## Training procedure [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/yifanwang/huggingface/runs/jbqvd8s4) This model was trained with DPO, a method introduced in [Direct Preference Optimization: Your Language Model is Secretly a Reward Model](https://huggingface.co/papers/2305.18290). ### Framework versions - TRL: 0.12.2 - Transformers: 4.46.3 - Pytorch: 2.5.1+cu118 - Datasets: 3.2.0 - Tokenizers: 0.20.3 ## Citations Cite DPO as: ```bibtex @inproceedings{rafailov2023direct, title = {{Direct Preference Optimization: Your Language Model is Secretly a Reward Model}}, author = {Rafael Rafailov and Archit Sharma and Eric Mitchell and Christopher D. Manning and Stefano Ermon and Chelsea Finn}, year = 2023, booktitle = {Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023}, url = {http://papers.nips.cc/paper_files/paper/2023/hash/a85b405ed65c6477a4fe8302b5e06ce7-Abstract-Conference.html}, editor = {Alice Oh and Tristan Naumann and Amir Globerson and Kate Saenko and Moritz Hardt and Sergey Levine}, } ``` Cite TRL as: ```bibtex @misc{vonwerra2022trl, title = {{TRL: Transformer Reinforcement Learning}}, author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallouédec}, year = 2020, journal = {GitHub repository}, publisher = {GitHub}, howpublished = {\url{https://github.com/huggingface/trl}} } ```
nblinh63/e25aed5f-5c03-4efe-9836-f29232e954f5	nblinh63	2025-01-21T11:53:50Z	7	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:unsloth/SmolLM2-1.7B-Instruct", "base_model:adapter:unsloth/SmolLM2-1.7B-Instruct", "license:apache-2.0", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-21T11:41:18Z	--- library_name: peft license: apache-2.0 base_model: unsloth/SmolLM2-1.7B-Instruct tags: - axolotl - generated_from_trainer model-index: - name: e25aed5f-5c03-4efe-9836-f29232e954f5 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/SmolLM2-1.7B-Instruct bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 4ae6450c41448135_train_data.json ds_type: json format: custom path: /workspace/input_data/4ae6450c41448135_train_data.json type: field_input: arguments field_instruction: instruction field_output: output format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: nblinh63/e25aed5f-5c03-4efe-9836-f29232e954f5 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/4ae6450c41448135_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 82c1cb78-ced4-49a5-85a8-db01b7542ac0 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 82c1cb78-ced4-49a5-85a8-db01b7542ac0 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details><br> # e25aed5f-5c03-4efe-9836-f29232e954f5 This model is a fine-tuned version of [unsloth/SmolLM2-1.7B-Instruct](https://huggingface.co/unsloth/SmolLM2-1.7B-Instruct) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.6300 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 0.529 \| 0.1644 \| 200 \| 0.6300 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
memevis/try56	memevis	2025-01-21T11:53:19Z	50	0	transformers	[ "transformers", "safetensors", "llama", "text-generation", "conversational", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2025-01-21T11:48:04Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
vertings6/1cbf9b6c-5749-4703-8e27-b35cd2724a2c	vertings6	2025-01-21T11:53:18Z	6	0	peft	[ "peft", "safetensors", "mistral", "axolotl", "generated_from_trainer", "base_model:Artples/L-MChat-7b", "base_model:adapter:Artples/L-MChat-7b", "license:apache-2.0", "region:us" ]	null	2025-01-21T11:48:51Z	--- library_name: peft license: apache-2.0 base_model: Artples/L-MChat-7b tags: - axolotl - generated_from_trainer model-index: - name: 1cbf9b6c-5749-4703-8e27-b35cd2724a2c results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: Artples/L-MChat-7b bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - df03514e65800f80_train_data.json ds_type: json format: custom path: /workspace/input_data/df03514e65800f80_train_data.json type: field_instruction: input field_output: response format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: 1 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: true hub_model_id: vertings6/1cbf9b6c-5749-4703-8e27-b35cd2724a2c hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 79GiB max_steps: 30 micro_batch_size: 4 mlflow_experiment_name: /tmp/df03514e65800f80_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optim_args: adam_beta1: 0.9 adam_beta2: 0.95 adam_epsilon: 1e-5 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 special_tokens: pad_token: <\|end_of_turn\|> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: e3508d62-5471-4cdf-8dba-5844f441931a wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: e3508d62-5471-4cdf-8dba-5844f441931a warmup_steps: 5 weight_decay: 0.001 xformers_attention: true ``` </details><br> # 1cbf9b6c-5749-4703-8e27-b35cd2724a2c This model is a fine-tuned version of [Artples/L-MChat-7b](https://huggingface.co/Artples/L-MChat-7b) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 16 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.95,adam_epsilon=1e-5 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 30 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| No log \| 0.0023 \| 1 \| nan \| \| 0.0 \| 0.0113 \| 5 \| nan \| \| 0.0 \| 0.0225 \| 10 \| nan \| \| 0.0 \| 0.0338 \| 15 \| nan \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
simshelper/task-1-google-gemma-2b	simshelper	2025-01-21T11:53:15Z	1,231	0	peft	[ "peft", "safetensors", "arxiv:1910.09700", "base_model:google/gemma-2b", "base_model:adapter:google/gemma-2b", "region:us" ]	null	2025-01-12T21:08:24Z	--- base_model: google/gemma-2b library_name: peft --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed] ### Framework versions - PEFT 0.13.2
ynuwara/SmolVLM-Base-vqav2	ynuwara	2025-01-21T11:53:15Z	16	0	peft	[ "peft", "tensorboard", "safetensors", "generated_from_trainer", "base_model:HuggingFaceTB/SmolVLM-Base", "base_model:adapter:HuggingFaceTB/SmolVLM-Base", "license:apache-2.0", "region:us" ]	null	2025-01-21T11:53:13Z	--- library_name: peft license: apache-2.0 base_model: HuggingFaceTB/SmolVLM-Base tags: - generated_from_trainer model-index: - name: SmolVLM-Base-vqav2 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # SmolVLM-Base-vqav2 This model is a fine-tuned version of [HuggingFaceTB/SmolVLM-Base](https://huggingface.co/HuggingFaceTB/SmolVLM-Base) on an unknown dataset. ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0001 - train_batch_size: 4 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 16 - optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 50 - num_epochs: 1 ### Training results ### Framework versions - PEFT 0.14.0 - Transformers 4.47.1 - Pytorch 2.5.1+cu121 - Datasets 3.2.0 - Tokenizers 0.21.0
memevis/try55	memevis	2025-01-21T11:53:11Z	47	0	transformers	[ "transformers", "safetensors", "llama", "text-generation", "conversational", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2025-01-21T11:47:15Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. 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memevis/try57	memevis	2025-01-21T11:52:18Z	17	0	transformers	[ "transformers", "safetensors", "llama", "text-generation", "conversational", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2025-01-21T11:47:14Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. 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lesso10/0a4c2570-7b1e-4bbc-b25e-573f2750a97a	lesso10	2025-01-21T11:51:48Z	6	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:unsloth/tinyllama", "base_model:adapter:unsloth/tinyllama", "license:apache-2.0", "4-bit", "bitsandbytes", "region:us" ]	null	2025-01-21T11:32:46Z	--- library_name: peft license: apache-2.0 base_model: unsloth/tinyllama tags: - axolotl - generated_from_trainer model-index: - name: 0a4c2570-7b1e-4bbc-b25e-573f2750a97a results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/tinyllama bf16: auto chat_template: llama3 datasets: - data_files: - 543802598c2bc8a9_train_data.json ds_type: json format: custom path: /workspace/input_data/543802598c2bc8a9_train_data.json type: field_input: cot field_instruction: query field_output: response format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: 1 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: true gradient_checkpointing: true group_by_length: false hub_model_id: lesso10/0a4c2570-7b1e-4bbc-b25e-573f2750a97a hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: true load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_steps: 25 micro_batch_size: 2 mlflow_experiment_name: /tmp/543802598c2bc8a9_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 5ade5524-ba32-4677-ac63-2a87ad5e9260 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 5ade5524-ba32-4677-ac63-2a87ad5e9260 warmup_steps: 10 weight_decay: 0.01 xformers_attention: null ``` </details><br> # 0a4c2570-7b1e-4bbc-b25e-573f2750a97a This model is a fine-tuned version of [unsloth/tinyllama](https://huggingface.co/unsloth/tinyllama) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 25 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| No log \| 0.0000 \| 1 \| nan \| \| 0.0 \| 0.0002 \| 5 \| nan \| \| 0.0 \| 0.0004 \| 10 \| nan \| \| 0.0 \| 0.0005 \| 15 \| nan \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
mini1013/master_cate_sl19	mini1013	2025-01-21T11:51:22Z	1,256	0	setfit	[ "setfit", "safetensors", "roberta", "sentence-transformers", "text-classification", "generated_from_setfit_trainer", "arxiv:2209.11055", "base_model:mini1013/master_domain", "base_model:finetune:mini1013/master_domain", "model-index", "region:us" ]	text-classification	2025-01-21T11:51:00Z	--- tags: - setfit - sentence-transformers - text-classification - generated_from_setfit_trainer widget: - text: 발열양말 방한 보온양말 등산 낚시 스키 스노우보드 스케이트 야외작업 스포츠/레저>스키/보드>스키/보드방한용품>양말 - text: 무크 엠 무크 펠로 데크 다크네이비 517413203ZB 스포츠/레저>스키/보드>스노보드장비>데크 - text: 스키복 성인 자켓 상의 여성용 JACKET 스키자켓 남성 스포츠/레저>스키/보드>스키복>상의 - text: Toko Edge Tuner Pro 스노우보드 엣지 튜닝 컷팅 스포츠/레저>스키/보드>스키/보드용품>보수장비 - text: 헬리아 주니어 고글 카이로스 무광퍼플블랙 보드고글 스포츠고글 스포츠/레저>스키/보드>스키/보드용품>고글 metrics: - accuracy pipeline_tag: text-classification library_name: setfit inference: true base_model: mini1013/master_domain model-index: - name: SetFit with mini1013/master_domain results: - task: type: text-classification name: Text Classification dataset: name: Unknown type: unknown split: test metrics: - type: accuracy value: 1.0 name: Accuracy --- # SetFit with mini1013/master_domain This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [mini1013/master_domain](https://huggingface.co/mini1013/master_domain) as the Sentence Transformer embedding model. A [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance is used for classification. The model has been trained using an efficient few-shot learning technique that involves: 1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning. 2. Training a classification head with features from the fine-tuned Sentence Transformer. ## Model Details ### Model Description - Model Type: SetFit - Sentence Transformer body: [mini1013/master_domain](https://huggingface.co/mini1013/master_domain) - Classification head: a [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance - Maximum Sequence Length: 512 tokens - Number of Classes: 6 classes <!-- - Training Dataset: [Unknown](https://huggingface.co/datasets/unknown) --> <!-- - Language: Unknown --> <!-- - License: Unknown --> ### Model Sources - Repository: [SetFit on GitHub](https://github.com/huggingface/setfit) - Paper: [Efficient Few-Shot Learning Without Prompts](https://arxiv.org/abs/2209.11055) - Blogpost: [SetFit: Efficient Few-Shot Learning Without Prompts](https://huggingface.co/blog/setfit) ### Model Labels \| Label \| Examples \| \|:------\|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\| \| 2.0 \| <ul><li>'충전식 열선양말 발열 스키장 보드 스키 등산 스포츠/레저>스키/보드>스키/보드방한용품>양말'</li><li>'우주마켓 겨울 방한 마스크 보온 등산 골프 따뜻한 자전거 귀덮개 귀마개 마스크 스포츠/레저>스키/보드>스키/보드방한용품>귀마개'</li><li>'다이나핏 폴디드 스몰로고 비니 Dark 스포츠/레저>스키/보드>스키/보드방한용품>비니'</li></ul> \| \| 0.0 \| <ul><li>'방풍 방수 여성 스노우 보드 플레이 여자 복 어스투 점퍼 점프 슈트 수트 스키 가프 스포츠/레저>스키/보드>보드복>재킷'</li><li>'2023 여성용 원피스 스키 슈트 겨울 야외 스포츠 방풍 방수 보온 스노보드 점프슈트 스포츠/레저>스키/보드>보드복>상하세트'</li><li>'여성용 스노우보드 점프수트 여성 일체형 스키복 방 -남성용 민트 그린 수트 스포츠/레저>스키/보드>보드복>상하세트'</li></ul> \| \| 5.0 \| <ul><li>'2223 헤드 스키 PURE JOY 여성용 스포츠/레저>스키/보드>스키장비>플레이트'</li><li>'미니 스키 부츠 스케이트 썰매 스노우 숏부츠 스포츠/레저>스키/보드>스키장비>부츠'</li><li>'PHOENIX 피닉스 주니어 스키 팀복 2223 PHENIX KOREA JR TEAM RD 스포츠/레저>스키/보드>스키장비>플레이트'</li></ul> \| \| 4.0 \| <ul><li>'스키복 세트 여성 남성 방한 방풍 스포츠/레저>스키/보드>스키복>상하세트'</li><li>'스파이더 남성 보르미오 GTX 스키 팬츠 SPFWCISP401MBLK LE1216929158 스포츠/레저>스키/보드>스키복>하의'</li><li>'카르포스 스키바지 남자 겨울 2521013 스포츠/레저>스키/보드>스키복>하의'</li></ul> \| \| 3.0 \| <ul><li>'XCMAN 4겹콘 스터드 디아 7 87인치 알루미늄 스노우보드 스톰프 패드 9pcs 스포츠/레저>스키/보드>스키/보드용품>스티커용품'</li><li>'Thule RoundTrip 스키 스노보드 더플 백 90L 다크 슬레이트 142322 스포츠/레저>스키/보드>스키/보드용품>보드가방'</li><li>'ToeJamR 스노우보드 스톰프 패드 나비 스포츠/레저>스키/보드>스키/보드용품>스티커용품'</li></ul> \| \| 1.0 \| <ul><li>'스노우 스키 여성 부츠 보드 롱 털 따듯한 스노보드 스포츠/레저>스키/보드>스노보드장비>부츠'</li><li>'나이트로 팀 바인딩 2223 NITRO Team 스포츠/레저>스키/보드>스노보드장비>바인딩'</li><li>'헌터 WOMEN 인트레피드 리플렉티브 카모 숏 스노우부츠 - 패턴그레이 WFS1004PCTPTG 스포츠/레저>스키/보드>스노보드장비>부츠'</li></ul> \| ## Evaluation ### Metrics \| Label \| Accuracy \| \|:--------\|:---------\| \| all \| 1.0 \| ## Uses ### Direct Use for Inference First install the SetFit library: ```bash pip install setfit ``` Then you can load this model and run inference. ```python from setfit import SetFitModel # Download from the 🤗 Hub model = SetFitModel.from_pretrained("mini1013/master_cate_sl19") # Run inference preds = model("스키복 성인 자켓 상의 여성용 JACKET 스키자켓 남성 스포츠/레저>스키/보드>스키복>상의") ``` <!-- ### Downstream Use List how someone could finetune this model on their own dataset. --> <!-- ### Out-of-Scope Use List how the model may foreseeably be misused and address what users ought not to do with the model. --> <!-- ## Bias, Risks and Limitations What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model. --> <!-- ### Recommendations What are recommendations with respect to the foreseeable issues? For example, filtering explicit content. --> ## Training Details ### Training Set Metrics \| Training set \| Min \| Median \| Max \| \|:-------------\|:----\|:-------\|:----\| \| Word count \| 4 \| 9.4619 \| 18 \| \| Label \| Training Sample Count \| \|:------\|:----------------------\| \| 0.0 \| 70 \| \| 1.0 \| 70 \| \| 2.0 \| 70 \| \| 3.0 \| 70 \| \| 4.0 \| 70 \| \| 5.0 \| 70 \| ### Training Hyperparameters - batch_size: (256, 256) - num_epochs: (30, 30) - max_steps: -1 - sampling_strategy: oversampling - num_iterations: 50 - body_learning_rate: (2e-05, 1e-05) - head_learning_rate: 0.01 - loss: CosineSimilarityLoss - distance_metric: cosine_distance - margin: 0.25 - end_to_end: False - use_amp: False - warmup_proportion: 0.1 - l2_weight: 0.01 - seed: 42 - eval_max_steps: -1 - load_best_model_at_end: False ### Training Results \| Epoch \| Step \| Training Loss \| Validation Loss \| \|:-------:\|:----:\|:-------------:\|:---------------:\| \| 0.0120 \| 1 \| 0.4926 \| - \| \| 0.6024 \| 50 \| 0.497 \| - \| \| 1.2048 \| 100 \| 0.5003 \| - \| \| 1.8072 \| 150 \| 0.1918 \| - \| \| 2.4096 \| 200 \| 0.0218 \| - \| \| 3.0120 \| 250 \| 0.0004 \| - \| \| 3.6145 \| 300 \| 0.0003 \| - \| \| 4.2169 \| 350 \| 0.0001 \| - \| \| 4.8193 \| 400 \| 0.0001 \| - \| \| 5.4217 \| 450 \| 0.0 \| - \| \| 6.0241 \| 500 \| 0.0 \| - \| \| 6.6265 \| 550 \| 0.0 \| - \| \| 7.2289 \| 600 \| 0.0 \| - \| \| 7.8313 \| 650 \| 0.0 \| - \| \| 8.4337 \| 700 \| 0.0 \| - \| \| 9.0361 \| 750 \| 0.0 \| - \| \| 9.6386 \| 800 \| 0.0 \| - \| \| 10.2410 \| 850 \| 0.0 \| - \| \| 10.8434 \| 900 \| 0.0 \| - \| \| 11.4458 \| 950 \| 0.0 \| - \| \| 12.0482 \| 1000 \| 0.0 \| - \| \| 12.6506 \| 1050 \| 0.0001 \| - \| \| 13.2530 \| 1100 \| 0.0 \| - \| \| 13.8554 \| 1150 \| 0.0 \| - \| \| 14.4578 \| 1200 \| 0.0 \| - \| \| 15.0602 \| 1250 \| 0.0 \| - \| \| 15.6627 \| 1300 \| 0.0 \| - \| \| 16.2651 \| 1350 \| 0.0 \| - \| \| 16.8675 \| 1400 \| 0.0 \| - \| \| 17.4699 \| 1450 \| 0.0 \| - \| \| 18.0723 \| 1500 \| 0.0 \| - \| \| 18.6747 \| 1550 \| 0.0 \| - \| \| 19.2771 \| 1600 \| 0.0 \| - \| \| 19.8795 \| 1650 \| 0.0 \| - \| \| 20.4819 \| 1700 \| 0.0 \| - \| \| 21.0843 \| 1750 \| 0.0 \| - \| \| 21.6867 \| 1800 \| 0.0 \| - \| \| 22.2892 \| 1850 \| 0.0 \| - \| \| 22.8916 \| 1900 \| 0.0 \| - \| \| 23.4940 \| 1950 \| 0.0 \| - \| \| 24.0964 \| 2000 \| 0.0 \| - \| \| 24.6988 \| 2050 \| 0.0 \| - \| \| 25.3012 \| 2100 \| 0.0 \| - \| \| 25.9036 \| 2150 \| 0.0 \| - \| \| 26.5060 \| 2200 \| 0.0 \| - \| \| 27.1084 \| 2250 \| 0.0 \| - \| \| 27.7108 \| 2300 \| 0.0 \| - \| \| 28.3133 \| 2350 \| 0.0 \| - \| \| 28.9157 \| 2400 \| 0.0 \| - \| \| 29.5181 \| 2450 \| 0.0 \| - \| ### Framework Versions - Python: 3.10.12 - SetFit: 1.1.0 - Sentence Transformers: 3.3.1 - Transformers: 4.44.2 - PyTorch: 2.2.0a0+81ea7a4 - Datasets: 3.2.0 - Tokenizers: 0.19.1 ## Citation ### BibTeX ```bibtex @article{https://doi.org/10.48550/arxiv.2209.11055, doi = {10.48550/ARXIV.2209.11055}, url = {https://arxiv.org/abs/2209.11055}, author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren}, keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences}, title = {Efficient Few-Shot Learning Without Prompts}, publisher = {arXiv}, year = {2022}, copyright = {Creative Commons Attribution 4.0 International} } ``` <!-- ## Glossary Clearly define terms in order to be accessible across audiences. --> <!-- ## Model Card Authors Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction. --> <!-- ## Model Card Contact Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors. -->
lesso09/0f79296c-b754-4989-b3bc-489ace006ef1	lesso09	2025-01-21T11:50:36Z	8	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:unsloth/llama-2-7b-chat", "base_model:adapter:unsloth/llama-2-7b-chat", "license:apache-2.0", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-21T08:34:01Z	--- library_name: peft license: apache-2.0 base_model: unsloth/llama-2-7b-chat tags: - axolotl - generated_from_trainer model-index: - name: 0f79296c-b754-4989-b3bc-489ace006ef1 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/llama-2-7b-chat bf16: true chat_template: llama3 datasets: - data_files: - 124bc05ddbf5ee81_train_data.json ds_type: json format: custom path: /workspace/input_data/124bc05ddbf5ee81_train_data.json type: field_instruction: docstring field_output: summary format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: 2 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null flash_attention: false fp16: false fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: lesso09/0f79296c-b754-4989-b3bc-489ace006ef1 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 25 micro_batch_size: 2 mlflow_experiment_name: /tmp/124bc05ddbf5ee81_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 5fe9995d-0a95-46fa-b89c-25f97cbb6eb6 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 5fe9995d-0a95-46fa-b89c-25f97cbb6eb6 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # 0f79296c-b754-4989-b3bc-489ace006ef1 This model is a fine-tuned version of [unsloth/llama-2-7b-chat](https://huggingface.co/unsloth/llama-2-7b-chat) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 25 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 0.0 \| 0.0000 \| 1 \| nan \| \| 0.0 \| 0.0001 \| 5 \| nan \| \| 0.0 \| 0.0002 \| 10 \| nan \| \| 0.0 \| 0.0003 \| 15 \| nan \| \| 0.0 \| 0.0003 \| 20 \| nan \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
CharlesLi/mistral_cot_simplest_code_math_4_3_epoch_full	CharlesLi	2025-01-21T11:50:33Z	5	0	transformers	[ "transformers", "tensorboard", "safetensors", "mistral", "text-generation", "alignment-handbook", "trl", "sft", "generated_from_trainer", "conversational", "dataset:generator", "base_model:mistralai/Mistral-7B-Instruct-v0.1", "base_model:finetune:mistralai/Mistral-7B-Instruct-v0.1", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2025-01-21T11:28:42Z	--- library_name: transformers license: apache-2.0 base_model: mistralai/Mistral-7B-Instruct-v0.1 tags: - alignment-handbook - trl - sft - generated_from_trainer - trl - sft - generated_from_trainer datasets: - generator model-index: - name: mistral_cot_simplest_code_math_4_3_epoch_full results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # mistral_cot_simplest_code_math_4_3_epoch_full This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1) on the generator dataset. It achieves the following results on the evaluation set: - Loss: 0.6232 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - distributed_type: multi-GPU - num_devices: 4 - gradient_accumulation_steps: 2 - total_train_batch_size: 32 - total_eval_batch_size: 16 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 3 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 0.4526 \| 1.9802 \| 100 \| 0.5809 \| ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.1+cu121 - Datasets 3.0.0 - Tokenizers 0.19.1
nhung03/5048b92e-4369-4158-938b-4347f8451cde	nhung03	2025-01-21T11:50:31Z	6	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:defog/sqlcoder-7b-2", "base_model:adapter:defog/sqlcoder-7b-2", "license:cc-by-sa-4.0", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-21T11:35:38Z	--- library_name: peft license: cc-by-sa-4.0 base_model: defog/sqlcoder-7b-2 tags: - axolotl - generated_from_trainer model-index: - name: 5048b92e-4369-4158-938b-4347f8451cde results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: defog/sqlcoder-7b-2 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - fdd56d09ce656747_train_data.json ds_type: json format: custom path: /workspace/input_data/fdd56d09ce656747_train_data.json type: field_instruction: INSTRUCTION field_output: RESPONSE format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: nhung03/5048b92e-4369-4158-938b-4347f8451cde hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/fdd56d09ce656747_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 special_tokens: pad_token: </s> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: fecef9ac-e0fb-4174-87a6-ec0f3fcd1777 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: fecef9ac-e0fb-4174-87a6-ec0f3fcd1777 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details><br> # 5048b92e-4369-4158-938b-4347f8451cde This model is a fine-tuned version of [defog/sqlcoder-7b-2](https://huggingface.co/defog/sqlcoder-7b-2) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.5537 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 0.5927 \| 0.1960 \| 200 \| 0.5537 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
gavrilstep/02378d6a-b7cf-4b37-9aa8-c35ba4ba1172	gavrilstep	2025-01-21T11:49:53Z	10	0	peft	[ "peft", "safetensors", "gemma", "axolotl", "generated_from_trainer", "base_model:unsloth/gemma-2b-it", "base_model:adapter:unsloth/gemma-2b-it", "license:apache-2.0", "4-bit", "bitsandbytes", "region:us" ]	null	2025-01-21T11:44:12Z	--- library_name: peft license: apache-2.0 base_model: unsloth/gemma-2b-it tags: - axolotl - generated_from_trainer model-index: - name: 02378d6a-b7cf-4b37-9aa8-c35ba4ba1172 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/gemma-2b-it bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 54704e0639ee0f16_train_data.json ds_type: json format: custom path: /workspace/input_data/54704e0639ee0f16_train_data.json type: field_input: statement field_instruction: queries field_output: paraphrased_statement format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: null eval_max_new_tokens: 256 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: false hub_model_id: gavrilstep/02378d6a-b7cf-4b37-9aa8-c35ba4ba1172 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: true load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 75GiB max_steps: 40 micro_batch_size: 2 mlflow_experiment_name: /tmp/54704e0639ee0f16_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 273f8157-2d8b-40fb-adae-f4a501d93f8b wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 273f8157-2d8b-40fb-adae-f4a501d93f8b warmup_steps: 10 weight_decay: 0.01 xformers_attention: true ``` </details><br> # 02378d6a-b7cf-4b37-9aa8-c35ba4ba1172 This model is a fine-tuned version of [unsloth/gemma-2b-it](https://huggingface.co/unsloth/gemma-2b-it) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.5929 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 40 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| No log \| 0.0014 \| 1 \| 3.4282 \| \| 3.3332 \| 0.0068 \| 5 \| 2.8551 \| \| 2.3572 \| 0.0136 \| 10 \| 2.0829 \| \| 1.8508 \| 0.0205 \| 15 \| 1.8183 \| \| 1.8325 \| 0.0273 \| 20 \| 1.6728 \| \| 1.773 \| 0.0341 \| 25 \| 1.6280 \| \| 1.6409 \| 0.0409 \| 30 \| 1.6051 \| \| 1.7932 \| 0.0478 \| 35 \| 1.5948 \| \| 1.5856 \| 0.0546 \| 40 \| 1.5929 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
ClarenceDan/b6422ae3-6e75-4f8a-9f23-67f0c343008d	ClarenceDan	2025-01-21T11:49:03Z	8	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:oopsung/llama2-7b-n-ox-test-v1", "base_model:adapter:oopsung/llama2-7b-n-ox-test-v1", "region:us" ]	null	2025-01-21T11:43:00Z	--- library_name: peft base_model: oopsung/llama2-7b-n-ox-test-v1 tags: - axolotl - generated_from_trainer model-index: - name: b6422ae3-6e75-4f8a-9f23-67f0c343008d results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: oopsung/llama2-7b-n-ox-test-v1 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - dddb0489dc663e1a_train_data.json ds_type: json format: custom path: /workspace/input_data/dddb0489dc663e1a_train_data.json type: field_input: Context field_instruction: Question field_output: Answers format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: ClarenceDan/b6422ae3-6e75-4f8a-9f23-67f0c343008d hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/dddb0489dc663e1a_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: bbd202cf-ffeb-42f5-82b2-0c60d893aeab wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: bbd202cf-ffeb-42f5-82b2-0c60d893aeab warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # b6422ae3-6e75-4f8a-9f23-67f0c343008d This model is a fine-tuned version of [oopsung/llama2-7b-n-ox-test-v1](https://huggingface.co/oopsung/llama2-7b-n-ox-test-v1) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 0.0 \| 0.0003 \| 1 \| nan \| \| 0.0 \| 0.0008 \| 3 \| nan \| \| 0.0 \| 0.0017 \| 6 \| nan \| \| 0.0 \| 0.0025 \| 9 \| nan \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

nhoxinh/56074fa1-1876-44f5-9e04-4019f008f055

nhoxinh

2025-01-21T12:55:18Z

6

0

peft

[ "peft", "safetensors", "mistral", "axolotl", "generated_from_trainer", "base_model:unsloth/zephyr-sft", "base_model:adapter:unsloth/zephyr-sft", "license:apache-2.0", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-21T11:44:17Z

--- library_name: peft license: apache-2.0 base_model: unsloth/zephyr-sft tags: - axolotl - generated_from_trainer model-index: - name: 56074fa1-1876-44f5-9e04-4019f008f055 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/zephyr-sft bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 6bb273fb8d3c0253_train_data.json ds_type: json format: custom path: /workspace/input_data/6bb273fb8d3c0253_train_data.json type: field_input: condition field_instruction: drugName field_output: review format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: nhoxinh/56074fa1-1876-44f5-9e04-4019f008f055 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/6bb273fb8d3c0253_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: f44a8599-bd2c-4b24-9468-fb17670debf8 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: f44a8599-bd2c-4b24-9468-fb17670debf8 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details> # 56074fa1-1876-44f5-9e04-4019f008f055 This model is a fine-tuned version of [unsloth/zephyr-sft](https://huggingface.co/unsloth/zephyr-sft) on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.0659 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 7.8806 | 0.0078 | 200 | 2.0659 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

Best000/601e1c9e-6e78-4c6c-83a7-ce96943576bf

Best000

2025-01-21T12:55:06Z

11

0

peft

[ "peft", "safetensors", "falcon", "axolotl", "generated_from_trainer", "custom_code", "base_model:fxmarty/really-tiny-falcon-testing", "base_model:adapter:fxmarty/really-tiny-falcon-testing", "license:mit", "region:us" ]

null

2025-01-21T12:54:41Z

--- library_name: peft license: mit base_model: fxmarty/really-tiny-falcon-testing tags: - axolotl - generated_from_trainer model-index: - name: 601e1c9e-6e78-4c6c-83a7-ce96943576bf results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: fxmarty/really-tiny-falcon-testing bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 4214a6acaa4ea6d5_train_data.json ds_type: json format: custom path: /workspace/input_data/4214a6acaa4ea6d5_train_data.json type: field_input: tags field_instruction: sentences field_output: NER_TAGS format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: Best000/601e1c9e-6e78-4c6c-83a7-ce96943576bf hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/4214a6acaa4ea6d5_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 7c1cea2e-e61e-4570-af77-6f76e74a258b wandb_project: Birthday-SN56-16-Gradients-On-Demand wandb_run: your_name wandb_runid: 7c1cea2e-e61e-4570-af77-6f76e74a258b warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # 601e1c9e-6e78-4c6c-83a7-ce96943576bf This model is a fine-tuned version of [fxmarty/really-tiny-falcon-testing](https://huggingface.co/fxmarty/really-tiny-falcon-testing) on the None dataset. It achieves the following results on the evaluation set: - Loss: 10.8839 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 43.6855 | 0.0009 | 1 | 10.9245 | | 43.7175 | 0.0028 | 3 | 10.9243 | | 43.7176 | 0.0056 | 6 | 10.9227 | | 43.6932 | 0.0084 | 9 | 10.8839 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

sergioalves/05618dee-ab92-4757-af73-12793dbaba30

sergioalves

2025-01-21T12:55:00Z

6

0

peft

[ "peft", "safetensors", "phi3", "axolotl", "generated_from_trainer", "custom_code", "base_model:microsoft/Phi-3-mini-128k-instruct", "base_model:adapter:microsoft/Phi-3-mini-128k-instruct", "license:mit", "region:us" ]

null

2025-01-21T12:44:20Z

--- library_name: peft license: mit base_model: microsoft/Phi-3-mini-128k-instruct tags: - axolotl - generated_from_trainer model-index: - name: 05618dee-ab92-4757-af73-12793dbaba30 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: microsoft/Phi-3-mini-128k-instruct bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 2285406178062357_train_data.json ds_type: json format: custom path: /workspace/input_data/2285406178062357_train_data.json type: field_input: code_before field_instruction: func_before field_output: code_after format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: 1 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: false hub_model_id: sergioalves/05618dee-ab92-4757-af73-12793dbaba30 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0001 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 75GiB max_steps: 30 micro_batch_size: 2 mlflow_experiment_name: /tmp/2285406178062357_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_hf output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: ad2f2b3d-aa0d-468c-9405-73b96cd163da wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: ad2f2b3d-aa0d-468c-9405-73b96cd163da warmup_steps: 10 weight_decay: 0.01 xformers_attention: true ``` </details> # 05618dee-ab92-4757-af73-12793dbaba30 This model is a fine-tuned version of [microsoft/Phi-3-mini-128k-instruct](https://huggingface.co/microsoft/Phi-3-mini-128k-instruct) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.7229 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0001 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_HF with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 30 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.0020 | 1 | 0.7530 | | 2.7448 | 0.0101 | 5 | 0.7507 | | 3.0068 | 0.0202 | 10 | 0.7387 | | 2.7597 | 0.0302 | 15 | 0.7309 | | 2.8839 | 0.0403 | 20 | 0.7269 | | 2.7014 | 0.0504 | 25 | 0.7234 | | 2.6363 | 0.0605 | 30 | 0.7229 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

havinash-ai/5a51f800-f03b-497d-9dc7-c04b99c41fb6

havinash-ai

2025-01-21T12:54:31Z

6

0

peft

[ "peft", "safetensors", "mistral", "axolotl", "generated_from_trainer", "base_model:Artples/L-MChat-7b", "base_model:adapter:Artples/L-MChat-7b", "license:apache-2.0", "region:us" ]

null

2025-01-21T12:53:16Z

--- library_name: peft license: apache-2.0 base_model: Artples/L-MChat-7b tags: - axolotl - generated_from_trainer model-index: - name: 5a51f800-f03b-497d-9dc7-c04b99c41fb6 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: Artples/L-MChat-7b bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - df03514e65800f80_train_data.json ds_type: json format: custom path: /workspace/input_data/df03514e65800f80_train_data.json type: field_instruction: input field_output: response format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: havinash-ai/5a51f800-f03b-497d-9dc7-c04b99c41fb6 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/df03514e65800f80_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 special_tokens: pad_token: <|end_of_turn|> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: e3508d62-5471-4cdf-8dba-5844f441931a wandb_project: Mine-SN56-2-Gradients-On-Demand wandb_run: your_name wandb_runid: e3508d62-5471-4cdf-8dba-5844f441931a warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # 5a51f800-f03b-497d-9dc7-c04b99c41fb6 This model is a fine-tuned version of [Artples/L-MChat-7b](https://huggingface.co/Artples/L-MChat-7b) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.0 | 0.0011 | 1 | nan | | 0.0 | 0.0034 | 3 | nan | | 0.0 | 0.0068 | 6 | nan | | 0.0 | 0.0101 | 9 | nan | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

Best000/1220e340-6dd5-449f-955a-5c7b981b876f

Best000

2025-01-21T12:54:14Z

6

0

peft

[ "peft", "safetensors", "gemma2", "axolotl", "generated_from_trainer", "base_model:UCLA-AGI/Gemma-2-9B-It-SPPO-Iter2", "base_model:adapter:UCLA-AGI/Gemma-2-9B-It-SPPO-Iter2", "license:gemma", "region:us" ]

null

2025-01-21T11:50:56Z

--- library_name: peft license: gemma base_model: UCLA-AGI/Gemma-2-9B-It-SPPO-Iter2 tags: - axolotl - generated_from_trainer model-index: - name: 1220e340-6dd5-449f-955a-5c7b981b876f results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: UCLA-AGI/Gemma-2-9B-It-SPPO-Iter2 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 7152f650ecb2903c_train_data.json ds_type: json format: custom path: /workspace/input_data/7152f650ecb2903c_train_data.json type: field_instruction: pattern field_output: sentence format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: Best000/1220e340-6dd5-449f-955a-5c7b981b876f hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/7152f650ecb2903c_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 2f783681-0954-497d-858e-f6a9740d789d wandb_project: Birthday-SN56-16-Gradients-On-Demand wandb_run: your_name wandb_runid: 2f783681-0954-497d-858e-f6a9740d789d warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # 1220e340-6dd5-449f-955a-5c7b981b876f This model is a fine-tuned version of [UCLA-AGI/Gemma-2-9B-It-SPPO-Iter2](https://huggingface.co/UCLA-AGI/Gemma-2-9B-It-SPPO-Iter2) on the None dataset. It achieves the following results on the evaluation set: - Loss: 3.5726 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 6.1394 | 0.0000 | 1 | 5.6277 | | 5.728 | 0.0001 | 3 | 5.5548 | | 5.1083 | 0.0001 | 6 | 4.6567 | | 3.2958 | 0.0002 | 9 | 3.5726 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

nhung03/e06908a5-3e83-40a2-971b-3893a66fe938

nhung03

2025-01-21T12:53:53Z

6

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:JackFram/llama-160m", "base_model:adapter:JackFram/llama-160m", "license:apache-2.0", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-21T12:48:12Z

--- library_name: peft license: apache-2.0 base_model: JackFram/llama-160m tags: - axolotl - generated_from_trainer model-index: - name: e06908a5-3e83-40a2-971b-3893a66fe938 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: JackFram/llama-160m bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - a75236d5c65ead30_train_data.json ds_type: json format: custom path: /workspace/input_data/a75236d5c65ead30_train_data.json type: field_input: scene_setting field_instruction: user_setting field_output: assistant_setting format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: nhung03/e06908a5-3e83-40a2-971b-3893a66fe938 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/a75236d5c65ead30_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 special_tokens: pad_token: </s> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: a26c3dbd-260b-429a-b4e4-cbf7b2da5f3d wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: a26c3dbd-260b-429a-b4e4-cbf7b2da5f3d warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details> # e06908a5-3e83-40a2-971b-3893a66fe938 This model is a fine-tuned version of [JackFram/llama-160m](https://huggingface.co/JackFram/llama-160m) on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.5639 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 2.404 | 0.0427 | 200 | 2.5639 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

Best000/7cc54379-cd55-4a1a-a934-592749a9aa76

Best000

2025-01-21T12:53:40Z

6

0

peft

[ "peft", "safetensors", "gemma2", "axolotl", "generated_from_trainer", "base_model:unsloth/gemma-2-2b-it", "base_model:adapter:unsloth/gemma-2-2b-it", "license:gemma", "region:us" ]

null

2025-01-21T12:52:58Z

--- library_name: peft license: gemma base_model: unsloth/gemma-2-2b-it tags: - axolotl - generated_from_trainer model-index: - name: 7cc54379-cd55-4a1a-a934-592749a9aa76 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/gemma-2-2b-it bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - ddbeadb543cf2f4e_train_data.json ds_type: json format: custom path: /workspace/input_data/ddbeadb543cf2f4e_train_data.json type: field_instruction: instruction field_output: output format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: Best000/7cc54379-cd55-4a1a-a934-592749a9aa76 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/ddbeadb543cf2f4e_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 42dfa003-a971-4f6d-a499-5d2f92d18baa wandb_project: Birthday-SN56-15-Gradients-On-Demand wandb_run: your_name wandb_runid: 42dfa003-a971-4f6d-a499-5d2f92d18baa warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # 7cc54379-cd55-4a1a-a934-592749a9aa76 This model is a fine-tuned version of [unsloth/gemma-2-2b-it](https://huggingface.co/unsloth/gemma-2-2b-it) on the None dataset. It achieves the following results on the evaluation set: - Loss: 3.4881 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 4.4439 | 0.0092 | 1 | 4.2637 | | 3.8856 | 0.0277 | 3 | 4.2370 | | 3.7924 | 0.0554 | 6 | 3.9160 | | 3.1065 | 0.0831 | 9 | 3.4881 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

thdihan/gemma-2b-finetuned-psych8k-1k

thdihan

2025-01-21T12:51:49Z

38

0

transformers

[ "transformers", "safetensors", "gemma", "text-generation", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2025-01-21T12:44:34Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

nhunglaaaaaaa/f773374e-60ef-4fe9-b325-4ce2a455347b

nhunglaaaaaaa

2025-01-21T12:51:49Z

6

0

peft

[ "peft", "safetensors", "gemma2", "axolotl", "generated_from_trainer", "base_model:unsloth/gemma-2-9b-it", "base_model:adapter:unsloth/gemma-2-9b-it", "license:gemma", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-21T12:16:05Z

--- library_name: peft license: gemma base_model: unsloth/gemma-2-9b-it tags: - axolotl - generated_from_trainer model-index: - name: f773374e-60ef-4fe9-b325-4ce2a455347b results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/gemma-2-9b-it bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - baac717caf978860_train_data.json ds_type: json format: custom path: /workspace/input_data/baac717caf978860_train_data.json type: field_input: chosen-r field_instruction: source field_output: chosen-refined format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: nhunglaaaaaaa/f773374e-60ef-4fe9-b325-4ce2a455347b hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/baac717caf978860_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 15392e77-9853-4e00-86aa-ecd75e9c25d7 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 15392e77-9853-4e00-86aa-ecd75e9c25d7 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details> # f773374e-60ef-4fe9-b325-4ce2a455347b This model is a fine-tuned version of [unsloth/gemma-2-9b-it](https://huggingface.co/unsloth/gemma-2-9b-it) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.8181 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.8422 | 0.0687 | 200 | 0.8181 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

great0001/40731a2d-6e66-4847-9aad-f6c99c65c3c0

great0001

2025-01-21T12:50:20Z

6

0

peft

[ "peft", "safetensors", "gemma2", "axolotl", "generated_from_trainer", "base_model:unsloth/gemma-2-2b-it", "base_model:adapter:unsloth/gemma-2-2b-it", "license:gemma", "region:us" ]

null

2025-01-21T12:48:40Z

--- library_name: peft license: gemma base_model: unsloth/gemma-2-2b-it tags: - axolotl - generated_from_trainer model-index: - name: 40731a2d-6e66-4847-9aad-f6c99c65c3c0 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/gemma-2-2b-it bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - ddbeadb543cf2f4e_train_data.json ds_type: json format: custom path: /workspace/input_data/ddbeadb543cf2f4e_train_data.json type: field_instruction: instruction field_output: output format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: great0001/40731a2d-6e66-4847-9aad-f6c99c65c3c0 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/ddbeadb543cf2f4e_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 42dfa003-a971-4f6d-a499-5d2f92d18baa wandb_project: Birthday-SN56-14-Gradients-On-Demand wandb_run: your_name wandb_runid: 42dfa003-a971-4f6d-a499-5d2f92d18baa warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # 40731a2d-6e66-4847-9aad-f6c99c65c3c0 This model is a fine-tuned version of [unsloth/gemma-2-2b-it](https://huggingface.co/unsloth/gemma-2-2b-it) on the None dataset. It achieves the following results on the evaluation set: - Loss: 3.4869 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 4.4439 | 0.0092 | 1 | 4.2637 | | 3.8892 | 0.0277 | 3 | 4.2397 | | 3.797 | 0.0554 | 6 | 3.9266 | | 3.1095 | 0.0831 | 9 | 3.4869 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

MayBashendy/ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k8_task7_organization

MayBashendy

2025-01-21T12:48:54Z

5

0

transformers

[ "transformers", "safetensors", "bert", "text-classification", "generated_from_trainer", "base_model:aubmindlab/bert-base-arabertv02", "base_model:finetune:aubmindlab/bert-base-arabertv02", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-classification

2025-01-21T12:44:58Z

--- library_name: transformers base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k8_task7_organization results: [] ---  # ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k8_task7_organization This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.9402 - Qwk: 0.2460 - Mse: 0.9402 - Rmse: 0.9697 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 100 ### Training results | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse | Rmse | |:-------------:|:-------:|:----:|:---------------:|:-------:|:------:|:------:| | No log | 0.1053 | 2 | 2.4641 | -0.0568 | 2.4641 | 1.5697 | | No log | 0.2105 | 4 | 1.2791 | 0.1882 | 1.2791 | 1.1310 | | No log | 0.3158 | 6 | 1.0031 | -0.0550 | 1.0031 | 1.0015 | | No log | 0.4211 | 8 | 1.1737 | -0.1355 | 1.1737 | 1.0834 | | No log | 0.5263 | 10 | 1.2532 | -0.1993 | 1.2532 | 1.1195 | | No log | 0.6316 | 12 | 0.8472 | 0.0 | 0.8472 | 0.9204 | | No log | 0.7368 | 14 | 0.6607 | 0.1232 | 0.6607 | 0.8128 | | No log | 0.8421 | 16 | 0.6433 | 0.2676 | 0.6433 | 0.8021 | | No log | 0.9474 | 18 | 0.7040 | 0.3019 | 0.7040 | 0.8391 | | No log | 1.0526 | 20 | 0.7188 | 0.3019 | 0.7188 | 0.8478 | | No log | 1.1579 | 22 | 0.6808 | 0.2676 | 0.6808 | 0.8251 | | No log | 1.2632 | 24 | 0.6844 | 0.2676 | 0.6844 | 0.8273 | | No log | 1.3684 | 26 | 0.6940 | 0.2676 | 0.6940 | 0.8331 | | No log | 1.4737 | 28 | 0.7603 | 0.3125 | 0.7603 | 0.8720 | | No log | 1.5789 | 30 | 0.8185 | 0.1660 | 0.8185 | 0.9047 | | No log | 1.6842 | 32 | 0.7336 | 0.2748 | 0.7336 | 0.8565 | | No log | 1.7895 | 34 | 0.8494 | 0.2358 | 0.8494 | 0.9217 | | No log | 1.8947 | 36 | 1.0127 | 0.1955 | 1.0127 | 1.0063 | | No log | 2.0 | 38 | 0.8270 | 0.1459 | 0.8270 | 0.9094 | | No log | 2.1053 | 40 | 0.7232 | 0.1277 | 0.7232 | 0.8504 | | No log | 2.2105 | 42 | 0.7874 | 0.2156 | 0.7874 | 0.8874 | | No log | 2.3158 | 44 | 0.7714 | 0.1365 | 0.7714 | 0.8783 | | No log | 2.4211 | 46 | 0.7528 | 0.0717 | 0.7528 | 0.8677 | | No log | 2.5263 | 48 | 0.8233 | 0.2407 | 0.8233 | 0.9073 | | No log | 2.6316 | 50 | 0.8316 | 0.2652 | 0.8316 | 0.9119 | | No log | 2.7368 | 52 | 0.7702 | 0.1863 | 0.7702 | 0.8776 | | No log | 2.8421 | 54 | 0.7735 | 0.2884 | 0.7735 | 0.8795 | | No log | 2.9474 | 56 | 0.7935 | 0.3238 | 0.7935 | 0.8908 | | No log | 3.0526 | 58 | 1.0933 | 0.1241 | 1.0933 | 1.0456 | | No log | 3.1579 | 60 | 1.2316 | 0.1839 | 1.2316 | 1.1098 | | No log | 3.2632 | 62 | 1.0365 | 0.2460 | 1.0365 | 1.0181 | | No log | 3.3684 | 64 | 0.9874 | 0.1692 | 0.9874 | 0.9937 | | No log | 3.4737 | 66 | 1.1110 | 0.2209 | 1.1110 | 1.0540 | | No log | 3.5789 | 68 | 1.4546 | 0.1067 | 1.4546 | 1.2061 | | No log | 3.6842 | 70 | 1.6366 | 0.1555 | 1.6366 | 1.2793 | | No log | 3.7895 | 72 | 1.3934 | 0.1093 | 1.3934 | 1.1804 | | No log | 3.8947 | 74 | 1.3039 | 0.1175 | 1.3039 | 1.1419 | | No log | 4.0 | 76 | 1.1431 | 0.1394 | 1.1431 | 1.0692 | | No log | 4.1053 | 78 | 1.1404 | 0.1976 | 1.1404 | 1.0679 | | No log | 4.2105 | 80 | 1.3409 | 0.1568 | 1.3409 | 1.1580 | | No log | 4.3158 | 82 | 1.1559 | 0.1618 | 1.1559 | 1.0751 | | No log | 4.4211 | 84 | 1.2002 | 0.1799 | 1.2002 | 1.0955 | | No log | 4.5263 | 86 | 1.5611 | 0.1169 | 1.5611 | 1.2495 | | No log | 4.6316 | 88 | 1.9707 | 0.0421 | 1.9707 | 1.4038 | | No log | 4.7368 | 90 | 1.9777 | 0.0421 | 1.9777 | 1.4063 | | No log | 4.8421 | 92 | 1.7506 | 0.0589 | 1.7506 | 1.3231 | | No log | 4.9474 | 94 | 1.5731 | 0.1195 | 1.5731 | 1.2542 | | No log | 5.0526 | 96 | 1.4243 | 0.1093 | 1.4243 | 1.1934 | | No log | 5.1579 | 98 | 1.3725 | 0.1093 | 1.3725 | 1.1716 | | No log | 5.2632 | 100 | 1.6731 | 0.0689 | 1.6731 | 1.2935 | | No log | 5.3684 | 102 | 1.6296 | 0.0300 | 1.6296 | 1.2766 | | No log | 5.4737 | 104 | 1.1849 | 0.1029 | 1.1849 | 1.0885 | | No log | 5.5789 | 106 | 0.9579 | 0.1661 | 0.9579 | 0.9787 | | No log | 5.6842 | 108 | 0.9987 | 0.1603 | 0.9987 | 0.9994 | | No log | 5.7895 | 110 | 1.2834 | 0.1458 | 1.2834 | 1.1329 | | No log | 5.8947 | 112 | 1.4733 | 0.0803 | 1.4733 | 1.2138 | | No log | 6.0 | 114 | 1.3218 | 0.1458 | 1.3218 | 1.1497 | | No log | 6.1053 | 116 | 0.9666 | 0.1651 | 0.9666 | 0.9832 | | No log | 6.2105 | 118 | 0.9062 | 0.2076 | 0.9062 | 0.9519 | | No log | 6.3158 | 120 | 1.0268 | 0.1210 | 1.0268 | 1.0133 | | No log | 6.4211 | 122 | 1.4521 | 0.0361 | 1.4521 | 1.2050 | | No log | 6.5263 | 124 | 1.8056 | 0.0350 | 1.8056 | 1.3437 | | No log | 6.6316 | 126 | 1.7978 | 0.0350 | 1.7978 | 1.3408 | | No log | 6.7368 | 128 | 1.5457 | 0.0447 | 1.5457 | 1.2433 | | No log | 6.8421 | 130 | 1.2205 | 0.1262 | 1.2205 | 1.1048 | | No log | 6.9474 | 132 | 1.1007 | 0.1356 | 1.1007 | 1.0491 | | No log | 7.0526 | 134 | 1.1800 | 0.1293 | 1.1800 | 1.0863 | | No log | 7.1579 | 136 | 1.3351 | 0.1174 | 1.3351 | 1.1555 | | No log | 7.2632 | 138 | 1.2657 | 0.1293 | 1.2657 | 1.1251 | | No log | 7.3684 | 140 | 1.2024 | 0.1293 | 1.2024 | 1.0965 | | No log | 7.4737 | 142 | 1.3602 | 0.1175 | 1.3602 | 1.1663 | | No log | 7.5789 | 144 | 1.5870 | 0.0283 | 1.5870 | 1.2598 | | No log | 7.6842 | 146 | 1.5829 | 0.0283 | 1.5829 | 1.2581 | | No log | 7.7895 | 148 | 1.3217 | 0.1175 | 1.3217 | 1.1497 | | No log | 7.8947 | 150 | 1.0634 | 0.2119 | 1.0634 | 1.0312 | | No log | 8.0 | 152 | 1.0604 | 0.1787 | 1.0604 | 1.0298 | | No log | 8.1053 | 154 | 1.1823 | 0.2412 | 1.1823 | 1.0873 | | No log | 8.2105 | 156 | 1.3899 | 0.0873 | 1.3899 | 1.1789 | | No log | 8.3158 | 158 | 1.3188 | 0.1464 | 1.3188 | 1.1484 | | No log | 8.4211 | 160 | 1.0921 | 0.1709 | 1.0921 | 1.0450 | | No log | 8.5263 | 162 | 0.9088 | 0.1777 | 0.9088 | 0.9533 | | No log | 8.6316 | 164 | 0.8664 | 0.2692 | 0.8664 | 0.9308 | | No log | 8.7368 | 166 | 0.9342 | 0.1955 | 0.9342 | 0.9665 | | No log | 8.8421 | 168 | 1.2602 | 0.1458 | 1.2602 | 1.1226 | | No log | 8.9474 | 170 | 1.4897 | 0.0745 | 1.4897 | 1.2205 | | No log | 9.0526 | 172 | 1.3828 | 0.0829 | 1.3828 | 1.1759 | | No log | 9.1579 | 174 | 1.0783 | 0.2782 | 1.0783 | 1.0384 | | No log | 9.2632 | 176 | 0.8226 | 0.2352 | 0.8226 | 0.9070 | | No log | 9.3684 | 178 | 0.7643 | 0.2407 | 0.7643 | 0.8743 | | No log | 9.4737 | 180 | 0.7740 | 0.2718 | 0.7740 | 0.8798 | | No log | 9.5789 | 182 | 0.9104 | 0.2000 | 0.9104 | 0.9541 | | No log | 9.6842 | 184 | 1.2011 | 0.2045 | 1.2011 | 1.0959 | | No log | 9.7895 | 186 | 1.3583 | 0.1427 | 1.3583 | 1.1655 | | No log | 9.8947 | 188 | 1.3863 | 0.1275 | 1.3863 | 1.1774 | | No log | 10.0 | 190 | 1.4604 | 0.1549 | 1.4604 | 1.2085 | | No log | 10.1053 | 192 | 1.2898 | 0.1638 | 1.2898 | 1.1357 | | No log | 10.2105 | 194 | 1.1966 | 0.1784 | 1.1966 | 1.0939 | | No log | 10.3158 | 196 | 1.1865 | 0.1784 | 1.1865 | 1.0893 | | No log | 10.4211 | 198 | 1.2104 | 0.1490 | 1.2104 | 1.1002 | | No log | 10.5263 | 200 | 1.2296 | 0.1458 | 1.2296 | 1.1089 | | No log | 10.6316 | 202 | 1.2308 | 0.1458 | 1.2308 | 1.1094 | | No log | 10.7368 | 204 | 1.1178 | 0.1626 | 1.1178 | 1.0573 | | No log | 10.8421 | 206 | 0.9721 | 0.1274 | 0.9721 | 0.9859 | | No log | 10.9474 | 208 | 0.9787 | 0.1557 | 0.9787 | 0.9893 | | No log | 11.0526 | 210 | 1.0491 | 0.0925 | 1.0491 | 1.0242 | | No log | 11.1579 | 212 | 1.2200 | 0.1943 | 1.2200 | 1.1046 | | No log | 11.2632 | 214 | 1.3621 | 0.1220 | 1.3621 | 1.1671 | | No log | 11.3684 | 216 | 1.2789 | 0.1427 | 1.2789 | 1.1309 | | No log | 11.4737 | 218 | 1.1262 | 0.2782 | 1.1262 | 1.0612 | | No log | 11.5789 | 220 | 1.0803 | 0.1787 | 1.0803 | 1.0394 | | No log | 11.6842 | 222 | 1.0540 | 0.1787 | 1.0540 | 1.0266 | | No log | 11.7895 | 224 | 1.1171 | 0.1949 | 1.1171 | 1.0569 | | No log | 11.8947 | 226 | 1.2800 | 0.0712 | 1.2800 | 1.1314 | | No log | 12.0 | 228 | 1.3595 | 0.0419 | 1.3595 | 1.1660 | | No log | 12.1053 | 230 | 1.3345 | 0.0694 | 1.3345 | 1.1552 | | No log | 12.2105 | 232 | 1.5379 | 0.0832 | 1.5379 | 1.2401 | | No log | 12.3158 | 234 | 1.7880 | 0.0932 | 1.7880 | 1.3372 | | No log | 12.4211 | 236 | 1.6579 | 0.1549 | 1.6579 | 1.2876 | | No log | 12.5263 | 238 | 1.3537 | 0.0952 | 1.3537 | 1.1635 | | No log | 12.6316 | 240 | 1.1170 | 0.0448 | 1.1170 | 1.0569 | | No log | 12.7368 | 242 | 1.0241 | 0.0448 | 1.0241 | 1.0120 | | No log | 12.8421 | 244 | 1.0171 | 0.0799 | 1.0171 | 1.0085 | | No log | 12.9474 | 246 | 1.1371 | 0.0585 | 1.1371 | 1.0663 | | No log | 13.0526 | 248 | 1.2053 | 0.1205 | 1.2053 | 1.0979 | | No log | 13.1579 | 250 | 1.1845 | 0.0538 | 1.1845 | 1.0884 | | No log | 13.2632 | 252 | 1.0946 | 0.0982 | 1.0946 | 1.0463 | | No log | 13.3684 | 254 | 1.1487 | 0.0982 | 1.1487 | 1.0718 | | No log | 13.4737 | 256 | 1.3419 | 0.0694 | 1.3419 | 1.1584 | | No log | 13.5789 | 258 | 1.5060 | 0.0086 | 1.5060 | 1.2272 | | No log | 13.6842 | 260 | 1.4753 | 0.0086 | 1.4753 | 1.2146 | | No log | 13.7895 | 262 | 1.2918 | 0.0459 | 1.2918 | 1.1366 | | No log | 13.8947 | 264 | 1.2588 | 0.0761 | 1.2588 | 1.1220 | | No log | 14.0 | 266 | 1.1447 | 0.1147 | 1.1447 | 1.0699 | | No log | 14.1053 | 268 | 1.0228 | 0.1385 | 1.0228 | 1.0114 | | No log | 14.2105 | 270 | 1.0093 | 0.1734 | 1.0093 | 1.0046 | | No log | 14.3158 | 272 | 1.1433 | 0.0561 | 1.1433 | 1.0692 | | No log | 14.4211 | 274 | 1.3866 | 0.0584 | 1.3866 | 1.1776 | | No log | 14.5263 | 276 | 1.5194 | 0.0465 | 1.5194 | 1.2326 | | No log | 14.6316 | 278 | 1.4404 | 0.0531 | 1.4404 | 1.2002 | | No log | 14.7368 | 280 | 1.3060 | 0.1458 | 1.3060 | 1.1428 | | No log | 14.8421 | 282 | 1.2034 | 0.0546 | 1.2034 | 1.0970 | | No log | 14.9474 | 284 | 1.1476 | 0.0315 | 1.1476 | 1.0712 | | No log | 15.0526 | 286 | 1.2144 | 0.1262 | 1.2144 | 1.1020 | | No log | 15.1579 | 288 | 1.3063 | 0.0648 | 1.3063 | 1.1429 | | No log | 15.2632 | 290 | 1.3645 | 0.0921 | 1.3645 | 1.1681 | | No log | 15.3684 | 292 | 1.2482 | 0.0921 | 1.2482 | 1.1172 | | No log | 15.4737 | 294 | 1.0915 | 0.2183 | 1.0915 | 1.0447 | | No log | 15.5789 | 296 | 1.0100 | 0.2032 | 1.0100 | 1.0050 | | No log | 15.6842 | 298 | 0.9617 | 0.1651 | 0.9617 | 0.9807 | | No log | 15.7895 | 300 | 0.9237 | 0.1822 | 0.9237 | 0.9611 | | No log | 15.8947 | 302 | 0.9719 | 0.1651 | 0.9719 | 0.9859 | | No log | 16.0 | 304 | 1.0726 | 0.1389 | 1.0726 | 1.0357 | | No log | 16.1053 | 306 | 1.2458 | 0.1490 | 1.2458 | 1.1162 | | No log | 16.2105 | 308 | 1.4795 | 0.0519 | 1.4795 | 1.2164 | | No log | 16.3158 | 310 | 1.4706 | 0.0519 | 1.4706 | 1.2127 | | No log | 16.4211 | 312 | 1.2663 | 0.1233 | 1.2663 | 1.1253 | | No log | 16.5263 | 314 | 1.0773 | 0.0569 | 1.0773 | 1.0379 | | No log | 16.6316 | 316 | 1.0396 | 0.0592 | 1.0396 | 1.0196 | | No log | 16.7368 | 318 | 1.0507 | 0.0894 | 1.0507 | 1.0251 | | No log | 16.8421 | 320 | 1.0997 | 0.1394 | 1.0997 | 1.0487 | | No log | 16.9474 | 322 | 1.1279 | 0.1635 | 1.1279 | 1.0620 | | No log | 17.0526 | 324 | 1.1312 | 0.1635 | 1.1312 | 1.0636 | | No log | 17.1579 | 326 | 1.0328 | 0.1463 | 1.0328 | 1.0163 | | No log | 17.2632 | 328 | 0.9286 | 0.1612 | 0.9286 | 0.9636 | | No log | 17.3684 | 330 | 0.9605 | 0.1612 | 0.9605 | 0.9800 | | No log | 17.4737 | 332 | 1.0802 | 0.2183 | 1.0802 | 1.0393 | | No log | 17.5789 | 334 | 1.2681 | 0.0921 | 1.2681 | 1.1261 | | No log | 17.6842 | 336 | 1.3526 | 0.0343 | 1.3526 | 1.1630 | | No log | 17.7895 | 338 | 1.3346 | 0.0898 | 1.3346 | 1.1553 | | No log | 17.8947 | 340 | 1.3625 | 0.0873 | 1.3625 | 1.1673 | | No log | 18.0 | 342 | 1.1606 | 0.1523 | 1.1606 | 1.0773 | | No log | 18.1053 | 344 | 0.9443 | 0.1803 | 0.9443 | 0.9717 | | No log | 18.2105 | 346 | 0.9077 | 0.2287 | 0.9077 | 0.9527 | | No log | 18.3158 | 348 | 0.9189 | 0.2000 | 0.9189 | 0.9586 | | No log | 18.4211 | 350 | 0.9441 | 0.2211 | 0.9441 | 0.9717 | | No log | 18.5263 | 352 | 0.9530 | 0.2211 | 0.9530 | 0.9762 | | No log | 18.6316 | 354 | 1.0559 | 0.2316 | 1.0559 | 1.0276 | | No log | 18.7368 | 356 | 1.1002 | 0.2552 | 1.1002 | 1.0489 | | No log | 18.8421 | 358 | 1.1299 | 0.1858 | 1.1299 | 1.0629 | | No log | 18.9474 | 360 | 1.1509 | 0.1821 | 1.1509 | 1.0728 | | No log | 19.0526 | 362 | 1.0969 | 0.1709 | 1.0969 | 1.0473 | | No log | 19.1579 | 364 | 1.0309 | 0.1869 | 1.0309 | 1.0153 | | No log | 19.2632 | 366 | 1.0453 | 0.1869 | 1.0453 | 1.0224 | | No log | 19.3684 | 368 | 1.0596 | 0.2032 | 1.0596 | 1.0294 | | No log | 19.4737 | 370 | 1.1637 | 0.1870 | 1.1637 | 1.0788 | | No log | 19.5789 | 372 | 1.2256 | 0.1205 | 1.2256 | 1.1070 | | No log | 19.6842 | 374 | 1.2246 | 0.1205 | 1.2246 | 1.1066 | | No log | 19.7895 | 376 | 1.1160 | 0.2183 | 1.1160 | 1.0564 | | No log | 19.8947 | 378 | 1.0576 | 0.1210 | 1.0576 | 1.0284 | | No log | 20.0 | 380 | 1.0879 | 0.1463 | 1.0879 | 1.0430 | | No log | 20.1053 | 382 | 1.1567 | 0.1463 | 1.1567 | 1.0755 | | No log | 20.2105 | 384 | 1.2232 | 0.1262 | 1.2232 | 1.1060 | | No log | 20.3158 | 386 | 1.2875 | 0.1233 | 1.2875 | 1.1347 | | No log | 20.4211 | 388 | 1.3831 | 0.0343 | 1.3831 | 1.1761 | | No log | 20.5263 | 390 | 1.4274 | 0.0708 | 1.4274 | 1.1947 | | No log | 20.6316 | 392 | 1.3132 | 0.1233 | 1.3132 | 1.1459 | | No log | 20.7368 | 394 | 1.1052 | 0.1747 | 1.1052 | 1.0513 | | No log | 20.8421 | 396 | 0.9038 | 0.1651 | 0.9038 | 0.9507 | | No log | 20.9474 | 398 | 0.8384 | 0.2632 | 0.8384 | 0.9157 | | No log | 21.0526 | 400 | 0.8279 | 0.2063 | 0.8279 | 0.9099 | | No log | 21.1579 | 402 | 0.8476 | 0.2297 | 0.8476 | 0.9206 | | No log | 21.2632 | 404 | 0.9798 | 0.0616 | 0.9798 | 0.9899 | | No log | 21.3684 | 406 | 1.2113 | 0.1591 | 1.2113 | 1.1006 | | No log | 21.4737 | 408 | 1.4117 | 0.1093 | 1.4117 | 1.1882 | | No log | 21.5789 | 410 | 1.5392 | 0.1285 | 1.5392 | 1.2407 | | No log | 21.6842 | 412 | 1.4635 | 0.0766 | 1.4635 | 1.2097 | | No log | 21.7895 | 414 | 1.1993 | 0.1324 | 1.1993 | 1.0951 | | No log | 21.8947 | 416 | 0.9784 | 0.0896 | 0.9784 | 0.9891 | | No log | 22.0 | 418 | 0.8859 | 0.0895 | 0.8859 | 0.9412 | | No log | 22.1053 | 420 | 0.8847 | 0.0895 | 0.8847 | 0.9406 | | No log | 22.2105 | 422 | 0.8522 | 0.2171 | 0.8522 | 0.9232 | | No log | 22.3158 | 424 | 0.8241 | 0.2171 | 0.8241 | 0.9078 | | No log | 22.4211 | 426 | 0.8996 | 0.1718 | 0.8996 | 0.9485 | | No log | 22.5263 | 428 | 1.0471 | 0.0896 | 1.0471 | 1.0233 | | No log | 22.6316 | 430 | 1.0850 | 0.0842 | 1.0850 | 1.0416 | | No log | 22.7368 | 432 | 1.0406 | 0.0896 | 1.0406 | 1.0201 | | No log | 22.8421 | 434 | 0.9429 | 0.1692 | 0.9429 | 0.9711 | | No log | 22.9474 | 436 | 0.8892 | 0.2632 | 0.8892 | 0.9430 | | No log | 23.0526 | 438 | 0.8751 | 0.2409 | 0.8751 | 0.9355 | | No log | 23.1579 | 440 | 0.8877 | 0.1914 | 0.8877 | 0.9422 | | No log | 23.2632 | 442 | 0.8993 | 0.1914 | 0.8993 | 0.9483 | | No log | 23.3684 | 444 | 0.9416 | 0.2000 | 0.9416 | 0.9703 | | No log | 23.4737 | 446 | 0.9549 | 0.1651 | 0.9549 | 0.9772 | | No log | 23.5789 | 448 | 0.8887 | 0.1962 | 0.8887 | 0.9427 | | No log | 23.6842 | 450 | 0.8707 | 0.2352 | 0.8707 | 0.9331 | | No log | 23.7895 | 452 | 0.9281 | 0.2142 | 0.9281 | 0.9634 | | No log | 23.8947 | 454 | 0.9651 | 0.2259 | 0.9651 | 0.9824 | | No log | 24.0 | 456 | 0.9547 | 0.2000 | 0.9547 | 0.9771 | | No log | 24.1053 | 458 | 0.9812 | 0.2259 | 0.9812 | 0.9905 | | No log | 24.2105 | 460 | 0.9499 | 0.2000 | 0.9499 | 0.9746 | | No log | 24.3158 | 462 | 0.9134 | 0.1734 | 0.9134 | 0.9557 | | No log | 24.4211 | 464 | 0.8957 | 0.1542 | 0.8957 | 0.9464 | | No log | 24.5263 | 466 | 0.9177 | 0.1501 | 0.9177 | 0.9580 | | No log | 24.6316 | 468 | 0.9123 | 0.1144 | 0.9123 | 0.9552 | | No log | 24.7368 | 470 | 0.9427 | 0.0803 | 0.9427 | 0.9709 | | No log | 24.8421 | 472 | 0.9644 | 0.1045 | 0.9644 | 0.9820 | | No log | 24.9474 | 474 | 0.9877 | 0.0953 | 0.9877 | 0.9938 | | No log | 25.0526 | 476 | 0.9548 | 0.0746 | 0.9548 | 0.9771 | | No log | 25.1579 | 478 | 0.8722 | 0.1962 | 0.8722 | 0.9339 | | No log | 25.2632 | 480 | 0.8807 | 0.1962 | 0.8807 | 0.9385 | | No log | 25.3684 | 482 | 0.9581 | 0.1642 | 0.9581 | 0.9788 | | No log | 25.4737 | 484 | 0.9240 | 0.1379 | 0.9240 | 0.9612 | | No log | 25.5789 | 486 | 0.8329 | 0.2883 | 0.8329 | 0.9126 | | No log | 25.6842 | 488 | 0.7711 | 0.3312 | 0.7711 | 0.8781 | | No log | 25.7895 | 490 | 0.7734 | 0.2883 | 0.7734 | 0.8794 | | No log | 25.8947 | 492 | 0.7991 | 0.3167 | 0.7991 | 0.8939 | | No log | 26.0 | 494 | 0.8618 | 0.3359 | 0.8618 | 0.9283 | | No log | 26.1053 | 496 | 0.8989 | 0.3231 | 0.8989 | 0.9481 | | No log | 26.2105 | 498 | 0.8341 | 0.3294 | 0.8341 | 0.9133 | | 0.2424 | 26.3158 | 500 | 0.7303 | 0.3099 | 0.7303 | 0.8546 | | 0.2424 | 26.4211 | 502 | 0.7038 | 0.2817 | 0.7038 | 0.8389 | | 0.2424 | 26.5263 | 504 | 0.7111 | 0.3099 | 0.7111 | 0.8433 | | 0.2424 | 26.6316 | 506 | 0.7457 | 0.3099 | 0.7457 | 0.8635 | | 0.2424 | 26.7368 | 508 | 0.8348 | 0.3359 | 0.8348 | 0.9137 | | 0.2424 | 26.8421 | 510 | 0.9436 | 0.2460 | 0.9436 | 0.9714 | | 0.2424 | 26.9474 | 512 | 1.0461 | 0.2141 | 1.0461 | 1.0228 | | 0.2424 | 27.0526 | 514 | 1.1003 | 0.1832 | 1.1003 | 1.0490 | | 0.2424 | 27.1579 | 516 | 1.0420 | 0.2227 | 1.0420 | 1.0208 | | 0.2424 | 27.2632 | 518 | 0.9402 | 0.2460 | 0.9402 | 0.9697 | ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.0+cu118 - Datasets 2.21.0 - Tokenizers 0.19.1

ClarenceDan/8500479a-7b5d-46f1-9208-c970e58819a2

ClarenceDan

2025-01-21T12:48:49Z

8

0

peft

[ "peft", "safetensors", "mistral", "axolotl", "generated_from_trainer", "base_model:teknium/OpenHermes-2.5-Mistral-7B", "base_model:adapter:teknium/OpenHermes-2.5-Mistral-7B", "license:apache-2.0", "region:us" ]

null

2025-01-21T12:39:14Z

--- library_name: peft license: apache-2.0 base_model: teknium/OpenHermes-2.5-Mistral-7B tags: - axolotl - generated_from_trainer model-index: - name: 8500479a-7b5d-46f1-9208-c970e58819a2 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: teknium/OpenHermes-2.5-Mistral-7B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 1b5fe4b652f9222e_train_data.json ds_type: json format: custom path: /workspace/input_data/1b5fe4b652f9222e_train_data.json type: field_instruction: instruction field_output: output format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: ClarenceDan/8500479a-7b5d-46f1-9208-c970e58819a2 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/1b5fe4b652f9222e_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 special_tokens: pad_token: <|im_end|> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 857fa1e7-73d3-440e-a388-76fc6a5b2495 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 857fa1e7-73d3-440e-a388-76fc6a5b2495 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # 8500479a-7b5d-46f1-9208-c970e58819a2 This model is a fine-tuned version of [teknium/OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.0 | 0.0002 | 1 | nan | | 0.0 | 0.0006 | 3 | nan | | 0.0 | 0.0012 | 6 | nan | | 0.0 | 0.0018 | 9 | nan | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

ClarenceDan/8d4acffc-77b2-45e7-b2db-56fd18aa1ade

ClarenceDan

2025-01-21T12:48:20Z

6

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:heegyu/WizardVicuna-open-llama-3b-v2", "base_model:adapter:heegyu/WizardVicuna-open-llama-3b-v2", "license:apache-2.0", "region:us" ]

null

2025-01-21T12:33:03Z

--- library_name: peft license: apache-2.0 base_model: heegyu/WizardVicuna-open-llama-3b-v2 tags: - axolotl - generated_from_trainer model-index: - name: 8d4acffc-77b2-45e7-b2db-56fd18aa1ade results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: heegyu/WizardVicuna-open-llama-3b-v2 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 0eba3e80d15355a6_train_data.json ds_type: json format: custom path: /workspace/input_data/0eba3e80d15355a6_train_data.json type: field_input: input field_instruction: instruction field_output: accepted format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: ClarenceDan/8d4acffc-77b2-45e7-b2db-56fd18aa1ade hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/0eba3e80d15355a6_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 special_tokens: pad_token: </s> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 84f8a085-50df-4e7c-9e21-f8d55ac51824 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 84f8a085-50df-4e7c-9e21-f8d55ac51824 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # 8d4acffc-77b2-45e7-b2db-56fd18aa1ade This model is a fine-tuned version of [heegyu/WizardVicuna-open-llama-3b-v2](https://huggingface.co/heegyu/WizardVicuna-open-llama-3b-v2) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.7682 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.904 | 0.0002 | 1 | 0.7949 | | 0.7439 | 0.0005 | 3 | 0.7944 | | 0.7234 | 0.0009 | 6 | 0.7882 | | 0.7158 | 0.0014 | 9 | 0.7682 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

Manas32122/whisper_merged_new

Manas32122

2025-01-21T12:48:01Z

6

0

transformers

[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]

null

2025-01-21T12:42:08Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

ryusangwon/ko_en_qe_ppo_0.9_1e-6

ryusangwon

2025-01-21T12:47:12Z

5

0

transformers

[ "transformers", "safetensors", "m2m_100", "text2text-generation", "trl", "reinforcement-learning", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]

reinforcement-learning

2025-01-21T12:43:47Z

--- license: apache-2.0 tags: - trl - transformers - reinforcement-learning --- # TRL Model This is a [TRL language model](https://github.com/huggingface/trl) that has been fine-tuned with reinforcement learning to guide the model outputs according to a value, function, or human feedback. The model can be used for text generation. ## Usage To use this model for inference, first install the TRL library: ```bash python -m pip install trl ``` You can then generate text as follows: ```python from transformers import pipeline generator = pipeline("text-generation", model="ryusangwon//tmp/tmpbj0hofua/ryusangwon/ko_en_qe_ppo_0.9_1e-6") outputs = generator("Hello, my llama is cute") ``` If you want to use the model for training or to obtain the outputs from the value head, load the model as follows: ```python from transformers import AutoTokenizer from trl import AutoModelForCausalLMWithValueHead tokenizer = AutoTokenizer.from_pretrained("ryusangwon//tmp/tmpbj0hofua/ryusangwon/ko_en_qe_ppo_0.9_1e-6") model = AutoModelForCausalLMWithValueHead.from_pretrained("ryusangwon//tmp/tmpbj0hofua/ryusangwon/ko_en_qe_ppo_0.9_1e-6") inputs = tokenizer("Hello, my llama is cute", return_tensors="pt") outputs = model(**inputs, labels=inputs["input_ids"]) ```

nhung03/ba28972f-a518-42ba-8b7e-9a76b2c77273

nhung03

2025-01-21T12:45:44Z

6

0

peft

[ "peft", "safetensors", "gemma2", "axolotl", "generated_from_trainer", "base_model:unsloth/gemma-2-2b-it", "base_model:adapter:unsloth/gemma-2-2b-it", "license:gemma", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-21T12:39:33Z

--- library_name: peft license: gemma base_model: unsloth/gemma-2-2b-it tags: - axolotl - generated_from_trainer model-index: - name: ba28972f-a518-42ba-8b7e-9a76b2c77273 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/gemma-2-2b-it bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - ddbeadb543cf2f4e_train_data.json ds_type: json format: custom path: /workspace/input_data/ddbeadb543cf2f4e_train_data.json type: field_instruction: instruction field_output: output format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: nhung03/ba28972f-a518-42ba-8b7e-9a76b2c77273 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/ddbeadb543cf2f4e_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 42dfa003-a971-4f6d-a499-5d2f92d18baa wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 42dfa003-a971-4f6d-a499-5d2f92d18baa warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details> # ba28972f-a518-42ba-8b7e-9a76b2c77273 This model is a fine-tuned version of [unsloth/gemma-2-2b-it](https://huggingface.co/unsloth/gemma-2-2b-it) on the None dataset. It achieves the following results on the evaluation set: - Loss: 3.1683 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 109 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 4.3957 | 0.9977 | 108 | 3.1566 | | 5.1265 | 1.0069 | 109 | 3.1683 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

havinash-ai/785c4b87-9684-48b5-abf4-93a55427d946

havinash-ai

2025-01-21T12:44:54Z

7

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:lmsys/vicuna-7b-v1.5", "base_model:adapter:lmsys/vicuna-7b-v1.5", "license:llama2", "region:us" ]

null

2025-01-21T12:39:58Z

--- library_name: peft license: llama2 base_model: lmsys/vicuna-7b-v1.5 tags: - axolotl - generated_from_trainer model-index: - name: 785c4b87-9684-48b5-abf4-93a55427d946 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: lmsys/vicuna-7b-v1.5 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 87ecfef6de5c4ae6_train_data.json ds_type: json format: custom path: /workspace/input_data/87ecfef6de5c4ae6_train_data.json type: field_input: input field_instruction: instruction field_output: output format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: havinash-ai/785c4b87-9684-48b5-abf4-93a55427d946 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/87ecfef6de5c4ae6_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 08949a5f-0b74-4dce-877f-c6b2eba8999f wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 08949a5f-0b74-4dce-877f-c6b2eba8999f warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # 785c4b87-9684-48b5-abf4-93a55427d946 This model is a fine-tuned version of [lmsys/vicuna-7b-v1.5](https://huggingface.co/lmsys/vicuna-7b-v1.5) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.0688 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 1.3716 | 0.0002 | 1 | 1.5921 | | 1.9101 | 0.0006 | 3 | 1.5875 | | 1.8918 | 0.0011 | 6 | 1.4767 | | 1.4858 | 0.0017 | 9 | 1.0688 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

Alecardo/Ricardo-Fort-678f930b9d5393dc7e1a8ca9

Alecardo

2025-01-21T12:44:49Z

110

0

diffusers

[ "diffusers", "flux", "lora", "replicate", "text-to-image", "en", "base_model:black-forest-labs/FLUX.1-dev", "base_model:adapter:black-forest-labs/FLUX.1-dev", "license:other", "region:us" ]

text-to-image

2025-01-21T12:29:02Z

--- license: other license_name: flux-1-dev-non-commercial-license license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md language: - en tags: - flux - diffusers - lora - replicate base_model: "black-forest-labs/FLUX.1-dev" pipeline_tag: text-to-image # widget: # - text: >- # prompt # output: # url: https://... instance_prompt: ricmaiamefort --- # Ricardo Fort 678F930B9D5393Dc7E1A8Ca9 <Gallery /> Trained on Replicate using: https://replicate.com/ostris/flux-dev-lora-trainer/train ## Trigger words You should use `ricmaiamefort` to trigger the image generation. ## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers) ```py from diffusers import AutoPipelineForText2Image import torch pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.float16).to('cuda') pipeline.load_lora_weights('Alecardo/Ricardo-Fort-678f930b9d5393dc7e1a8ca9', weight_name='lora.safetensors') image = pipeline('your prompt').images[0] ``` For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)

tarabukinivan/88f3286d-c2d1-4d09-9e58-f6eb64e10140

tarabukinivan

2025-01-21T12:44:37Z

6

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:TinyLlama/TinyLlama-1.1B-Chat-v1.0", "base_model:adapter:TinyLlama/TinyLlama-1.1B-Chat-v1.0", "license:apache-2.0", "region:us" ]

null

2025-01-21T12:30:38Z

--- library_name: peft license: apache-2.0 base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0 tags: - axolotl - generated_from_trainer model-index: - name: 88f3286d-c2d1-4d09-9e58-f6eb64e10140 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 9c321e8cf88f16f0_train_data.json ds_type: json format: custom path: /workspace/input_data/9c321e8cf88f16f0_train_data.json type: field_input: input field_instruction: instruction field_output: output format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: null eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: false hub_model_id: tarabukinivan/88f3286d-c2d1-4d09-9e58-f6eb64e10140 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 75GiB max_steps: 30 micro_batch_size: 2 mlflow_experiment_name: /tmp/9c321e8cf88f16f0_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 1a9527a4-dbed-4d09-b3dc-303d2f7479cd wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 1a9527a4-dbed-4d09-b3dc-303d2f7479cd warmup_steps: 10 weight_decay: 0.01 xformers_attention: true ``` </details> # 88f3286d-c2d1-4d09-9e58-f6eb64e10140 This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.4001 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 30 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.0002 | 1 | 1.6017 | | 1.4713 | 0.0008 | 5 | 1.5789 | | 1.4853 | 0.0016 | 10 | 1.4876 | | 1.3148 | 0.0024 | 15 | 1.4307 | | 1.3637 | 0.0033 | 20 | 1.4131 | | 1.5555 | 0.0041 | 25 | 1.4021 | | 1.3646 | 0.0049 | 30 | 1.4001 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

MayBashendy/ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k7_task7_organization

MayBashendy

2025-01-21T12:44:35Z

5

0

transformers

[ "transformers", "safetensors", "bert", "text-classification", "generated_from_trainer", "base_model:aubmindlab/bert-base-arabertv02", "base_model:finetune:aubmindlab/bert-base-arabertv02", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-classification

2025-01-21T12:40:22Z

--- library_name: transformers base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k7_task7_organization results: [] ---  # ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k7_task7_organization This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.7187 - Qwk: 0.3341 - Mse: 0.7187 - Rmse: 0.8478 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 100 ### Training results | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse | Rmse | |:-------------:|:-------:|:----:|:---------------:|:-------:|:------:|:------:| | No log | 0.1176 | 2 | 2.5757 | -0.0924 | 2.5757 | 1.6049 | | No log | 0.2353 | 4 | 1.3587 | 0.0994 | 1.3587 | 1.1656 | | No log | 0.3529 | 6 | 1.1844 | -0.2292 | 1.1844 | 1.0883 | | No log | 0.4706 | 8 | 0.9977 | -0.0426 | 0.9977 | 0.9988 | | No log | 0.5882 | 10 | 0.9364 | 0.1007 | 0.9364 | 0.9677 | | No log | 0.7059 | 12 | 0.8715 | 0.1648 | 0.8715 | 0.9335 | | No log | 0.8235 | 14 | 0.8307 | -0.0103 | 0.8307 | 0.9114 | | No log | 0.9412 | 16 | 0.8269 | -0.0483 | 0.8269 | 0.9094 | | No log | 1.0588 | 18 | 0.9257 | 0.0495 | 0.9257 | 0.9621 | | No log | 1.1765 | 20 | 0.9539 | -0.0700 | 0.9539 | 0.9767 | | No log | 1.2941 | 22 | 0.8720 | 0.0027 | 0.8720 | 0.9338 | | No log | 1.4118 | 24 | 0.8314 | 0.0 | 0.8314 | 0.9118 | | No log | 1.5294 | 26 | 0.8248 | 0.0 | 0.8248 | 0.9082 | | No log | 1.6471 | 28 | 0.8307 | 0.1236 | 0.8307 | 0.9114 | | No log | 1.7647 | 30 | 0.7798 | 0.0 | 0.7798 | 0.8831 | | No log | 1.8824 | 32 | 0.7549 | 0.0 | 0.7549 | 0.8688 | | No log | 2.0 | 34 | 0.7683 | 0.0 | 0.7683 | 0.8765 | | No log | 2.1176 | 36 | 0.8061 | 0.0481 | 0.8061 | 0.8978 | | No log | 2.2353 | 38 | 0.9177 | 0.2526 | 0.9177 | 0.9579 | | No log | 2.3529 | 40 | 0.9241 | 0.3444 | 0.9241 | 0.9613 | | No log | 2.4706 | 42 | 0.8782 | 0.3173 | 0.8782 | 0.9371 | | No log | 2.5882 | 44 | 0.7992 | 0.1372 | 0.7992 | 0.8940 | | No log | 2.7059 | 46 | 0.7477 | 0.0937 | 0.7477 | 0.8647 | | No log | 2.8235 | 48 | 0.7057 | 0.0428 | 0.7057 | 0.8400 | | No log | 2.9412 | 50 | 0.7487 | 0.3243 | 0.7487 | 0.8653 | | No log | 3.0588 | 52 | 0.8144 | 0.1648 | 0.8144 | 0.9025 | | No log | 3.1765 | 54 | 0.8334 | 0.1699 | 0.8334 | 0.9129 | | No log | 3.2941 | 56 | 0.8386 | 0.1094 | 0.8386 | 0.9157 | | No log | 3.4118 | 58 | 0.8747 | -0.0027 | 0.8747 | 0.9353 | | No log | 3.5294 | 60 | 0.9345 | -0.1275 | 0.9345 | 0.9667 | | No log | 3.6471 | 62 | 0.8860 | -0.0444 | 0.8860 | 0.9413 | | No log | 3.7647 | 64 | 0.7937 | 0.0 | 0.7937 | 0.8909 | | No log | 3.8824 | 66 | 0.7158 | 0.0889 | 0.7158 | 0.8460 | | No log | 4.0 | 68 | 0.7009 | 0.0393 | 0.7009 | 0.8372 | | No log | 4.1176 | 70 | 0.7320 | 0.0359 | 0.7320 | 0.8556 | | No log | 4.2353 | 72 | 0.7952 | -0.0051 | 0.7952 | 0.8917 | | No log | 4.3529 | 74 | 0.8104 | 0.0265 | 0.8104 | 0.9002 | | No log | 4.4706 | 76 | 0.8378 | 0.0927 | 0.8378 | 0.9153 | | No log | 4.5882 | 78 | 0.8915 | 0.0966 | 0.8915 | 0.9442 | | No log | 4.7059 | 80 | 0.9184 | 0.1699 | 0.9184 | 0.9583 | | No log | 4.8235 | 82 | 0.9273 | 0.2171 | 0.9273 | 0.9630 | | No log | 4.9412 | 84 | 0.9053 | 0.1972 | 0.9053 | 0.9515 | | No log | 5.0588 | 86 | 0.9132 | 0.0245 | 0.9132 | 0.9556 | | No log | 5.1765 | 88 | 0.8966 | 0.0968 | 0.8966 | 0.9469 | | No log | 5.2941 | 90 | 0.9317 | 0.1303 | 0.9317 | 0.9652 | | No log | 5.4118 | 92 | 0.9620 | 0.2063 | 0.9620 | 0.9808 | | No log | 5.5294 | 94 | 0.9345 | 0.2632 | 0.9345 | 0.9667 | | No log | 5.6471 | 96 | 0.8433 | 0.3238 | 0.8433 | 0.9183 | | No log | 5.7647 | 98 | 0.8240 | 0.2007 | 0.8240 | 0.9078 | | No log | 5.8824 | 100 | 0.8275 | -0.0070 | 0.8275 | 0.9096 | | No log | 6.0 | 102 | 0.8620 | 0.0362 | 0.8620 | 0.9284 | | No log | 6.1176 | 104 | 0.8316 | 0.0697 | 0.8316 | 0.9119 | | No log | 6.2353 | 106 | 0.8263 | 0.2345 | 0.8263 | 0.9090 | | No log | 6.3529 | 108 | 0.8755 | 0.2604 | 0.8755 | 0.9357 | | No log | 6.4706 | 110 | 0.8392 | 0.2171 | 0.8392 | 0.9161 | | No log | 6.5882 | 112 | 0.8389 | 0.2063 | 0.8389 | 0.9159 | | No log | 6.7059 | 114 | 0.8407 | 0.0 | 0.8407 | 0.9169 | | No log | 6.8235 | 116 | 0.7234 | 0.1829 | 0.7234 | 0.8505 | | No log | 6.9412 | 118 | 0.6556 | 0.2819 | 0.6556 | 0.8097 | | No log | 7.0588 | 120 | 0.6881 | 0.3950 | 0.6881 | 0.8295 | | No log | 7.1765 | 122 | 0.8563 | 0.3499 | 0.8563 | 0.9254 | | No log | 7.2941 | 124 | 0.9866 | 0.2921 | 0.9866 | 0.9933 | | No log | 7.4118 | 126 | 0.9981 | 0.2464 | 0.9981 | 0.9991 | | No log | 7.5294 | 128 | 1.0640 | 0.1354 | 1.0640 | 1.0315 | | No log | 7.6471 | 130 | 1.5347 | 0.1007 | 1.5347 | 1.2388 | | No log | 7.7647 | 132 | 1.5733 | 0.0790 | 1.5733 | 1.2543 | | No log | 7.8824 | 134 | 1.2396 | 0.1332 | 1.2396 | 1.1134 | | No log | 8.0 | 136 | 0.9817 | 0.0801 | 0.9817 | 0.9908 | | No log | 8.1176 | 138 | 0.9364 | 0.2832 | 0.9364 | 0.9677 | | No log | 8.2353 | 140 | 0.8926 | 0.3183 | 0.8926 | 0.9448 | | No log | 8.3529 | 142 | 0.8516 | 0.3221 | 0.8516 | 0.9228 | | No log | 8.4706 | 144 | 0.8222 | 0.2414 | 0.8222 | 0.9068 | | No log | 8.5882 | 146 | 0.8010 | 0.2813 | 0.8010 | 0.8950 | | No log | 8.7059 | 148 | 0.7963 | 0.2784 | 0.7963 | 0.8924 | | No log | 8.8235 | 150 | 0.8079 | 0.3372 | 0.8079 | 0.8989 | | No log | 8.9412 | 152 | 0.8412 | 0.3699 | 0.8412 | 0.9171 | | No log | 9.0588 | 154 | 0.7978 | 0.3637 | 0.7978 | 0.8932 | | No log | 9.1765 | 156 | 0.7614 | 0.3099 | 0.7614 | 0.8726 | | No log | 9.2941 | 158 | 0.7245 | 0.1699 | 0.7245 | 0.8512 | | No log | 9.4118 | 160 | 0.7185 | 0.1807 | 0.7185 | 0.8477 | | No log | 9.5294 | 162 | 0.7381 | 0.1268 | 0.7381 | 0.8592 | | No log | 9.6471 | 164 | 0.7843 | 0.2171 | 0.7843 | 0.8856 | | No log | 9.7647 | 166 | 0.8367 | 0.2328 | 0.8367 | 0.9147 | | No log | 9.8824 | 168 | 0.8363 | 0.1995 | 0.8363 | 0.9145 | | No log | 10.0 | 170 | 0.8047 | 0.2589 | 0.8047 | 0.8970 | | No log | 10.1176 | 172 | 0.8180 | 0.0652 | 0.8180 | 0.9044 | | No log | 10.2353 | 174 | 0.8233 | 0.0652 | 0.8233 | 0.9074 | | No log | 10.3529 | 176 | 0.7997 | 0.2027 | 0.7997 | 0.8942 | | No log | 10.4706 | 178 | 0.8016 | 0.3372 | 0.8016 | 0.8953 | | No log | 10.5882 | 180 | 0.7845 | 0.3819 | 0.7845 | 0.8857 | | No log | 10.7059 | 182 | 0.6968 | 0.3032 | 0.6968 | 0.8347 | | No log | 10.8235 | 184 | 0.6736 | 0.3425 | 0.6736 | 0.8208 | | No log | 10.9412 | 186 | 0.7071 | 0.3127 | 0.7071 | 0.8409 | | No log | 11.0588 | 188 | 0.7794 | 0.3372 | 0.7794 | 0.8828 | | No log | 11.1765 | 190 | 0.8896 | 0.3782 | 0.8896 | 0.9432 | | No log | 11.2941 | 192 | 0.8603 | 0.4251 | 0.8603 | 0.9275 | | No log | 11.4118 | 194 | 0.7622 | 0.2784 | 0.7622 | 0.8730 | | No log | 11.5294 | 196 | 0.7462 | 0.2683 | 0.7462 | 0.8638 | | No log | 11.6471 | 198 | 0.7544 | 0.2683 | 0.7544 | 0.8686 | | No log | 11.7647 | 200 | 0.7524 | 0.2319 | 0.7524 | 0.8674 | | No log | 11.8824 | 202 | 0.8204 | 0.4089 | 0.8204 | 0.9058 | | No log | 12.0 | 204 | 0.8332 | 0.3590 | 0.8332 | 0.9128 | | No log | 12.1176 | 206 | 0.8053 | 0.1264 | 0.8053 | 0.8974 | | No log | 12.2353 | 208 | 0.8030 | 0.2043 | 0.8030 | 0.8961 | | No log | 12.3529 | 210 | 0.8035 | 0.1051 | 0.8035 | 0.8964 | | No log | 12.4706 | 212 | 0.7790 | 0.2158 | 0.7790 | 0.8826 | | No log | 12.5882 | 214 | 0.7441 | 0.2319 | 0.7441 | 0.8626 | | No log | 12.7059 | 216 | 0.7776 | 0.3894 | 0.7776 | 0.8818 | | No log | 12.8235 | 218 | 0.7996 | 0.4014 | 0.7996 | 0.8942 | | No log | 12.9412 | 220 | 0.7439 | 0.4052 | 0.7439 | 0.8625 | | No log | 13.0588 | 222 | 0.7111 | 0.3471 | 0.7111 | 0.8433 | | No log | 13.1765 | 224 | 0.6985 | 0.3341 | 0.6985 | 0.8357 | | No log | 13.2941 | 226 | 0.7284 | 0.3545 | 0.7284 | 0.8535 | | No log | 13.4118 | 228 | 0.8148 | 0.3372 | 0.8148 | 0.9027 | | No log | 13.5294 | 230 | 0.9035 | 0.3519 | 0.9035 | 0.9505 | | No log | 13.6471 | 232 | 0.8974 | 0.2754 | 0.8974 | 0.9473 | | No log | 13.7647 | 234 | 0.8592 | 0.2847 | 0.8592 | 0.9269 | | No log | 13.8824 | 236 | 0.8327 | 0.3737 | 0.8327 | 0.9125 | | No log | 14.0 | 238 | 0.8219 | 0.3918 | 0.8219 | 0.9066 | | No log | 14.1176 | 240 | 0.7738 | 0.3032 | 0.7738 | 0.8797 | | No log | 14.2353 | 242 | 0.7455 | 0.3712 | 0.7455 | 0.8634 | | No log | 14.3529 | 244 | 0.7875 | 0.3302 | 0.7875 | 0.8874 | | No log | 14.4706 | 246 | 0.8593 | 0.3869 | 0.8593 | 0.9270 | | No log | 14.5882 | 248 | 0.9272 | 0.3825 | 0.9272 | 0.9629 | | No log | 14.7059 | 250 | 0.8637 | 0.3538 | 0.8637 | 0.9294 | | No log | 14.8235 | 252 | 0.7736 | 0.3894 | 0.7736 | 0.8795 | | No log | 14.9412 | 254 | 0.7035 | 0.3594 | 0.7035 | 0.8387 | | No log | 15.0588 | 256 | 0.6780 | 0.4001 | 0.6780 | 0.8234 | | No log | 15.1765 | 258 | 0.6778 | 0.4291 | 0.6778 | 0.8233 | | No log | 15.2941 | 260 | 0.6805 | 0.4001 | 0.6805 | 0.8249 | | No log | 15.4118 | 262 | 0.7081 | 0.4158 | 0.7081 | 0.8415 | | No log | 15.5294 | 264 | 0.7434 | 0.3868 | 0.7434 | 0.8622 | | No log | 15.6471 | 266 | 0.8074 | 0.3746 | 0.8074 | 0.8986 | | No log | 15.7647 | 268 | 0.8077 | 0.3699 | 0.8077 | 0.8987 | | No log | 15.8824 | 270 | 0.8001 | 0.4014 | 0.8001 | 0.8945 | | No log | 16.0 | 272 | 0.7637 | 0.3770 | 0.7637 | 0.8739 | | No log | 16.1176 | 274 | 0.7132 | 0.3518 | 0.7132 | 0.8445 | | No log | 16.2353 | 276 | 0.7116 | 0.3238 | 0.7116 | 0.8436 | | No log | 16.3529 | 278 | 0.7267 | 0.3238 | 0.7267 | 0.8525 | | No log | 16.4706 | 280 | 0.7366 | 0.3099 | 0.7366 | 0.8583 | | No log | 16.5882 | 282 | 0.7447 | 0.3712 | 0.7447 | 0.8630 | | No log | 16.7059 | 284 | 0.7767 | 0.3712 | 0.7767 | 0.8813 | | No log | 16.8235 | 286 | 0.8651 | 0.3675 | 0.8651 | 0.9301 | | No log | 16.9412 | 288 | 0.8676 | 0.3606 | 0.8676 | 0.9315 | | No log | 17.0588 | 290 | 0.8148 | 0.3819 | 0.8148 | 0.9027 | | No log | 17.1765 | 292 | 0.8137 | 0.3637 | 0.8137 | 0.9021 | | No log | 17.2941 | 294 | 0.7826 | 0.3737 | 0.7826 | 0.8847 | | No log | 17.4118 | 296 | 0.7781 | 0.2847 | 0.7781 | 0.8821 | | No log | 17.5294 | 298 | 0.7970 | 0.2319 | 0.7970 | 0.8927 | | No log | 17.6471 | 300 | 0.8518 | 0.1918 | 0.8518 | 0.9230 | | No log | 17.7647 | 302 | 0.9251 | 0.1866 | 0.9251 | 0.9618 | | No log | 17.8824 | 304 | 0.9407 | 0.1866 | 0.9407 | 0.9699 | | No log | 18.0 | 306 | 0.8990 | 0.1918 | 0.8990 | 0.9482 | | No log | 18.1176 | 308 | 0.8168 | 0.2847 | 0.8168 | 0.9038 | | No log | 18.2353 | 310 | 0.7374 | 0.3919 | 0.7374 | 0.8587 | | No log | 18.3529 | 312 | 0.7206 | 0.3919 | 0.7206 | 0.8489 | | No log | 18.4706 | 314 | 0.7563 | 0.4684 | 0.7563 | 0.8696 | | No log | 18.5882 | 316 | 0.7759 | 0.4684 | 0.7759 | 0.8809 | | No log | 18.7059 | 318 | 0.7929 | 0.4684 | 0.7929 | 0.8905 | | No log | 18.8235 | 320 | 0.7879 | 0.3572 | 0.7879 | 0.8876 | | No log | 18.9412 | 322 | 0.7850 | 0.3572 | 0.7850 | 0.8860 | | No log | 19.0588 | 324 | 0.7964 | 0.4270 | 0.7964 | 0.8924 | | No log | 19.1765 | 326 | 0.8016 | 0.3996 | 0.8016 | 0.8953 | | No log | 19.2941 | 328 | 0.8174 | 0.3590 | 0.8174 | 0.9041 | | No log | 19.4118 | 330 | 0.7876 | 0.4247 | 0.7876 | 0.8874 | | No log | 19.5294 | 332 | 0.8040 | 0.3770 | 0.8040 | 0.8966 | | No log | 19.6471 | 334 | 0.7851 | 0.3770 | 0.7851 | 0.8861 | | No log | 19.7647 | 336 | 0.7121 | 0.4592 | 0.7121 | 0.8439 | | No log | 19.8824 | 338 | 0.6655 | 0.2819 | 0.6655 | 0.8158 | | No log | 20.0 | 340 | 0.6671 | 0.2819 | 0.6671 | 0.8167 | | No log | 20.1176 | 342 | 0.6997 | 0.3782 | 0.6997 | 0.8365 | | No log | 20.2353 | 344 | 0.7596 | 0.4076 | 0.7596 | 0.8715 | | No log | 20.3529 | 346 | 0.8016 | 0.3372 | 0.8016 | 0.8953 | | No log | 20.4706 | 348 | 0.8415 | 0.3372 | 0.8415 | 0.9173 | | No log | 20.5882 | 350 | 0.8207 | 0.3519 | 0.8207 | 0.9059 | | No log | 20.7059 | 352 | 0.8039 | 0.3519 | 0.8039 | 0.8966 | | No log | 20.8235 | 354 | 0.7602 | 0.3544 | 0.7602 | 0.8719 | | No log | 20.9412 | 356 | 0.7442 | 0.4190 | 0.7442 | 0.8626 | | No log | 21.0588 | 358 | 0.7384 | 0.4167 | 0.7384 | 0.8593 | | No log | 21.1765 | 360 | 0.7168 | 0.4479 | 0.7168 | 0.8467 | | No log | 21.2941 | 362 | 0.7191 | 0.4479 | 0.7191 | 0.8480 | | No log | 21.4118 | 364 | 0.7384 | 0.4576 | 0.7384 | 0.8593 | | No log | 21.5294 | 366 | 0.7592 | 0.4167 | 0.7592 | 0.8713 | | No log | 21.6471 | 368 | 0.7503 | 0.4576 | 0.7503 | 0.8662 | | No log | 21.7647 | 370 | 0.7116 | 0.4576 | 0.7116 | 0.8436 | | No log | 21.8824 | 372 | 0.6735 | 0.3755 | 0.6735 | 0.8207 | | No log | 22.0 | 374 | 0.6573 | 0.3123 | 0.6573 | 0.8107 | | No log | 22.1176 | 376 | 0.6633 | 0.3976 | 0.6633 | 0.8144 | | No log | 22.2353 | 378 | 0.7019 | 0.4753 | 0.7019 | 0.8378 | | No log | 22.3529 | 380 | 0.7806 | 0.4167 | 0.7806 | 0.8835 | | No log | 22.4706 | 382 | 0.9162 | 0.3913 | 0.9162 | 0.9572 | | No log | 22.5882 | 384 | 0.9838 | 0.3128 | 0.9838 | 0.9919 | | No log | 22.7059 | 386 | 0.9348 | 0.3012 | 0.9348 | 0.9668 | | No log | 22.8235 | 388 | 0.8444 | 0.2883 | 0.8444 | 0.9189 | | No log | 22.9412 | 390 | 0.7869 | 0.2145 | 0.7869 | 0.8871 | | No log | 23.0588 | 392 | 0.7715 | 0.1863 | 0.7715 | 0.8783 | | No log | 23.1765 | 394 | 0.7584 | 0.2206 | 0.7584 | 0.8709 | | No log | 23.2941 | 396 | 0.7867 | 0.3020 | 0.7867 | 0.8870 | | No log | 23.4118 | 398 | 0.8898 | 0.3972 | 0.8898 | 0.9433 | | No log | 23.5294 | 400 | 0.9919 | 0.3473 | 0.9919 | 0.9960 | | No log | 23.6471 | 402 | 1.0320 | 0.2781 | 1.0320 | 1.0159 | | No log | 23.7647 | 404 | 1.0073 | 0.2387 | 1.0073 | 1.0036 | | No log | 23.8824 | 406 | 0.9323 | 0.3060 | 0.9323 | 0.9656 | | No log | 24.0 | 408 | 0.9247 | 0.2532 | 0.9247 | 0.9616 | | No log | 24.1176 | 410 | 0.9271 | 0.2838 | 0.9271 | 0.9629 | | No log | 24.2353 | 412 | 0.9283 | 0.3106 | 0.9283 | 0.9635 | | No log | 24.3529 | 414 | 0.9059 | 0.2813 | 0.9059 | 0.9518 | | No log | 24.4706 | 416 | 0.9277 | 0.3344 | 0.9277 | 0.9632 | | No log | 24.5882 | 418 | 0.9200 | 0.3918 | 0.9200 | 0.9591 | | No log | 24.7059 | 420 | 0.8989 | 0.3991 | 0.8989 | 0.9481 | | No log | 24.8235 | 422 | 0.8600 | 0.3894 | 0.8600 | 0.9274 | | No log | 24.9412 | 424 | 0.8149 | 0.4392 | 0.8149 | 0.9027 | | No log | 25.0588 | 426 | 0.7731 | 0.4243 | 0.7731 | 0.8793 | | No log | 25.1765 | 428 | 0.7624 | 0.3976 | 0.7624 | 0.8731 | | No log | 25.2941 | 430 | 0.7936 | 0.4243 | 0.7936 | 0.8909 | | No log | 25.4118 | 432 | 0.8036 | 0.3622 | 0.8036 | 0.8964 | | No log | 25.5294 | 434 | 0.8172 | 0.3224 | 0.8172 | 0.9040 | | No log | 25.6471 | 436 | 0.7936 | 0.3224 | 0.7936 | 0.8908 | | No log | 25.7647 | 438 | 0.7833 | 0.3498 | 0.7833 | 0.8851 | | No log | 25.8824 | 440 | 0.7797 | 0.4663 | 0.7797 | 0.8830 | | No log | 26.0 | 442 | 0.8268 | 0.3843 | 0.8268 | 0.9093 | | No log | 26.1176 | 444 | 0.8310 | 0.3843 | 0.8310 | 0.9116 | | No log | 26.2353 | 446 | 0.7962 | 0.4753 | 0.7962 | 0.8923 | | No log | 26.3529 | 448 | 0.7693 | 0.4753 | 0.7693 | 0.8771 | | No log | 26.4706 | 450 | 0.7771 | 0.4479 | 0.7771 | 0.8816 | | No log | 26.5882 | 452 | 0.8233 | 0.4052 | 0.8233 | 0.9074 | | No log | 26.7059 | 454 | 0.8303 | 0.3637 | 0.8303 | 0.9112 | | No log | 26.8235 | 456 | 0.7922 | 0.4479 | 0.7922 | 0.8901 | | No log | 26.9412 | 458 | 0.7423 | 0.3622 | 0.7423 | 0.8616 | | No log | 27.0588 | 460 | 0.7357 | 0.2981 | 0.7357 | 0.8577 | | No log | 27.1765 | 462 | 0.7645 | 0.3594 | 0.7645 | 0.8744 | | No log | 27.2941 | 464 | 0.8427 | 0.3972 | 0.8427 | 0.9180 | | No log | 27.4118 | 466 | 0.9057 | 0.3675 | 0.9057 | 0.9517 | | No log | 27.5294 | 468 | 0.9028 | 0.3675 | 0.9028 | 0.9501 | | No log | 27.6471 | 470 | 0.8554 | 0.3894 | 0.8554 | 0.9249 | | No log | 27.7647 | 472 | 0.8067 | 0.4247 | 0.8067 | 0.8982 | | No log | 27.8824 | 474 | 0.8030 | 0.4247 | 0.8030 | 0.8961 | | No log | 28.0 | 476 | 0.7978 | 0.4247 | 0.7978 | 0.8932 | | No log | 28.1176 | 478 | 0.8022 | 0.4052 | 0.8022 | 0.8957 | | No log | 28.2353 | 480 | 0.8193 | 0.3972 | 0.8193 | 0.9051 | | No log | 28.3529 | 482 | 0.8121 | 0.4479 | 0.8121 | 0.9012 | | No log | 28.4706 | 484 | 0.8070 | 0.4479 | 0.8070 | 0.8984 | | No log | 28.5882 | 486 | 0.7850 | 0.4219 | 0.7850 | 0.8860 | | No log | 28.7059 | 488 | 0.7744 | 0.4502 | 0.7744 | 0.8800 | | No log | 28.8235 | 490 | 0.7633 | 0.4502 | 0.7633 | 0.8737 | | No log | 28.9412 | 492 | 0.7753 | 0.4774 | 0.7753 | 0.8805 | | No log | 29.0588 | 494 | 0.8084 | 0.4076 | 0.8084 | 0.8991 | | No log | 29.1765 | 496 | 0.8381 | 0.4330 | 0.8381 | 0.9155 | | No log | 29.2941 | 498 | 0.8586 | 0.4409 | 0.8586 | 0.9266 | | 0.3134 | 29.4118 | 500 | 0.8490 | 0.4224 | 0.8490 | 0.9214 | | 0.3134 | 29.5294 | 502 | 0.8322 | 0.3972 | 0.8322 | 0.9123 | | 0.3134 | 29.6471 | 504 | 0.7995 | 0.4479 | 0.7995 | 0.8942 | | 0.3134 | 29.7647 | 506 | 0.7992 | 0.4845 | 0.7992 | 0.8940 | | 0.3134 | 29.8824 | 508 | 0.8180 | 0.4414 | 0.8180 | 0.9044 | | 0.3134 | 30.0 | 510 | 0.8297 | 0.4414 | 0.8297 | 0.9109 | | 0.3134 | 30.1176 | 512 | 0.8231 | 0.3649 | 0.8231 | 0.9072 | | 0.3134 | 30.2353 | 514 | 0.8386 | 0.3737 | 0.8386 | 0.9158 | | 0.3134 | 30.3529 | 516 | 0.8447 | 0.3737 | 0.8447 | 0.9191 | | 0.3134 | 30.4706 | 518 | 0.8344 | 0.3471 | 0.8344 | 0.9135 | | 0.3134 | 30.5882 | 520 | 0.7964 | 0.4330 | 0.7964 | 0.8924 | | 0.3134 | 30.7059 | 522 | 0.7581 | 0.3782 | 0.7581 | 0.8707 | | 0.3134 | 30.8235 | 524 | 0.7483 | 0.3782 | 0.7483 | 0.8651 | | 0.3134 | 30.9412 | 526 | 0.7706 | 0.4414 | 0.7706 | 0.8779 | | 0.3134 | 31.0588 | 528 | 0.8221 | 0.3972 | 0.8221 | 0.9067 | | 0.3134 | 31.1765 | 530 | 0.8522 | 0.3972 | 0.8522 | 0.9231 | | 0.3134 | 31.2941 | 532 | 0.8332 | 0.4392 | 0.8332 | 0.9128 | | 0.3134 | 31.4118 | 534 | 0.7971 | 0.4219 | 0.7971 | 0.8928 | | 0.3134 | 31.5294 | 536 | 0.7689 | 0.3950 | 0.7689 | 0.8768 | | 0.3134 | 31.6471 | 538 | 0.7299 | 0.3976 | 0.7299 | 0.8543 | | 0.3134 | 31.7647 | 540 | 0.7136 | 0.3976 | 0.7136 | 0.8447 | | 0.3134 | 31.8824 | 542 | 0.7187 | 0.3341 | 0.7187 | 0.8478 | ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.0+cu118 - Datasets 2.21.0 - Tokenizers 0.19.1

kostiantynk1205/2dd26e7f-9d61-472b-959a-69573b14c63f

kostiantynk1205

2025-01-21T12:44:12Z

6

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:openlm-research/open_llama_3b", "base_model:adapter:openlm-research/open_llama_3b", "license:apache-2.0", "region:us" ]

null

2025-01-21T12:32:47Z

--- library_name: peft license: apache-2.0 base_model: openlm-research/open_llama_3b tags: - axolotl - generated_from_trainer model-index: - name: 2dd26e7f-9d61-472b-959a-69573b14c63f results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: openlm-research/open_llama_3b bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 88305afcc505bc32_train_data.json ds_type: json format: custom path: /workspace/input_data/88305afcc505bc32_train_data.json type: field_input: context field_instruction: question field_output: answer format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: kostiantynk1205/2dd26e7f-9d61-472b-959a-69573b14c63f hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/88305afcc505bc32_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 special_tokens: pad_token: </s> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 3c103d36-11cb-4530-bc3a-9d1b166132e7 wandb_project: Birthday-SN56-6-Gradients-On-Demand wandb_run: your_name wandb_runid: 3c103d36-11cb-4530-bc3a-9d1b166132e7 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # 2dd26e7f-9d61-472b-959a-69573b14c63f This model is a fine-tuned version of [openlm-research/open_llama_3b](https://huggingface.co/openlm-research/open_llama_3b) on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.0551 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 2.8039 | 0.0001 | 1 | 3.1952 | | 4.0102 | 0.0002 | 3 | 3.1831 | | 2.2182 | 0.0004 | 6 | 2.9729 | | 1.3269 | 0.0006 | 9 | 2.0551 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

thalllsssss/0f03e4cb-bf5c-44f3-871d-201307142e82

thalllsssss

2025-01-21T12:42:58Z

7

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:TinyLlama/TinyLlama-1.1B-Chat-v1.0", "base_model:adapter:TinyLlama/TinyLlama-1.1B-Chat-v1.0", "license:apache-2.0", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-21T12:30:41Z

--- library_name: peft license: apache-2.0 base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0 tags: - axolotl - generated_from_trainer model-index: - name: 0f03e4cb-bf5c-44f3-871d-201307142e82 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 9c321e8cf88f16f0_train_data.json ds_type: json format: custom path: /workspace/input_data/9c321e8cf88f16f0_train_data.json type: field_input: input field_instruction: instruction field_output: output format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: thalllsssss/0f03e4cb-bf5c-44f3-871d-201307142e82 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/9c321e8cf88f16f0_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 1a9527a4-dbed-4d09-b3dc-303d2f7479cd wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 1a9527a4-dbed-4d09-b3dc-303d2f7479cd warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details> # 0f03e4cb-bf5c-44f3-871d-201307142e82 This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.1885 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 1.2752 | 0.0326 | 200 | 1.1885 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

fedovtt/8fc9f7fb-2a88-4444-a575-f1294e1b3b5d

fedovtt

2025-01-21T12:41:57Z

7

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "custom_code", "base_model:NousResearch/Yarn-Llama-2-13b-64k", "base_model:adapter:NousResearch/Yarn-Llama-2-13b-64k", "region:us" ]

null

2025-01-21T11:48:38Z

--- library_name: peft base_model: NousResearch/Yarn-Llama-2-13b-64k tags: - axolotl - generated_from_trainer model-index: - name: 8fc9f7fb-2a88-4444-a575-f1294e1b3b5d results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: NousResearch/Yarn-Llama-2-13b-64k bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 9eb6b8bdf2350702_train_data.json ds_type: json format: custom path: /workspace/input_data/9eb6b8bdf2350702_train_data.json type: field_input: '' field_instruction: Text field_output: Clean_Text format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: 1 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: false hub_model_id: fedovtt/8fc9f7fb-2a88-4444-a575-f1294e1b3b5d hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 78GiB max_steps: 30 micro_batch_size: 2 mlflow_experiment_name: /tmp/9eb6b8bdf2350702_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 2d1a479d-63b0-4baa-834e-801f81f8def7 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 2d1a479d-63b0-4baa-834e-801f81f8def7 warmup_steps: 10 weight_decay: 0.01 xformers_attention: true ``` </details> # 8fc9f7fb-2a88-4444-a575-f1294e1b3b5d This model is a fine-tuned version of [NousResearch/Yarn-Llama-2-13b-64k](https://huggingface.co/NousResearch/Yarn-Llama-2-13b-64k) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.1936 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 30 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.0002 | 1 | 1.5564 | | 6.24 | 0.0012 | 5 | 1.4933 | | 5.5815 | 0.0024 | 10 | 1.3498 | | 4.9161 | 0.0036 | 15 | 1.2571 | | 4.7732 | 0.0048 | 20 | 1.2136 | | 4.7155 | 0.0061 | 25 | 1.1968 | | 4.8142 | 0.0073 | 30 | 1.1936 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

nadejdatarabukina/2328ba71-018b-406a-9616-710264e1f406

nadejdatarabukina

2025-01-21T12:41:54Z

6

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:TinyLlama/TinyLlama-1.1B-Chat-v1.0", "base_model:adapter:TinyLlama/TinyLlama-1.1B-Chat-v1.0", "license:apache-2.0", "region:us" ]

null

2025-01-21T12:30:40Z

--- library_name: peft license: apache-2.0 base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0 tags: - axolotl - generated_from_trainer model-index: - name: 2328ba71-018b-406a-9616-710264e1f406 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 9c321e8cf88f16f0_train_data.json ds_type: json format: custom path: /workspace/input_data/9c321e8cf88f16f0_train_data.json type: field_input: input field_instruction: instruction field_output: output format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: null eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: false hub_model_id: nadejdatarabukina/2328ba71-018b-406a-9616-710264e1f406 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 75GiB max_steps: 30 micro_batch_size: 2 mlflow_experiment_name: /tmp/9c321e8cf88f16f0_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 1a9527a4-dbed-4d09-b3dc-303d2f7479cd wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 1a9527a4-dbed-4d09-b3dc-303d2f7479cd warmup_steps: 10 weight_decay: 0.01 xformers_attention: true ``` </details> # 2328ba71-018b-406a-9616-710264e1f406 This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.4001 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 30 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.0002 | 1 | 1.6018 | | 1.4712 | 0.0008 | 5 | 1.5746 | | 1.485 | 0.0016 | 10 | 1.4882 | | 1.3159 | 0.0024 | 15 | 1.4275 | | 1.3649 | 0.0033 | 20 | 1.4139 | | 1.5573 | 0.0041 | 25 | 1.4024 | | 1.3646 | 0.0049 | 30 | 1.4001 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

datlaaaaaaa/daac2d22-2b87-4368-98d4-0bc82576b148

datlaaaaaaa

2025-01-21T12:41:26Z

6

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:NousResearch/Nous-Hermes-llama-2-7b", "base_model:adapter:NousResearch/Nous-Hermes-llama-2-7b", "license:mit", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-21T11:41:30Z

--- library_name: peft license: mit base_model: NousResearch/Nous-Hermes-llama-2-7b tags: - axolotl - generated_from_trainer model-index: - name: daac2d22-2b87-4368-98d4-0bc82576b148 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: NousResearch/Nous-Hermes-llama-2-7b bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - db35a4b2827972f9_train_data.json ds_type: json format: custom path: /workspace/input_data/db35a4b2827972f9_train_data.json type: field_input: rejected field_instruction: context field_output: chosen format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: datlaaaaaaa/daac2d22-2b87-4368-98d4-0bc82576b148 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/db35a4b2827972f9_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 881827a9-7bb9-4a3a-bfa5-bc8cbc8f588f wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 881827a9-7bb9-4a3a-bfa5-bc8cbc8f588f warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details> # daac2d22-2b87-4368-98d4-0bc82576b148 This model is a fine-tuned version of [NousResearch/Nous-Hermes-llama-2-7b](https://huggingface.co/NousResearch/Nous-Hermes-llama-2-7b) on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.1089 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 1.879 | 0.0294 | 200 | 2.1089 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

great0001/b6c1df64-4838-486b-8a93-fee44f12a3b9

great0001

2025-01-21T12:38:03Z

6

0

peft

[ "peft", "safetensors", "mistral", "axolotl", "generated_from_trainer", "base_model:unsloth/zephyr-sft", "base_model:adapter:unsloth/zephyr-sft", "license:apache-2.0", "region:us" ]

null

2025-01-21T12:16:00Z

--- library_name: peft license: apache-2.0 base_model: unsloth/zephyr-sft tags: - axolotl - generated_from_trainer model-index: - name: b6c1df64-4838-486b-8a93-fee44f12a3b9 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/zephyr-sft bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 6bb273fb8d3c0253_train_data.json ds_type: json format: custom path: /workspace/input_data/6bb273fb8d3c0253_train_data.json type: field_input: condition field_instruction: drugName field_output: review format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: great0001/b6c1df64-4838-486b-8a93-fee44f12a3b9 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/6bb273fb8d3c0253_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: f44a8599-bd2c-4b24-9468-fb17670debf8 wandb_project: Mine-SN56-20-Gradients-On-Demand wandb_run: your_name wandb_runid: f44a8599-bd2c-4b24-9468-fb17670debf8 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # b6c1df64-4838-486b-8a93-fee44f12a3b9 This model is a fine-tuned version of [unsloth/zephyr-sft](https://huggingface.co/unsloth/zephyr-sft) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.0 | 0.0000 | 1 | nan | | 0.0 | 0.0001 | 3 | nan | | 0.0 | 0.0002 | 6 | nan | | 0.0 | 0.0004 | 9 | nan | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

lesso04/41f6379f-db9e-4d10-acc0-68151277842e

lesso04

2025-01-21T12:35:42Z

6

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:NousResearch/Nous-Hermes-llama-2-7b", "base_model:adapter:NousResearch/Nous-Hermes-llama-2-7b", "license:mit", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-21T11:42:25Z

--- library_name: peft license: mit base_model: NousResearch/Nous-Hermes-llama-2-7b tags: - axolotl - generated_from_trainer model-index: - name: 41f6379f-db9e-4d10-acc0-68151277842e results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: NousResearch/Nous-Hermes-llama-2-7b bf16: true chat_template: llama3 datasets: - data_files: - db35a4b2827972f9_train_data.json ds_type: json format: custom path: /workspace/input_data/db35a4b2827972f9_train_data.json type: field_input: rejected field_instruction: context field_output: chosen format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: 2 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null flash_attention: false fp16: false fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: lesso04/41f6379f-db9e-4d10-acc0-68151277842e hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 25 micro_batch_size: 2 mlflow_experiment_name: /tmp/db35a4b2827972f9_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 881827a9-7bb9-4a3a-bfa5-bc8cbc8f588f wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 881827a9-7bb9-4a3a-bfa5-bc8cbc8f588f warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # 41f6379f-db9e-4d10-acc0-68151277842e This model is a fine-tuned version of [NousResearch/Nous-Hermes-llama-2-7b](https://huggingface.co/NousResearch/Nous-Hermes-llama-2-7b) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 25 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.0 | 0.0001 | 1 | nan | | 0.0 | 0.0007 | 5 | nan | | 0.0 | 0.0015 | 10 | nan | | 0.0 | 0.0022 | 15 | nan | | 0.0 | 0.0029 | 20 | nan | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

nhung02/6e52b841-35b7-4d2f-867b-4cc3b62567c5

nhung02

2025-01-21T12:34:55Z

6

0

peft

[ "peft", "safetensors", "qwen2", "axolotl", "generated_from_trainer", "base_model:Qwen/Qwen1.5-0.5B", "base_model:adapter:Qwen/Qwen1.5-0.5B", "license:other", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-21T12:23:30Z

--- library_name: peft license: other base_model: Qwen/Qwen1.5-0.5B tags: - axolotl - generated_from_trainer model-index: - name: 6e52b841-35b7-4d2f-867b-4cc3b62567c5 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: Qwen/Qwen1.5-0.5B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 1de821793308c2b7_train_data.json ds_type: json format: custom path: /workspace/input_data/1de821793308c2b7_train_data.json type: field_input: context field_instruction: question field_output: answer format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: nhung02/6e52b841-35b7-4d2f-867b-4cc3b62567c5 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/1de821793308c2b7_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 7a0563f4-7af4-494e-9dbf-8003b312e74d wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 7a0563f4-7af4-494e-9dbf-8003b312e74d warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details> # 6e52b841-35b7-4d2f-867b-4cc3b62567c5 This model is a fine-tuned version of [Qwen/Qwen1.5-0.5B](https://huggingface.co/Qwen/Qwen1.5-0.5B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.5976 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.5455 | 0.1792 | 200 | 0.5976 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

visdata/kw5

visdata

2025-01-21T12:34:36Z

16

0

transformers

[ "transformers", "safetensors", "llama", "text-generation", "conversational", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2025-01-21T12:29:51Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

visdata/kw6

visdata

2025-01-21T12:33:35Z

31

0

transformers

[ "transformers", "safetensors", "llama", "text-generation", "conversational", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2025-01-21T12:29:21Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

VenkataRanjith/llama-3-8b-Instruct-bnb-4bit-Ranjith-coderTrainer

VenkataRanjith

2025-01-21T12:33:24Z

20

0

transformers

[ "transformers", "gguf", "llama", "text-generation-inference", "unsloth", "en", "base_model:unsloth/llama-3-8b-Instruct-bnb-4bit", "base_model:quantized:unsloth/llama-3-8b-Instruct-bnb-4bit", "license:apache-2.0", "endpoints_compatible", "region:us", "conversational" ]

null

2025-01-21T12:29:29Z

--- base_model: unsloth/llama-3-8b-Instruct-bnb-4bit tags: - text-generation-inference - transformers - unsloth - llama - gguf license: apache-2.0 language: - en --- # Uploaded model - **Developed by:** VenkataRanjith - **License:** apache-2.0 - **Finetuned from model :** unsloth/llama-3-8b-Instruct-bnb-4bit This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)

ClarenceDan/7848bbb3-caf9-490d-953b-ec68eb34e4ba

ClarenceDan

2025-01-21T12:31:38Z

6

0

peft

[ "peft", "safetensors", "falcon", "axolotl", "generated_from_trainer", "custom_code", "base_model:tiiuae/falcon-rw-1b", "base_model:adapter:tiiuae/falcon-rw-1b", "license:apache-2.0", "region:us" ]

null

2025-01-21T12:22:55Z

--- library_name: peft license: apache-2.0 base_model: tiiuae/falcon-rw-1b tags: - axolotl - generated_from_trainer model-index: - name: 7848bbb3-caf9-490d-953b-ec68eb34e4ba results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: tiiuae/falcon-rw-1b bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 8848939c923ff5a3_train_data.json ds_type: json format: custom path: /workspace/input_data/8848939c923ff5a3_train_data.json type: field_instruction: query field_output: answer format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: ClarenceDan/7848bbb3-caf9-490d-953b-ec68eb34e4ba hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/8848939c923ff5a3_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 special_tokens: pad_token: <|endoftext|> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 5acc14af-26c3-48ba-a29c-137d3b312a22 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 5acc14af-26c3-48ba-a29c-137d3b312a22 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # 7848bbb3-caf9-490d-953b-ec68eb34e4ba This model is a fine-tuned version of [tiiuae/falcon-rw-1b](https://huggingface.co/tiiuae/falcon-rw-1b) on the None dataset. It achieves the following results on the evaluation set: - Loss: 4.1183 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 22.7759 | 0.0001 | 1 | 4.7796 | | 19.6007 | 0.0002 | 3 | 4.7656 | | 16.7883 | 0.0004 | 6 | 4.6233 | | 17.1448 | 0.0006 | 9 | 4.1183 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

MayBashendy/ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k4_task7_organization

MayBashendy

2025-01-21T12:31:01Z

5

0

transformers

[ "transformers", "safetensors", "bert", "text-classification", "generated_from_trainer", "base_model:aubmindlab/bert-base-arabertv02", "base_model:finetune:aubmindlab/bert-base-arabertv02", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-classification

2025-01-21T12:27:04Z

--- library_name: transformers base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k4_task7_organization results: [] ---  # ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k4_task7_organization This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.7467 - Qwk: 0.0697 - Mse: 0.7467 - Rmse: 0.8641 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 100 ### Training results | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse | Rmse | |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:------:| | No log | 0.2 | 2 | 2.4280 | -0.0646 | 2.4280 | 1.5582 | | No log | 0.4 | 4 | 1.0881 | 0.2875 | 1.0881 | 1.0431 | | No log | 0.6 | 6 | 1.0474 | -0.1517 | 1.0474 | 1.0234 | | No log | 0.8 | 8 | 1.3691 | -0.1706 | 1.3691 | 1.1701 | | No log | 1.0 | 10 | 1.2737 | -0.1706 | 1.2737 | 1.1286 | | No log | 1.2 | 12 | 1.0007 | 0.0283 | 1.0007 | 1.0003 | | No log | 1.4 | 14 | 0.9275 | 0.1183 | 0.9275 | 0.9630 | | No log | 1.6 | 16 | 0.8221 | 0.0428 | 0.8221 | 0.9067 | | No log | 1.8 | 18 | 0.8087 | 0.0 | 0.8087 | 0.8993 | | No log | 2.0 | 20 | 0.7870 | 0.0 | 0.7870 | 0.8871 | | No log | 2.2 | 22 | 0.7671 | 0.0 | 0.7671 | 0.8758 | | No log | 2.4 | 24 | 0.7781 | 0.0 | 0.7781 | 0.8821 | | No log | 2.6 | 26 | 0.8770 | -0.0320 | 0.8770 | 0.9365 | | No log | 2.8 | 28 | 1.0144 | -0.0076 | 1.0144 | 1.0072 | | No log | 3.0 | 30 | 0.8925 | -0.0700 | 0.8925 | 0.9447 | | No log | 3.2 | 32 | 0.7964 | 0.0481 | 0.7964 | 0.8924 | | No log | 3.4 | 34 | 0.7693 | 0.1674 | 0.7693 | 0.8771 | | No log | 3.6 | 36 | 0.8324 | 0.2285 | 0.8324 | 0.9123 | | No log | 3.8 | 38 | 0.8665 | 0.2319 | 0.8665 | 0.9309 | | No log | 4.0 | 40 | 0.9179 | -0.0045 | 0.9179 | 0.9581 | | No log | 4.2 | 42 | 1.2147 | 0.0367 | 1.2147 | 1.1021 | | No log | 4.4 | 44 | 1.0913 | -0.0033 | 1.0913 | 1.0446 | | No log | 4.6 | 46 | 0.8643 | 0.2063 | 0.8643 | 0.9297 | | No log | 4.8 | 48 | 0.8581 | 0.1550 | 0.8581 | 0.9263 | | No log | 5.0 | 50 | 0.8888 | 0.1815 | 0.8888 | 0.9428 | | No log | 5.2 | 52 | 0.8949 | 0.1766 | 0.8949 | 0.9460 | | No log | 5.4 | 54 | 0.8389 | 0.1699 | 0.8389 | 0.9159 | | No log | 5.6 | 56 | 0.8780 | 0.0410 | 0.8780 | 0.9370 | | No log | 5.8 | 58 | 1.0235 | 0.0975 | 1.0235 | 1.0117 | | No log | 6.0 | 60 | 1.0118 | 0.1259 | 1.0118 | 1.0059 | | No log | 6.2 | 62 | 0.8937 | 0.1498 | 0.8937 | 0.9454 | | No log | 6.4 | 64 | 0.8858 | 0.1541 | 0.8858 | 0.9412 | | No log | 6.6 | 66 | 0.8867 | 0.1541 | 0.8867 | 0.9416 | | No log | 6.8 | 68 | 0.8969 | 0.0930 | 0.8969 | 0.9471 | | No log | 7.0 | 70 | 0.8899 | 0.1760 | 0.8899 | 0.9434 | | No log | 7.2 | 72 | 0.9062 | 0.1866 | 0.9062 | 0.9519 | | No log | 7.4 | 74 | 1.0502 | 0.1271 | 1.0502 | 1.0248 | | No log | 7.6 | 76 | 0.9760 | 0.1712 | 0.9760 | 0.9879 | | No log | 7.8 | 78 | 0.8485 | 0.1303 | 0.8485 | 0.9211 | | No log | 8.0 | 80 | 0.8510 | 0.1379 | 0.8510 | 0.9225 | | No log | 8.2 | 82 | 0.8621 | 0.1969 | 0.8621 | 0.9285 | | No log | 8.4 | 84 | 0.8653 | 0.2747 | 0.8653 | 0.9302 | | No log | 8.6 | 86 | 0.8761 | 0.2987 | 0.8761 | 0.9360 | | No log | 8.8 | 88 | 0.9020 | 0.2593 | 0.9020 | 0.9498 | | No log | 9.0 | 90 | 0.8735 | 0.2888 | 0.8735 | 0.9346 | | No log | 9.2 | 92 | 0.8758 | 0.2256 | 0.8758 | 0.9359 | | No log | 9.4 | 94 | 0.8433 | 0.2936 | 0.8433 | 0.9183 | | No log | 9.6 | 96 | 0.8244 | 0.3296 | 0.8244 | 0.9080 | | No log | 9.8 | 98 | 0.8399 | 0.3060 | 0.8399 | 0.9165 | | No log | 10.0 | 100 | 0.8450 | 0.3060 | 0.8450 | 0.9192 | | No log | 10.2 | 102 | 0.8358 | 0.3478 | 0.8358 | 0.9142 | | No log | 10.4 | 104 | 0.9045 | 0.0678 | 0.9045 | 0.9511 | | No log | 10.6 | 106 | 0.8931 | 0.0702 | 0.8931 | 0.9450 | | No log | 10.8 | 108 | 0.8382 | 0.1379 | 0.8382 | 0.9155 | | No log | 11.0 | 110 | 0.8312 | 0.2475 | 0.8312 | 0.9117 | | No log | 11.2 | 112 | 0.8191 | 0.2360 | 0.8191 | 0.9050 | | No log | 11.4 | 114 | 0.8313 | 0.1797 | 0.8313 | 0.9118 | | No log | 11.6 | 116 | 0.8490 | 0.1179 | 0.8490 | 0.9214 | | No log | 11.8 | 118 | 0.8143 | 0.1179 | 0.8143 | 0.9024 | | No log | 12.0 | 120 | 0.7943 | 0.3002 | 0.7943 | 0.8912 | | No log | 12.2 | 122 | 0.7994 | 0.2973 | 0.7994 | 0.8941 | | No log | 12.4 | 124 | 0.8554 | 0.2633 | 0.8554 | 0.9249 | | No log | 12.6 | 126 | 0.8489 | 0.2633 | 0.8489 | 0.9213 | | No log | 12.8 | 128 | 0.8310 | 0.2561 | 0.8310 | 0.9116 | | No log | 13.0 | 130 | 0.8112 | 0.1471 | 0.8112 | 0.9006 | | No log | 13.2 | 132 | 0.8178 | 0.1697 | 0.8178 | 0.9043 | | No log | 13.4 | 134 | 0.9047 | 0.2899 | 0.9047 | 0.9511 | | No log | 13.6 | 136 | 1.0909 | 0.1142 | 1.0909 | 1.0445 | | No log | 13.8 | 138 | 1.0766 | 0.1743 | 1.0766 | 1.0376 | | No log | 14.0 | 140 | 0.9207 | 0.2495 | 0.9207 | 0.9595 | | No log | 14.2 | 142 | 0.8547 | 0.2072 | 0.8547 | 0.9245 | | No log | 14.4 | 144 | 0.9249 | 0.1156 | 0.9249 | 0.9617 | | No log | 14.6 | 146 | 0.8786 | 0.1494 | 0.8786 | 0.9373 | | No log | 14.8 | 148 | 0.8118 | 0.1760 | 0.8118 | 0.9010 | | No log | 15.0 | 150 | 0.8315 | 0.2261 | 0.8315 | 0.9119 | | No log | 15.2 | 152 | 0.8498 | 0.1740 | 0.8498 | 0.9218 | | No log | 15.4 | 154 | 0.8157 | 0.2590 | 0.8157 | 0.9031 | | No log | 15.6 | 156 | 0.8095 | 0.2424 | 0.8095 | 0.8997 | | No log | 15.8 | 158 | 0.8147 | 0.1870 | 0.8147 | 0.9026 | | No log | 16.0 | 160 | 0.7790 | 0.0741 | 0.7790 | 0.8826 | | No log | 16.2 | 162 | 0.7751 | 0.2353 | 0.7751 | 0.8804 | | No log | 16.4 | 164 | 0.8274 | 0.2995 | 0.8274 | 0.9096 | | No log | 16.6 | 166 | 0.8519 | 0.2521 | 0.8519 | 0.9230 | | No log | 16.8 | 168 | 0.7997 | 0.2558 | 0.7997 | 0.8943 | | No log | 17.0 | 170 | 0.7449 | 0.1386 | 0.7449 | 0.8631 | | No log | 17.2 | 172 | 0.7760 | 0.1873 | 0.7760 | 0.8809 | | No log | 17.4 | 174 | 0.7825 | 0.2926 | 0.7825 | 0.8846 | | No log | 17.6 | 176 | 0.7185 | 0.1133 | 0.7185 | 0.8477 | | No log | 17.8 | 178 | 0.6876 | 0.1456 | 0.6876 | 0.8292 | | No log | 18.0 | 180 | 0.7060 | 0.2685 | 0.7060 | 0.8402 | | No log | 18.2 | 182 | 0.7141 | 0.2471 | 0.7141 | 0.8450 | | No log | 18.4 | 184 | 0.7117 | 0.2652 | 0.7117 | 0.8436 | | No log | 18.6 | 186 | 0.7238 | 0.2287 | 0.7238 | 0.8508 | | No log | 18.8 | 188 | 0.7424 | 0.2182 | 0.7424 | 0.8617 | | No log | 19.0 | 190 | 0.7592 | 0.2132 | 0.7592 | 0.8713 | | No log | 19.2 | 192 | 0.7723 | 0.2772 | 0.7723 | 0.8788 | | No log | 19.4 | 194 | 0.7658 | 0.2458 | 0.7658 | 0.8751 | | No log | 19.6 | 196 | 0.7629 | 0.2405 | 0.7629 | 0.8735 | | No log | 19.8 | 198 | 0.7542 | 0.2749 | 0.7542 | 0.8684 | | No log | 20.0 | 200 | 0.8205 | 0.2995 | 0.8205 | 0.9058 | | No log | 20.2 | 202 | 0.8206 | 0.3399 | 0.8206 | 0.9059 | | No log | 20.4 | 204 | 0.7879 | 0.2784 | 0.7879 | 0.8876 | | No log | 20.6 | 206 | 0.7408 | 0.2589 | 0.7408 | 0.8607 | | No log | 20.8 | 208 | 0.7042 | 0.1407 | 0.7042 | 0.8392 | | No log | 21.0 | 210 | 0.7484 | 0.1528 | 0.7484 | 0.8651 | | No log | 21.2 | 212 | 0.8096 | 0.2068 | 0.8096 | 0.8998 | | No log | 21.4 | 214 | 0.7809 | 0.1716 | 0.7809 | 0.8837 | | No log | 21.6 | 216 | 0.7705 | 0.2475 | 0.7705 | 0.8778 | | No log | 21.8 | 218 | 0.8606 | 0.3586 | 0.8606 | 0.9277 | | No log | 22.0 | 220 | 0.9064 | 0.3586 | 0.9064 | 0.9521 | | No log | 22.2 | 222 | 0.8311 | 0.3590 | 0.8311 | 0.9116 | | No log | 22.4 | 224 | 0.7556 | 0.1353 | 0.7556 | 0.8693 | | No log | 22.6 | 226 | 0.7622 | -0.0023 | 0.7622 | 0.8731 | | No log | 22.8 | 228 | 0.7908 | 0.1716 | 0.7908 | 0.8893 | | No log | 23.0 | 230 | 0.7844 | 0.2349 | 0.7844 | 0.8857 | | No log | 23.2 | 232 | 0.7792 | 0.2379 | 0.7792 | 0.8827 | | No log | 23.4 | 234 | 0.7998 | 0.2784 | 0.7998 | 0.8943 | | No log | 23.6 | 236 | 0.8093 | 0.2899 | 0.8093 | 0.8996 | | No log | 23.8 | 238 | 0.7995 | 0.3127 | 0.7995 | 0.8942 | | No log | 24.0 | 240 | 0.7712 | 0.1835 | 0.7712 | 0.8782 | | No log | 24.2 | 242 | 0.7589 | 0.1813 | 0.7589 | 0.8711 | | No log | 24.4 | 244 | 0.7670 | 0.1133 | 0.7670 | 0.8758 | | No log | 24.6 | 246 | 0.7585 | 0.1850 | 0.7585 | 0.8709 | | No log | 24.8 | 248 | 0.7605 | 0.2590 | 0.7605 | 0.8721 | | No log | 25.0 | 250 | 0.7949 | 0.3121 | 0.7949 | 0.8916 | | No log | 25.2 | 252 | 0.8086 | 0.3121 | 0.8086 | 0.8992 | | No log | 25.4 | 254 | 0.7797 | 0.2161 | 0.7797 | 0.8830 | | No log | 25.6 | 256 | 0.7776 | 0.2713 | 0.7776 | 0.8818 | | No log | 25.8 | 258 | 0.8006 | 0.1775 | 0.8006 | 0.8948 | | No log | 26.0 | 260 | 0.7976 | 0.2683 | 0.7976 | 0.8931 | | No log | 26.2 | 262 | 0.8170 | 0.2445 | 0.8170 | 0.9039 | | No log | 26.4 | 264 | 0.8895 | 0.3320 | 0.8895 | 0.9432 | | No log | 26.6 | 266 | 0.9028 | 0.3320 | 0.9028 | 0.9501 | | No log | 26.8 | 268 | 0.8500 | 0.3723 | 0.8500 | 0.9220 | | No log | 27.0 | 270 | 0.7773 | 0.2237 | 0.7773 | 0.8816 | | No log | 27.2 | 272 | 0.7466 | 0.1432 | 0.7466 | 0.8640 | | No log | 27.4 | 274 | 0.7358 | 0.1432 | 0.7358 | 0.8578 | | No log | 27.6 | 276 | 0.7184 | 0.1400 | 0.7184 | 0.8476 | | No log | 27.8 | 278 | 0.7469 | 0.2913 | 0.7469 | 0.8642 | | No log | 28.0 | 280 | 0.8341 | 0.4167 | 0.8341 | 0.9133 | | No log | 28.2 | 282 | 0.9025 | 0.3480 | 0.9025 | 0.9500 | | No log | 28.4 | 284 | 0.8798 | 0.3480 | 0.8798 | 0.9380 | | No log | 28.6 | 286 | 0.7983 | 0.3305 | 0.7983 | 0.8935 | | No log | 28.8 | 288 | 0.7546 | 0.2530 | 0.7546 | 0.8687 | | No log | 29.0 | 290 | 0.7365 | 0.3198 | 0.7365 | 0.8582 | | No log | 29.2 | 292 | 0.7642 | 0.3369 | 0.7642 | 0.8742 | | No log | 29.4 | 294 | 0.7576 | 0.3369 | 0.7576 | 0.8704 | | No log | 29.6 | 296 | 0.7301 | 0.3603 | 0.7301 | 0.8545 | | No log | 29.8 | 298 | 0.7250 | 0.2182 | 0.7250 | 0.8515 | | No log | 30.0 | 300 | 0.7324 | 0.2471 | 0.7324 | 0.8558 | | No log | 30.2 | 302 | 0.7285 | 0.2471 | 0.7285 | 0.8535 | | No log | 30.4 | 304 | 0.7248 | 0.2973 | 0.7248 | 0.8514 | | No log | 30.6 | 306 | 0.7439 | 0.3859 | 0.7439 | 0.8625 | | No log | 30.8 | 308 | 0.7629 | 0.3716 | 0.7629 | 0.8734 | | No log | 31.0 | 310 | 0.7752 | 0.3093 | 0.7752 | 0.8804 | | No log | 31.2 | 312 | 0.7833 | 0.3433 | 0.7833 | 0.8850 | | No log | 31.4 | 314 | 0.7665 | 0.2535 | 0.7665 | 0.8755 | | No log | 31.6 | 316 | 0.7582 | 0.2862 | 0.7582 | 0.8707 | | No log | 31.8 | 318 | 0.7551 | 0.4081 | 0.7551 | 0.8690 | | No log | 32.0 | 320 | 0.7494 | 0.4081 | 0.7494 | 0.8657 | | No log | 32.2 | 322 | 0.7288 | 0.3144 | 0.7288 | 0.8537 | | No log | 32.4 | 324 | 0.7226 | 0.2360 | 0.7226 | 0.8500 | | No log | 32.6 | 326 | 0.7280 | 0.2392 | 0.7280 | 0.8532 | | No log | 32.8 | 328 | 0.7445 | 0.2092 | 0.7445 | 0.8628 | | No log | 33.0 | 330 | 0.7433 | 0.2092 | 0.7433 | 0.8622 | | No log | 33.2 | 332 | 0.7497 | 0.3144 | 0.7497 | 0.8658 | | No log | 33.4 | 334 | 0.7552 | 0.3088 | 0.7552 | 0.8690 | | No log | 33.6 | 336 | 0.7637 | 0.3355 | 0.7637 | 0.8739 | | No log | 33.8 | 338 | 0.7622 | 0.2751 | 0.7622 | 0.8730 | | No log | 34.0 | 340 | 0.7537 | 0.3253 | 0.7537 | 0.8681 | | No log | 34.2 | 342 | 0.7522 | 0.2621 | 0.7522 | 0.8673 | | No log | 34.4 | 344 | 0.7579 | 0.2530 | 0.7579 | 0.8706 | | No log | 34.6 | 346 | 0.7845 | 0.3399 | 0.7845 | 0.8857 | | No log | 34.8 | 348 | 0.8104 | 0.3918 | 0.8104 | 0.9002 | | No log | 35.0 | 350 | 0.8344 | 0.4167 | 0.8344 | 0.9135 | | No log | 35.2 | 352 | 0.8210 | 0.4167 | 0.8210 | 0.9061 | | No log | 35.4 | 354 | 0.7846 | 0.3662 | 0.7846 | 0.8858 | | No log | 35.6 | 356 | 0.7560 | 0.2813 | 0.7560 | 0.8695 | | No log | 35.8 | 358 | 0.7321 | 0.3551 | 0.7321 | 0.8556 | | No log | 36.0 | 360 | 0.7285 | 0.2113 | 0.7285 | 0.8535 | | No log | 36.2 | 362 | 0.7275 | 0.1760 | 0.7275 | 0.8529 | | No log | 36.4 | 364 | 0.7351 | 0.2973 | 0.7351 | 0.8574 | | No log | 36.6 | 366 | 0.7917 | 0.3121 | 0.7917 | 0.8898 | | No log | 36.8 | 368 | 0.8597 | 0.3092 | 0.8597 | 0.9272 | | No log | 37.0 | 370 | 0.8741 | 0.3320 | 0.8741 | 0.9349 | | No log | 37.2 | 372 | 0.8339 | 0.3092 | 0.8339 | 0.9132 | | No log | 37.4 | 374 | 0.7728 | 0.3088 | 0.7728 | 0.8791 | | No log | 37.6 | 376 | 0.7437 | 0.2684 | 0.7437 | 0.8624 | | No log | 37.8 | 378 | 0.7441 | 0.0741 | 0.7441 | 0.8626 | | No log | 38.0 | 380 | 0.7444 | 0.1133 | 0.7444 | 0.8628 | | No log | 38.2 | 382 | 0.7398 | 0.0330 | 0.7398 | 0.8601 | | No log | 38.4 | 384 | 0.7364 | 0.1050 | 0.7364 | 0.8581 | | No log | 38.6 | 386 | 0.7439 | 0.1988 | 0.7439 | 0.8625 | | No log | 38.8 | 388 | 0.7504 | 0.2652 | 0.7504 | 0.8663 | | No log | 39.0 | 390 | 0.7610 | 0.2590 | 0.7610 | 0.8724 | | No log | 39.2 | 392 | 0.7666 | 0.2877 | 0.7666 | 0.8755 | | No log | 39.4 | 394 | 0.7729 | 0.2877 | 0.7729 | 0.8791 | | No log | 39.6 | 396 | 0.7772 | 0.2943 | 0.7772 | 0.8816 | | No log | 39.8 | 398 | 0.7828 | 0.2327 | 0.7828 | 0.8848 | | No log | 40.0 | 400 | 0.7829 | 0.2327 | 0.7829 | 0.8848 | | No log | 40.2 | 402 | 0.7780 | 0.2270 | 0.7780 | 0.8820 | | No log | 40.4 | 404 | 0.7750 | 0.2590 | 0.7750 | 0.8804 | | No log | 40.6 | 406 | 0.7717 | 0.3224 | 0.7717 | 0.8785 | | No log | 40.8 | 408 | 0.7689 | 0.3224 | 0.7689 | 0.8769 | | No log | 41.0 | 410 | 0.7627 | 0.1935 | 0.7627 | 0.8733 | | No log | 41.2 | 412 | 0.7545 | 0.1303 | 0.7545 | 0.8686 | | No log | 41.4 | 414 | 0.7458 | 0.0652 | 0.7458 | 0.8636 | | No log | 41.6 | 416 | 0.7394 | 0.0652 | 0.7394 | 0.8599 | | No log | 41.8 | 418 | 0.7392 | 0.0652 | 0.7392 | 0.8598 | | No log | 42.0 | 420 | 0.7425 | 0.1432 | 0.7425 | 0.8617 | | No log | 42.2 | 422 | 0.7477 | 0.1697 | 0.7477 | 0.8647 | | No log | 42.4 | 424 | 0.7587 | 0.1341 | 0.7587 | 0.8710 | | No log | 42.6 | 426 | 0.7674 | 0.1673 | 0.7674 | 0.8760 | | No log | 42.8 | 428 | 0.7715 | 0.1673 | 0.7715 | 0.8783 | | No log | 43.0 | 430 | 0.7743 | 0.2023 | 0.7743 | 0.8800 | | No log | 43.2 | 432 | 0.7788 | 0.1697 | 0.7788 | 0.8825 | | No log | 43.4 | 434 | 0.7774 | 0.2004 | 0.7774 | 0.8817 | | No log | 43.6 | 436 | 0.7802 | 0.1672 | 0.7802 | 0.8833 | | No log | 43.8 | 438 | 0.7689 | 0.1697 | 0.7689 | 0.8769 | | No log | 44.0 | 440 | 0.7487 | 0.1393 | 0.7487 | 0.8653 | | No log | 44.2 | 442 | 0.7407 | 0.1009 | 0.7407 | 0.8607 | | No log | 44.4 | 444 | 0.7507 | 0.1686 | 0.7507 | 0.8664 | | No log | 44.6 | 446 | 0.7712 | 0.3471 | 0.7712 | 0.8782 | | No log | 44.8 | 448 | 0.8306 | 0.3918 | 0.8306 | 0.9114 | | No log | 45.0 | 450 | 0.8624 | 0.3243 | 0.8624 | 0.9286 | | No log | 45.2 | 452 | 0.8467 | 0.3918 | 0.8467 | 0.9202 | | No log | 45.4 | 454 | 0.8022 | 0.3996 | 0.8022 | 0.8956 | | No log | 45.6 | 456 | 0.7728 | 0.3545 | 0.7728 | 0.8791 | | No log | 45.8 | 458 | 0.7627 | 0.2621 | 0.7627 | 0.8733 | | No log | 46.0 | 460 | 0.7581 | 0.1341 | 0.7581 | 0.8707 | | No log | 46.2 | 462 | 0.7569 | 0.1341 | 0.7569 | 0.8700 | | No log | 46.4 | 464 | 0.7586 | 0.1341 | 0.7586 | 0.8710 | | No log | 46.6 | 466 | 0.7676 | 0.2023 | 0.7676 | 0.8761 | | No log | 46.8 | 468 | 0.7907 | 0.3050 | 0.7907 | 0.8892 | | No log | 47.0 | 470 | 0.8157 | 0.3196 | 0.8157 | 0.9031 | | No log | 47.2 | 472 | 0.8223 | 0.2261 | 0.8223 | 0.9068 | | No log | 47.4 | 474 | 0.8078 | 0.2063 | 0.8078 | 0.8988 | | No log | 47.6 | 476 | 0.7929 | 0.2063 | 0.7929 | 0.8904 | | No log | 47.8 | 478 | 0.7951 | 0.2063 | 0.7951 | 0.8917 | | No log | 48.0 | 480 | 0.8073 | 0.2379 | 0.8073 | 0.8985 | | No log | 48.2 | 482 | 0.8317 | 0.2981 | 0.8317 | 0.9120 | | No log | 48.4 | 484 | 0.8679 | 0.3737 | 0.8679 | 0.9316 | | No log | 48.6 | 486 | 0.8842 | 0.3544 | 0.8842 | 0.9403 | | No log | 48.8 | 488 | 0.8807 | 0.3737 | 0.8807 | 0.9384 | | No log | 49.0 | 490 | 0.8616 | 0.3737 | 0.8616 | 0.9282 | | No log | 49.2 | 492 | 0.8484 | 0.3471 | 0.8484 | 0.9211 | | No log | 49.4 | 494 | 0.8225 | 0.2319 | 0.8225 | 0.9069 | | No log | 49.6 | 496 | 0.8099 | 0.2379 | 0.8099 | 0.9000 | | No log | 49.8 | 498 | 0.8027 | 0.2379 | 0.8027 | 0.8960 | | 0.2553 | 50.0 | 500 | 0.8057 | 0.2379 | 0.8057 | 0.8976 | | 0.2553 | 50.2 | 502 | 0.8048 | 0.2379 | 0.8048 | 0.8971 | | 0.2553 | 50.4 | 504 | 0.7961 | 0.1988 | 0.7961 | 0.8922 | | 0.2553 | 50.6 | 506 | 0.7901 | 0.2685 | 0.7901 | 0.8889 | | 0.2553 | 50.8 | 508 | 0.7940 | 0.2685 | 0.7940 | 0.8911 | | 0.2553 | 51.0 | 510 | 0.8051 | 0.2847 | 0.8051 | 0.8973 | | 0.2553 | 51.2 | 512 | 0.8122 | 0.2847 | 0.8122 | 0.9012 | | 0.2553 | 51.4 | 514 | 0.8100 | 0.2847 | 0.8100 | 0.9000 | | 0.2553 | 51.6 | 516 | 0.8060 | 0.2847 | 0.8060 | 0.8978 | | 0.2553 | 51.8 | 518 | 0.8079 | 0.2847 | 0.8079 | 0.8988 | | 0.2553 | 52.0 | 520 | 0.7941 | 0.2621 | 0.7941 | 0.8911 | | 0.2553 | 52.2 | 522 | 0.7804 | 0.2685 | 0.7804 | 0.8834 | | 0.2553 | 52.4 | 524 | 0.7663 | 0.2685 | 0.7663 | 0.8754 | | 0.2553 | 52.6 | 526 | 0.7580 | 0.1737 | 0.7580 | 0.8706 | | 0.2553 | 52.8 | 528 | 0.7571 | 0.1737 | 0.7571 | 0.8701 | | 0.2553 | 53.0 | 530 | 0.7622 | 0.2294 | 0.7622 | 0.8730 | | 0.2553 | 53.2 | 532 | 0.7758 | 0.2685 | 0.7758 | 0.8808 | | 0.2553 | 53.4 | 534 | 0.8022 | 0.3088 | 0.8022 | 0.8957 | | 0.2553 | 53.6 | 536 | 0.8215 | 0.3287 | 0.8215 | 0.9064 | | 0.2553 | 53.8 | 538 | 0.8320 | 0.3287 | 0.8320 | 0.9121 | | 0.2553 | 54.0 | 540 | 0.8215 | 0.3287 | 0.8215 | 0.9063 | | 0.2553 | 54.2 | 542 | 0.7971 | 0.3688 | 0.7971 | 0.8928 | | 0.2553 | 54.4 | 544 | 0.7801 | 0.2652 | 0.7801 | 0.8832 | | 0.2553 | 54.6 | 546 | 0.7654 | 0.1673 | 0.7654 | 0.8749 | | 0.2553 | 54.8 | 548 | 0.7574 | 0.0971 | 0.7574 | 0.8703 | | 0.2553 | 55.0 | 550 | 0.7524 | 0.0971 | 0.7524 | 0.8674 | | 0.2553 | 55.2 | 552 | 0.7489 | 0.0283 | 0.7489 | 0.8654 | | 0.2553 | 55.4 | 554 | 0.7467 | 0.0697 | 0.7467 | 0.8641 | ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.0+cu118 - Datasets 2.21.0 - Tokenizers 0.19.1

kostiantynk/19c4fa41-fdff-4798-a49e-259eac91f176

kostiantynk

2025-01-21T12:31:01Z

6

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:oopsung/llama2-7b-n-ox-test-v1", "base_model:adapter:oopsung/llama2-7b-n-ox-test-v1", "region:us" ]

null

2025-01-21T12:24:58Z

--- library_name: peft base_model: oopsung/llama2-7b-n-ox-test-v1 tags: - axolotl - generated_from_trainer model-index: - name: 19c4fa41-fdff-4798-a49e-259eac91f176 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: oopsung/llama2-7b-n-ox-test-v1 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - dddb0489dc663e1a_train_data.json ds_type: json format: custom path: /workspace/input_data/dddb0489dc663e1a_train_data.json type: field_input: Context field_instruction: Question field_output: Answers format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: kostiantynk/19c4fa41-fdff-4798-a49e-259eac91f176 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/dddb0489dc663e1a_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: bbd202cf-ffeb-42f5-82b2-0c60d893aeab wandb_project: Birthday-SN56-7-Gradients-On-Demand wandb_run: your_name wandb_runid: bbd202cf-ffeb-42f5-82b2-0c60d893aeab warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # 19c4fa41-fdff-4798-a49e-259eac91f176 This model is a fine-tuned version of [oopsung/llama2-7b-n-ox-test-v1](https://huggingface.co/oopsung/llama2-7b-n-ox-test-v1) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.0 | 0.0003 | 1 | nan | | 0.0 | 0.0008 | 3 | nan | | 0.0 | 0.0017 | 6 | nan | | 0.0 | 0.0025 | 9 | nan | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

akh99/DeepSeek-R1-Distill-Qwen-7B_AWQ-tok-norm

akh99

2025-01-21T12:30:25Z

141

0

transformers

[ "transformers", "safetensors", "qwen2", "text-generation", "conversational", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "4-bit", "awq", "region:us" ]

text-generation

2025-01-21T12:29:31Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

nhung01/37ee035e-1e50-44b7-aa8a-1086267f8630

nhung01

2025-01-21T12:29:49Z

6

0

peft

[ "peft", "safetensors", "gpt_neox", "axolotl", "generated_from_trainer", "base_model:EleutherAI/pythia-1b", "base_model:adapter:EleutherAI/pythia-1b", "license:apache-2.0", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-21T12:17:26Z

--- library_name: peft license: apache-2.0 base_model: EleutherAI/pythia-1b tags: - axolotl - generated_from_trainer model-index: - name: 37ee035e-1e50-44b7-aa8a-1086267f8630 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: EleutherAI/pythia-1b bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - b88fbb911025d0a2_train_data.json ds_type: json format: custom path: /workspace/input_data/b88fbb911025d0a2_train_data.json type: field_input: Primary Keyword field_instruction: Long Description field_output: Position format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: nhung01/37ee035e-1e50-44b7-aa8a-1086267f8630 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/b88fbb911025d0a2_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 special_tokens: pad_token: <|endoftext|> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 9ff18266-1053-4343-a163-393cb535b12c wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 9ff18266-1053-4343-a163-393cb535b12c warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details> # 37ee035e-1e50-44b7-aa8a-1086267f8630 This model is a fine-tuned version of [EleutherAI/pythia-1b](https://huggingface.co/EleutherAI/pythia-1b) on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.0207 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 10.0779 | 0.0119 | 200 | 2.0207 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

josty11/roberta-optimized

josty11

2025-01-21T12:29:35Z

23

0

transformers

[ "transformers", "safetensors", "distilbert", "text-classification", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-classification

2025-01-21T12:29:09Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

lesso11/d853c065-1f63-4c2f-99c9-18ee9227719f

lesso11

2025-01-21T12:29:00Z

6

0

peft

[ "peft", "safetensors", "phi3", "axolotl", "generated_from_trainer", "custom_code", "base_model:migtissera/Tess-v2.5-Phi-3-medium-128k-14B", "base_model:adapter:migtissera/Tess-v2.5-Phi-3-medium-128k-14B", "license:mit", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-21T12:20:37Z

--- library_name: peft license: mit base_model: migtissera/Tess-v2.5-Phi-3-medium-128k-14B tags: - axolotl - generated_from_trainer model-index: - name: d853c065-1f63-4c2f-99c9-18ee9227719f results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: migtissera/Tess-v2.5-Phi-3-medium-128k-14B bf16: true chat_template: llama3 datasets: - data_files: - 5fe705ae677c52cd_train_data.json ds_type: json format: custom path: /workspace/input_data/5fe705ae677c52cd_train_data.json type: field_input: code_before field_instruction: func_before field_output: code_after format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: 2 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null flash_attention: false fp16: false fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: lesso11/d853c065-1f63-4c2f-99c9-18ee9227719f hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 25 micro_batch_size: 2 mlflow_experiment_name: /tmp/5fe705ae677c52cd_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: c9913a62-6036-4cc0-92bf-1f189dbde5c4 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: c9913a62-6036-4cc0-92bf-1f189dbde5c4 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # d853c065-1f63-4c2f-99c9-18ee9227719f This model is a fine-tuned version of [migtissera/Tess-v2.5-Phi-3-medium-128k-14B](https://huggingface.co/migtissera/Tess-v2.5-Phi-3-medium-128k-14B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.6170 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 25 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 2.286 | 0.0020 | 1 | 0.6638 | | 2.5694 | 0.0101 | 5 | 0.6637 | | 2.2073 | 0.0202 | 10 | 0.6503 | | 2.4329 | 0.0302 | 15 | 0.6293 | | 1.1466 | 0.0403 | 20 | 0.6194 | | 2.8759 | 0.0504 | 25 | 0.6170 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

cvoffer/ddc7dbca-7bbb-4a64-9065-11f4e2616878

cvoffer

2025-01-21T12:27:43Z

6

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:unsloth/llama-2-7b-chat", "base_model:adapter:unsloth/llama-2-7b-chat", "license:apache-2.0", "region:us" ]

null

2025-01-21T08:34:57Z

--- library_name: peft license: apache-2.0 base_model: unsloth/llama-2-7b-chat tags: - axolotl - generated_from_trainer model-index: - name: ddc7dbca-7bbb-4a64-9065-11f4e2616878 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/llama-2-7b-chat bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 124bc05ddbf5ee81_train_data.json ds_type: json format: custom path: /workspace/input_data/124bc05ddbf5ee81_train_data.json type: field_instruction: docstring field_output: summary format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: 1 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: true hub_model_id: cvoffer/ddc7dbca-7bbb-4a64-9065-11f4e2616878 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 78GiB max_steps: 30 micro_batch_size: 2 mlflow_experiment_name: /tmp/124bc05ddbf5ee81_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 5fe9995d-0a95-46fa-b89c-25f97cbb6eb6 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 5fe9995d-0a95-46fa-b89c-25f97cbb6eb6 warmup_steps: 5 weight_decay: 0.001 xformers_attention: true ``` </details> # ddc7dbca-7bbb-4a64-9065-11f4e2616878 This model is a fine-tuned version of [unsloth/llama-2-7b-chat](https://huggingface.co/unsloth/llama-2-7b-chat) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 30 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.0000 | 1 | nan | | 0.0 | 0.0001 | 5 | nan | | 0.0 | 0.0002 | 10 | nan | | 0.0 | 0.0003 | 15 | nan | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

thaffggg/c0a3ae1e-da6c-43d4-9442-7848c0ffddeb

thaffggg

2025-01-21T12:27:07Z

6

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:TinyLlama/TinyLlama-1.1B-Chat-v1.0", "base_model:adapter:TinyLlama/TinyLlama-1.1B-Chat-v1.0", "license:apache-2.0", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-21T12:13:58Z

--- library_name: peft license: apache-2.0 base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0 tags: - axolotl - generated_from_trainer model-index: - name: c0a3ae1e-da6c-43d4-9442-7848c0ffddeb results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - b73b66c21220caaf_train_data.json ds_type: json format: custom path: /workspace/input_data/b73b66c21220caaf_train_data.json type: field_input: categories field_instruction: title field_output: markdown format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: thaffggg/c0a3ae1e-da6c-43d4-9442-7848c0ffddeb hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/b73b66c21220caaf_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: fc2a71fc-f606-4cf6-887a-e73c961e3be1 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: fc2a71fc-f606-4cf6-887a-e73c961e3be1 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details> # c0a3ae1e-da6c-43d4-9442-7848c0ffddeb This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.8160 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 1.9254 | 0.0378 | 200 | 1.8160 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

nadejdatarabukina/c663e43a-fce1-4aed-aabb-ac7bc046445f

nadejdatarabukina

2025-01-21T12:27:02Z

6

0

peft

[ "peft", "safetensors", "mistral", "axolotl", "generated_from_trainer", "base_model:teknium/OpenHermes-2.5-Mistral-7B", "base_model:adapter:teknium/OpenHermes-2.5-Mistral-7B", "license:apache-2.0", "region:us" ]

null

2025-01-21T11:55:46Z

--- library_name: peft license: apache-2.0 base_model: teknium/OpenHermes-2.5-Mistral-7B tags: - axolotl - generated_from_trainer model-index: - name: c663e43a-fce1-4aed-aabb-ac7bc046445f results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: teknium/OpenHermes-2.5-Mistral-7B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 1b5fe4b652f9222e_train_data.json ds_type: json format: custom path: /workspace/input_data/1b5fe4b652f9222e_train_data.json type: field_instruction: instruction field_output: output format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: null eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: false hub_model_id: nadejdatarabukina/c663e43a-fce1-4aed-aabb-ac7bc046445f hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 75GiB max_steps: 30 micro_batch_size: 2 mlflow_experiment_name: /tmp/1b5fe4b652f9222e_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 special_tokens: pad_token: <|im_end|> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 857fa1e7-73d3-440e-a388-76fc6a5b2495 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 857fa1e7-73d3-440e-a388-76fc6a5b2495 warmup_steps: 10 weight_decay: 0.01 xformers_attention: true ``` </details> # c663e43a-fce1-4aed-aabb-ac7bc046445f This model is a fine-tuned version of [teknium/OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 30 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.0002 | 1 | nan | | 0.0 | 0.0010 | 5 | nan | | 0.0 | 0.0019 | 10 | nan | | 0.0 | 0.0029 | 15 | nan | | 0.0 | 0.0039 | 20 | nan | | 0.0 | 0.0049 | 25 | nan | | 0.0 | 0.0058 | 30 | nan | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

filipesantoscv11/87dd10c7-f67d-4031-94e7-cba82e9cbe5a

filipesantoscv11

2025-01-21T12:26:56Z

6

0

peft

[ "peft", "safetensors", "gemma", "axolotl", "generated_from_trainer", "base_model:fxmarty/tiny-random-GemmaForCausalLM", "base_model:adapter:fxmarty/tiny-random-GemmaForCausalLM", "license:mit", "region:us" ]

null

2025-01-21T12:18:45Z

--- library_name: peft license: mit base_model: fxmarty/tiny-random-GemmaForCausalLM tags: - axolotl - generated_from_trainer model-index: - name: 87dd10c7-f67d-4031-94e7-cba82e9cbe5a results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: fxmarty/tiny-random-GemmaForCausalLM bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - dabeeced6597d53e_train_data.json ds_type: json format: custom path: /workspace/input_data/dabeeced6597d53e_train_data.json type: field_instruction: sentence1_en field_output: sentence2_en format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: 1 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: true hub_model_id: filipesantoscv11/87dd10c7-f67d-4031-94e7-cba82e9cbe5a hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 79GiB max_steps: 30 micro_batch_size: 4 mlflow_experiment_name: /tmp/dabeeced6597d53e_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optim_args: adam_beta1: 0.9 adam_beta2: 0.95 adam_epsilon: 1e-5 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 8140ab10-5da7-47df-b106-2846f0a02738 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 8140ab10-5da7-47df-b106-2846f0a02738 warmup_steps: 5 weight_decay: 0.001 xformers_attention: true ``` </details> # 87dd10c7-f67d-4031-94e7-cba82e9cbe5a This model is a fine-tuned version of [fxmarty/tiny-random-GemmaForCausalLM](https://huggingface.co/fxmarty/tiny-random-GemmaForCausalLM) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 16 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.95,adam_epsilon=1e-5 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 30 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.0000 | 1 | nan | | 0.0 | 0.0002 | 5 | nan | | 0.0 | 0.0004 | 10 | nan | | 0.0 | 0.0006 | 15 | nan | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

dimasik87/6effa428-7d2c-4d09-8936-920f11f80aa1

dimasik87

2025-01-21T12:25:55Z

6

0

peft

[ "peft", "safetensors", "gemma", "axolotl", "generated_from_trainer", "base_model:fxmarty/tiny-random-GemmaForCausalLM", "base_model:adapter:fxmarty/tiny-random-GemmaForCausalLM", "license:mit", "region:us" ]

null

2025-01-21T12:17:08Z

--- library_name: peft license: mit base_model: fxmarty/tiny-random-GemmaForCausalLM tags: - axolotl - generated_from_trainer model-index: - name: 6effa428-7d2c-4d09-8936-920f11f80aa1 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: fxmarty/tiny-random-GemmaForCausalLM bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - dabeeced6597d53e_train_data.json ds_type: json format: custom path: /workspace/input_data/dabeeced6597d53e_train_data.json type: field_instruction: sentence1_en field_output: sentence2_en format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: 1 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: true hub_model_id: dimasik87/6effa428-7d2c-4d09-8936-920f11f80aa1 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 79GiB max_steps: 30 micro_batch_size: 4 mlflow_experiment_name: /tmp/dabeeced6597d53e_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optim_args: adam_beta1: 0.9 adam_beta2: 0.95 adam_epsilon: 1e-5 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 8140ab10-5da7-47df-b106-2846f0a02738 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 8140ab10-5da7-47df-b106-2846f0a02738 warmup_steps: 5 weight_decay: 0.001 xformers_attention: true ``` </details> # 6effa428-7d2c-4d09-8936-920f11f80aa1 This model is a fine-tuned version of [fxmarty/tiny-random-GemmaForCausalLM](https://huggingface.co/fxmarty/tiny-random-GemmaForCausalLM) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 16 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.95,adam_epsilon=1e-5 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 30 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.0000 | 1 | nan | | 0.0 | 0.0002 | 5 | nan | | 0.0 | 0.0004 | 10 | nan | | 0.0 | 0.0006 | 15 | nan | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

mrHungddddh/ee0ee47e-2d5b-4367-8e93-9087d184a92e

mrHungddddh

2025-01-21T12:25:51Z

6

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:unsloth/tinyllama", "base_model:adapter:unsloth/tinyllama", "license:apache-2.0", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-21T12:17:08Z

--- library_name: peft license: apache-2.0 base_model: unsloth/tinyllama tags: - axolotl - generated_from_trainer model-index: - name: ee0ee47e-2d5b-4367-8e93-9087d184a92e results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/tinyllama bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 487571a5edd806c1_train_data.json ds_type: json format: custom path: /workspace/input_data/487571a5edd806c1_train_data.json type: field_input: strategy field_instruction: original_text field_output: reframed_text format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: mrHungddddh/ee0ee47e-2d5b-4367-8e93-9087d184a92e hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/487571a5edd806c1_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 37054b4e-d0d5-4aaa-9839-6cdc15c24dbf wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 37054b4e-d0d5-4aaa-9839-6cdc15c24dbf warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details> # ee0ee47e-2d5b-4367-8e93-9087d184a92e This model is a fine-tuned version of [unsloth/tinyllama](https://huggingface.co/unsloth/tinyllama) on the None dataset. It achieves the following results on the evaluation set: - Loss: 3.6298 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 3.7227 | 0.2042 | 200 | 3.6298 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

tarabukinivan/1066e8a2-3893-4cd1-8fd8-e1b505b5a1b3

tarabukinivan

2025-01-21T12:25:00Z

6

0

peft

[ "peft", "safetensors", "opt", "axolotl", "generated_from_trainer", "base_model:facebook/opt-125m", "base_model:adapter:facebook/opt-125m", "license:other", "region:us" ]

null

2025-01-21T12:20:06Z

--- library_name: peft license: other base_model: facebook/opt-125m tags: - axolotl - generated_from_trainer model-index: - name: 1066e8a2-3893-4cd1-8fd8-e1b505b5a1b3 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: facebook/opt-125m bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 807edbe01d3143fb_train_data.json ds_type: json format: custom path: /workspace/input_data/807edbe01d3143fb_train_data.json type: field_input: question field_instruction: answer field_output: context field_system: distractors format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: null eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: false hub_model_id: tarabukinivan/1066e8a2-3893-4cd1-8fd8-e1b505b5a1b3 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 75GiB max_steps: 30 micro_batch_size: 2 mlflow_experiment_name: /tmp/807edbe01d3143fb_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 87d40317-ca50-4c35-ad9f-1a82b7dfae06 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 87d40317-ca50-4c35-ad9f-1a82b7dfae06 warmup_steps: 10 weight_decay: 0.01 xformers_attention: true ``` </details> # 1066e8a2-3893-4cd1-8fd8-e1b505b5a1b3 This model is a fine-tuned version of [facebook/opt-125m](https://huggingface.co/facebook/opt-125m) on the None dataset. It achieves the following results on the evaluation set: - Loss: 3.2501 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 30 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.0001 | 1 | 3.4432 | | 14.4001 | 0.0007 | 5 | 3.4202 | | 13.9917 | 0.0014 | 10 | 3.3622 | | 13.5667 | 0.0021 | 15 | 3.3026 | | 13.4465 | 0.0028 | 20 | 3.2633 | | 13.4339 | 0.0035 | 25 | 3.2522 | | 13.0761 | 0.0042 | 30 | 3.2501 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

Ancastal/mistral-7b-literary-creamt-ita-v2

Ancastal

2025-01-21T12:24:44Z

18

0

transformers

[ "transformers", "safetensors", "mistral", "text-generation", "trl", "sft", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "4-bit", "bitsandbytes", "region:us" ]

text-generation

2025-01-21T12:22:09Z

--- library_name: transformers tags: - trl - sft --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

kokovova/a68a6605-dbd4-4a06-94e6-cf4a93ba65b4

kokovova

2025-01-21T12:22:52Z

5

0

peft

[ "peft", "safetensors", "opt", "axolotl", "generated_from_trainer", "base_model:facebook/opt-125m", "base_model:adapter:facebook/opt-125m", "license:other", "region:us" ]

null

2025-01-21T12:20:06Z

--- library_name: peft license: other base_model: facebook/opt-125m tags: - axolotl - generated_from_trainer model-index: - name: a68a6605-dbd4-4a06-94e6-cf4a93ba65b4 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: facebook/opt-125m bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 807edbe01d3143fb_train_data.json ds_type: json format: custom path: /workspace/input_data/807edbe01d3143fb_train_data.json type: field_input: question field_instruction: answer field_output: context field_system: distractors format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: 1 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: true hub_model_id: kokovova/a68a6605-dbd4-4a06-94e6-cf4a93ba65b4 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 79GiB max_steps: 30 micro_batch_size: 4 mlflow_experiment_name: /tmp/807edbe01d3143fb_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optim_args: adam_beta1: 0.9 adam_beta2: 0.95 adam_epsilon: 1e-5 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 87d40317-ca50-4c35-ad9f-1a82b7dfae06 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 87d40317-ca50-4c35-ad9f-1a82b7dfae06 warmup_steps: 5 weight_decay: 0.001 xformers_attention: true ``` </details> # a68a6605-dbd4-4a06-94e6-cf4a93ba65b4 This model is a fine-tuned version of [facebook/opt-125m](https://huggingface.co/facebook/opt-125m) on the None dataset. It achieves the following results on the evaluation set: - Loss: 3.3495 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 16 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.95,adam_epsilon=1e-5 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 30 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.0003 | 1 | 3.5459 | | 12.8135 | 0.0014 | 5 | 3.5057 | | 13.1425 | 0.0028 | 10 | 3.4401 | | 13.0512 | 0.0042 | 15 | 3.3813 | | 12.9854 | 0.0056 | 20 | 3.3556 | | 13.2067 | 0.0070 | 25 | 3.3501 | | 12.8119 | 0.0084 | 30 | 3.3495 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

ClarenceDan/55ee309d-0518-4ff9-9817-91bd856ea2b9

ClarenceDan

2025-01-21T12:21:37Z

6

0

peft

[ "peft", "safetensors", "qwen2", "axolotl", "generated_from_trainer", "base_model:Qwen/Qwen1.5-14B-Chat", "base_model:adapter:Qwen/Qwen1.5-14B-Chat", "license:other", "region:us" ]

null

2025-01-21T12:19:59Z

--- library_name: peft license: other base_model: Qwen/Qwen1.5-14B-Chat tags: - axolotl - generated_from_trainer model-index: - name: 55ee309d-0518-4ff9-9817-91bd856ea2b9 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: Qwen/Qwen1.5-14B-Chat bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - a6fd907479ec4d1c_train_data.json ds_type: json format: custom path: /workspace/input_data/a6fd907479ec4d1c_train_data.json type: field_instruction: text field_output: title format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: ClarenceDan/55ee309d-0518-4ff9-9817-91bd856ea2b9 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/a6fd907479ec4d1c_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: fded3919-5ba0-4f07-810d-e0ea78b083dd wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: fded3919-5ba0-4f07-810d-e0ea78b083dd warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # 55ee309d-0518-4ff9-9817-91bd856ea2b9 This model is a fine-tuned version of [Qwen/Qwen1.5-14B-Chat](https://huggingface.co/Qwen/Qwen1.5-14B-Chat) on the None dataset. It achieves the following results on the evaluation set: - Loss: 3.5376 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 3.8175 | 0.0028 | 1 | 3.9889 | | 3.7012 | 0.0085 | 3 | 3.9837 | | 4.6257 | 0.0171 | 6 | 3.9136 | | 3.7991 | 0.0256 | 9 | 3.5376 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

lesso15/c922ade5-6e42-482f-8b7f-f2fb56073597

lesso15

2025-01-21T12:21:27Z

6

0

peft

[ "peft", "safetensors", "gpt_neox", "axolotl", "generated_from_trainer", "base_model:EleutherAI/pythia-14m", "base_model:adapter:EleutherAI/pythia-14m", "4-bit", "bitsandbytes", "region:us" ]

null

2025-01-21T12:20:52Z

--- library_name: peft base_model: EleutherAI/pythia-14m tags: - axolotl - generated_from_trainer model-index: - name: c922ade5-6e42-482f-8b7f-f2fb56073597 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: EleutherAI/pythia-14m bf16: auto chat_template: llama3 datasets: - data_files: - eb2c9ecdcfd4c8a6_train_data.json ds_type: json format: custom path: /workspace/input_data/eb2c9ecdcfd4c8a6_train_data.json type: field_instruction: image field_output: description format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: 2 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: true gradient_checkpointing: false group_by_length: false hub_model_id: lesso15/c922ade5-6e42-482f-8b7f-f2fb56073597 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: true load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_steps: 25 micro_batch_size: 2 mlflow_experiment_name: /tmp/eb2c9ecdcfd4c8a6_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 special_tokens: pad_token: <|endoftext|> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 99d526df-9766-4d1f-80b3-c918100a230c wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 99d526df-9766-4d1f-80b3-c918100a230c warmup_steps: 10 weight_decay: 0.01 xformers_attention: null ``` </details> # c922ade5-6e42-482f-8b7f-f2fb56073597 This model is a fine-tuned version of [EleutherAI/pythia-14m](https://huggingface.co/EleutherAI/pythia-14m) on the None dataset. It achieves the following results on the evaluation set: - Loss: 3.0091 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 25 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.0012 | 1 | 5.6256 | | 5.6383 | 0.0058 | 5 | 5.3829 | | 4.8286 | 0.0117 | 10 | 4.4874 | | 3.6903 | 0.0175 | 15 | 3.6561 | | 3.5467 | 0.0234 | 20 | 3.1049 | | 2.657 | 0.0292 | 25 | 3.0091 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

demohong/b7c5fd23-cbe4-469e-bdc5-e977a9051452

demohong

2025-01-21T12:21:27Z

6

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:codellama/CodeLlama-7b-Instruct-hf", "base_model:adapter:codellama/CodeLlama-7b-Instruct-hf", "license:llama2", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-21T11:54:20Z

--- library_name: peft license: llama2 base_model: codellama/CodeLlama-7b-Instruct-hf tags: - axolotl - generated_from_trainer model-index: - name: b7c5fd23-cbe4-469e-bdc5-e977a9051452 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: codellama/CodeLlama-7b-Instruct-hf bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - e61b15027cdb8f0f_train_data.json ds_type: json format: custom path: /workspace/input_data/e61b15027cdb8f0f_train_data.json type: field_instruction: text_description field_output: text format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: demohong/b7c5fd23-cbe4-469e-bdc5-e977a9051452 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/e61b15027cdb8f0f_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 special_tokens: pad_token: </s> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 52dcb611-f58d-420b-a954-552a3249dfec wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 52dcb611-f58d-420b-a954-552a3249dfec warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details> # b7c5fd23-cbe4-469e-bdc5-e977a9051452 This model is a fine-tuned version of [codellama/CodeLlama-7b-Instruct-hf](https://huggingface.co/codellama/CodeLlama-7b-Instruct-hf) on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.1081 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 1.9469 | 0.0800 | 200 | 2.1081 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

minsangK/20250120-bge-m3-8192-bs-4-1-epoch-5e-6-hn-2

minsangK

2025-01-21T12:21:19Z

7

0

transformers

[ "transformers", "safetensors", "xlm-roberta", "feature-extraction", "generated_from_trainer", "text-embeddings-inference", "endpoints_compatible", "region:us" ]

feature-extraction

2025-01-21T05:05:07Z

--- library_name: transformers tags: - generated_from_trainer model-index: - name: 20250120-bge-m3-8192-bs-4-1-epoch-5e-6-hn-2 results: [] ---  # 20250120-bge-m3-8192-bs-4-1-epoch-5e-6-hn-2 This model was trained from scratch on an unknown dataset. ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-06 - train_batch_size: 4 - eval_batch_size: 8 - seed: 42 - distributed_type: multi-GPU - num_devices: 4 - total_train_batch_size: 16 - total_eval_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 1.0 - mixed_precision_training: Native AMP ### Training results ### Framework versions - Transformers 4.44.2 - Pytorch 2.2.2 - Datasets 2.19.0 - Tokenizers 0.19.1

MayBashendy/ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k2_task7_organization

MayBashendy

2025-01-21T12:21:14Z

5

0

transformers

[ "transformers", "safetensors", "bert", "text-classification", "generated_from_trainer", "base_model:aubmindlab/bert-base-arabertv02", "base_model:finetune:aubmindlab/bert-base-arabertv02", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-classification

2025-01-21T12:17:18Z

--- library_name: transformers base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k2_task7_organization results: [] ---  # ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k2_task7_organization This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.0238 - Qwk: 0.2898 - Mse: 1.0238 - Rmse: 1.0119 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 100 ### Training results | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse | Rmse | |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:------:| | No log | 0.4 | 2 | 2.5043 | -0.0788 | 2.5043 | 1.5825 | | No log | 0.8 | 4 | 1.1496 | 0.1284 | 1.1496 | 1.0722 | | No log | 1.2 | 6 | 0.8398 | 0.0535 | 0.8398 | 0.9164 | | No log | 1.6 | 8 | 0.8665 | 0.0313 | 0.8665 | 0.9309 | | No log | 2.0 | 10 | 0.9418 | 0.1181 | 0.9418 | 0.9705 | | No log | 2.4 | 12 | 0.8754 | 0.1268 | 0.8754 | 0.9356 | | No log | 2.8 | 14 | 0.7780 | 0.0804 | 0.7780 | 0.8821 | | No log | 3.2 | 16 | 0.7806 | 0.0444 | 0.7806 | 0.8835 | | No log | 3.6 | 18 | 0.7911 | 0.0444 | 0.7911 | 0.8895 | | No log | 4.0 | 20 | 0.8116 | 0.0481 | 0.8116 | 0.9009 | | No log | 4.4 | 22 | 0.7852 | 0.0444 | 0.7852 | 0.8861 | | No log | 4.8 | 24 | 0.7556 | 0.1187 | 0.7556 | 0.8693 | | No log | 5.2 | 26 | 0.7550 | 0.1094 | 0.7550 | 0.8689 | | No log | 5.6 | 28 | 0.7873 | 0.2285 | 0.7873 | 0.8873 | | No log | 6.0 | 30 | 0.8195 | 0.1867 | 0.8195 | 0.9053 | | No log | 6.4 | 32 | 0.7905 | 0.1584 | 0.7905 | 0.8891 | | No log | 6.8 | 34 | 0.8006 | 0.1542 | 0.8006 | 0.8947 | | No log | 7.2 | 36 | 0.8280 | 0.1946 | 0.8280 | 0.9100 | | No log | 7.6 | 38 | 1.0096 | 0.1501 | 1.0096 | 1.0048 | | No log | 8.0 | 40 | 1.0556 | 0.1867 | 1.0556 | 1.0274 | | No log | 8.4 | 42 | 0.9515 | 0.0241 | 0.9515 | 0.9754 | | No log | 8.8 | 44 | 0.8984 | 0.1289 | 0.8984 | 0.9478 | | No log | 9.2 | 46 | 0.9670 | 0.1385 | 0.9670 | 0.9834 | | No log | 9.6 | 48 | 1.0413 | 0.2119 | 1.0413 | 1.0204 | | No log | 10.0 | 50 | 1.1556 | 0.1115 | 1.1556 | 1.0750 | | No log | 10.4 | 52 | 1.1839 | 0.0845 | 1.1839 | 1.0881 | | No log | 10.8 | 54 | 1.2097 | 0.0686 | 1.2097 | 1.0998 | | No log | 11.2 | 56 | 1.2016 | 0.0686 | 1.2016 | 1.0962 | | No log | 11.6 | 58 | 1.1247 | 0.0713 | 1.1247 | 1.0605 | | No log | 12.0 | 60 | 1.0039 | 0.1775 | 1.0039 | 1.0020 | | No log | 12.4 | 62 | 0.9073 | 0.2239 | 0.9073 | 0.9525 | | No log | 12.8 | 64 | 1.0174 | 0.1014 | 1.0174 | 1.0087 | | No log | 13.2 | 66 | 1.2606 | 0.1176 | 1.2606 | 1.1228 | | No log | 13.6 | 68 | 1.3323 | 0.1479 | 1.3323 | 1.1542 | | No log | 14.0 | 70 | 1.3229 | 0.0704 | 1.3229 | 1.1502 | | No log | 14.4 | 72 | 1.0368 | 0.1843 | 1.0368 | 1.0182 | | No log | 14.8 | 74 | 0.9368 | 0.2124 | 0.9368 | 0.9679 | | No log | 15.2 | 76 | 0.9609 | 0.2076 | 0.9609 | 0.9803 | | No log | 15.6 | 78 | 1.1684 | 0.1086 | 1.1684 | 1.0809 | | No log | 16.0 | 80 | 1.2916 | 0.1417 | 1.2916 | 1.1365 | | No log | 16.4 | 82 | 1.2723 | 0.1145 | 1.2723 | 1.1279 | | No log | 16.8 | 84 | 1.1180 | 0.2070 | 1.1180 | 1.0573 | | No log | 17.2 | 86 | 0.9465 | 0.3134 | 0.9465 | 0.9729 | | No log | 17.6 | 88 | 0.9163 | 0.3194 | 0.9163 | 0.9572 | | No log | 18.0 | 90 | 1.0376 | 0.2209 | 1.0376 | 1.0186 | | No log | 18.4 | 92 | 1.2168 | 0.2070 | 1.2168 | 1.1031 | | No log | 18.8 | 94 | 1.2754 | 0.0727 | 1.2754 | 1.1293 | | No log | 19.2 | 96 | 1.2909 | 0.1200 | 1.2909 | 1.1362 | | No log | 19.6 | 98 | 1.2740 | 0.2138 | 1.2740 | 1.1287 | | No log | 20.0 | 100 | 1.0757 | 0.2354 | 1.0757 | 1.0372 | | No log | 20.4 | 102 | 0.9648 | 0.3134 | 0.9648 | 0.9823 | | No log | 20.8 | 104 | 0.9900 | 0.2537 | 0.9900 | 0.9950 | | No log | 21.2 | 106 | 1.0386 | 0.1549 | 1.0386 | 1.0191 | | No log | 21.6 | 108 | 1.1480 | 0.1206 | 1.1480 | 1.0714 | | No log | 22.0 | 110 | 1.2393 | 0.1254 | 1.2393 | 1.1133 | | No log | 22.4 | 112 | 1.3027 | 0.1198 | 1.3027 | 1.1414 | | No log | 22.8 | 114 | 1.2327 | 0.1473 | 1.2327 | 1.1102 | | No log | 23.2 | 116 | 1.0803 | 0.1176 | 1.0803 | 1.0394 | | No log | 23.6 | 118 | 1.0485 | 0.2330 | 1.0485 | 1.0240 | | No log | 24.0 | 120 | 1.0691 | 0.2545 | 1.0691 | 1.0340 | | No log | 24.4 | 122 | 1.1256 | 0.2580 | 1.1256 | 1.0610 | | No log | 24.8 | 124 | 1.1114 | 0.1764 | 1.1114 | 1.0542 | | No log | 25.2 | 126 | 1.0668 | 0.1576 | 1.0668 | 1.0328 | | No log | 25.6 | 128 | 0.9976 | 0.1726 | 0.9976 | 0.9988 | | No log | 26.0 | 130 | 0.9405 | 0.2389 | 0.9405 | 0.9698 | | No log | 26.4 | 132 | 0.9616 | 0.2507 | 0.9616 | 0.9806 | | No log | 26.8 | 134 | 0.9992 | 0.2872 | 0.9992 | 0.9996 | | No log | 27.2 | 136 | 0.9222 | 0.3022 | 0.9222 | 0.9603 | | No log | 27.6 | 138 | 0.8651 | 0.3319 | 0.8651 | 0.9301 | | No log | 28.0 | 140 | 0.8733 | 0.2328 | 0.8733 | 0.9345 | | No log | 28.4 | 142 | 0.8902 | 0.2440 | 0.8902 | 0.9435 | | No log | 28.8 | 144 | 0.9273 | 0.2116 | 0.9273 | 0.9629 | | No log | 29.2 | 146 | 0.9950 | 0.1672 | 0.9950 | 0.9975 | | No log | 29.6 | 148 | 1.0746 | 0.1238 | 1.0746 | 1.0366 | | No log | 30.0 | 150 | 1.2142 | 0.1583 | 1.2142 | 1.1019 | | No log | 30.4 | 152 | 1.2794 | 0.1174 | 1.2794 | 1.1311 | | No log | 30.8 | 154 | 1.2352 | 0.1956 | 1.2352 | 1.1114 | | No log | 31.2 | 156 | 1.1476 | 0.1884 | 1.1476 | 1.0712 | | No log | 31.6 | 158 | 1.0861 | 0.1451 | 1.0861 | 1.0422 | | No log | 32.0 | 160 | 1.0964 | 0.0648 | 1.0964 | 1.0471 | | No log | 32.4 | 162 | 1.1565 | 0.0872 | 1.1565 | 1.0754 | | No log | 32.8 | 164 | 1.1985 | 0.1320 | 1.1985 | 1.0948 | | No log | 33.2 | 166 | 1.1957 | 0.1550 | 1.1957 | 1.0935 | | No log | 33.6 | 168 | 1.1242 | 0.1774 | 1.1242 | 1.0603 | | No log | 34.0 | 170 | 1.0184 | 0.2166 | 1.0184 | 1.0092 | | No log | 34.4 | 172 | 1.0672 | 0.2031 | 1.0672 | 1.0330 | | No log | 34.8 | 174 | 1.0674 | 0.2961 | 1.0674 | 1.0332 | | No log | 35.2 | 176 | 1.0550 | 0.2288 | 1.0550 | 1.0272 | | No log | 35.6 | 178 | 1.0939 | 0.1618 | 1.0939 | 1.0459 | | No log | 36.0 | 180 | 1.1366 | 0.0953 | 1.1366 | 1.0661 | | No log | 36.4 | 182 | 1.1833 | 0.1618 | 1.1833 | 1.0878 | | No log | 36.8 | 184 | 1.2085 | 0.2247 | 1.2085 | 1.0993 | | No log | 37.2 | 186 | 1.1489 | 0.2330 | 1.1489 | 1.0719 | | No log | 37.6 | 188 | 1.0133 | 0.3059 | 1.0133 | 1.0066 | | No log | 38.0 | 190 | 0.9738 | 0.3110 | 0.9738 | 0.9868 | | No log | 38.4 | 192 | 0.9567 | 0.2554 | 0.9567 | 0.9781 | | No log | 38.8 | 194 | 1.0198 | 0.2554 | 1.0198 | 1.0099 | | No log | 39.2 | 196 | 1.0940 | 0.2192 | 1.0940 | 1.0459 | | No log | 39.6 | 198 | 1.0901 | 0.1726 | 1.0901 | 1.0441 | | No log | 40.0 | 200 | 1.0486 | 0.2323 | 1.0486 | 1.0240 | | No log | 40.4 | 202 | 1.0287 | 0.2507 | 1.0287 | 1.0142 | | No log | 40.8 | 204 | 1.0958 | 0.2330 | 1.0958 | 1.0468 | | No log | 41.2 | 206 | 1.1211 | 0.2330 | 1.1211 | 1.0588 | | No log | 41.6 | 208 | 1.1175 | 0.2330 | 1.1175 | 1.0571 | | No log | 42.0 | 210 | 1.0222 | 0.2461 | 1.0222 | 1.0110 | | No log | 42.4 | 212 | 0.9571 | 0.2934 | 0.9571 | 0.9783 | | No log | 42.8 | 214 | 0.9372 | 0.2934 | 0.9372 | 0.9681 | | No log | 43.2 | 216 | 0.9523 | 0.2830 | 0.9523 | 0.9759 | | No log | 43.6 | 218 | 0.9940 | 0.2682 | 0.9940 | 0.9970 | | No log | 44.0 | 220 | 1.0150 | 0.2682 | 1.0150 | 1.0075 | | No log | 44.4 | 222 | 0.9591 | 0.2898 | 0.9591 | 0.9793 | | No log | 44.8 | 224 | 0.9037 | 0.3579 | 0.9037 | 0.9506 | | No log | 45.2 | 226 | 0.8545 | 0.3777 | 0.8545 | 0.9244 | | No log | 45.6 | 228 | 0.8533 | 0.3777 | 0.8533 | 0.9237 | | No log | 46.0 | 230 | 0.8554 | 0.3409 | 0.8554 | 0.9249 | | No log | 46.4 | 232 | 0.7829 | 0.3494 | 0.7829 | 0.8848 | | No log | 46.8 | 234 | 0.7568 | 0.3737 | 0.7568 | 0.8700 | | No log | 47.2 | 236 | 0.7869 | 0.3425 | 0.7869 | 0.8871 | | No log | 47.6 | 238 | 0.8789 | 0.3579 | 0.8789 | 0.9375 | | No log | 48.0 | 240 | 0.9512 | 0.3161 | 0.9512 | 0.9753 | | No log | 48.4 | 242 | 0.9939 | 0.2982 | 0.9939 | 0.9969 | | No log | 48.8 | 244 | 0.9759 | 0.2982 | 0.9759 | 0.9879 | | No log | 49.2 | 246 | 0.9258 | 0.3161 | 0.9258 | 0.9622 | | No log | 49.6 | 248 | 0.8924 | 0.3269 | 0.8924 | 0.9447 | | No log | 50.0 | 250 | 0.8939 | 0.3269 | 0.8939 | 0.9455 | | No log | 50.4 | 252 | 0.8985 | 0.3214 | 0.8985 | 0.9479 | | No log | 50.8 | 254 | 0.9009 | 0.3359 | 0.9009 | 0.9492 | | No log | 51.2 | 256 | 0.9503 | 0.3302 | 0.9503 | 0.9748 | | No log | 51.6 | 258 | 1.0464 | 0.2643 | 1.0464 | 1.0229 | | No log | 52.0 | 260 | 1.1513 | 0.2518 | 1.1513 | 1.0730 | | No log | 52.4 | 262 | 1.1727 | 0.2518 | 1.1727 | 1.0829 | | No log | 52.8 | 264 | 1.1205 | 0.2843 | 1.1205 | 1.0585 | | No log | 53.2 | 266 | 1.0426 | 0.3010 | 1.0426 | 1.0211 | | No log | 53.6 | 268 | 0.9458 | 0.3110 | 0.9458 | 0.9725 | | No log | 54.0 | 270 | 0.9039 | 0.3110 | 0.9039 | 0.9507 | | No log | 54.4 | 272 | 0.8963 | 0.3214 | 0.8963 | 0.9467 | | No log | 54.8 | 274 | 0.9164 | 0.2682 | 0.9164 | 0.9573 | | No log | 55.2 | 276 | 0.9534 | 0.2682 | 0.9534 | 0.9764 | | No log | 55.6 | 278 | 1.0053 | 0.2682 | 1.0053 | 1.0026 | | No log | 56.0 | 280 | 1.0373 | 0.2682 | 1.0373 | 1.0185 | | No log | 56.4 | 282 | 1.0683 | 0.2682 | 1.0683 | 1.0336 | | No log | 56.8 | 284 | 1.0886 | 0.2850 | 1.0886 | 1.0433 | | No log | 57.2 | 286 | 1.1172 | 0.2687 | 1.1172 | 1.0570 | | No log | 57.6 | 288 | 1.1151 | 0.2687 | 1.1151 | 1.0560 | | No log | 58.0 | 290 | 1.0486 | 0.2682 | 1.0486 | 1.0240 | | No log | 58.4 | 292 | 0.9765 | 0.2934 | 0.9765 | 0.9882 | | No log | 58.8 | 294 | 0.9303 | 0.2754 | 0.9303 | 0.9645 | | No log | 59.2 | 296 | 0.8948 | 0.2807 | 0.8948 | 0.9459 | | No log | 59.6 | 298 | 0.9041 | 0.2754 | 0.9041 | 0.9508 | | No log | 60.0 | 300 | 0.9135 | 0.3217 | 0.9135 | 0.9558 | | No log | 60.4 | 302 | 0.9702 | 0.2999 | 0.9702 | 0.9850 | | No log | 60.8 | 304 | 1.0872 | 0.2732 | 1.0872 | 1.0427 | | No log | 61.2 | 306 | 1.1963 | 0.2601 | 1.1963 | 1.0937 | | No log | 61.6 | 308 | 1.2333 | 0.2319 | 1.2333 | 1.1105 | | No log | 62.0 | 310 | 1.2058 | 0.2319 | 1.2058 | 1.0981 | | No log | 62.4 | 312 | 1.1687 | 0.2643 | 1.1687 | 1.0811 | | No log | 62.8 | 314 | 1.1065 | 0.2330 | 1.1065 | 1.0519 | | No log | 63.2 | 316 | 1.0488 | 0.2416 | 1.0488 | 1.0241 | | No log | 63.6 | 318 | 1.0236 | 0.2461 | 1.0236 | 1.0117 | | No log | 64.0 | 320 | 1.0416 | 0.2461 | 1.0416 | 1.0206 | | No log | 64.4 | 322 | 1.0806 | 0.2312 | 1.0806 | 1.0395 | | No log | 64.8 | 324 | 1.0938 | 0.2312 | 1.0938 | 1.0458 | | No log | 65.2 | 326 | 1.0957 | 0.2312 | 1.0957 | 1.0468 | | No log | 65.6 | 328 | 1.1094 | 0.2231 | 1.1094 | 1.0533 | | No log | 66.0 | 330 | 1.0897 | 0.2372 | 1.0897 | 1.0439 | | No log | 66.4 | 332 | 1.0418 | 0.2507 | 1.0418 | 1.0207 | | No log | 66.8 | 334 | 1.0109 | 0.2554 | 1.0109 | 1.0054 | | No log | 67.2 | 336 | 0.9840 | 0.2537 | 0.9840 | 0.9919 | | No log | 67.6 | 338 | 0.9836 | 0.2728 | 0.9836 | 0.9918 | | No log | 68.0 | 340 | 1.0211 | 0.2507 | 1.0211 | 1.0105 | | No log | 68.4 | 342 | 1.0395 | 0.2461 | 1.0395 | 1.0196 | | No log | 68.8 | 344 | 1.0772 | 0.2635 | 1.0772 | 1.0379 | | No log | 69.2 | 346 | 1.1149 | 0.2590 | 1.1149 | 1.0559 | | No log | 69.6 | 348 | 1.1039 | 0.2590 | 1.1039 | 1.0507 | | No log | 70.0 | 350 | 1.0739 | 0.2372 | 1.0739 | 1.0363 | | No log | 70.4 | 352 | 1.0404 | 0.2507 | 1.0404 | 1.0200 | | No log | 70.8 | 354 | 0.9935 | 0.2881 | 0.9935 | 0.9968 | | No log | 71.2 | 356 | 0.9676 | 0.2781 | 0.9676 | 0.9837 | | No log | 71.6 | 358 | 0.9752 | 0.3052 | 0.9752 | 0.9875 | | No log | 72.0 | 360 | 0.9769 | 0.3052 | 0.9769 | 0.9884 | | No log | 72.4 | 362 | 1.0081 | 0.3052 | 1.0081 | 1.0041 | | No log | 72.8 | 364 | 1.0776 | 0.2524 | 1.0776 | 1.0381 | | No log | 73.2 | 366 | 1.1453 | 0.1943 | 1.1453 | 1.0702 | | No log | 73.6 | 368 | 1.1644 | 0.1873 | 1.1644 | 1.0791 | | No log | 74.0 | 370 | 1.1727 | 0.1873 | 1.1727 | 1.0829 | | No log | 74.4 | 372 | 1.1770 | 0.1873 | 1.1770 | 1.0849 | | No log | 74.8 | 374 | 1.1415 | 0.1873 | 1.1415 | 1.0684 | | No log | 75.2 | 376 | 1.1092 | 0.2115 | 1.1092 | 1.0532 | | No log | 75.6 | 378 | 1.0808 | 0.2898 | 1.0808 | 1.0396 | | No log | 76.0 | 380 | 1.0451 | 0.2948 | 1.0451 | 1.0223 | | No log | 76.4 | 382 | 1.0226 | 0.2806 | 1.0226 | 1.0112 | | No log | 76.8 | 384 | 1.0140 | 0.3029 | 1.0140 | 1.0070 | | No log | 77.2 | 386 | 1.0344 | 0.3161 | 1.0344 | 1.0171 | | No log | 77.6 | 388 | 1.0730 | 0.2802 | 1.0730 | 1.0359 | | No log | 78.0 | 390 | 1.0829 | 0.2687 | 1.0829 | 1.0406 | | No log | 78.4 | 392 | 1.0565 | 0.2802 | 1.0565 | 1.0279 | | No log | 78.8 | 394 | 1.0195 | 0.3110 | 1.0195 | 1.0097 | | No log | 79.2 | 396 | 0.9883 | 0.3082 | 0.9883 | 0.9941 | | No log | 79.6 | 398 | 0.9735 | 0.3082 | 0.9735 | 0.9867 | | No log | 80.0 | 400 | 0.9817 | 0.3082 | 0.9817 | 0.9908 | | No log | 80.4 | 402 | 0.9895 | 0.3082 | 0.9895 | 0.9947 | | No log | 80.8 | 404 | 1.0064 | 0.3082 | 1.0064 | 1.0032 | | No log | 81.2 | 406 | 1.0443 | 0.3110 | 1.0443 | 1.0219 | | No log | 81.6 | 408 | 1.0929 | 0.2601 | 1.0929 | 1.0454 | | No log | 82.0 | 410 | 1.1361 | 0.2319 | 1.1361 | 1.0659 | | No log | 82.4 | 412 | 1.1534 | 0.2280 | 1.1534 | 1.0740 | | No log | 82.8 | 414 | 1.1552 | 0.2280 | 1.1552 | 1.0748 | | No log | 83.2 | 416 | 1.1361 | 0.2280 | 1.1361 | 1.0659 | | No log | 83.6 | 418 | 1.1090 | 0.2319 | 1.1090 | 1.0531 | | No log | 84.0 | 420 | 1.0682 | 0.2643 | 1.0682 | 1.0335 | | No log | 84.4 | 422 | 1.0314 | 0.2898 | 1.0314 | 1.0156 | | No log | 84.8 | 424 | 1.0096 | 0.2577 | 1.0096 | 1.0048 | | No log | 85.2 | 426 | 1.0108 | 0.2806 | 1.0108 | 1.0054 | | No log | 85.6 | 428 | 1.0292 | 0.2948 | 1.0292 | 1.0145 | | No log | 86.0 | 430 | 1.0497 | 0.2850 | 1.0497 | 1.0245 | | No log | 86.4 | 432 | 1.0606 | 0.2545 | 1.0606 | 1.0298 | | No log | 86.8 | 434 | 1.0645 | 0.2590 | 1.0645 | 1.0317 | | No log | 87.2 | 436 | 1.0567 | 0.2590 | 1.0567 | 1.0279 | | No log | 87.6 | 438 | 1.0379 | 0.2590 | 1.0379 | 1.0188 | | No log | 88.0 | 440 | 1.0118 | 0.2756 | 1.0118 | 1.0059 | | No log | 88.4 | 442 | 0.9808 | 0.3029 | 0.9808 | 0.9903 | | No log | 88.8 | 444 | 0.9686 | 0.3029 | 0.9686 | 0.9842 | | No log | 89.2 | 446 | 0.9716 | 0.3029 | 0.9716 | 0.9857 | | No log | 89.6 | 448 | 0.9889 | 0.3029 | 0.9889 | 0.9944 | | No log | 90.0 | 450 | 1.0088 | 0.2977 | 1.0088 | 1.0044 | | No log | 90.4 | 452 | 1.0223 | 0.2898 | 1.0223 | 1.0111 | | No log | 90.8 | 454 | 1.0382 | 0.2898 | 1.0382 | 1.0189 | | No log | 91.2 | 456 | 1.0432 | 0.2590 | 1.0432 | 1.0214 | | No log | 91.6 | 458 | 1.0437 | 0.2898 | 1.0437 | 1.0216 | | No log | 92.0 | 460 | 1.0541 | 0.2590 | 1.0541 | 1.0267 | | No log | 92.4 | 462 | 1.0675 | 0.2590 | 1.0675 | 1.0332 | | No log | 92.8 | 464 | 1.0758 | 0.2590 | 1.0758 | 1.0372 | | No log | 93.2 | 466 | 1.0764 | 0.2481 | 1.0764 | 1.0375 | | No log | 93.6 | 468 | 1.0694 | 0.2590 | 1.0694 | 1.0341 | | No log | 94.0 | 470 | 1.0591 | 0.2898 | 1.0591 | 1.0291 | | No log | 94.4 | 472 | 1.0470 | 0.2898 | 1.0470 | 1.0232 | | No log | 94.8 | 474 | 1.0427 | 0.2898 | 1.0427 | 1.0211 | | No log | 95.2 | 476 | 1.0401 | 0.2898 | 1.0401 | 1.0199 | | No log | 95.6 | 478 | 1.0364 | 0.2898 | 1.0364 | 1.0180 | | No log | 96.0 | 480 | 1.0309 | 0.2898 | 1.0309 | 1.0153 | | No log | 96.4 | 482 | 1.0296 | 0.2898 | 1.0296 | 1.0147 | | No log | 96.8 | 484 | 1.0257 | 0.2898 | 1.0257 | 1.0128 | | No log | 97.2 | 486 | 1.0236 | 0.2898 | 1.0236 | 1.0117 | | No log | 97.6 | 488 | 1.0233 | 0.2898 | 1.0233 | 1.0116 | | No log | 98.0 | 490 | 1.0236 | 0.2898 | 1.0236 | 1.0117 | | No log | 98.4 | 492 | 1.0240 | 0.2898 | 1.0240 | 1.0119 | | No log | 98.8 | 494 | 1.0237 | 0.2898 | 1.0237 | 1.0118 | | No log | 99.2 | 496 | 1.0235 | 0.2898 | 1.0235 | 1.0117 | | No log | 99.6 | 498 | 1.0237 | 0.2898 | 1.0237 | 1.0118 | | 0.1613 | 100.0 | 500 | 1.0238 | 0.2898 | 1.0238 | 1.0119 | ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.0+cu118 - Datasets 2.21.0 - Tokenizers 0.19.1

mamung/345fef6a-8237-4ee7-82b7-ba614660cdd1

mamung

2025-01-21T12:20:18Z

14

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:trl-internal-testing/tiny-random-LlamaForCausalLM", "base_model:adapter:trl-internal-testing/tiny-random-LlamaForCausalLM", "region:us" ]

null

2025-01-21T12:18:20Z

--- library_name: peft base_model: trl-internal-testing/tiny-random-LlamaForCausalLM tags: - axolotl - generated_from_trainer model-index: - name: 345fef6a-8237-4ee7-82b7-ba614660cdd1 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: trl-internal-testing/tiny-random-LlamaForCausalLM bf16: true chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 570f06fa330a02a8_train_data.json ds_type: json format: custom path: /workspace/input_data/570f06fa330a02a8_train_data.json type: field_input: starter_code field_instruction: question_content field_output: test format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 256 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 32 gradient_checkpointing: true group_by_length: false hub_model_id: mamung/345fef6a-8237-4ee7-82b7-ba614660cdd1 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 64 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 32 lora_target_linear: true lora_target_modules: - q_proj - k_proj - v_proj - o_proj lr_scheduler: cosine max_grad_norm: 2 max_steps: 100 micro_batch_size: 2 mlflow_experiment_name: /tmp/570f06fa330a02a8_train_data.json model_type: AutoModelForCausalLM num_epochs: 3 optim_args: adam_beta1: 0.9 adam_beta2: 0.95 adam_epsilon: 1.0e-05 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 2048 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: eddysang wandb_mode: online wandb_name: 835a7d05-70b3-4946-9a54-04ee779c4f19 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 835a7d05-70b3-4946-9a54-04ee779c4f19 warmup_steps: 20 weight_decay: 0.02 xformers_attention: false ``` </details> # 345fef6a-8237-4ee7-82b7-ba614660cdd1 This model is a fine-tuned version of [trl-internal-testing/tiny-random-LlamaForCausalLM](https://huggingface.co/trl-internal-testing/tiny-random-LlamaForCausalLM) on the None dataset. It achieves the following results on the evaluation set: - Loss: 10.2883 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 32 - total_train_batch_size: 64 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.95,adam_epsilon=1e-05 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 20 - training_steps: 86 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.0350 | 1 | 10.3792 | | 10.3758 | 0.2801 | 8 | 10.3774 | | 10.3712 | 0.5602 | 16 | 10.3714 | | 10.3635 | 0.8403 | 24 | 10.3584 | | 13.5544 | 1.1368 | 32 | 10.3373 | | 10.2418 | 1.4168 | 40 | 10.3136 | | 10.2948 | 1.6969 | 48 | 10.2994 | | 10.258 | 1.9770 | 56 | 10.2935 | | 10.1202 | 2.2735 | 64 | 10.2904 | | 10.3454 | 2.5536 | 72 | 10.2889 | | 10.0236 | 2.8337 | 80 | 10.2883 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

tolgaakar/Mistral-Small-Instruct-2409-FP8-Dynamic

tolgaakar

2025-01-21T12:20:13Z

28

0

null

[ "safetensors", "mistral", "base_model:mistralai/Mistral-Small-Instruct-2409", "base_model:quantized:mistralai/Mistral-Small-Instruct-2409", "license:other", "compressed-tensors", "region:us" ]

null

2025-01-21T11:40:26Z

--- license: other license_name: mrl license_link: https://mistral.ai/licenses/MRL-0.1.md base_model: - mistralai/Mistral-Small-Instruct-2409 --- This model was converted to FP8 format from mistralai/Mistral-Small-Instruct-2409 using the llmcompressor library by vLLM. Refer to the [original model card](https://huggingface.co/mistralai/Mistral-Small-Instruct-2409) for more details on the model.

chauhoang/e3c40096-d899-4c00-83fe-a263498a511e

chauhoang

2025-01-21T12:20:02Z

6

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:TinyLlama/TinyLlama-1.1B-Chat-v0.6", "base_model:adapter:TinyLlama/TinyLlama-1.1B-Chat-v0.6", "license:apache-2.0", "region:us" ]

null

2025-01-21T12:16:49Z

--- library_name: peft license: apache-2.0 base_model: TinyLlama/TinyLlama-1.1B-Chat-v0.6 tags: - axolotl - generated_from_trainer model-index: - name: e3c40096-d899-4c00-83fe-a263498a511e results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: TinyLlama/TinyLlama-1.1B-Chat-v0.6 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 5b44368ea0d7d142_train_data.json ds_type: json format: custom path: /workspace/input_data/5b44368ea0d7d142_train_data.json type: field_input: aspect field_instruction: document field_output: summary format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 5 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: chauhoang/e3c40096-d899-4c00-83fe-a263498a511e hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0001 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 5 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 50 micro_batch_size: 2 mlflow_experiment_name: /tmp/5b44368ea0d7d142_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 074be582-c2ba-4209-b6c2-0d56b0df9cdc wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 074be582-c2ba-4209-b6c2-0d56b0df9cdc warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # e3c40096-d899-4c00-83fe-a263498a511e This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-Chat-v0.6](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v0.6) on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.2210 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0001 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 50 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.0047 | 1 | 2.4446 | | 2.5709 | 0.0468 | 10 | 2.4348 | | 2.3494 | 0.0936 | 20 | 2.3377 | | 2.227 | 0.1404 | 30 | 2.2550 | | 2.2299 | 0.1871 | 40 | 2.2244 | | 2.3316 | 0.2339 | 50 | 2.2210 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

trenden/51365222-6e8d-44e5-b9fb-c99768921c36

trenden

2025-01-21T12:18:36Z

6

0

peft

[ "peft", "safetensors", "phi3", "axolotl", "generated_from_trainer", "custom_code", "base_model:microsoft/Phi-3-mini-128k-instruct", "base_model:adapter:microsoft/Phi-3-mini-128k-instruct", "license:mit", "region:us" ]

null

2025-01-21T12:05:23Z

--- library_name: peft license: mit base_model: microsoft/Phi-3-mini-128k-instruct tags: - axolotl - generated_from_trainer model-index: - name: 51365222-6e8d-44e5-b9fb-c99768921c36 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: microsoft/Phi-3-mini-128k-instruct bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - d23a80b910821333_train_data.json ds_type: json format: custom path: /workspace/input_data/d23a80b910821333_train_data.json type: field_input: input field_instruction: instruction field_output: output format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: trenden/51365222-6e8d-44e5-b9fb-c99768921c36 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/d23a80b910821333_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: c7400a48-f57f-4a5f-8c57-bf09a3ce88d3 wandb_project: Birthday-SN56-3-Gradients-On-Demand wandb_run: your_name wandb_runid: c7400a48-f57f-4a5f-8c57-bf09a3ce88d3 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # 51365222-6e8d-44e5-b9fb-c99768921c36 This model is a fine-tuned version of [microsoft/Phi-3-mini-128k-instruct](https://huggingface.co/microsoft/Phi-3-mini-128k-instruct) on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.4281 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 10.658 | 0.0001 | 1 | 2.5837 | | 10.4572 | 0.0002 | 3 | 2.5780 | | 9.8738 | 0.0004 | 6 | 2.5291 | | 8.7801 | 0.0006 | 9 | 2.4281 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

MayBashendy/ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k1_task7_organization

MayBashendy

2025-01-21T12:16:56Z

5

0

transformers

[ "transformers", "safetensors", "bert", "text-classification", "generated_from_trainer", "base_model:aubmindlab/bert-base-arabertv02", "base_model:finetune:aubmindlab/bert-base-arabertv02", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-classification

2025-01-21T12:14:27Z

--- library_name: transformers base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k1_task7_organization results: [] ---  # ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k1_task7_organization This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.7404 - Qwk: 0.3238 - Mse: 0.7404 - Rmse: 0.8605 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 100 ### Training results | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse | Rmse | |:-------------:|:-------:|:----:|:---------------:|:-------:|:------:|:------:| | No log | 0.6667 | 2 | 2.6632 | -0.1213 | 2.6632 | 1.6319 | | No log | 1.3333 | 4 | 1.3882 | 0.1265 | 1.3882 | 1.1782 | | No log | 2.0 | 6 | 1.1319 | -0.0970 | 1.1319 | 1.0639 | | No log | 2.6667 | 8 | 1.0927 | -0.0810 | 1.0927 | 1.0453 | | No log | 3.3333 | 10 | 0.9247 | 0.0058 | 0.9247 | 0.9616 | | No log | 4.0 | 12 | 0.8601 | 0.0236 | 0.8601 | 0.9274 | | No log | 4.6667 | 14 | 0.8247 | 0.0393 | 0.8247 | 0.9081 | | No log | 5.3333 | 16 | 0.7599 | 0.0 | 0.7599 | 0.8717 | | No log | 6.0 | 18 | 0.7561 | 0.0481 | 0.7561 | 0.8696 | | No log | 6.6667 | 20 | 0.7398 | 0.0937 | 0.7398 | 0.8601 | | No log | 7.3333 | 22 | 0.6974 | 0.0889 | 0.6974 | 0.8351 | | No log | 8.0 | 24 | 0.7067 | 0.0840 | 0.7067 | 0.8407 | | No log | 8.6667 | 26 | 0.7288 | 0.1139 | 0.7288 | 0.8537 | | No log | 9.3333 | 28 | 0.7213 | 0.0327 | 0.7213 | 0.8493 | | No log | 10.0 | 30 | 0.6967 | 0.0393 | 0.6967 | 0.8347 | | No log | 10.6667 | 32 | 0.6970 | 0.0846 | 0.6970 | 0.8349 | | No log | 11.3333 | 34 | 0.6807 | 0.1327 | 0.6807 | 0.8251 | | No log | 12.0 | 36 | 0.6864 | 0.2783 | 0.6864 | 0.8285 | | No log | 12.6667 | 38 | 0.7758 | 0.1341 | 0.7758 | 0.8808 | | No log | 13.3333 | 40 | 1.0549 | 0.1650 | 1.0549 | 1.0271 | | No log | 14.0 | 42 | 1.0926 | 0.1753 | 1.0926 | 1.0453 | | No log | 14.6667 | 44 | 0.9507 | 0.1323 | 0.9507 | 0.9750 | | No log | 15.3333 | 46 | 0.9933 | 0.2153 | 0.9933 | 0.9966 | | No log | 16.0 | 48 | 1.0836 | 0.1926 | 1.0836 | 1.0410 | | No log | 16.6667 | 50 | 1.1782 | 0.1077 | 1.1782 | 1.0854 | | No log | 17.3333 | 52 | 1.0397 | 0.1339 | 1.0397 | 1.0196 | | No log | 18.0 | 54 | 0.8137 | 0.2715 | 0.8137 | 0.9021 | | No log | 18.6667 | 56 | 0.7808 | 0.3541 | 0.7808 | 0.8836 | | No log | 19.3333 | 58 | 0.7654 | 0.3622 | 0.7654 | 0.8749 | | No log | 20.0 | 60 | 0.9714 | 0.2239 | 0.9714 | 0.9856 | | No log | 20.6667 | 62 | 1.0619 | 0.2507 | 1.0619 | 1.0305 | | No log | 21.3333 | 64 | 1.0113 | 0.1856 | 1.0113 | 1.0056 | | No log | 22.0 | 66 | 0.8359 | 0.2662 | 0.8359 | 0.9143 | | No log | 22.6667 | 68 | 0.7538 | 0.2414 | 0.7538 | 0.8682 | | No log | 23.3333 | 70 | 0.7411 | 0.2237 | 0.7411 | 0.8609 | | No log | 24.0 | 72 | 0.8121 | 0.2096 | 0.8121 | 0.9012 | | No log | 24.6667 | 74 | 0.9212 | 0.2253 | 0.9212 | 0.9598 | | No log | 25.3333 | 76 | 0.9368 | 0.3586 | 0.9368 | 0.9679 | | No log | 26.0 | 78 | 0.8852 | 0.3344 | 0.8852 | 0.9409 | | No log | 26.6667 | 80 | 0.8121 | 0.3261 | 0.8121 | 0.9012 | | No log | 27.3333 | 82 | 0.8265 | 0.3918 | 0.8265 | 0.9091 | | No log | 28.0 | 84 | 0.8877 | 0.3234 | 0.8877 | 0.9422 | | No log | 28.6667 | 86 | 0.8820 | 0.3099 | 0.8820 | 0.9392 | | No log | 29.3333 | 88 | 0.8031 | 0.3196 | 0.8031 | 0.8962 | | No log | 30.0 | 90 | 0.8070 | 0.3127 | 0.8070 | 0.8983 | | No log | 30.6667 | 92 | 0.9023 | 0.2967 | 0.9023 | 0.9499 | | No log | 31.3333 | 94 | 0.9381 | 0.2692 | 0.9381 | 0.9686 | | No log | 32.0 | 96 | 0.8218 | 0.2967 | 0.8218 | 0.9066 | | No log | 32.6667 | 98 | 0.6896 | 0.2099 | 0.6896 | 0.8304 | | No log | 33.3333 | 100 | 0.6649 | 0.2317 | 0.6649 | 0.8154 | | No log | 34.0 | 102 | 0.6654 | 0.2476 | 0.6654 | 0.8157 | | No log | 34.6667 | 104 | 0.7198 | 0.3840 | 0.7198 | 0.8484 | | No log | 35.3333 | 106 | 0.7595 | 0.4020 | 0.7595 | 0.8715 | | No log | 36.0 | 108 | 0.7477 | 0.3498 | 0.7477 | 0.8647 | | No log | 36.6667 | 110 | 0.7214 | 0.3572 | 0.7214 | 0.8494 | | No log | 37.3333 | 112 | 0.7180 | 0.2379 | 0.7180 | 0.8474 | | No log | 38.0 | 114 | 0.7629 | 0.1972 | 0.7629 | 0.8735 | | No log | 38.6667 | 116 | 0.7824 | 0.1972 | 0.7824 | 0.8845 | | No log | 39.3333 | 118 | 0.7750 | 0.1972 | 0.7750 | 0.8804 | | No log | 40.0 | 120 | 0.7531 | 0.2652 | 0.7531 | 0.8678 | | No log | 40.6667 | 122 | 0.7773 | 0.2171 | 0.7773 | 0.8817 | | No log | 41.3333 | 124 | 0.8507 | 0.2692 | 0.8507 | 0.9223 | | No log | 42.0 | 126 | 0.9124 | 0.3234 | 0.9124 | 0.9552 | | No log | 42.6667 | 128 | 0.8637 | 0.2967 | 0.8637 | 0.9293 | | No log | 43.3333 | 130 | 0.8389 | 0.2967 | 0.8389 | 0.9159 | | No log | 44.0 | 132 | 0.7617 | 0.2498 | 0.7617 | 0.8727 | | No log | 44.6667 | 134 | 0.7038 | 0.3341 | 0.7038 | 0.8390 | | No log | 45.3333 | 136 | 0.6932 | 0.2981 | 0.6932 | 0.8326 | | No log | 46.0 | 138 | 0.6988 | 0.3894 | 0.6988 | 0.8359 | | No log | 46.6667 | 140 | 0.7067 | 0.3894 | 0.7067 | 0.8406 | | No log | 47.3333 | 142 | 0.7387 | 0.3399 | 0.7387 | 0.8595 | | No log | 48.0 | 144 | 0.7523 | 0.3590 | 0.7523 | 0.8673 | | No log | 48.6667 | 146 | 0.7570 | 0.3590 | 0.7570 | 0.8701 | | No log | 49.3333 | 148 | 0.8021 | 0.3940 | 0.8021 | 0.8956 | | No log | 50.0 | 150 | 0.7996 | 0.4329 | 0.7996 | 0.8942 | | No log | 50.6667 | 152 | 0.7466 | 0.3590 | 0.7466 | 0.8640 | | No log | 51.3333 | 154 | 0.6695 | 0.3788 | 0.6695 | 0.8182 | | No log | 52.0 | 156 | 0.6423 | 0.3070 | 0.6423 | 0.8015 | | No log | 52.6667 | 158 | 0.6455 | 0.3336 | 0.6455 | 0.8034 | | No log | 53.3333 | 160 | 0.6411 | 0.3070 | 0.6411 | 0.8007 | | No log | 54.0 | 162 | 0.6462 | 0.3599 | 0.6462 | 0.8039 | | No log | 54.6667 | 164 | 0.6690 | 0.3524 | 0.6690 | 0.8179 | | No log | 55.3333 | 166 | 0.6858 | 0.3267 | 0.6858 | 0.8281 | | No log | 56.0 | 168 | 0.7004 | 0.3545 | 0.7004 | 0.8369 | | No log | 56.6667 | 170 | 0.7119 | 0.3545 | 0.7119 | 0.8437 | | No log | 57.3333 | 172 | 0.7268 | 0.3060 | 0.7268 | 0.8525 | | No log | 58.0 | 174 | 0.7169 | 0.3127 | 0.7169 | 0.8467 | | No log | 58.6667 | 176 | 0.6937 | 0.3498 | 0.6937 | 0.8329 | | No log | 59.3333 | 178 | 0.6644 | 0.3524 | 0.6644 | 0.8151 | | No log | 60.0 | 180 | 0.6653 | 0.3170 | 0.6653 | 0.8157 | | No log | 60.6667 | 182 | 0.6667 | 0.3481 | 0.6667 | 0.8165 | | No log | 61.3333 | 184 | 0.6775 | 0.3860 | 0.6775 | 0.8231 | | No log | 62.0 | 186 | 0.6774 | 0.3806 | 0.6774 | 0.8230 | | No log | 62.6667 | 188 | 0.6643 | 0.2652 | 0.6643 | 0.8150 | | No log | 63.3333 | 190 | 0.6663 | 0.3280 | 0.6663 | 0.8163 | | No log | 64.0 | 192 | 0.6705 | 0.3280 | 0.6705 | 0.8188 | | No log | 64.6667 | 194 | 0.6854 | 0.2973 | 0.6854 | 0.8279 | | No log | 65.3333 | 196 | 0.6973 | 0.3524 | 0.6973 | 0.8350 | | No log | 66.0 | 198 | 0.7181 | 0.3840 | 0.7181 | 0.8474 | | No log | 66.6667 | 200 | 0.7369 | 0.3425 | 0.7369 | 0.8584 | | No log | 67.3333 | 202 | 0.7561 | 0.3060 | 0.7561 | 0.8695 | | No log | 68.0 | 204 | 0.7591 | 0.2754 | 0.7591 | 0.8712 | | No log | 68.6667 | 206 | 0.7362 | 0.3060 | 0.7362 | 0.8580 | | No log | 69.3333 | 208 | 0.7107 | 0.2558 | 0.7107 | 0.8430 | | No log | 70.0 | 210 | 0.7025 | 0.3267 | 0.7025 | 0.8382 | | No log | 70.6667 | 212 | 0.6982 | 0.3267 | 0.6982 | 0.8356 | | No log | 71.3333 | 214 | 0.7089 | 0.3267 | 0.7089 | 0.8420 | | No log | 72.0 | 216 | 0.7317 | 0.3545 | 0.7317 | 0.8554 | | No log | 72.6667 | 218 | 0.7634 | 0.2754 | 0.7634 | 0.8737 | | No log | 73.3333 | 220 | 0.8069 | 0.3169 | 0.8069 | 0.8983 | | No log | 74.0 | 222 | 0.8195 | 0.3675 | 0.8195 | 0.9053 | | No log | 74.6667 | 224 | 0.8127 | 0.3564 | 0.8127 | 0.9015 | | No log | 75.3333 | 226 | 0.8149 | 0.3564 | 0.8149 | 0.9027 | | No log | 76.0 | 228 | 0.7888 | 0.3032 | 0.7888 | 0.8881 | | No log | 76.6667 | 230 | 0.7572 | 0.3518 | 0.7572 | 0.8702 | | No log | 77.3333 | 232 | 0.7508 | 0.3518 | 0.7508 | 0.8665 | | No log | 78.0 | 234 | 0.7350 | 0.3312 | 0.7350 | 0.8573 | | No log | 78.6667 | 236 | 0.7308 | 0.3312 | 0.7308 | 0.8549 | | No log | 79.3333 | 238 | 0.7419 | 0.3594 | 0.7419 | 0.8613 | | No log | 80.0 | 240 | 0.7610 | 0.3518 | 0.7610 | 0.8724 | | No log | 80.6667 | 242 | 0.7882 | 0.3302 | 0.7882 | 0.8878 | | No log | 81.3333 | 244 | 0.8140 | 0.3564 | 0.8140 | 0.9022 | | No log | 82.0 | 246 | 0.8316 | 0.3819 | 0.8316 | 0.9119 | | No log | 82.6667 | 248 | 0.8344 | 0.3819 | 0.8344 | 0.9135 | | No log | 83.3333 | 250 | 0.8211 | 0.3819 | 0.8211 | 0.9062 | | No log | 84.0 | 252 | 0.7963 | 0.3564 | 0.7963 | 0.8924 | | No log | 84.6667 | 254 | 0.7777 | 0.3302 | 0.7777 | 0.8819 | | No log | 85.3333 | 256 | 0.7631 | 0.3444 | 0.7631 | 0.8736 | | No log | 86.0 | 258 | 0.7530 | 0.3444 | 0.7530 | 0.8678 | | No log | 86.6667 | 260 | 0.7475 | 0.3444 | 0.7475 | 0.8646 | | No log | 87.3333 | 262 | 0.7487 | 0.3444 | 0.7487 | 0.8652 | | No log | 88.0 | 264 | 0.7545 | 0.3032 | 0.7545 | 0.8686 | | No log | 88.6667 | 266 | 0.7650 | 0.3032 | 0.7650 | 0.8747 | | No log | 89.3333 | 268 | 0.7701 | 0.3032 | 0.7701 | 0.8776 | | No log | 90.0 | 270 | 0.7715 | 0.3032 | 0.7715 | 0.8783 | | No log | 90.6667 | 272 | 0.7700 | 0.3032 | 0.7700 | 0.8775 | | No log | 91.3333 | 274 | 0.7710 | 0.3032 | 0.7710 | 0.8781 | | No log | 92.0 | 276 | 0.7701 | 0.3032 | 0.7701 | 0.8775 | | No log | 92.6667 | 278 | 0.7653 | 0.3032 | 0.7653 | 0.8748 | | No log | 93.3333 | 280 | 0.7617 | 0.3032 | 0.7617 | 0.8727 | | No log | 94.0 | 282 | 0.7548 | 0.3444 | 0.7548 | 0.8688 | | No log | 94.6667 | 284 | 0.7498 | 0.3167 | 0.7498 | 0.8659 | | No log | 95.3333 | 286 | 0.7451 | 0.3238 | 0.7451 | 0.8632 | | No log | 96.0 | 288 | 0.7421 | 0.3238 | 0.7421 | 0.8615 | | No log | 96.6667 | 290 | 0.7399 | 0.3238 | 0.7399 | 0.8602 | | No log | 97.3333 | 292 | 0.7388 | 0.3238 | 0.7388 | 0.8595 | | No log | 98.0 | 294 | 0.7384 | 0.3238 | 0.7384 | 0.8593 | | No log | 98.6667 | 296 | 0.7393 | 0.3238 | 0.7393 | 0.8598 | | No log | 99.3333 | 298 | 0.7400 | 0.3238 | 0.7400 | 0.8603 | | No log | 100.0 | 300 | 0.7404 | 0.3238 | 0.7404 | 0.8605 | ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.0+cu118 - Datasets 2.21.0 - Tokenizers 0.19.1

nhung02/909af27c-2380-46a2-abbd-cd15fe4d4de0

nhung02

2025-01-21T12:16:53Z

8

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:heegyu/WizardVicuna-open-llama-3b-v2", "base_model:adapter:heegyu/WizardVicuna-open-llama-3b-v2", "license:apache-2.0", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-21T11:51:36Z

--- library_name: peft license: apache-2.0 base_model: heegyu/WizardVicuna-open-llama-3b-v2 tags: - axolotl - generated_from_trainer model-index: - name: 909af27c-2380-46a2-abbd-cd15fe4d4de0 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: heegyu/WizardVicuna-open-llama-3b-v2 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 0eba3e80d15355a6_train_data.json ds_type: json format: custom path: /workspace/input_data/0eba3e80d15355a6_train_data.json type: field_input: input field_instruction: instruction field_output: accepted format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: nhung02/909af27c-2380-46a2-abbd-cd15fe4d4de0 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/0eba3e80d15355a6_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 special_tokens: pad_token: </s> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 84f8a085-50df-4e7c-9e21-f8d55ac51824 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 84f8a085-50df-4e7c-9e21-f8d55ac51824 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details> # 909af27c-2380-46a2-abbd-cd15fe4d4de0 This model is a fine-tuned version of [heegyu/WizardVicuna-open-llama-3b-v2](https://huggingface.co/heegyu/WizardVicuna-open-llama-3b-v2) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.7229 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.6899 | 0.0313 | 200 | 0.7229 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

ivangrapher/744e6875-2fc5-49e8-9a0e-2975ca5870ac

ivangrapher

2025-01-21T12:15:54Z

6

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:unsloth/llama-2-7b-chat", "base_model:adapter:unsloth/llama-2-7b-chat", "license:apache-2.0", "region:us" ]

null

2025-01-21T08:34:31Z

--- library_name: peft license: apache-2.0 base_model: unsloth/llama-2-7b-chat tags: - axolotl - generated_from_trainer model-index: - name: 744e6875-2fc5-49e8-9a0e-2975ca5870ac results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/llama-2-7b-chat bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 124bc05ddbf5ee81_train_data.json ds_type: json format: custom path: /workspace/input_data/124bc05ddbf5ee81_train_data.json type: field_instruction: docstring field_output: summary format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: null eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: false hub_model_id: ivangrapher/744e6875-2fc5-49e8-9a0e-2975ca5870ac hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 75GiB max_steps: 30 micro_batch_size: 2 mlflow_experiment_name: /tmp/124bc05ddbf5ee81_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 15 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 5fe9995d-0a95-46fa-b89c-25f97cbb6eb6 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 5fe9995d-0a95-46fa-b89c-25f97cbb6eb6 warmup_steps: 15 weight_decay: 0.01 xformers_attention: true ``` </details> # 744e6875-2fc5-49e8-9a0e-2975ca5870ac This model is a fine-tuned version of [unsloth/llama-2-7b-chat](https://huggingface.co/unsloth/llama-2-7b-chat) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 15 - training_steps: 30 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.0000 | 1 | nan | | 0.0 | 0.0001 | 5 | nan | | 0.0 | 0.0002 | 10 | nan | | 0.0 | 0.0003 | 15 | nan | | 0.0 | 0.0003 | 20 | nan | | 0.0 | 0.0004 | 25 | nan | | 0.0 | 0.0005 | 30 | nan | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

kokovova/28cfc357-be2e-4eb7-87e6-ede5f44cf913

kokovova

2025-01-21T12:15:28Z

5

0

peft

[ "peft", "safetensors", "gpt_neox", "axolotl", "generated_from_trainer", "base_model:databricks/dolly-v2-3b", "base_model:adapter:databricks/dolly-v2-3b", "license:mit", "region:us" ]

null

2025-01-21T11:32:50Z

--- library_name: peft license: mit base_model: databricks/dolly-v2-3b tags: - axolotl - generated_from_trainer model-index: - name: 28cfc357-be2e-4eb7-87e6-ede5f44cf913 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: databricks/dolly-v2-3b bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - d4ad1f4ec6a1fae0_train_data.json ds_type: json format: custom path: /workspace/input_data/d4ad1f4ec6a1fae0_train_data.json type: field_instruction: Patient field_output: Description format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: 1 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: true hub_model_id: kokovova/28cfc357-be2e-4eb7-87e6-ede5f44cf913 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 79GiB max_steps: 30 micro_batch_size: 4 mlflow_experiment_name: /tmp/d4ad1f4ec6a1fae0_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optim_args: adam_beta1: 0.9 adam_beta2: 0.95 adam_epsilon: 1e-5 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 6874924e-0eae-4909-b19a-0c7087adfd79 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 6874924e-0eae-4909-b19a-0c7087adfd79 warmup_steps: 5 weight_decay: 0.001 xformers_attention: true ``` </details> # 28cfc357-be2e-4eb7-87e6-ede5f44cf913 This model is a fine-tuned version of [databricks/dolly-v2-3b](https://huggingface.co/databricks/dolly-v2-3b) on the None dataset. It achieves the following results on the evaluation set: - Loss: 3.0565 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 16 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.95,adam_epsilon=1e-5 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 30 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.0001 | 1 | 3.7270 | | 13.4442 | 0.0003 | 5 | 3.4392 | | 12.3538 | 0.0007 | 10 | 3.1945 | | 11.8357 | 0.0010 | 15 | 3.1070 | | 11.9725 | 0.0013 | 20 | 3.0723 | | 12.3078 | 0.0016 | 25 | 3.0603 | | 12.0133 | 0.0020 | 30 | 3.0565 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

ClarenceDan/7a6c4aff-60cf-4296-906d-a04240417885

ClarenceDan

2025-01-21T12:14:35Z

8

0

peft

[ "peft", "safetensors", "bloom", "axolotl", "generated_from_trainer", "base_model:bigscience/bloom-560m", "base_model:adapter:bigscience/bloom-560m", "license:bigscience-bloom-rail-1.0", "region:us" ]

null

2025-01-21T12:14:06Z

--- library_name: peft license: bigscience-bloom-rail-1.0 base_model: bigscience/bloom-560m tags: - axolotl - generated_from_trainer model-index: - name: 7a6c4aff-60cf-4296-906d-a04240417885 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: bigscience/bloom-560m bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 5c4eef0d51e921ea_train_data.json ds_type: json format: custom path: /workspace/input_data/5c4eef0d51e921ea_train_data.json type: field_input: world_literals field_instruction: logical_form_pretty field_output: question format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: ClarenceDan/7a6c4aff-60cf-4296-906d-a04240417885 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/5c4eef0d51e921ea_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 847dcfd1-dbaf-4b00-af61-47e0ea3d66d1 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 847dcfd1-dbaf-4b00-af61-47e0ea3d66d1 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # 7a6c4aff-60cf-4296-906d-a04240417885 This model is a fine-tuned version of [bigscience/bloom-560m](https://huggingface.co/bigscience/bloom-560m) on the None dataset. It achieves the following results on the evaluation set: - Loss: 3.1212 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 14.3622 | 0.0033 | 1 | 3.6128 | | 14.3937 | 0.0098 | 3 | 3.5999 | | 14.6205 | 0.0197 | 6 | 3.4420 | | 12.5179 | 0.0295 | 9 | 3.1212 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

mrHungddddh/fbb70a8d-5819-43ab-ad46-15fd560412cd

mrHungddddh

2025-01-21T12:13:42Z

6

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:unsloth/Llama-3.1-Storm-8B", "base_model:adapter:unsloth/Llama-3.1-Storm-8B", "license:llama3.1", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-21T11:41:48Z

--- library_name: peft license: llama3.1 base_model: unsloth/Llama-3.1-Storm-8B tags: - axolotl - generated_from_trainer model-index: - name: fbb70a8d-5819-43ab-ad46-15fd560412cd results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/Llama-3.1-Storm-8B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - dc5c201d257f4800_train_data.json ds_type: json format: custom path: /workspace/input_data/dc5c201d257f4800_train_data.json type: field_instruction: instruction field_output: output format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: mrHungddddh/fbb70a8d-5819-43ab-ad46-15fd560412cd hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/dc5c201d257f4800_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 1fb620f4-588e-4556-8dd0-8ed7c42fd6cc wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 1fb620f4-588e-4556-8dd0-8ed7c42fd6cc warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details> # fbb70a8d-5819-43ab-ad46-15fd560412cd This model is a fine-tuned version of [unsloth/Llama-3.1-Storm-8B](https://huggingface.co/unsloth/Llama-3.1-Storm-8B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.6449 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.39 | 0.0681 | 200 | 0.6449 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

vertings6/46326f04-0a71-4c3b-a8ef-4c0ff1144789

vertings6

2025-01-21T12:13:16Z

6

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "custom_code", "base_model:NousResearch/Yarn-Llama-2-7b-64k", "base_model:adapter:NousResearch/Yarn-Llama-2-7b-64k", "region:us" ]

null

2025-01-21T12:12:14Z

--- library_name: peft base_model: NousResearch/Yarn-Llama-2-7b-64k tags: - axolotl - generated_from_trainer model-index: - name: 46326f04-0a71-4c3b-a8ef-4c0ff1144789 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: NousResearch/Yarn-Llama-2-7b-64k bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 6f632f47d3ee06ff_train_data.json ds_type: json format: custom path: /workspace/input_data/6f632f47d3ee06ff_train_data.json type: field_input: choices field_instruction: question field_output: answer format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: 1 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: true hub_model_id: vertings6/46326f04-0a71-4c3b-a8ef-4c0ff1144789 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 79GiB max_steps: 30 micro_batch_size: 4 mlflow_experiment_name: /tmp/6f632f47d3ee06ff_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optim_args: adam_beta1: 0.9 adam_beta2: 0.95 adam_epsilon: 1e-5 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: a2153675-d455-4bd4-a862-69a06baed90a wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: a2153675-d455-4bd4-a862-69a06baed90a warmup_steps: 5 weight_decay: 0.001 xformers_attention: true ``` </details> # 46326f04-0a71-4c3b-a8ef-4c0ff1144789 This model is a fine-tuned version of [NousResearch/Yarn-Llama-2-7b-64k](https://huggingface.co/NousResearch/Yarn-Llama-2-7b-64k) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.2940 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 16 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.95,adam_epsilon=1e-5 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 7 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.1538 | 1 | 1.5155 | | 6.176 | 0.7692 | 5 | 1.2940 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

nhung01/eaf0f1fd-8467-470a-aa52-e26bbce9c105

nhung01

2025-01-21T12:11:02Z

6

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:codellama/CodeLlama-7b-Instruct-hf", "base_model:adapter:codellama/CodeLlama-7b-Instruct-hf", "license:llama2", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-21T11:54:14Z

--- library_name: peft license: llama2 base_model: codellama/CodeLlama-7b-Instruct-hf tags: - axolotl - generated_from_trainer model-index: - name: eaf0f1fd-8467-470a-aa52-e26bbce9c105 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: codellama/CodeLlama-7b-Instruct-hf bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - e61b15027cdb8f0f_train_data.json ds_type: json format: custom path: /workspace/input_data/e61b15027cdb8f0f_train_data.json type: field_instruction: text_description field_output: text format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: nhung01/eaf0f1fd-8467-470a-aa52-e26bbce9c105 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/e61b15027cdb8f0f_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 special_tokens: pad_token: </s> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 52dcb611-f58d-420b-a954-552a3249dfec wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 52dcb611-f58d-420b-a954-552a3249dfec warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details> # eaf0f1fd-8467-470a-aa52-e26bbce9c105 This model is a fine-tuned version of [codellama/CodeLlama-7b-Instruct-hf](https://huggingface.co/codellama/CodeLlama-7b-Instruct-hf) on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.1119 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 1.9689 | 0.0800 | 200 | 2.1119 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

thaffggg/91ed7274-5dc1-4bef-99e1-48c9fd775ff6

thaffggg

2025-01-21T12:09:40Z

6

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:heegyu/WizardVicuna-open-llama-3b-v2", "base_model:adapter:heegyu/WizardVicuna-open-llama-3b-v2", "license:apache-2.0", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-21T11:51:42Z

--- library_name: peft license: apache-2.0 base_model: heegyu/WizardVicuna-open-llama-3b-v2 tags: - axolotl - generated_from_trainer model-index: - name: 91ed7274-5dc1-4bef-99e1-48c9fd775ff6 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: heegyu/WizardVicuna-open-llama-3b-v2 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 0eba3e80d15355a6_train_data.json ds_type: json format: custom path: /workspace/input_data/0eba3e80d15355a6_train_data.json type: field_input: input field_instruction: instruction field_output: accepted format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: thaffggg/91ed7274-5dc1-4bef-99e1-48c9fd775ff6 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/0eba3e80d15355a6_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 special_tokens: pad_token: </s> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 84f8a085-50df-4e7c-9e21-f8d55ac51824 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 84f8a085-50df-4e7c-9e21-f8d55ac51824 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details> # 91ed7274-5dc1-4bef-99e1-48c9fd775ff6 This model is a fine-tuned version of [heegyu/WizardVicuna-open-llama-3b-v2](https://huggingface.co/heegyu/WizardVicuna-open-llama-3b-v2) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.7231 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.6918 | 0.0313 | 200 | 0.7231 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

philip-hightech/9312526f-695d-4bea-b99b-212790fd97bb

philip-hightech

2025-01-21T12:09:21Z

6

0

peft

[ "peft", "safetensors", "mistral", "axolotl", "generated_from_trainer", "base_model:Intel/neural-chat-7b-v3-3", "base_model:adapter:Intel/neural-chat-7b-v3-3", "license:apache-2.0", "region:us" ]

null

2025-01-21T12:07:17Z

--- library_name: peft license: apache-2.0 base_model: Intel/neural-chat-7b-v3-3 tags: - axolotl - generated_from_trainer model-index: - name: 9312526f-695d-4bea-b99b-212790fd97bb results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: Intel/neural-chat-7b-v3-3 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - b5e06bf0e602bd38_train_data.json ds_type: json format: custom path: /workspace/input_data/b5e06bf0e602bd38_train_data.json type: field_instruction: section field_output: text format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: philip-hightech/9312526f-695d-4bea-b99b-212790fd97bb hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/b5e06bf0e602bd38_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 special_tokens: pad_token: </s> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 5312563a-16b4-452e-84f7-611f95b514ff wandb_project: Mine-SN56-21-Gradients-On-Demand wandb_run: your_name wandb_runid: 5312563a-16b4-452e-84f7-611f95b514ff warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # 9312526f-695d-4bea-b99b-212790fd97bb This model is a fine-tuned version of [Intel/neural-chat-7b-v3-3](https://huggingface.co/Intel/neural-chat-7b-v3-3) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.0 | 0.0010 | 1 | nan | | 0.0 | 0.0030 | 3 | nan | | 0.0 | 0.0059 | 6 | nan | | 0.0 | 0.0089 | 9 | nan | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

kostiantynk1205/96658c36-8901-4700-8dc4-7caa48990751

kostiantynk1205

2025-01-21T12:09:11Z

6

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:oopsung/llama2-7b-n-ox-test-v1", "base_model:adapter:oopsung/llama2-7b-n-ox-test-v1", "region:us" ]

null

2025-01-21T12:03:08Z

--- library_name: peft base_model: oopsung/llama2-7b-n-ox-test-v1 tags: - axolotl - generated_from_trainer model-index: - name: 96658c36-8901-4700-8dc4-7caa48990751 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: oopsung/llama2-7b-n-ox-test-v1 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - dddb0489dc663e1a_train_data.json ds_type: json format: custom path: /workspace/input_data/dddb0489dc663e1a_train_data.json type: field_input: Context field_instruction: Question field_output: Answers format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: kostiantynk1205/96658c36-8901-4700-8dc4-7caa48990751 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/dddb0489dc663e1a_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: bbd202cf-ffeb-42f5-82b2-0c60d893aeab wandb_project: Birthday-SN56-23-Gradients-On-Demand wandb_run: your_name wandb_runid: bbd202cf-ffeb-42f5-82b2-0c60d893aeab warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # 96658c36-8901-4700-8dc4-7caa48990751 This model is a fine-tuned version of [oopsung/llama2-7b-n-ox-test-v1](https://huggingface.co/oopsung/llama2-7b-n-ox-test-v1) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.0 | 0.0003 | 1 | nan | | 0.0 | 0.0008 | 3 | nan | | 0.0 | 0.0017 | 6 | nan | | 0.0 | 0.0025 | 9 | nan | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

ClarenceDan/fd941b3a-7d6d-4a90-a386-08b3ed99ba71

ClarenceDan

2025-01-21T12:08:08Z

6

0

peft

[ "peft", "safetensors", "mistral", "axolotl", "generated_from_trainer", "base_model:Artples/L-MChat-7b", "base_model:adapter:Artples/L-MChat-7b", "license:apache-2.0", "region:us" ]

null

2025-01-21T12:06:27Z

--- library_name: peft license: apache-2.0 base_model: Artples/L-MChat-7b tags: - axolotl - generated_from_trainer model-index: - name: fd941b3a-7d6d-4a90-a386-08b3ed99ba71 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: Artples/L-MChat-7b bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - df03514e65800f80_train_data.json ds_type: json format: custom path: /workspace/input_data/df03514e65800f80_train_data.json type: field_instruction: input field_output: response format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: ClarenceDan/fd941b3a-7d6d-4a90-a386-08b3ed99ba71 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/df03514e65800f80_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 special_tokens: pad_token: <|end_of_turn|> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: e3508d62-5471-4cdf-8dba-5844f441931a wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: e3508d62-5471-4cdf-8dba-5844f441931a warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # fd941b3a-7d6d-4a90-a386-08b3ed99ba71 This model is a fine-tuned version of [Artples/L-MChat-7b](https://huggingface.co/Artples/L-MChat-7b) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.0 | 0.0011 | 1 | nan | | 0.0 | 0.0034 | 3 | nan | | 0.0 | 0.0068 | 6 | nan | | 0.0 | 0.0101 | 9 | nan | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

havinash-ai/0c7eaea0-bf84-47bb-838e-c5ec19a67fe9

havinash-ai

2025-01-21T12:08:02Z

5

0

peft

[ "peft", "safetensors", "gpt_neox", "axolotl", "generated_from_trainer", "base_model:databricks/dolly-v2-3b", "base_model:adapter:databricks/dolly-v2-3b", "license:mit", "region:us" ]

null

2025-01-21T11:50:34Z

--- library_name: peft license: mit base_model: databricks/dolly-v2-3b tags: - axolotl - generated_from_trainer model-index: - name: 0c7eaea0-bf84-47bb-838e-c5ec19a67fe9 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: databricks/dolly-v2-3b bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - d4ad1f4ec6a1fae0_train_data.json ds_type: json format: custom path: /workspace/input_data/d4ad1f4ec6a1fae0_train_data.json type: field_instruction: Patient field_output: Description format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: havinash-ai/0c7eaea0-bf84-47bb-838e-c5ec19a67fe9 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/d4ad1f4ec6a1fae0_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 6874924e-0eae-4909-b19a-0c7087adfd79 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 6874924e-0eae-4909-b19a-0c7087adfd79 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # 0c7eaea0-bf84-47bb-838e-c5ec19a67fe9 This model is a fine-tuned version of [databricks/dolly-v2-3b](https://huggingface.co/databricks/dolly-v2-3b) on the None dataset. It achieves the following results on the evaluation set: - Loss: 3.1139 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 14.3662 | 0.0000 | 1 | 4.0295 | | 13.6342 | 0.0001 | 3 | 4.0051 | | 18.6691 | 0.0002 | 6 | 3.7901 | | 13.7199 | 0.0003 | 9 | 3.1139 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

nhungphammmmm/a916d37c-5230-43a3-ad27-5b9669db8192

nhungphammmmm

2025-01-21T12:07:53Z

6

0

peft

[ "peft", "safetensors", "phi3", "axolotl", "generated_from_trainer", "custom_code", "base_model:microsoft/Phi-3-mini-128k-instruct", "base_model:adapter:microsoft/Phi-3-mini-128k-instruct", "license:mit", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-21T11:49:16Z

--- library_name: peft license: mit base_model: microsoft/Phi-3-mini-128k-instruct tags: - axolotl - generated_from_trainer model-index: - name: a916d37c-5230-43a3-ad27-5b9669db8192 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: microsoft/Phi-3-mini-128k-instruct bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - d23a80b910821333_train_data.json ds_type: json format: custom path: /workspace/input_data/d23a80b910821333_train_data.json type: field_input: input field_instruction: instruction field_output: output format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: nhungphammmmm/a916d37c-5230-43a3-ad27-5b9669db8192 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/d23a80b910821333_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: c7400a48-f57f-4a5f-8c57-bf09a3ce88d3 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: c7400a48-f57f-4a5f-8c57-bf09a3ce88d3 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details> # a916d37c-5230-43a3-ad27-5b9669db8192 This model is a fine-tuned version of [microsoft/Phi-3-mini-128k-instruct](https://huggingface.co/microsoft/Phi-3-mini-128k-instruct) on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.1734 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 8.2072 | 0.0143 | 200 | 2.1734 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

hongngo/d131082f-bd87-4d91-b9ee-d2089181769a

hongngo

2025-01-21T12:04:36Z

6

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:unsloth/Llama-3.1-Storm-8B", "base_model:adapter:unsloth/Llama-3.1-Storm-8B", "license:llama3.1", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-21T11:41:40Z

--- library_name: peft license: llama3.1 base_model: unsloth/Llama-3.1-Storm-8B tags: - axolotl - generated_from_trainer model-index: - name: d131082f-bd87-4d91-b9ee-d2089181769a results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/Llama-3.1-Storm-8B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - dc5c201d257f4800_train_data.json ds_type: json format: custom path: /workspace/input_data/dc5c201d257f4800_train_data.json type: field_instruction: instruction field_output: output format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: hongngo/d131082f-bd87-4d91-b9ee-d2089181769a hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/dc5c201d257f4800_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 1fb620f4-588e-4556-8dd0-8ed7c42fd6cc wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 1fb620f4-588e-4556-8dd0-8ed7c42fd6cc warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details> # d131082f-bd87-4d91-b9ee-d2089181769a This model is a fine-tuned version of [unsloth/Llama-3.1-Storm-8B](https://huggingface.co/unsloth/Llama-3.1-Storm-8B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.6455 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.3866 | 0.0681 | 200 | 0.6455 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

trangtrannnnn/91e46b57-4c5a-411c-9cd3-585cb158ce5e

trangtrannnnn

2025-01-21T12:03:49Z

5

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:NousResearch/Nous-Hermes-llama-2-7b", "base_model:adapter:NousResearch/Nous-Hermes-llama-2-7b", "license:mit", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-21T11:41:25Z

--- library_name: peft license: mit base_model: NousResearch/Nous-Hermes-llama-2-7b tags: - axolotl - generated_from_trainer model-index: - name: 91e46b57-4c5a-411c-9cd3-585cb158ce5e results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: NousResearch/Nous-Hermes-llama-2-7b bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - db35a4b2827972f9_train_data.json ds_type: json format: custom path: /workspace/input_data/db35a4b2827972f9_train_data.json type: field_input: rejected field_instruction: context field_output: chosen format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: trangtrannnnn/91e46b57-4c5a-411c-9cd3-585cb158ce5e hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/db35a4b2827972f9_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 881827a9-7bb9-4a3a-bfa5-bc8cbc8f588f wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 881827a9-7bb9-4a3a-bfa5-bc8cbc8f588f warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details> # 91e46b57-4c5a-411c-9cd3-585cb158ce5e This model is a fine-tuned version of [NousResearch/Nous-Hermes-llama-2-7b](https://huggingface.co/NousResearch/Nous-Hermes-llama-2-7b) on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.1095 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 1.8807 | 0.0294 | 200 | 2.1095 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

lesso02/afd91423-4ee5-4fb8-a211-976981cf01f6

lesso02

2025-01-21T12:03:00Z

6

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:oopsung/llama2-7b-n-ox-test-v1", "base_model:adapter:oopsung/llama2-7b-n-ox-test-v1", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-21T11:38:23Z

--- library_name: peft base_model: oopsung/llama2-7b-n-ox-test-v1 tags: - axolotl - generated_from_trainer model-index: - name: afd91423-4ee5-4fb8-a211-976981cf01f6 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: oopsung/llama2-7b-n-ox-test-v1 bf16: true chat_template: llama3 datasets: - data_files: - dddb0489dc663e1a_train_data.json ds_type: json format: custom path: /workspace/input_data/dddb0489dc663e1a_train_data.json type: field_input: Context field_instruction: Question field_output: Answers format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: 2 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null flash_attention: false fp16: false fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: lesso02/afd91423-4ee5-4fb8-a211-976981cf01f6 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 25 micro_batch_size: 2 mlflow_experiment_name: /tmp/dddb0489dc663e1a_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: bbd202cf-ffeb-42f5-82b2-0c60d893aeab wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: bbd202cf-ffeb-42f5-82b2-0c60d893aeab warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # afd91423-4ee5-4fb8-a211-976981cf01f6 This model is a fine-tuned version of [oopsung/llama2-7b-n-ox-test-v1](https://huggingface.co/oopsung/llama2-7b-n-ox-test-v1) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 25 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.0 | 0.0003 | 1 | nan | | 0.0 | 0.0014 | 5 | nan | | 0.0 | 0.0028 | 10 | nan | | 0.0 | 0.0042 | 15 | nan | | 0.0 | 0.0056 | 20 | nan | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

kostiantynk1205/524eee36-38c7-4c32-811d-314e799d4341

kostiantynk1205

2025-01-21T12:01:21Z

5

0

peft

[ "peft", "safetensors", "gpt_neox", "axolotl", "generated_from_trainer", "base_model:databricks/dolly-v2-3b", "base_model:adapter:databricks/dolly-v2-3b", "license:mit", "region:us" ]

null

2025-01-21T11:44:21Z

--- library_name: peft license: mit base_model: databricks/dolly-v2-3b tags: - axolotl - generated_from_trainer model-index: - name: 524eee36-38c7-4c32-811d-314e799d4341 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: databricks/dolly-v2-3b bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - d4ad1f4ec6a1fae0_train_data.json ds_type: json format: custom path: /workspace/input_data/d4ad1f4ec6a1fae0_train_data.json type: field_instruction: Patient field_output: Description format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: kostiantynk1205/524eee36-38c7-4c32-811d-314e799d4341 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/d4ad1f4ec6a1fae0_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 6874924e-0eae-4909-b19a-0c7087adfd79 wandb_project: Birthday-SN56-6-Gradients-On-Demand wandb_run: your_name wandb_runid: 6874924e-0eae-4909-b19a-0c7087adfd79 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # 524eee36-38c7-4c32-811d-314e799d4341 This model is a fine-tuned version of [databricks/dolly-v2-3b](https://huggingface.co/databricks/dolly-v2-3b) on the None dataset. It achieves the following results on the evaluation set: - Loss: 3.1108 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 14.3662 | 0.0000 | 1 | 4.0295 | | 13.7001 | 0.0001 | 3 | 4.0041 | | 18.6084 | 0.0002 | 6 | 3.7846 | | 13.6494 | 0.0003 | 9 | 3.1108 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

nblinh/7f6d68fe-a293-4c30-b25c-143527739229

nblinh

2025-01-21T12:00:24Z

6

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:defog/sqlcoder-7b-2", "base_model:adapter:defog/sqlcoder-7b-2", "license:cc-by-sa-4.0", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-21T11:35:38Z

--- library_name: peft license: cc-by-sa-4.0 base_model: defog/sqlcoder-7b-2 tags: - axolotl - generated_from_trainer model-index: - name: 7f6d68fe-a293-4c30-b25c-143527739229 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: defog/sqlcoder-7b-2 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - fdd56d09ce656747_train_data.json ds_type: json format: custom path: /workspace/input_data/fdd56d09ce656747_train_data.json type: field_instruction: INSTRUCTION field_output: RESPONSE format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: nblinh/7f6d68fe-a293-4c30-b25c-143527739229 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/fdd56d09ce656747_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 special_tokens: pad_token: </s> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: fecef9ac-e0fb-4174-87a6-ec0f3fcd1777 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: fecef9ac-e0fb-4174-87a6-ec0f3fcd1777 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details> # 7f6d68fe-a293-4c30-b25c-143527739229 This model is a fine-tuned version of [defog/sqlcoder-7b-2](https://huggingface.co/defog/sqlcoder-7b-2) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.5545 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.59 | 0.1960 | 200 | 0.5545 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

ClarenceDan/1b016248-9d07-4011-a03a-975b03b2ce03

ClarenceDan

2025-01-21T12:00:14Z

6

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:unsloth/Llama-3.1-Storm-8B", "base_model:adapter:unsloth/Llama-3.1-Storm-8B", "license:llama3.1", "region:us" ]

null

2025-01-21T11:56:03Z

--- library_name: peft license: llama3.1 base_model: unsloth/Llama-3.1-Storm-8B tags: - axolotl - generated_from_trainer model-index: - name: 1b016248-9d07-4011-a03a-975b03b2ce03 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/Llama-3.1-Storm-8B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - dc5c201d257f4800_train_data.json ds_type: json format: custom path: /workspace/input_data/dc5c201d257f4800_train_data.json type: field_instruction: instruction field_output: output format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: ClarenceDan/1b016248-9d07-4011-a03a-975b03b2ce03 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/dc5c201d257f4800_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 1fb620f4-588e-4556-8dd0-8ed7c42fd6cc wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 1fb620f4-588e-4556-8dd0-8ed7c42fd6cc warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # 1b016248-9d07-4011-a03a-975b03b2ce03 This model is a fine-tuned version of [unsloth/Llama-3.1-Storm-8B](https://huggingface.co/unsloth/Llama-3.1-Storm-8B) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.0 | 0.0003 | 1 | nan | | 0.0 | 0.0010 | 3 | nan | | 0.0 | 0.0020 | 6 | nan | | 0.0 | 0.0031 | 9 | nan | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

havinash-ai/c0a35a3f-01eb-453e-b74f-a4f270d22a82

havinash-ai

2025-01-21T11:59:58Z

6

0

peft

[ "peft", "safetensors", "mistral", "axolotl", "generated_from_trainer", "base_model:Intel/neural-chat-7b-v3-3", "base_model:adapter:Intel/neural-chat-7b-v3-3", "license:apache-2.0", "region:us" ]

null

2025-01-21T11:57:56Z

--- library_name: peft license: apache-2.0 base_model: Intel/neural-chat-7b-v3-3 tags: - axolotl - generated_from_trainer model-index: - name: c0a35a3f-01eb-453e-b74f-a4f270d22a82 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: Intel/neural-chat-7b-v3-3 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - b5e06bf0e602bd38_train_data.json ds_type: json format: custom path: /workspace/input_data/b5e06bf0e602bd38_train_data.json type: field_instruction: section field_output: text format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: havinash-ai/c0a35a3f-01eb-453e-b74f-a4f270d22a82 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/b5e06bf0e602bd38_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 special_tokens: pad_token: </s> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 5312563a-16b4-452e-84f7-611f95b514ff wandb_project: Mine-SN56-2-Gradients-On-Demand wandb_run: your_name wandb_runid: 5312563a-16b4-452e-84f7-611f95b514ff warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # c0a35a3f-01eb-453e-b74f-a4f270d22a82 This model is a fine-tuned version of [Intel/neural-chat-7b-v3-3](https://huggingface.co/Intel/neural-chat-7b-v3-3) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.0 | 0.0010 | 1 | nan | | 0.0 | 0.0030 | 3 | nan | | 0.0 | 0.0059 | 6 | nan | | 0.0 | 0.0089 | 9 | nan | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

JetBrains-Research/deepseek-coder-1.3b-instruct-comment-resolution

JetBrains-Research

2025-01-21T11:59:54Z

63

0

transformers

[ "transformers", "safetensors", "text-generation", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-generation

2024-12-02T17:35:56Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

MayBashendy/ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k17_task7_organization

MayBashendy

2025-01-21T11:59:01Z

5

0

transformers

[ "transformers", "safetensors", "bert", "text-classification", "generated_from_trainer", "base_model:aubmindlab/bert-base-arabertv02", "base_model:finetune:aubmindlab/bert-base-arabertv02", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-classification

2025-01-21T11:55:01Z

--- library_name: transformers base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k17_task7_organization results: [] ---  # ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k17_task7_organization This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.0676 - Qwk: 0.2683 - Mse: 1.0676 - Rmse: 1.0333 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 100 ### Training results | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse | Rmse | |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:------:| | No log | 0.05 | 2 | 2.7815 | -0.0481 | 2.7815 | 1.6678 | | No log | 0.1 | 4 | 1.7927 | 0.0061 | 1.7927 | 1.3389 | | No log | 0.15 | 6 | 2.0211 | -0.1653 | 2.0211 | 1.4217 | | No log | 0.2 | 8 | 1.3569 | -0.1328 | 1.3569 | 1.1648 | | No log | 0.25 | 10 | 1.0144 | 0.0054 | 1.0144 | 1.0072 | | No log | 0.3 | 12 | 0.9010 | 0.1461 | 0.9010 | 0.9492 | | No log | 0.35 | 14 | 0.9014 | 0.1534 | 0.9014 | 0.9494 | | No log | 0.4 | 16 | 0.8922 | 0.1636 | 0.8922 | 0.9445 | | No log | 0.45 | 18 | 0.8487 | 0.0679 | 0.8487 | 0.9212 | | No log | 0.5 | 20 | 0.9147 | 0.1511 | 0.9147 | 0.9564 | | No log | 0.55 | 22 | 1.0285 | 0.1259 | 1.0285 | 1.0141 | | No log | 0.6 | 24 | 1.0813 | 0.0986 | 1.0813 | 1.0398 | | No log | 0.65 | 26 | 0.8837 | 0.2132 | 0.8837 | 0.9401 | | No log | 0.7 | 28 | 0.7961 | 0.0937 | 0.7961 | 0.8922 | | No log | 0.75 | 30 | 0.7689 | 0.0481 | 0.7689 | 0.8769 | | No log | 0.8 | 32 | 0.7462 | 0.0481 | 0.7462 | 0.8638 | | No log | 0.85 | 34 | 0.7381 | 0.0884 | 0.7381 | 0.8591 | | No log | 0.9 | 36 | 0.7520 | 0.0 | 0.7520 | 0.8672 | | No log | 0.95 | 38 | 0.7783 | 0.0481 | 0.7783 | 0.8822 | | No log | 1.0 | 40 | 0.7709 | 0.0 | 0.7709 | 0.8780 | | No log | 1.05 | 42 | 0.7433 | 0.0 | 0.7433 | 0.8622 | | No log | 1.1 | 44 | 0.7383 | 0.0 | 0.7383 | 0.8592 | | No log | 1.15 | 46 | 0.7397 | 0.0 | 0.7397 | 0.8601 | | No log | 1.2 | 48 | 0.7337 | 0.0884 | 0.7337 | 0.8566 | | No log | 1.25 | 50 | 0.7301 | 0.1236 | 0.7301 | 0.8544 | | No log | 1.3 | 52 | 0.7242 | 0.1456 | 0.7242 | 0.8510 | | No log | 1.35 | 54 | 0.7434 | 0.1807 | 0.7434 | 0.8622 | | No log | 1.4 | 56 | 0.7364 | 0.1508 | 0.7364 | 0.8581 | | No log | 1.45 | 58 | 0.7273 | 0.1187 | 0.7273 | 0.8528 | | No log | 1.5 | 60 | 0.7258 | 0.0840 | 0.7258 | 0.8520 | | No log | 1.55 | 62 | 0.7335 | 0.0444 | 0.7335 | 0.8564 | | No log | 1.6 | 64 | 0.7513 | 0.0937 | 0.7513 | 0.8668 | | No log | 1.65 | 66 | 0.7398 | 0.0481 | 0.7398 | 0.8601 | | No log | 1.7 | 68 | 0.7442 | 0.0 | 0.7442 | 0.8627 | | No log | 1.75 | 70 | 0.7480 | 0.0 | 0.7480 | 0.8649 | | No log | 1.8 | 72 | 0.7431 | -0.0027 | 0.7431 | 0.8620 | | No log | 1.85 | 74 | 0.7483 | 0.0893 | 0.7483 | 0.8651 | | No log | 1.9 | 76 | 0.7506 | 0.0026 | 0.7506 | 0.8664 | | No log | 1.95 | 78 | 0.7455 | 0.0026 | 0.7455 | 0.8634 | | No log | 2.0 | 80 | 0.7296 | 0.0764 | 0.7296 | 0.8542 | | No log | 2.05 | 82 | 0.7244 | 0.0410 | 0.7244 | 0.8511 | | No log | 2.1 | 84 | 0.7185 | 0.0481 | 0.7185 | 0.8476 | | No log | 2.15 | 86 | 0.7201 | 0.0481 | 0.7201 | 0.8486 | | No log | 2.2 | 88 | 0.7684 | 0.0688 | 0.7684 | 0.8766 | | No log | 2.25 | 90 | 0.8471 | -0.0047 | 0.8471 | 0.9204 | | No log | 2.3 | 92 | 0.9219 | 0.0336 | 0.9219 | 0.9602 | | No log | 2.35 | 94 | 0.8593 | 0.0661 | 0.8593 | 0.9270 | | No log | 2.4 | 96 | 0.7927 | 0.1448 | 0.7927 | 0.8903 | | No log | 2.45 | 98 | 0.7396 | 0.2158 | 0.7396 | 0.8600 | | No log | 2.5 | 100 | 0.7441 | 0.2158 | 0.7441 | 0.8626 | | No log | 2.55 | 102 | 0.7275 | 0.1867 | 0.7275 | 0.8530 | | No log | 2.6 | 104 | 0.7325 | 0.2509 | 0.7325 | 0.8559 | | No log | 2.65 | 106 | 0.7702 | 0.2218 | 0.7702 | 0.8776 | | No log | 2.7 | 108 | 0.7711 | 0.2158 | 0.7711 | 0.8781 | | No log | 2.75 | 110 | 0.7585 | 0.2158 | 0.7585 | 0.8709 | | No log | 2.8 | 112 | 0.7625 | 0.2158 | 0.7625 | 0.8732 | | No log | 2.85 | 114 | 0.7762 | 0.2413 | 0.7762 | 0.8810 | | No log | 2.9 | 116 | 0.7775 | 0.1901 | 0.7775 | 0.8818 | | No log | 2.95 | 118 | 0.7895 | 0.2847 | 0.7895 | 0.8886 | | No log | 3.0 | 120 | 0.7612 | 0.1624 | 0.7612 | 0.8724 | | No log | 3.05 | 122 | 0.7445 | 0.2158 | 0.7445 | 0.8629 | | No log | 3.1 | 124 | 0.7593 | 0.1010 | 0.7593 | 0.8714 | | No log | 3.15 | 126 | 0.8076 | 0.0971 | 0.8076 | 0.8986 | | No log | 3.2 | 128 | 0.7975 | 0.0971 | 0.7975 | 0.8930 | | No log | 3.25 | 130 | 0.7766 | 0.0697 | 0.7766 | 0.8812 | | No log | 3.3 | 132 | 0.7984 | 0.1051 | 0.7984 | 0.8935 | | No log | 3.35 | 134 | 0.9101 | 0.2149 | 0.9101 | 0.9540 | | No log | 3.4 | 136 | 1.0361 | 0.2521 | 1.0361 | 1.0179 | | No log | 3.45 | 138 | 1.0476 | 0.2364 | 1.0476 | 1.0235 | | No log | 3.5 | 140 | 0.9632 | 0.1995 | 0.9632 | 0.9814 | | No log | 3.55 | 142 | 0.9064 | 0.0584 | 0.9064 | 0.9521 | | No log | 3.6 | 144 | 0.8631 | 0.0697 | 0.8631 | 0.9290 | | No log | 3.65 | 146 | 0.9331 | 0.0975 | 0.9331 | 0.9660 | | No log | 3.7 | 148 | 0.9420 | 0.0856 | 0.9420 | 0.9706 | | No log | 3.75 | 150 | 0.9851 | 0.2193 | 0.9851 | 0.9925 | | No log | 3.8 | 152 | 0.9770 | 0.2892 | 0.9770 | 0.9885 | | No log | 3.85 | 154 | 0.9237 | 0.2439 | 0.9237 | 0.9611 | | No log | 3.9 | 156 | 0.8649 | 0.2943 | 0.8649 | 0.9300 | | No log | 3.95 | 158 | 0.8627 | 0.3369 | 0.8627 | 0.9288 | | No log | 4.0 | 160 | 0.9110 | 0.2912 | 0.9110 | 0.9544 | | No log | 4.05 | 162 | 0.8747 | 0.3115 | 0.8747 | 0.9353 | | No log | 4.1 | 164 | 0.8485 | 0.3157 | 0.8485 | 0.9211 | | No log | 4.15 | 166 | 0.8876 | 0.2059 | 0.8876 | 0.9421 | | No log | 4.2 | 168 | 0.8396 | 0.2662 | 0.8396 | 0.9163 | | No log | 4.25 | 170 | 0.7145 | 0.3020 | 0.7145 | 0.8453 | | No log | 4.3 | 172 | 0.6763 | 0.1829 | 0.6763 | 0.8224 | | No log | 4.35 | 174 | 0.6848 | 0.2181 | 0.6848 | 0.8275 | | No log | 4.4 | 176 | 0.7393 | 0.4052 | 0.7393 | 0.8598 | | No log | 4.45 | 178 | 0.8544 | 0.4251 | 0.8544 | 0.9243 | | No log | 4.5 | 180 | 0.8607 | 0.3754 | 0.8607 | 0.9277 | | No log | 4.55 | 182 | 0.8286 | 0.4251 | 0.8286 | 0.9103 | | No log | 4.6 | 184 | 0.7767 | 0.3167 | 0.7767 | 0.8813 | | No log | 4.65 | 186 | 0.7748 | 0.3167 | 0.7748 | 0.8802 | | No log | 4.7 | 188 | 0.7632 | 0.3622 | 0.7632 | 0.8736 | | No log | 4.75 | 190 | 0.7500 | 0.3341 | 0.7500 | 0.8660 | | No log | 4.8 | 192 | 0.7483 | 0.2950 | 0.7483 | 0.8651 | | No log | 4.85 | 194 | 0.7769 | 0.4642 | 0.7769 | 0.8814 | | No log | 4.9 | 196 | 0.7819 | 0.5120 | 0.7819 | 0.8843 | | No log | 4.95 | 198 | 0.8057 | 0.3789 | 0.8057 | 0.8976 | | No log | 5.0 | 200 | 0.8061 | 0.2950 | 0.8061 | 0.8978 | | No log | 5.05 | 202 | 0.8570 | 0.2967 | 0.8570 | 0.9257 | | No log | 5.1 | 204 | 0.8946 | 0.4462 | 0.8946 | 0.9458 | | No log | 5.15 | 206 | 0.8111 | 0.3372 | 0.8111 | 0.9006 | | No log | 5.2 | 208 | 0.7667 | 0.2847 | 0.7667 | 0.8756 | | No log | 5.25 | 210 | 0.8306 | 0.4247 | 0.8306 | 0.9114 | | No log | 5.3 | 212 | 0.9020 | 0.3333 | 0.9020 | 0.9498 | | No log | 5.35 | 214 | 0.9648 | 0.3727 | 0.9648 | 0.9822 | | No log | 5.4 | 216 | 0.9330 | 0.3012 | 0.9330 | 0.9659 | | No log | 5.45 | 218 | 0.9431 | 0.2779 | 0.9431 | 0.9712 | | No log | 5.5 | 220 | 0.8969 | 0.1029 | 0.8969 | 0.9471 | | No log | 5.55 | 222 | 0.8776 | 0.1918 | 0.8776 | 0.9368 | | No log | 5.6 | 224 | 0.8238 | 0.1935 | 0.8238 | 0.9076 | | No log | 5.65 | 226 | 0.7614 | 0.3127 | 0.7614 | 0.8726 | | No log | 5.7 | 228 | 0.7729 | 0.3399 | 0.7729 | 0.8791 | | No log | 5.75 | 230 | 0.8301 | 0.3425 | 0.8301 | 0.9111 | | No log | 5.8 | 232 | 0.9000 | 0.3579 | 0.9000 | 0.9487 | | No log | 5.85 | 234 | 0.9826 | 0.2886 | 0.9826 | 0.9913 | | No log | 5.9 | 236 | 1.0048 | 0.3059 | 1.0048 | 1.0024 | | No log | 5.95 | 238 | 0.9560 | 0.2886 | 0.9560 | 0.9778 | | No log | 6.0 | 240 | 0.9846 | 0.2886 | 0.9846 | 0.9923 | | No log | 6.05 | 242 | 1.0053 | 0.3247 | 1.0053 | 1.0026 | | No log | 6.1 | 244 | 0.8946 | 0.2923 | 0.8946 | 0.9458 | | No log | 6.15 | 246 | 0.8653 | 0.2518 | 0.8653 | 0.9302 | | No log | 6.2 | 248 | 0.8387 | 0.3127 | 0.8387 | 0.9158 | | No log | 6.25 | 250 | 0.8439 | 0.3060 | 0.8439 | 0.9187 | | No log | 6.3 | 252 | 0.8582 | 0.2632 | 0.8582 | 0.9264 | | No log | 6.35 | 254 | 0.9131 | 0.4113 | 0.9131 | 0.9556 | | No log | 6.4 | 256 | 0.9065 | 0.4113 | 0.9065 | 0.9521 | | No log | 6.45 | 258 | 0.8590 | 0.4462 | 0.8590 | 0.9268 | | No log | 6.5 | 260 | 0.8227 | 0.3169 | 0.8227 | 0.9070 | | No log | 6.55 | 262 | 0.8932 | 0.3371 | 0.8932 | 0.9451 | | No log | 6.6 | 264 | 1.0092 | 0.2802 | 1.0092 | 1.0046 | | No log | 6.65 | 266 | 1.0151 | 0.2926 | 1.0151 | 1.0075 | | No log | 6.7 | 268 | 0.9591 | 0.3417 | 0.9591 | 0.9794 | | No log | 6.75 | 270 | 0.9389 | 0.3579 | 0.9389 | 0.9690 | | No log | 6.8 | 272 | 0.9699 | 0.3302 | 0.9699 | 0.9848 | | No log | 6.85 | 274 | 1.0013 | 0.2501 | 1.0013 | 1.0007 | | No log | 6.9 | 276 | 1.0755 | 0.2264 | 1.0755 | 1.0371 | | No log | 6.95 | 278 | 1.1285 | 0.2264 | 1.1285 | 1.0623 | | No log | 7.0 | 280 | 1.0357 | 0.2796 | 1.0357 | 1.0177 | | No log | 7.05 | 282 | 0.9956 | 0.3608 | 0.9956 | 0.9978 | | No log | 7.1 | 284 | 0.9900 | 0.3557 | 0.9900 | 0.9950 | | No log | 7.15 | 286 | 0.9507 | 0.3557 | 0.9507 | 0.9751 | | No log | 7.2 | 288 | 0.8655 | 0.4862 | 0.8655 | 0.9303 | | No log | 7.25 | 290 | 0.8401 | 0.4144 | 0.8401 | 0.9166 | | No log | 7.3 | 292 | 0.8795 | 0.4462 | 0.8795 | 0.9378 | | No log | 7.35 | 294 | 1.0027 | 0.2732 | 1.0027 | 1.0014 | | No log | 7.4 | 296 | 1.0642 | 0.1981 | 1.0642 | 1.0316 | | No log | 7.45 | 298 | 1.0066 | 0.3114 | 1.0066 | 1.0033 | | No log | 7.5 | 300 | 0.8917 | 0.4541 | 0.8917 | 0.9443 | | No log | 7.55 | 302 | 0.8794 | 0.5077 | 0.8794 | 0.9378 | | No log | 7.6 | 304 | 0.9474 | 0.4044 | 0.9474 | 0.9733 | | No log | 7.65 | 306 | 0.9984 | 0.3031 | 0.9984 | 0.9992 | | No log | 7.7 | 308 | 0.9133 | 0.4114 | 0.9133 | 0.9557 | | No log | 7.75 | 310 | 0.7844 | 0.2605 | 0.7844 | 0.8857 | | No log | 7.8 | 312 | 0.7335 | 0.2809 | 0.7335 | 0.8564 | | No log | 7.85 | 314 | 0.7312 | 0.2809 | 0.7312 | 0.8551 | | No log | 7.9 | 316 | 0.7909 | 0.3121 | 0.7909 | 0.8893 | | No log | 7.95 | 318 | 1.0015 | 0.2389 | 1.0015 | 1.0007 | | No log | 8.0 | 320 | 1.2296 | 0.1391 | 1.2296 | 1.1089 | | No log | 8.05 | 322 | 1.4373 | 0.1122 | 1.4373 | 1.1989 | | No log | 8.1 | 324 | 1.4303 | 0.1122 | 1.4303 | 1.1960 | | No log | 8.15 | 326 | 1.2038 | 0.1654 | 1.2038 | 1.0972 | | No log | 8.2 | 328 | 0.9614 | 0.2075 | 0.9614 | 0.9805 | | No log | 8.25 | 330 | 0.8355 | 0.3564 | 0.8355 | 0.9141 | | No log | 8.3 | 332 | 0.8083 | 0.4329 | 0.8083 | 0.8991 | | No log | 8.35 | 334 | 0.8333 | 0.4644 | 0.8333 | 0.9129 | | No log | 8.4 | 336 | 0.8453 | 0.4627 | 0.8453 | 0.9194 | | No log | 8.45 | 338 | 0.8036 | 0.4167 | 0.8036 | 0.8965 | | No log | 8.5 | 340 | 0.7977 | 0.3399 | 0.7977 | 0.8931 | | No log | 8.55 | 342 | 0.8403 | 0.3544 | 0.8403 | 0.9167 | | No log | 8.6 | 344 | 0.8785 | 0.3121 | 0.8785 | 0.9373 | | No log | 8.65 | 346 | 0.9207 | 0.3207 | 0.9207 | 0.9595 | | No log | 8.7 | 348 | 0.9339 | 0.2669 | 0.9339 | 0.9664 | | No log | 8.75 | 350 | 0.8966 | 0.3677 | 0.8966 | 0.9469 | | No log | 8.8 | 352 | 0.8942 | 0.3329 | 0.8942 | 0.9456 | | No log | 8.85 | 354 | 0.9491 | 0.3560 | 0.9491 | 0.9742 | | No log | 8.9 | 356 | 1.1092 | 0.2520 | 1.1092 | 1.0532 | | No log | 8.95 | 358 | 1.2857 | 0.2197 | 1.2857 | 1.1339 | | No log | 9.0 | 360 | 1.3019 | 0.1793 | 1.3019 | 1.1410 | | No log | 9.05 | 362 | 1.1466 | 0.2191 | 1.1466 | 1.0708 | | No log | 9.1 | 364 | 0.9258 | 0.4113 | 0.9258 | 0.9622 | | No log | 9.15 | 366 | 0.8345 | 0.3746 | 0.8345 | 0.9135 | | No log | 9.2 | 368 | 0.8240 | 0.3972 | 0.8240 | 0.9077 | | No log | 9.25 | 370 | 0.8596 | 0.4462 | 0.8596 | 0.9271 | | No log | 9.3 | 372 | 0.9124 | 0.4008 | 0.9124 | 0.9552 | | No log | 9.35 | 374 | 0.9869 | 0.3359 | 0.9869 | 0.9934 | | No log | 9.4 | 376 | 1.0105 | 0.2926 | 1.0105 | 1.0052 | | No log | 9.45 | 378 | 0.9363 | 0.4328 | 0.9363 | 0.9676 | | No log | 9.5 | 380 | 0.8247 | 0.3564 | 0.8247 | 0.9081 | | No log | 9.55 | 382 | 0.7809 | 0.2589 | 0.7809 | 0.8837 | | No log | 9.6 | 384 | 0.7887 | 0.2589 | 0.7887 | 0.8881 | | No log | 9.65 | 386 | 0.8558 | 0.3564 | 0.8558 | 0.9251 | | No log | 9.7 | 388 | 1.0092 | 0.2659 | 1.0092 | 1.0046 | | No log | 9.75 | 390 | 1.1964 | 0.1805 | 1.1964 | 1.0938 | | No log | 9.8 | 392 | 1.2204 | 0.1479 | 1.2204 | 1.1047 | | No log | 9.85 | 394 | 1.1127 | 0.2264 | 1.1127 | 1.0548 | | No log | 9.9 | 396 | 0.9637 | 0.3516 | 0.9637 | 0.9817 | | No log | 9.95 | 398 | 0.8570 | 0.4144 | 0.8570 | 0.9257 | | No log | 10.0 | 400 | 0.8032 | 0.3099 | 0.8032 | 0.8962 | | No log | 10.05 | 402 | 0.8018 | 0.2527 | 0.8018 | 0.8954 | | No log | 10.1 | 404 | 0.8452 | 0.3564 | 0.8452 | 0.9193 | | No log | 10.15 | 406 | 0.9750 | 0.2651 | 0.9750 | 0.9874 | | No log | 10.2 | 408 | 1.1752 | 0.1508 | 1.1752 | 1.0841 | | No log | 10.25 | 410 | 1.2968 | 0.1522 | 1.2968 | 1.1388 | | No log | 10.3 | 412 | 1.3569 | 0.1414 | 1.3569 | 1.1649 | | No log | 10.35 | 414 | 1.2820 | 0.1549 | 1.2820 | 1.1323 | | No log | 10.4 | 416 | 1.1277 | 0.1568 | 1.1277 | 1.0619 | | No log | 10.45 | 418 | 0.9659 | 0.3761 | 0.9659 | 0.9828 | | No log | 10.5 | 420 | 0.8109 | 0.4247 | 0.8109 | 0.9005 | | No log | 10.55 | 422 | 0.7443 | 0.2558 | 0.7443 | 0.8628 | | No log | 10.6 | 424 | 0.7236 | 0.2261 | 0.7236 | 0.8506 | | No log | 10.65 | 426 | 0.7324 | 0.2261 | 0.7324 | 0.8558 | | No log | 10.7 | 428 | 0.7808 | 0.3399 | 0.7808 | 0.8836 | | No log | 10.75 | 430 | 0.8909 | 0.4404 | 0.8909 | 0.9439 | | No log | 10.8 | 432 | 1.0132 | 0.4044 | 1.0132 | 1.0066 | | No log | 10.85 | 434 | 1.0463 | 0.2264 | 1.0463 | 1.0229 | | No log | 10.9 | 436 | 1.0307 | 0.1858 | 1.0307 | 1.0152 | | No log | 10.95 | 438 | 0.9524 | 0.2510 | 0.9524 | 0.9759 | | No log | 11.0 | 440 | 0.9381 | 0.2866 | 0.9381 | 0.9686 | | No log | 11.05 | 442 | 0.9587 | 0.2460 | 0.9587 | 0.9791 | | No log | 11.1 | 444 | 0.9440 | 0.2510 | 0.9440 | 0.9716 | | No log | 11.15 | 446 | 0.9761 | 0.1747 | 0.9761 | 0.9880 | | No log | 11.2 | 448 | 1.1083 | 0.1870 | 1.1083 | 1.0527 | | No log | 11.25 | 450 | 1.1684 | 0.1203 | 1.1684 | 1.0809 | | No log | 11.3 | 452 | 1.1929 | 0.1530 | 1.1929 | 1.0922 | | No log | 11.35 | 454 | 1.1310 | 0.1671 | 1.1310 | 1.0635 | | No log | 11.4 | 456 | 1.0862 | 0.0922 | 1.0862 | 1.0422 | | No log | 11.45 | 458 | 1.0900 | 0.1463 | 1.0900 | 1.0440 | | No log | 11.5 | 460 | 1.0844 | 0.1671 | 1.0844 | 1.0414 | | No log | 11.55 | 462 | 1.0999 | 0.1909 | 1.0999 | 1.0488 | | No log | 11.6 | 464 | 1.1240 | 0.2020 | 1.1240 | 1.0602 | | No log | 11.65 | 466 | 1.0884 | 0.2020 | 1.0884 | 1.0433 | | No log | 11.7 | 468 | 1.0469 | 0.2732 | 1.0469 | 1.0232 | | No log | 11.75 | 470 | 1.0083 | 0.2271 | 1.0083 | 1.0041 | | No log | 11.8 | 472 | 0.9795 | 0.2119 | 0.9795 | 0.9897 | | No log | 11.85 | 474 | 0.9908 | 0.2703 | 0.9908 | 0.9954 | | No log | 11.9 | 476 | 1.0087 | 0.2886 | 1.0087 | 1.0044 | | No log | 11.95 | 478 | 1.0151 | 0.2552 | 1.0151 | 1.0075 | | No log | 12.0 | 480 | 1.0537 | 0.2045 | 1.0537 | 1.0265 | | No log | 12.05 | 482 | 1.0959 | 0.2006 | 1.0959 | 1.0468 | | No log | 12.1 | 484 | 1.0750 | 0.2006 | 1.0750 | 1.0368 | | No log | 12.15 | 486 | 1.0557 | 0.2833 | 1.0557 | 1.0275 | | No log | 12.2 | 488 | 1.0304 | 0.2886 | 1.0304 | 1.0151 | | No log | 12.25 | 490 | 1.0110 | 0.2995 | 1.0110 | 1.0055 | | No log | 12.3 | 492 | 0.9812 | 0.3110 | 0.9812 | 0.9906 | | No log | 12.35 | 494 | 0.9318 | 0.3606 | 0.9318 | 0.9653 | | No log | 12.4 | 496 | 0.9165 | 0.3359 | 0.9165 | 0.9573 | | No log | 12.45 | 498 | 0.9682 | 0.2487 | 0.9682 | 0.9840 | | 0.3594 | 12.5 | 500 | 1.0243 | 0.3193 | 1.0243 | 1.0121 | | 0.3594 | 12.55 | 502 | 0.9971 | 0.3193 | 0.9971 | 0.9985 | | 0.3594 | 12.6 | 504 | 0.9262 | 0.3846 | 0.9262 | 0.9624 | | 0.3594 | 12.65 | 506 | 0.9074 | 0.3918 | 0.9074 | 0.9526 | | 0.3594 | 12.7 | 508 | 0.9062 | 0.3991 | 0.9062 | 0.9520 | | 0.3594 | 12.75 | 510 | 0.9505 | 0.2703 | 0.9505 | 0.9750 | | 0.3594 | 12.8 | 512 | 1.0398 | 0.2683 | 1.0398 | 1.0197 | | 0.3594 | 12.85 | 514 | 1.1322 | 0.2059 | 1.1322 | 1.0640 | | 0.3594 | 12.9 | 516 | 1.1282 | 0.2059 | 1.1282 | 1.0622 | | 0.3594 | 12.95 | 518 | 1.0676 | 0.2683 | 1.0676 | 1.0333 | ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.0+cu118 - Datasets 2.21.0 - Tokenizers 0.19.1

trenden/1c28c7f4-a783-47ef-8d8c-acd4814f8fca

trenden

2025-01-21T11:56:54Z

5

0

peft

[ "peft", "safetensors", "gpt_neox", "axolotl", "generated_from_trainer", "base_model:databricks/dolly-v2-3b", "base_model:adapter:databricks/dolly-v2-3b", "license:mit", "region:us" ]

null

2025-01-21T11:41:06Z

--- library_name: peft license: mit base_model: databricks/dolly-v2-3b tags: - axolotl - generated_from_trainer model-index: - name: 1c28c7f4-a783-47ef-8d8c-acd4814f8fca results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: databricks/dolly-v2-3b bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - d4ad1f4ec6a1fae0_train_data.json ds_type: json format: custom path: /workspace/input_data/d4ad1f4ec6a1fae0_train_data.json type: field_instruction: Patient field_output: Description format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: trenden/1c28c7f4-a783-47ef-8d8c-acd4814f8fca hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/d4ad1f4ec6a1fae0_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 6874924e-0eae-4909-b19a-0c7087adfd79 wandb_project: Birthday-SN56-26-Gradients-On-Demand wandb_run: your_name wandb_runid: 6874924e-0eae-4909-b19a-0c7087adfd79 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # 1c28c7f4-a783-47ef-8d8c-acd4814f8fca This model is a fine-tuned version of [databricks/dolly-v2-3b](https://huggingface.co/databricks/dolly-v2-3b) on the None dataset. It achieves the following results on the evaluation set: - Loss: 3.1110 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 14.3662 | 0.0000 | 1 | 4.0295 | | 13.7863 | 0.0001 | 3 | 4.0044 | | 18.6008 | 0.0002 | 6 | 3.7874 | | 13.7364 | 0.0003 | 9 | 3.1110 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

JuniperChinenye/wakeupvalis8

JuniperChinenye

2025-01-21T11:56:08Z

30

0

transformers

[ "transformers", "safetensors", "llama", "text-generation", "conversational", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2025-01-21T11:53:32Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

lesso14/66972514-8697-43de-9112-4681ac299b37

lesso14

2025-01-21T11:55:37Z

6

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:unsloth/Phi-3.5-mini-instruct", "base_model:adapter:unsloth/Phi-3.5-mini-instruct", "license:mit", "region:us" ]

null

2025-01-21T11:50:52Z

--- library_name: peft license: mit base_model: unsloth/Phi-3.5-mini-instruct tags: - axolotl - generated_from_trainer model-index: - name: 66972514-8697-43de-9112-4681ac299b37 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/Phi-3.5-mini-instruct bf16: true chat_template: llama3 datasets: - data_files: - 223b73ed5c333b1a_train_data.json ds_type: json format: custom path: /workspace/input_data/223b73ed5c333b1a_train_data.json type: field_instruction: category field_output: prompt format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: 2 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null flash_attention: false fp16: false fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: lesso14/66972514-8697-43de-9112-4681ac299b37 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0001 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 25 micro_batch_size: 2 mlflow_experiment_name: /tmp/223b73ed5c333b1a_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_hf output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: a7378db3-707d-4698-9a3f-5c035ca3db01 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: a7378db3-707d-4698-9a3f-5c035ca3db01 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # 66972514-8697-43de-9112-4681ac299b37 This model is a fine-tuned version of [unsloth/Phi-3.5-mini-instruct](https://huggingface.co/unsloth/Phi-3.5-mini-instruct) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0001 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_HF with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 25 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.0 | 0.0009 | 1 | nan | | 0.0 | 0.0043 | 5 | nan | | 0.0 | 0.0086 | 10 | nan | | 0.0 | 0.0129 | 15 | nan | | 0.0 | 0.0172 | 20 | nan | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

lesso09/31427da4-2cde-4f4b-abb3-2871ae1631e1

lesso09

2025-01-21T11:55:15Z

11

0

peft

[ "peft", "safetensors", "opt", "axolotl", "generated_from_trainer", "base_model:facebook/opt-125m", "base_model:adapter:facebook/opt-125m", "license:other", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-21T11:53:11Z

--- library_name: peft license: other base_model: facebook/opt-125m tags: - axolotl - generated_from_trainer model-index: - name: 31427da4-2cde-4f4b-abb3-2871ae1631e1 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: facebook/opt-125m bf16: true chat_template: llama3 datasets: - data_files: - ac24df8c526e3c85_train_data.json ds_type: json format: custom path: /workspace/input_data/ac24df8c526e3c85_train_data.json type: field_input: vw_text field_instruction: id field_output: raw_text format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: 2 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null flash_attention: false fp16: false fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: lesso09/31427da4-2cde-4f4b-abb3-2871ae1631e1 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 25 micro_batch_size: 2 mlflow_experiment_name: /tmp/ac24df8c526e3c85_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 722a0b59-9cc9-4456-b05d-e688625587ce wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 722a0b59-9cc9-4456-b05d-e688625587ce warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # 31427da4-2cde-4f4b-abb3-2871ae1631e1 This model is a fine-tuned version of [facebook/opt-125m](https://huggingface.co/facebook/opt-125m) on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.7460 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 25 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 13.0725 | 0.0011 | 1 | 3.1971 | | 12.7422 | 0.0055 | 5 | 3.1474 | | 12.8721 | 0.0110 | 10 | 2.9925 | | 11.728 | 0.0165 | 15 | 2.8301 | | 11.6738 | 0.0221 | 20 | 2.7617 | | 11.938 | 0.0276 | 25 | 2.7460 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

simshelper/task-1-google-gemma-7b

simshelper

2025-01-21T11:55:11Z

412

0

peft

[ "peft", "safetensors", "arxiv:1910.09700", "base_model:google/gemma-7b", "base_model:adapter:google/gemma-7b", "region:us" ]

null

2025-01-12T21:23:12Z

--- base_model: google/gemma-7b library_name: peft --- # Model Card for Model ID  ## Model Details ### Model Description  - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed] ### Framework versions - PEFT 0.13.2

mrcuddle/Ministral-Instruct-2410-8B-DPO-RP

mrcuddle

2025-01-21T11:54:32Z

173

1

transformers

[ "transformers", "tensorboard", "safetensors", "mistral", "text-generation", "autotrain", "text-generation-inference", "conversational", "en", "dataset:athirdpath/DPO_Pairs-Roleplay-Alpaca-NSFW", "base_model:mistralai/Ministral-8B-Instruct-2410", "base_model:finetune:mistralai/Ministral-8B-Instruct-2410", "license:other", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-generation

2025-01-21T02:03:02Z

--- tags: - autotrain - text-generation-inference - text-generation library_name: transformers base_model: mistralai/Ministral-8B-Instruct-2410 widget: - messages: - role: user content: What is your favorite condiment? license: other datasets: - athirdpath/DPO_Pairs-Roleplay-Alpaca-NSFW language: - en --- # Model Trained Using AutoTrain This model was trained using AutoTrain. For more information, please visit [AutoTrain](https://hf.co/docs/autotrain). # Usage ```python from transformers import AutoModelForCausalLM, AutoTokenizer model_path = "mrcuddle/Ministral-Instruct-2410-8B-DPO-RP" tokenizer = AutoTokenizer.from_pretrained(model_path) model = AutoModelForCausalLM.from_pretrained( model_path, device_map="auto", torch_dtype='auto' ).eval() # Prompt content: "hi" messages = [ {"role": "user", "content": "hi"} ] input_ids = tokenizer.apply_chat_template(conversation=messages, tokenize=True, add_generation_prompt=True, return_tensors='pt') output_ids = model.generate(input_ids.to('cuda')) response = tokenizer.decode(output_ids[0][input_ids.shape[1]:], skip_special_tokens=True) # Model response: "Hello! How can I assist you today?" print(response) ```

AmberYifan/Llama-2-7b-sft-peers-pool

AmberYifan

2025-01-21T11:54:06Z

7

0

transformers

[ "transformers", "safetensors", "llama", "text-generation", "generated_from_trainer", "trl", "dpo", "conversational", "arxiv:2305.18290", "base_model:AmberYifan/llama2-7b-sft-ultrachat-safeRLHF", "base_model:finetune:AmberYifan/llama2-7b-sft-ultrachat-safeRLHF", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2025-01-17T09:20:27Z

--- base_model: AmberYifan/llama2-7b-sft-ultrachat-safeRLHF library_name: transformers model_name: Llama-2-7b-sft-peers-pool tags: - generated_from_trainer - trl - dpo licence: license --- # Model Card for Llama-2-7b-sft-peers-pool This model is a fine-tuned version of [AmberYifan/llama2-7b-sft-ultrachat-safeRLHF](https://huggingface.co/AmberYifan/llama2-7b-sft-ultrachat-safeRLHF). It has been trained using [TRL](https://github.com/huggingface/trl). ## Quick start ```python from transformers import pipeline question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?" generator = pipeline("text-generation", model="AmberYifan/Llama-2-7b-sft-peers-pool", device="cuda") output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0] print(output["generated_text"]) ``` ## Training procedure [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/yifanwang/huggingface/runs/jbqvd8s4) This model was trained with DPO, a method introduced in [Direct Preference Optimization: Your Language Model is Secretly a Reward Model](https://huggingface.co/papers/2305.18290). ### Framework versions - TRL: 0.12.2 - Transformers: 4.46.3 - Pytorch: 2.5.1+cu118 - Datasets: 3.2.0 - Tokenizers: 0.20.3 ## Citations Cite DPO as: ```bibtex @inproceedings{rafailov2023direct, title = {{Direct Preference Optimization: Your Language Model is Secretly a Reward Model}}, author = {Rafael Rafailov and Archit Sharma and Eric Mitchell and Christopher D. Manning and Stefano Ermon and Chelsea Finn}, year = 2023, booktitle = {Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023}, url = {http://papers.nips.cc/paper_files/paper/2023/hash/a85b405ed65c6477a4fe8302b5e06ce7-Abstract-Conference.html}, editor = {Alice Oh and Tristan Naumann and Amir Globerson and Kate Saenko and Moritz Hardt and Sergey Levine}, } ``` Cite TRL as: ```bibtex @misc{vonwerra2022trl, title = {{TRL: Transformer Reinforcement Learning}}, author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallouédec}, year = 2020, journal = {GitHub repository}, publisher = {GitHub}, howpublished = {\url{https://github.com/huggingface/trl}} } ```

nblinh63/e25aed5f-5c03-4efe-9836-f29232e954f5

nblinh63

2025-01-21T11:53:50Z

7

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:unsloth/SmolLM2-1.7B-Instruct", "base_model:adapter:unsloth/SmolLM2-1.7B-Instruct", "license:apache-2.0", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-21T11:41:18Z

--- library_name: peft license: apache-2.0 base_model: unsloth/SmolLM2-1.7B-Instruct tags: - axolotl - generated_from_trainer model-index: - name: e25aed5f-5c03-4efe-9836-f29232e954f5 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/SmolLM2-1.7B-Instruct bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 4ae6450c41448135_train_data.json ds_type: json format: custom path: /workspace/input_data/4ae6450c41448135_train_data.json type: field_input: arguments field_instruction: instruction field_output: output format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: nblinh63/e25aed5f-5c03-4efe-9836-f29232e954f5 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/4ae6450c41448135_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 82c1cb78-ced4-49a5-85a8-db01b7542ac0 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 82c1cb78-ced4-49a5-85a8-db01b7542ac0 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details> # e25aed5f-5c03-4efe-9836-f29232e954f5 This model is a fine-tuned version of [unsloth/SmolLM2-1.7B-Instruct](https://huggingface.co/unsloth/SmolLM2-1.7B-Instruct) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.6300 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.529 | 0.1644 | 200 | 0.6300 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

memevis/try56

memevis

2025-01-21T11:53:19Z

50

0

transformers

[ "transformers", "safetensors", "llama", "text-generation", "conversational", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2025-01-21T11:48:04Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

vertings6/1cbf9b6c-5749-4703-8e27-b35cd2724a2c

vertings6

2025-01-21T11:53:18Z

6

0

peft

[ "peft", "safetensors", "mistral", "axolotl", "generated_from_trainer", "base_model:Artples/L-MChat-7b", "base_model:adapter:Artples/L-MChat-7b", "license:apache-2.0", "region:us" ]

null

2025-01-21T11:48:51Z

--- library_name: peft license: apache-2.0 base_model: Artples/L-MChat-7b tags: - axolotl - generated_from_trainer model-index: - name: 1cbf9b6c-5749-4703-8e27-b35cd2724a2c results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: Artples/L-MChat-7b bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - df03514e65800f80_train_data.json ds_type: json format: custom path: /workspace/input_data/df03514e65800f80_train_data.json type: field_instruction: input field_output: response format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: 1 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: true hub_model_id: vertings6/1cbf9b6c-5749-4703-8e27-b35cd2724a2c hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 79GiB max_steps: 30 micro_batch_size: 4 mlflow_experiment_name: /tmp/df03514e65800f80_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optim_args: adam_beta1: 0.9 adam_beta2: 0.95 adam_epsilon: 1e-5 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 special_tokens: pad_token: <|end_of_turn|> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: e3508d62-5471-4cdf-8dba-5844f441931a wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: e3508d62-5471-4cdf-8dba-5844f441931a warmup_steps: 5 weight_decay: 0.001 xformers_attention: true ``` </details> # 1cbf9b6c-5749-4703-8e27-b35cd2724a2c This model is a fine-tuned version of [Artples/L-MChat-7b](https://huggingface.co/Artples/L-MChat-7b) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 16 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.95,adam_epsilon=1e-5 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 30 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.0023 | 1 | nan | | 0.0 | 0.0113 | 5 | nan | | 0.0 | 0.0225 | 10 | nan | | 0.0 | 0.0338 | 15 | nan | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

simshelper/task-1-google-gemma-2b

simshelper

2025-01-21T11:53:15Z

1,231

0

peft

[ "peft", "safetensors", "arxiv:1910.09700", "base_model:google/gemma-2b", "base_model:adapter:google/gemma-2b", "region:us" ]

null

2025-01-12T21:08:24Z

--- base_model: google/gemma-2b library_name: peft --- # Model Card for Model ID  ## Model Details ### Model Description  - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed] ### Framework versions - PEFT 0.13.2

ynuwara/SmolVLM-Base-vqav2

ynuwara

2025-01-21T11:53:15Z

16

0

peft

[ "peft", "tensorboard", "safetensors", "generated_from_trainer", "base_model:HuggingFaceTB/SmolVLM-Base", "base_model:adapter:HuggingFaceTB/SmolVLM-Base", "license:apache-2.0", "region:us" ]

null

2025-01-21T11:53:13Z

--- library_name: peft license: apache-2.0 base_model: HuggingFaceTB/SmolVLM-Base tags: - generated_from_trainer model-index: - name: SmolVLM-Base-vqav2 results: [] ---  # SmolVLM-Base-vqav2 This model is a fine-tuned version of [HuggingFaceTB/SmolVLM-Base](https://huggingface.co/HuggingFaceTB/SmolVLM-Base) on an unknown dataset. ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0001 - train_batch_size: 4 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 16 - optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 50 - num_epochs: 1 ### Training results ### Framework versions - PEFT 0.14.0 - Transformers 4.47.1 - Pytorch 2.5.1+cu121 - Datasets 3.2.0 - Tokenizers 0.21.0

memevis/try55

memevis

2025-01-21T11:53:11Z

47

0

transformers

[ "transformers", "safetensors", "llama", "text-generation", "conversational", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2025-01-21T11:47:15Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

memevis/try57

memevis

2025-01-21T11:52:18Z

17

0

transformers

[ "transformers", "safetensors", "llama", "text-generation", "conversational", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2025-01-21T11:47:14Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

lesso10/0a4c2570-7b1e-4bbc-b25e-573f2750a97a

lesso10

2025-01-21T11:51:48Z

6

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:unsloth/tinyllama", "base_model:adapter:unsloth/tinyllama", "license:apache-2.0", "4-bit", "bitsandbytes", "region:us" ]

null

2025-01-21T11:32:46Z

--- library_name: peft license: apache-2.0 base_model: unsloth/tinyllama tags: - axolotl - generated_from_trainer model-index: - name: 0a4c2570-7b1e-4bbc-b25e-573f2750a97a results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/tinyllama bf16: auto chat_template: llama3 datasets: - data_files: - 543802598c2bc8a9_train_data.json ds_type: json format: custom path: /workspace/input_data/543802598c2bc8a9_train_data.json type: field_input: cot field_instruction: query field_output: response format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: 1 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: true gradient_checkpointing: true group_by_length: false hub_model_id: lesso10/0a4c2570-7b1e-4bbc-b25e-573f2750a97a hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: true load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_steps: 25 micro_batch_size: 2 mlflow_experiment_name: /tmp/543802598c2bc8a9_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 5ade5524-ba32-4677-ac63-2a87ad5e9260 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 5ade5524-ba32-4677-ac63-2a87ad5e9260 warmup_steps: 10 weight_decay: 0.01 xformers_attention: null ``` </details> # 0a4c2570-7b1e-4bbc-b25e-573f2750a97a This model is a fine-tuned version of [unsloth/tinyllama](https://huggingface.co/unsloth/tinyllama) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 25 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.0000 | 1 | nan | | 0.0 | 0.0002 | 5 | nan | | 0.0 | 0.0004 | 10 | nan | | 0.0 | 0.0005 | 15 | nan | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

mini1013/master_cate_sl19

mini1013

2025-01-21T11:51:22Z

1,256

0

setfit

[ "setfit", "safetensors", "roberta", "sentence-transformers", "text-classification", "generated_from_setfit_trainer", "arxiv:2209.11055", "base_model:mini1013/master_domain", "base_model:finetune:mini1013/master_domain", "model-index", "region:us" ]

text-classification

2025-01-21T11:51:00Z

--- tags: - setfit - sentence-transformers - text-classification - generated_from_setfit_trainer widget: - text: 발열양말 방한 보온양말 등산 낚시 스키 스노우보드 스케이트 야외작업 스포츠/레저>스키/보드>스키/보드방한용품>양말 - text: 무크 엠 무크 펠로 데크 다크네이비 517413203ZB 스포츠/레저>스키/보드>스노보드장비>데크 - text: 스키복 성인 자켓 상의 여성용 JACKET 스키자켓 남성 스포츠/레저>스키/보드>스키복>상의 - text: Toko Edge Tuner Pro 스노우보드 엣지 튜닝 컷팅 스포츠/레저>스키/보드>스키/보드용품>보수장비 - text: 헬리아 주니어 고글 카이로스 무광퍼플블랙 보드고글 스포츠고글 스포츠/레저>스키/보드>스키/보드용품>고글 metrics: - accuracy pipeline_tag: text-classification library_name: setfit inference: true base_model: mini1013/master_domain model-index: - name: SetFit with mini1013/master_domain results: - task: type: text-classification name: Text Classification dataset: name: Unknown type: unknown split: test metrics: - type: accuracy value: 1.0 name: Accuracy --- # SetFit with mini1013/master_domain This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [mini1013/master_domain](https://huggingface.co/mini1013/master_domain) as the Sentence Transformer embedding model. A [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance is used for classification. The model has been trained using an efficient few-shot learning technique that involves: 1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning. 2. Training a classification head with features from the fine-tuned Sentence Transformer. ## Model Details ### Model Description - **Model Type:** SetFit - **Sentence Transformer body:** [mini1013/master_domain](https://huggingface.co/mini1013/master_domain) - **Classification head:** a [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance - **Maximum Sequence Length:** 512 tokens - **Number of Classes:** 6 classes    ### Model Sources - **Repository:** [SetFit on GitHub](https://github.com/huggingface/setfit) - **Paper:** [Efficient Few-Shot Learning Without Prompts](https://arxiv.org/abs/2209.11055) - **Blogpost:** [SetFit: Efficient Few-Shot Learning Without Prompts](https://huggingface.co/blog/setfit) ### Model Labels | Label | Examples | |:------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | 2.0 | <ul><li>'충전식 열선양말 발열 스키장 보드 스키 등산 스포츠/레저>스키/보드>스키/보드방한용품>양말'</li><li>'우주마켓 겨울 방한 마스크 보온 등산 골프 따뜻한 자전거 귀덮개 귀마개 마스크 스포츠/레저>스키/보드>스키/보드방한용품>귀마개'</li><li>'다이나핏 폴디드 스몰로고 비니 Dark 스포츠/레저>스키/보드>스키/보드방한용품>비니'</li></ul> | | 0.0 | <ul><li>'방풍 방수 여성 스노우 보드 플레이 여자 복 어스투 점퍼 점프 슈트 수트 스키 가프 스포츠/레저>스키/보드>보드복>재킷'</li><li>'2023 여성용 원피스 스키 슈트 겨울 야외 스포츠 방풍 방수 보온 스노보드 점프슈트 스포츠/레저>스키/보드>보드복>상하세트'</li><li>'여성용 스노우보드 점프수트 여성 일체형 스키복 방 -남성용 민트 그린 수트 스포츠/레저>스키/보드>보드복>상하세트'</li></ul> | | 5.0 | <ul><li>'2223 헤드 스키 PURE JOY 여성용 스포츠/레저>스키/보드>스키장비>플레이트'</li><li>'미니 스키 부츠 스케이트 썰매 스노우 숏부츠 스포츠/레저>스키/보드>스키장비>부츠'</li><li>'PHOENIX 피닉스 주니어 스키 팀복 2223 PHENIX KOREA JR TEAM RD 스포츠/레저>스키/보드>스키장비>플레이트'</li></ul> | | 4.0 | <ul><li>'스키복 세트 여성 남성 방한 방풍 스포츠/레저>스키/보드>스키복>상하세트'</li><li>'스파이더 남성 보르미오 GTX 스키 팬츠 SPFWCISP401MBLK LE1216929158 스포츠/레저>스키/보드>스키복>하의'</li><li>'카르포스 스키바지 남자 겨울 2521013 스포츠/레저>스키/보드>스키복>하의'</li></ul> | | 3.0 | <ul><li>'XCMAN 4겹콘 스터드 디아 7 87인치 알루미늄 스노우보드 스톰프 패드 9pcs 스포츠/레저>스키/보드>스키/보드용품>스티커용품'</li><li>'Thule RoundTrip 스키 스노보드 더플 백 90L 다크 슬레이트 142322 스포츠/레저>스키/보드>스키/보드용품>보드가방'</li><li>'ToeJamR 스노우보드 스톰프 패드 나비 스포츠/레저>스키/보드>스키/보드용품>스티커용품'</li></ul> | | 1.0 | <ul><li>'스노우 스키 여성 부츠 보드 롱 털 따듯한 스노보드 스포츠/레저>스키/보드>스노보드장비>부츠'</li><li>'나이트로 팀 바인딩 2223 NITRO Team 스포츠/레저>스키/보드>스노보드장비>바인딩'</li><li>'헌터 WOMEN 인트레피드 리플렉티브 카모 숏 스노우부츠 - 패턴그레이 WFS1004PCTPTG 스포츠/레저>스키/보드>스노보드장비>부츠'</li></ul> | ## Evaluation ### Metrics | Label | Accuracy | |:--------|:---------| | **all** | 1.0 | ## Uses ### Direct Use for Inference First install the SetFit library: ```bash pip install setfit ``` Then you can load this model and run inference. ```python from setfit import SetFitModel # Download from the 🤗 Hub model = SetFitModel.from_pretrained("mini1013/master_cate_sl19") # Run inference preds = model("스키복 성인 자켓 상의 여성용 JACKET 스키자켓 남성 스포츠/레저>스키/보드>스키복>상의") ```     ## Training Details ### Training Set Metrics | Training set | Min | Median | Max | |:-------------|:----|:-------|:----| | Word count | 4 | 9.4619 | 18 | | Label | Training Sample Count | |:------|:----------------------| | 0.0 | 70 | | 1.0 | 70 | | 2.0 | 70 | | 3.0 | 70 | | 4.0 | 70 | | 5.0 | 70 | ### Training Hyperparameters - batch_size: (256, 256) - num_epochs: (30, 30) - max_steps: -1 - sampling_strategy: oversampling - num_iterations: 50 - body_learning_rate: (2e-05, 1e-05) - head_learning_rate: 0.01 - loss: CosineSimilarityLoss - distance_metric: cosine_distance - margin: 0.25 - end_to_end: False - use_amp: False - warmup_proportion: 0.1 - l2_weight: 0.01 - seed: 42 - eval_max_steps: -1 - load_best_model_at_end: False ### Training Results | Epoch | Step | Training Loss | Validation Loss | |:-------:|:----:|:-------------:|:---------------:| | 0.0120 | 1 | 0.4926 | - | | 0.6024 | 50 | 0.497 | - | | 1.2048 | 100 | 0.5003 | - | | 1.8072 | 150 | 0.1918 | - | | 2.4096 | 200 | 0.0218 | - | | 3.0120 | 250 | 0.0004 | - | | 3.6145 | 300 | 0.0003 | - | | 4.2169 | 350 | 0.0001 | - | | 4.8193 | 400 | 0.0001 | - | | 5.4217 | 450 | 0.0 | - | | 6.0241 | 500 | 0.0 | - | | 6.6265 | 550 | 0.0 | - | | 7.2289 | 600 | 0.0 | - | | 7.8313 | 650 | 0.0 | - | | 8.4337 | 700 | 0.0 | - | | 9.0361 | 750 | 0.0 | - | | 9.6386 | 800 | 0.0 | - | | 10.2410 | 850 | 0.0 | - | | 10.8434 | 900 | 0.0 | - | | 11.4458 | 950 | 0.0 | - | | 12.0482 | 1000 | 0.0 | - | | 12.6506 | 1050 | 0.0001 | - | | 13.2530 | 1100 | 0.0 | - | | 13.8554 | 1150 | 0.0 | - | | 14.4578 | 1200 | 0.0 | - | | 15.0602 | 1250 | 0.0 | - | | 15.6627 | 1300 | 0.0 | - | | 16.2651 | 1350 | 0.0 | - | | 16.8675 | 1400 | 0.0 | - | | 17.4699 | 1450 | 0.0 | - | | 18.0723 | 1500 | 0.0 | - | | 18.6747 | 1550 | 0.0 | - | | 19.2771 | 1600 | 0.0 | - | | 19.8795 | 1650 | 0.0 | - | | 20.4819 | 1700 | 0.0 | - | | 21.0843 | 1750 | 0.0 | - | | 21.6867 | 1800 | 0.0 | - | | 22.2892 | 1850 | 0.0 | - | | 22.8916 | 1900 | 0.0 | - | | 23.4940 | 1950 | 0.0 | - | | 24.0964 | 2000 | 0.0 | - | | 24.6988 | 2050 | 0.0 | - | | 25.3012 | 2100 | 0.0 | - | | 25.9036 | 2150 | 0.0 | - | | 26.5060 | 2200 | 0.0 | - | | 27.1084 | 2250 | 0.0 | - | | 27.7108 | 2300 | 0.0 | - | | 28.3133 | 2350 | 0.0 | - | | 28.9157 | 2400 | 0.0 | - | | 29.5181 | 2450 | 0.0 | - | ### Framework Versions - Python: 3.10.12 - SetFit: 1.1.0 - Sentence Transformers: 3.3.1 - Transformers: 4.44.2 - PyTorch: 2.2.0a0+81ea7a4 - Datasets: 3.2.0 - Tokenizers: 0.19.1 ## Citation ### BibTeX ```bibtex @article{https://doi.org/10.48550/arxiv.2209.11055, doi = {10.48550/ARXIV.2209.11055}, url = {https://arxiv.org/abs/2209.11055}, author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren}, keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences}, title = {Efficient Few-Shot Learning Without Prompts}, publisher = {arXiv}, year = {2022}, copyright = {Creative Commons Attribution 4.0 International} } ```

lesso09/0f79296c-b754-4989-b3bc-489ace006ef1

lesso09

2025-01-21T11:50:36Z

8

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:unsloth/llama-2-7b-chat", "base_model:adapter:unsloth/llama-2-7b-chat", "license:apache-2.0", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-21T08:34:01Z

--- library_name: peft license: apache-2.0 base_model: unsloth/llama-2-7b-chat tags: - axolotl - generated_from_trainer model-index: - name: 0f79296c-b754-4989-b3bc-489ace006ef1 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/llama-2-7b-chat bf16: true chat_template: llama3 datasets: - data_files: - 124bc05ddbf5ee81_train_data.json ds_type: json format: custom path: /workspace/input_data/124bc05ddbf5ee81_train_data.json type: field_instruction: docstring field_output: summary format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: 2 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null flash_attention: false fp16: false fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: lesso09/0f79296c-b754-4989-b3bc-489ace006ef1 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 25 micro_batch_size: 2 mlflow_experiment_name: /tmp/124bc05ddbf5ee81_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 5fe9995d-0a95-46fa-b89c-25f97cbb6eb6 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 5fe9995d-0a95-46fa-b89c-25f97cbb6eb6 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # 0f79296c-b754-4989-b3bc-489ace006ef1 This model is a fine-tuned version of [unsloth/llama-2-7b-chat](https://huggingface.co/unsloth/llama-2-7b-chat) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 25 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.0 | 0.0000 | 1 | nan | | 0.0 | 0.0001 | 5 | nan | | 0.0 | 0.0002 | 10 | nan | | 0.0 | 0.0003 | 15 | nan | | 0.0 | 0.0003 | 20 | nan | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

CharlesLi/mistral_cot_simplest_code_math_4_3_epoch_full

CharlesLi

2025-01-21T11:50:33Z

5

0

transformers

[ "transformers", "tensorboard", "safetensors", "mistral", "text-generation", "alignment-handbook", "trl", "sft", "generated_from_trainer", "conversational", "dataset:generator", "base_model:mistralai/Mistral-7B-Instruct-v0.1", "base_model:finetune:mistralai/Mistral-7B-Instruct-v0.1", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2025-01-21T11:28:42Z

--- library_name: transformers license: apache-2.0 base_model: mistralai/Mistral-7B-Instruct-v0.1 tags: - alignment-handbook - trl - sft - generated_from_trainer - trl - sft - generated_from_trainer datasets: - generator model-index: - name: mistral_cot_simplest_code_math_4_3_epoch_full results: [] ---  # mistral_cot_simplest_code_math_4_3_epoch_full This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1) on the generator dataset. It achieves the following results on the evaluation set: - Loss: 0.6232 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - distributed_type: multi-GPU - num_devices: 4 - gradient_accumulation_steps: 2 - total_train_batch_size: 32 - total_eval_batch_size: 16 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.4526 | 1.9802 | 100 | 0.5809 | ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.1+cu121 - Datasets 3.0.0 - Tokenizers 0.19.1

nhung03/5048b92e-4369-4158-938b-4347f8451cde

nhung03

2025-01-21T11:50:31Z

6

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:defog/sqlcoder-7b-2", "base_model:adapter:defog/sqlcoder-7b-2", "license:cc-by-sa-4.0", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-21T11:35:38Z

--- library_name: peft license: cc-by-sa-4.0 base_model: defog/sqlcoder-7b-2 tags: - axolotl - generated_from_trainer model-index: - name: 5048b92e-4369-4158-938b-4347f8451cde results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: defog/sqlcoder-7b-2 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - fdd56d09ce656747_train_data.json ds_type: json format: custom path: /workspace/input_data/fdd56d09ce656747_train_data.json type: field_instruction: INSTRUCTION field_output: RESPONSE format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: nhung03/5048b92e-4369-4158-938b-4347f8451cde hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/fdd56d09ce656747_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 special_tokens: pad_token: </s> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: fecef9ac-e0fb-4174-87a6-ec0f3fcd1777 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: fecef9ac-e0fb-4174-87a6-ec0f3fcd1777 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details> # 5048b92e-4369-4158-938b-4347f8451cde This model is a fine-tuned version of [defog/sqlcoder-7b-2](https://huggingface.co/defog/sqlcoder-7b-2) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.5537 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.5927 | 0.1960 | 200 | 0.5537 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

gavrilstep/02378d6a-b7cf-4b37-9aa8-c35ba4ba1172

gavrilstep

2025-01-21T11:49:53Z

10

0

peft

[ "peft", "safetensors", "gemma", "axolotl", "generated_from_trainer", "base_model:unsloth/gemma-2b-it", "base_model:adapter:unsloth/gemma-2b-it", "license:apache-2.0", "4-bit", "bitsandbytes", "region:us" ]

null

2025-01-21T11:44:12Z

--- library_name: peft license: apache-2.0 base_model: unsloth/gemma-2b-it tags: - axolotl - generated_from_trainer model-index: - name: 02378d6a-b7cf-4b37-9aa8-c35ba4ba1172 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/gemma-2b-it bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 54704e0639ee0f16_train_data.json ds_type: json format: custom path: /workspace/input_data/54704e0639ee0f16_train_data.json type: field_input: statement field_instruction: queries field_output: paraphrased_statement format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: null eval_max_new_tokens: 256 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: false hub_model_id: gavrilstep/02378d6a-b7cf-4b37-9aa8-c35ba4ba1172 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: true load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 75GiB max_steps: 40 micro_batch_size: 2 mlflow_experiment_name: /tmp/54704e0639ee0f16_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 273f8157-2d8b-40fb-adae-f4a501d93f8b wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 273f8157-2d8b-40fb-adae-f4a501d93f8b warmup_steps: 10 weight_decay: 0.01 xformers_attention: true ``` </details> # 02378d6a-b7cf-4b37-9aa8-c35ba4ba1172 This model is a fine-tuned version of [unsloth/gemma-2b-it](https://huggingface.co/unsloth/gemma-2b-it) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.5929 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 40 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.0014 | 1 | 3.4282 | | 3.3332 | 0.0068 | 5 | 2.8551 | | 2.3572 | 0.0136 | 10 | 2.0829 | | 1.8508 | 0.0205 | 15 | 1.8183 | | 1.8325 | 0.0273 | 20 | 1.6728 | | 1.773 | 0.0341 | 25 | 1.6280 | | 1.6409 | 0.0409 | 30 | 1.6051 | | 1.7932 | 0.0478 | 35 | 1.5948 | | 1.5856 | 0.0546 | 40 | 1.5929 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

ClarenceDan/b6422ae3-6e75-4f8a-9f23-67f0c343008d

ClarenceDan

2025-01-21T11:49:03Z

8

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:oopsung/llama2-7b-n-ox-test-v1", "base_model:adapter:oopsung/llama2-7b-n-ox-test-v1", "region:us" ]

null

2025-01-21T11:43:00Z

--- library_name: peft base_model: oopsung/llama2-7b-n-ox-test-v1 tags: - axolotl - generated_from_trainer model-index: - name: b6422ae3-6e75-4f8a-9f23-67f0c343008d results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: oopsung/llama2-7b-n-ox-test-v1 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - dddb0489dc663e1a_train_data.json ds_type: json format: custom path: /workspace/input_data/dddb0489dc663e1a_train_data.json type: field_input: Context field_instruction: Question field_output: Answers format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: ClarenceDan/b6422ae3-6e75-4f8a-9f23-67f0c343008d hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/dddb0489dc663e1a_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: bbd202cf-ffeb-42f5-82b2-0c60d893aeab wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: bbd202cf-ffeb-42f5-82b2-0c60d893aeab warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # b6422ae3-6e75-4f8a-9f23-67f0c343008d This model is a fine-tuned version of [oopsung/llama2-7b-n-ox-test-v1](https://huggingface.co/oopsung/llama2-7b-n-ox-test-v1) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.0 | 0.0003 | 1 | nan | | 0.0 | 0.0008 | 3 | nan | | 0.0 | 0.0017 | 6 | nan | | 0.0 | 0.0025 | 9 | nan | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1