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--- |
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library_name: peft |
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license: mit |
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base_model: microsoft/Phi-3.5-mini-instruct |
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tags: |
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- axolotl |
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- generated_from_trainer |
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model-index: |
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- name: sn_math_curator_on_ensemble_8 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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This is an open-source fine-tuned reasoning adapter of [microsoft/Phi-3.5-mini-instruct](https://huggingface.co/microsoft/Phi-3.5-mini-instruct), transformed into a math reasoning model using data curated from [collinear-ai/R1-Distill-SFT-Curated](https://huggingface.co/datasets/collinear-ai/R1-Distill-SFT-Curated). |
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[<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) |
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<details><summary>See axolotl version</summary> |
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axolotl version: `0.5.0` |
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<!-- ```yaml |
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strict: false |
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base_model: microsoft/Phi-3.5-mini-instruct |
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tokenizer_config: microsoft/Phi-3.5-mini-instruct |
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model_type: AutoModelForCausalLM |
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tokenizer_type: AutoTokenizer |
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# Output configuration |
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hub_model_id: collinear-ai/sn_math_curator_on_ensemble_8 |
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dataset_prepared_path: data/sn_math_curator_on_ensemble_8 |
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output_dir: model/sn_math_curator_on_ensemble_8 |
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# Format the dataset into the right instruction format. |
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chat_template: phi_3 |
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datasets: |
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- path: collinear-ai/R1-Distill-SFT-numina-math-ensemble_8_train |
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split: train |
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type: chat_template |
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chat_template: phi_3 |
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field_messages: train_conv |
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message_field_role: role |
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message_field_content: content |
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train_on_inputs: false #FALSE |
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val_set_size: 0.05 |
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# Data packing |
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sequence_len: 4096 |
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eval_sample_packing: false |
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sample_packing: false |
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pad_to_sequence_len: true |
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group_by_length: false |
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# Lora config |
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adapter: qlora |
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lora_model_dir: |
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load_in_8bit: false |
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load_in_4bit: true --> |
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<!-- lora_r: 128 |
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lora_alpha: 64 |
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lora_dropout: 0.2 |
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lora_target_linear: true |
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lora_fan_in_fan_out: |
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lora_target_modules: |
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- gate_proj |
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- down_proj |
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- up_proj |
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- q_proj |
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- v_proj |
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- k_proj |
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- o_proj |
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lora_modules_to_save: |
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- embed_tokens |
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- lm_head |
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# Logging config |
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wandb_project: sn-curators-downstream |
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wandb_entity: nazneen |
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wandb_name: curator_math_sn_ensemble_8_phi |
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# Trainer config |
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gradient_accumulation_steps: 2 |
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micro_batch_size: 10 |
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num_epochs: 1 |
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optimizer: paged_adamw_8bit |
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lr_scheduler: cosine |
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learning_rate: 0.000005 |
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bfloat16: true |
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bf16: true |
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fp16: |
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tf32: false --> |
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<!-- gradient_checkpointing: true |
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early_stopping_patience: |
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resume_from_checkpoint: |
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local_rank: |
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logging_steps: 10 |
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xformers_attention: |
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flash_attention: true |
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save_safetensors: true |
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warmup_steps: 50 |
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evals_per_epoch: 3 |
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eval_table_size: 3 |
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eval_max_new_tokens: 2048 |
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saves_per_epoch: 40 |
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debug: |
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deepspeed: |
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weight_decay: 0.02 |
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fsdp_config: |
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special_tokens: |
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bos_token: "<s>" |
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eos_token: "<|endoftext|>" |
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unk_token: "<unk>" |
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pad_token: "<|endoftext|>" |
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``` --> |
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</details><br> |
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## Intended uses & limitations |
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Math-Reasoning |
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## Training and evaluation data |
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Training data curated from [collinear-ai/R1-Distill-SFT-Curated](https://huggingface.co/datasets/collinear-ai/R1-Distill-SFT-Curated) |
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Evaluation data: [HuggingFaceH4/MATH-500](https://huggingface.co/datasets/HuggingFaceH4/MATH-500) |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-06 |
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- train_batch_size: 10 |
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- eval_batch_size: 10 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 160 |
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- total_eval_batch_size: 80 |
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- optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 50 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| No log | 0.0003 | 1 | 0.6646 | |
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| 0.3174 | 0.3335 | 1247 | 0.3329 | |
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| 0.307 | 0.6670 | 2494 | 0.3169 | |
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### Evaluation on Math500 |
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### Framework versions |
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- PEFT 0.13.2 |
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- Transformers 4.46.1 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.3 |
