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--- |
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library_name: peft |
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license: gemma |
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base_model: google/gemma-3-1b-it |
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tags: |
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- axolotl |
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- generated_from_trainer |
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datasets: |
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- deepakkarkala/sft_sitcom_chandlerbing_jsonl |
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model-index: |
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- name: gemma3_1b_lora_sft_sitcom |
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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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[<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 config</summary> |
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axolotl version: `0.10.0.dev0` |
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```yaml |
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adapter: qlora |
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base_model: google/gemma-3-1b-it |
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bf16: auto |
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chat_template: gemma3 |
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datasets: |
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- path: deepakkarkala/sft_sitcom_chandlerbing_jsonl |
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split: train_without_fewshots |
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type: alpaca |
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ddp_find_unused_parameters: true |
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eval_sample_packing: false |
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evals_per_epoch: null |
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flash_attention: true |
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gradient_accumulation_steps: 8 |
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gradient_checkpointing: true |
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gradient_checkpointing_kwargs: |
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use_reentrant: false |
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hub_model_id: deepakkarkala/gemma3_1b_lora_sft_sitcom |
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learning_rate: 0.0002 |
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load_in_4bit: true |
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load_in_8bit: false |
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logging_steps: 1 |
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lora_alpha: 16 |
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lora_dropout: 0.05 |
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lora_r: 32 |
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lora_target_linear: true |
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lr_scheduler: cosine |
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micro_batch_size: 2 |
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model_type: AutoModelForCausalLM |
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num_epochs: 4 |
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optimizer: adamw_bnb_8bit |
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output_dir: ./outputs/out |
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pad_to_sequence_len: true |
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resume_from_checkpoint: null |
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sample_packing: true |
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saves_per_epoch: 1 |
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sequence_len: 2048 |
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special_tokens: null |
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tf32: true |
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tokenizer_type: AutoTokenizer |
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val_set_size: 0.05 |
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wandb_entity: deepakkarkala-personal |
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wandb_log_model: checkpoint |
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wandb_name: sft_gemma3_1b |
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wandb_project: finetuning_llama31_8b_sitcom |
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wandb_run_id: sft_gemma3_1b_2 |
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wandb_watch: null |
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warmup_ratio: 0.1 |
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weight_decay: 0.0 |
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``` |
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</details><br> |
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/deepakkarkala-personal/finetuning_llama31_8b_sitcom/runs/sft_gemma3_1b_2) |
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# gemma3_1b_lora_sft_sitcom |
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This model is a fine-tuned version of [google/gemma-3-1b-it](https://huggingface.co/google/gemma-3-1b-it) on the deepakkarkala/sft_sitcom_chandlerbing_jsonl dataset. |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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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: 0.0002 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 16 |
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- optimizer: Use OptimizerNames.ADAMW_BNB 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: 26 |
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- training_steps: 264 |
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### Training results |
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### Framework versions |
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- PEFT 0.15.2 |
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- Transformers 4.51.3 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.5.1 |
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- Tokenizers 0.21.1 |
