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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: mistralai/Mistral-7B-v0.1 |
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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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- custom |
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model-index: |
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- name: test |
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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: `0.12.0.dev0` |
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```yaml |
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base_model: mistralai/Mistral-7B-v0.1 |
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model_type: MistralForCausalLM |
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tokenizer_type: AutoTokenizer |
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datasets: |
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- path: /workspace/axolotl/train_model/data/finetune_dataset.jsonl |
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type: |
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field_instruction: prompt |
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field_output: response |
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format: "[INST] {instruction} [/INST]" |
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no_input_format: "[INST] {instruction} [/INST]" |
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system_prompt: "" # optionnel |
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val_set_size: 0.05 |
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output_dir: /workspace/outputs-lovelace |
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hub_model_id: mikefol/test |
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sequence_len: 2048 |
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sample_packing: true |
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eval_sample_packing: false |
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micro_batch_size: 4 |
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gradient_accumulation_steps: 4 |
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num_epochs: 3 |
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optimizer: paged_adamw_32bit |
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lr_scheduler: cosine |
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learning_rate: 2e-5 |
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gradient_checkpointing: true |
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use_wandb: false |
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push_to_hub: false |
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hub_private_repo: false |
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trust_remote_code: true |
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save_strategy: "no" |
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save_optimizer: false |
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save_safetensors: false |
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``` |
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</details><br> |
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# test |
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This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the /workspace/axolotl/train_model/data/finetune_dataset.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: 2e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 16 |
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- optimizer: Use paged_adamw_32bit 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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- training_steps: 21 |
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### Training results |
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### Framework versions |
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- Transformers 4.53.1 |
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- Pytorch 2.7.1+cu126 |
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- Datasets 3.6.0 |
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- Tokenizers 0.21.2 |
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