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--- |
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base_model: mistralai/Mistral-7B-Instruct-v0.3 |
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datasets: |
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- GaetanMichelet/chat-60_ft_task-1_auto |
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library_name: peft |
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license: apache-2.0 |
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tags: |
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- alignment-handbook |
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- trl |
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- sft |
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- generated_from_trainer |
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model-index: |
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- name: Mistral-7B_task-1_60-samples_config-2_auto |
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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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# Mistral-7B_task-1_60-samples_config-2_auto |
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This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co./mistralai/Mistral-7B-Instruct-v0.3) on the GaetanMichelet/chat-60_ft_task-1_auto dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7918 |
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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: 0.0001 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 16 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 50 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-------:|:----:|:---------------:| |
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| 1.0805 | 0.6957 | 2 | 1.0819 | |
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| 1.0214 | 1.7391 | 5 | 0.9261 | |
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| 0.7668 | 2.7826 | 8 | 0.8322 | |
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| 0.7312 | 3.8261 | 11 | 0.7920 | |
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| 0.5041 | 4.8696 | 14 | 0.7918 | |
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| 0.4287 | 5.9130 | 17 | 0.8765 | |
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| 0.2628 | 6.9565 | 20 | 0.9647 | |
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| 0.1707 | 8.0 | 23 | 1.1113 | |
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| 0.1233 | 8.6957 | 25 | 1.2851 | |
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| 0.0474 | 9.7391 | 28 | 1.4284 | |
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| 0.0448 | 10.7826 | 31 | 1.4882 | |
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| 0.0198 | 11.8261 | 34 | 1.6129 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.44.0 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
