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--- |
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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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- generated_from_trainer |
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model-index: |
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- name: mistral-json-finetune |
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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-json-finetune |
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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 an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3730 |
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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: 2.5e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 8 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 5 |
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- training_steps: 1000 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 1.2986 | 0.57 | 50 | 0.6897 | |
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| 0.4469 | 1.14 | 100 | 0.4239 | |
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| 0.2978 | 1.71 | 150 | 0.3497 | |
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| 0.2279 | 2.29 | 200 | 0.3126 | |
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| 0.1869 | 2.86 | 250 | 0.2858 | |
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| 0.137 | 3.43 | 300 | 0.2848 | |
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| 0.1221 | 4.0 | 350 | 0.2713 | |
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| 0.0918 | 4.57 | 400 | 0.2750 | |
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| 0.0832 | 5.14 | 450 | 0.2781 | |
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| 0.0681 | 5.71 | 500 | 0.2807 | |
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| 0.055 | 6.29 | 550 | 0.2902 | |
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| 0.0515 | 6.86 | 600 | 0.2746 | |
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| 0.0463 | 7.43 | 650 | 0.3078 | |
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| 0.0421 | 8.0 | 700 | 0.2971 | |
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| 0.0354 | 8.57 | 750 | 0.3196 | |
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| 0.0276 | 9.14 | 800 | 0.3490 | |
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| 0.0281 | 9.71 | 850 | 0.3411 | |
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| 0.026 | 10.29 | 900 | 0.3658 | |
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| 0.0241 | 10.86 | 950 | 0.3661 | |
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| 0.0209 | 11.43 | 1000 | 0.3730 | |
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### Framework versions |
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- Transformers 4.36.0.dev0 |
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- Pytorch 2.1.1+cu121 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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