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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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base_model: mistralai/Mistral-7B-Instruct-v0.1 |
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model-index: |
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- name: mistral_docs_sum_p1_full |
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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_docs_sum_p1_full |
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This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5829 |
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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: 3.6e-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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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 1 |
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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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| 2.1167 | 0.0277 | 200 | 2.1333 | |
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| 2.3428 | 0.0553 | 400 | 1.6966 | |
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| 1.3784 | 0.0830 | 600 | 1.4972 | |
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| 1.456 | 0.1107 | 800 | 1.3942 | |
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| 1.3227 | 0.1383 | 1000 | 1.3084 | |
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| 1.2535 | 0.1660 | 1200 | 1.2001 | |
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| 1.0612 | 0.1937 | 1400 | 1.0451 | |
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| 0.8815 | 0.2213 | 1600 | 0.9632 | |
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| 0.8971 | 0.2490 | 1800 | 0.9132 | |
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| 0.7908 | 0.2767 | 2000 | 0.8712 | |
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| 0.7549 | 0.3043 | 2200 | 0.8309 | |
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| 0.8099 | 0.3320 | 2400 | 0.8058 | |
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| 0.6891 | 0.3597 | 2600 | 0.7879 | |
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| 0.5204 | 0.3873 | 2800 | 0.7684 | |
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| 0.6249 | 0.4150 | 3000 | 0.7515 | |
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| 0.6764 | 0.4427 | 3200 | 0.7342 | |
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| 0.6996 | 0.4703 | 3400 | 0.7214 | |
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| 0.6371 | 0.4980 | 3600 | 0.7084 | |
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| 0.6694 | 0.5257 | 3800 | 0.6951 | |
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| 0.7048 | 0.5533 | 4000 | 0.6845 | |
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| 0.7265 | 0.5810 | 4200 | 0.6778 | |
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| 0.5663 | 0.6087 | 4400 | 0.6657 | |
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| 0.6222 | 0.6363 | 4600 | 0.6595 | |
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| 0.6463 | 0.6640 | 4800 | 0.6488 | |
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| 0.5754 | 0.6917 | 5000 | 0.6410 | |
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| 0.6208 | 0.7193 | 5200 | 0.6363 | |
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| 0.5613 | 0.7470 | 5400 | 0.6275 | |
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| 0.6316 | 0.7747 | 5600 | 0.6227 | |
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| 0.6564 | 0.8023 | 5800 | 0.6159 | |
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| 0.633 | 0.8300 | 6000 | 0.6077 | |
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| 0.5268 | 0.8577 | 6200 | 0.6022 | |
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| 0.4166 | 0.8853 | 6400 | 0.5978 | |
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| 0.6539 | 0.9130 | 6600 | 0.5926 | |
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| 0.5695 | 0.9407 | 6800 | 0.5875 | |
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| 0.6358 | 0.9683 | 7000 | 0.5845 | |
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| 0.5318 | 0.9960 | 7200 | 0.5829 | |
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### Framework versions |
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- Transformers 4.40.1 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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