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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-7b |
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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 |
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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: 0.1919 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- gradient_accumulation_steps: 32 |
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- total_train_batch_size: 2048 |
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- total_eval_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.05 |
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- num_epochs: 12.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 1.7591 | 0.64 | 25 | 4.9279 | |
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| 2.0299 | 1.28 | 50 | 0.8182 | |
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| 0.6558 | 1.92 | 75 | 0.5750 | |
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| 0.4785 | 2.56 | 100 | 0.3823 | |
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| 0.3837 | 3.2 | 125 | 0.2941 | |
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| 0.3073 | 3.84 | 150 | 0.2318 | |
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| 0.2119 | 4.48 | 175 | 0.1871 | |
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| 0.1632 | 5.12 | 200 | 0.1595 | |
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| 0.1297 | 5.76 | 225 | 0.1487 | |
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| 0.1035 | 6.39 | 250 | 0.1476 | |
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| 0.0856 | 7.03 | 275 | 0.1427 | |
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| 0.0574 | 7.67 | 300 | 0.1482 | |
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| 0.0448 | 8.31 | 325 | 0.1552 | |
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| 0.0318 | 8.95 | 350 | 0.1562 | |
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| 0.0196 | 9.59 | 375 | 0.1709 | |
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| 0.0146 | 10.23 | 400 | 0.1793 | |
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| 0.0084 | 10.87 | 425 | 0.1854 | |
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| 0.0058 | 11.51 | 450 | 0.1919 | |
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### Framework versions |
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- Transformers 4.38.1 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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