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--- |
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license: mit |
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base_model: HuggingFaceH4/zephyr-7b-beta |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: models |
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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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# models |
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This model is a fine-tuned version of [HuggingFaceH4/zephyr-7b-beta](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7368 |
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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: 0.0004 |
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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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- gradient_accumulation_steps: 2 |
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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: linear |
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- lr_scheduler_warmup_steps: 100 |
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- training_steps: 40 |
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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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| 0.9828 | 0.02 | 1 | 1.0330 | |
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| 1.1538 | 0.03 | 2 | 1.0256 | |
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| 0.9734 | 0.05 | 3 | 1.0120 | |
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| 1.0574 | 0.07 | 4 | 0.9942 | |
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| 0.9797 | 0.09 | 5 | 0.9755 | |
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| 0.9399 | 0.1 | 6 | 0.9580 | |
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| 1.0294 | 0.12 | 7 | 0.9434 | |
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| 0.7965 | 0.14 | 8 | 0.9318 | |
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| 0.7741 | 0.16 | 9 | 0.9236 | |
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| 0.8252 | 0.17 | 10 | 0.9178 | |
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| 0.8478 | 0.19 | 11 | 0.9135 | |
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| 0.9641 | 0.21 | 12 | 0.9068 | |
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| 0.9073 | 0.22 | 13 | 0.8980 | |
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| 0.9682 | 0.24 | 14 | 0.8877 | |
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| 0.8794 | 0.26 | 15 | 0.8774 | |
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| 0.7602 | 0.28 | 16 | 0.8690 | |
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| 0.9019 | 0.29 | 17 | 0.8611 | |
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| 0.8619 | 0.31 | 18 | 0.8547 | |
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| 0.8195 | 0.33 | 19 | 0.8484 | |
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| 0.9562 | 0.34 | 20 | 0.8418 | |
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| 0.7822 | 0.36 | 21 | 0.8366 | |
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| 0.767 | 0.38 | 22 | 0.8308 | |
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| 0.9024 | 0.4 | 23 | 0.8242 | |
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| 0.8596 | 0.41 | 24 | 0.8183 | |
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| 0.8424 | 0.43 | 25 | 0.8123 | |
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| 0.7396 | 0.45 | 26 | 0.8059 | |
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| 0.7742 | 0.47 | 27 | 0.7999 | |
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| 0.7007 | 0.48 | 28 | 0.7943 | |
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| 0.6915 | 0.5 | 29 | 0.7890 | |
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| 0.7054 | 0.52 | 30 | 0.7836 | |
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| 0.7622 | 0.53 | 31 | 0.7785 | |
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| 0.6493 | 0.55 | 32 | 0.7720 | |
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| 0.6106 | 0.57 | 33 | 0.7650 | |
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| 0.7534 | 0.59 | 34 | 0.7583 | |
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| 0.7065 | 0.6 | 35 | 0.7532 | |
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| 0.8823 | 0.62 | 36 | 0.7472 | |
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| 0.7082 | 0.64 | 37 | 0.7424 | |
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| 0.7292 | 0.66 | 38 | 0.7405 | |
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| 0.8142 | 0.67 | 39 | 0.7390 | |
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| 0.6079 | 0.69 | 40 | 0.7368 | |
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### Framework versions |
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- Transformers 4.36.0.dev0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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