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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: non-qa-sft-zephyr-7b-beta-v1 |
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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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# non-qa-sft-zephyr-7b-beta-v1 |
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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: 0.5768 |
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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: 3e-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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- distributed_type: multi-GPU |
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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: 0.05 |
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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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| 1.3178 | 0.03 | 50 | 1.0767 | |
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| 0.7765 | 0.07 | 100 | 0.7130 | |
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| 0.6491 | 0.1 | 150 | 0.6840 | |
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| 0.6441 | 0.14 | 200 | 0.6829 | |
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| 0.701 | 0.17 | 250 | 0.6642 | |
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| 0.6936 | 0.21 | 300 | 0.6427 | |
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| 0.6538 | 0.24 | 350 | 0.6175 | |
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| 0.5927 | 0.27 | 400 | 0.6139 | |
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| 0.6709 | 0.31 | 450 | 0.6129 | |
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| 0.5961 | 0.34 | 500 | 0.6078 | |
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| 0.6161 | 0.38 | 550 | 0.5956 | |
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| 0.5999 | 0.41 | 600 | 0.5938 | |
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| 0.6248 | 0.44 | 650 | 0.5824 | |
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| 0.6494 | 0.48 | 700 | 0.5806 | |
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| 0.6259 | 0.51 | 750 | 0.5767 | |
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| 0.557 | 0.55 | 800 | 0.5762 | |
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| 0.6215 | 0.58 | 850 | 0.5777 | |
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| 0.5986 | 0.62 | 900 | 0.5770 | |
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| 0.6224 | 0.65 | 950 | 0.5767 | |
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| 0.6058 | 0.68 | 1000 | 0.5768 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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