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--- |
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license: mit |
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library_name: peft |
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tags: |
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- trl |
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- sft |
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- generated_from_trainer |
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base_model: HuggingFaceH4/zephyr-7b-beta |
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model-index: |
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- name: zephyr_instruct_generation |
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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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# zephyr_instruct_generation |
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This model is a fine-tuned version of [HuggingFaceH4/zephyr-7b-beta](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1686 |
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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: 8e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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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: constant |
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- lr_scheduler_warmup_steps: 0.03 |
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- training_steps: 200 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 3.048 | 0.77 | 10 | 2.4666 | |
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| 2.1245 | 1.54 | 20 | 1.6932 | |
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| 1.3178 | 2.31 | 30 | 1.1619 | |
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| 1.0341 | 3.08 | 40 | 0.9138 | |
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| 0.8234 | 3.85 | 50 | 0.8017 | |
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| 0.6618 | 4.62 | 60 | 0.7330 | |
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| 0.6123 | 5.38 | 70 | 0.7278 | |
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| 0.539 | 6.15 | 80 | 0.6836 | |
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| 0.4648 | 6.92 | 90 | 0.7171 | |
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| 0.4244 | 7.69 | 100 | 0.7712 | |
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| 0.3771 | 8.46 | 110 | 0.8586 | |
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| 0.351 | 9.23 | 120 | 0.8261 | |
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| 0.3233 | 10.0 | 130 | 0.8205 | |
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| 0.2946 | 10.77 | 140 | 0.8420 | |
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| 0.289 | 11.54 | 150 | 1.0008 | |
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| 0.2604 | 12.31 | 160 | 0.9676 | |
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| 0.2615 | 13.08 | 170 | 1.0381 | |
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| 0.2557 | 13.85 | 180 | 1.0656 | |
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| 0.2514 | 14.62 | 190 | 1.0422 | |
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| 0.2357 | 15.38 | 200 | 1.1686 | |
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### Framework versions |
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- PEFT 0.7.1 |
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- Transformers 4.36.2 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.16.0 |
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- Tokenizers 0.15.0 |
