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--- |
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license: mit |
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base_model: HuggingFaceH4/mistral-7b-sft-beta |
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tags: |
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- trl |
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- dpo |
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- generated_from_trainer |
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model-index: |
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- name: zephyr-7b-dpo-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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# zephyr-7b-dpo-full |
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This model is a fine-tuned version of [HuggingFaceH4/mistral-7b-sft-beta](https://huggingface.co/HuggingFaceH4/mistral-7b-sft-beta) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4920 |
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- Rewards/chosen: -2.3074 |
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- Rewards/rejected: -3.5196 |
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- Rewards/accuracies: 0.7734 |
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- Rewards/margins: 1.2122 |
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- Logps/rejected: -609.3139 |
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- Logps/chosen: -487.7755 |
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- Logits/rejected: -0.7242 |
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- Logits/chosen: -0.9597 |
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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: 5e-07 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 2 |
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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 128 |
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- total_eval_batch_size: 64 |
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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: 0.1 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | |
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|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| |
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| 0.5392 | 0.11 | 100 | 0.6286 | -0.6554 | -0.9418 | 0.6523 | 0.2865 | -351.5352 | -322.5750 | -2.5756 | -2.5908 | |
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| 0.4524 | 0.23 | 200 | 0.5475 | -1.4831 | -2.1698 | 0.7227 | 0.6867 | -474.3327 | -405.3454 | -1.9678 | -1.9878 | |
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| 0.3976 | 0.34 | 300 | 0.5194 | -1.8541 | -2.8790 | 0.7617 | 1.0249 | -545.2501 | -442.4474 | -0.9783 | -1.1841 | |
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| 0.3892 | 0.45 | 400 | 0.5160 | -2.0795 | -3.1766 | 0.7773 | 1.0971 | -575.0087 | -464.9888 | -0.6002 | -0.8579 | |
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| 0.3964 | 0.57 | 500 | 0.4992 | -2.1896 | -3.3081 | 0.7656 | 1.1185 | -588.1666 | -476.0038 | -0.8012 | -1.0189 | |
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| 0.4149 | 0.68 | 600 | 0.4948 | -2.2061 | -3.3241 | 0.7461 | 1.1179 | -589.7601 | -477.6525 | -1.0527 | -1.2398 | |
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| 0.4004 | 0.79 | 700 | 0.4905 | -2.1723 | -3.3652 | 0.7695 | 1.1929 | -593.8731 | -474.2662 | -0.8519 | -1.0643 | |
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| 0.3887 | 0.91 | 800 | 0.4920 | -2.3074 | -3.5196 | 0.7734 | 1.2122 | -609.3139 | -487.7755 | -0.7242 | -0.9597 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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