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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: 0.0465 |
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- Rewards/chosen: -2.6400 |
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- Rewards/rejected: -3.4900 |
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- Rewards/accuracies: 0.7227 |
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- Rewards/margins: 0.8499 |
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- Logps/rejected: -606.3505 |
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- Logps/chosen: -521.0439 |
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- Logits/rejected: -1.9091 |
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- Logits/chosen: -1.9501 |
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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: 5 |
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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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| 0.1485 | 0.11 | 100 | 0.1803 | -0.5621 | -0.7737 | 0.6406 | 0.2117 | -334.7263 | -313.2471 | -2.4998 | -2.5133 | |
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| 0.0592 | 0.23 | 200 | 0.0662 | -1.7402 | -2.3280 | 0.6797 | 0.5878 | -490.1518 | -431.0574 | -2.2396 | -2.2729 | |
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| 0.0394 | 0.34 | 300 | 0.0494 | -2.3707 | -2.9767 | 0.6953 | 0.6061 | -555.0248 | -494.1047 | -2.1101 | -2.1389 | |
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| 0.0401 | 0.45 | 400 | 0.0523 | -2.4275 | -3.1076 | 0.7031 | 0.6801 | -568.1116 | -499.7916 | -2.0429 | -2.0799 | |
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| 0.0335 | 0.57 | 500 | 0.0461 | -2.4063 | -3.2276 | 0.7148 | 0.8213 | -580.1129 | -497.6727 | -2.0057 | -2.0456 | |
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| 0.0273 | 0.68 | 600 | 0.0409 | -2.8465 | -3.7152 | 0.7070 | 0.8687 | -628.8741 | -541.6862 | -1.9162 | -1.9558 | |
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| 0.0377 | 0.79 | 700 | 0.0496 | -2.5317 | -3.3682 | 0.7227 | 0.8365 | -594.1712 | -510.2102 | -1.9274 | -1.9673 | |
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| 0.0352 | 0.91 | 800 | 0.0465 | -2.6400 | -3.4900 | 0.7227 | 0.8499 | -606.3505 | -521.0439 | -1.9091 | -1.9501 | |
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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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