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--- |
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license: apache-2.0 |
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library_name: peft |
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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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base_model: cognitivecomputations/dolphin-2.1-mistral-7b |
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model-index: |
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- name: doplhin-dpo-1-epoch |
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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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# doplhin-dpo-1-epoch |
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This model is a fine-tuned version of [cognitivecomputations/dolphin-2.1-mistral-7b](https://huggingface.co/cognitivecomputations/dolphin-2.1-mistral-7b) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6046 |
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- Rewards/chosen: -6.6173 |
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- Rewards/rejected: -10.5237 |
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- Rewards/accuracies: 0.7880 |
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- Rewards/margins: 3.9064 |
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- Logps/rejected: -431.3049 |
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- Logps/chosen: -422.0936 |
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- Logits/rejected: -2.5993 |
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- Logits/chosen: -2.6739 |
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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-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 8 |
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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: 0.9 |
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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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| 0.5544 | 0.62 | 700 | 0.6046 | -6.6173 | -10.5237 | 0.7880 | 3.9064 | -431.3049 | -422.0936 | -2.5993 | -2.6739 | |
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### Framework versions |
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- PEFT 0.8.2 |
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- Transformers 4.37.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.2 |
