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license: apache-2.0 |
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base_model: TheBloke/OpenHermes-2-Mistral-7B-GPTQ |
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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: mistral-dpo |
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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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# mistral-dpo |
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This model is a fine-tuned version of [TheBloke/OpenHermes-2-Mistral-7B-GPTQ](https://huggingface.co/TheBloke/OpenHermes-2-Mistral-7B-GPTQ) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7175 |
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- Rewards/chosen: 0.5987 |
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- Rewards/rejected: 0.4947 |
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- Rewards/accuracies: 0.5769 |
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- Rewards/margins: 0.1040 |
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- Logps/rejected: -155.3645 |
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- Logps/chosen: -178.6683 |
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- Logits/rejected: -2.3247 |
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- Logits/chosen: -2.3598 |
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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: 0.0002 |
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- train_batch_size: 1 |
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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: linear |
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- lr_scheduler_warmup_steps: 2 |
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- training_steps: 100 |
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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 | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | |
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|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| |
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| 0.7039 | 0.0 | 10 | 0.6929 | 0.0710 | 0.0692 | 0.5 | 0.0018 | -159.6188 | -183.9449 | -2.2886 | -2.3271 | |
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| 0.68 | 0.0 | 20 | 0.7113 | -0.0478 | -0.0188 | 0.4519 | -0.0290 | -160.4993 | -185.1333 | -2.2979 | -2.3361 | |
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| 0.8777 | 0.0 | 30 | 0.7367 | -0.3027 | -0.2538 | 0.4904 | -0.0489 | -162.8490 | -187.6822 | -2.3132 | -2.3525 | |
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| 0.8501 | 0.0 | 40 | 0.7407 | -0.2893 | -0.2458 | 0.4327 | -0.0435 | -162.7690 | -187.5477 | -2.3173 | -2.3556 | |
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| 0.7253 | 0.0 | 50 | 0.7207 | -0.0228 | -0.0265 | 0.4904 | 0.0037 | -160.5759 | -184.8833 | -2.3167 | -2.3538 | |
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| 0.7293 | 0.0 | 60 | 0.7066 | 0.1787 | 0.1240 | 0.5673 | 0.0547 | -159.0715 | -182.8687 | -2.3194 | -2.3553 | |
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| 0.6057 | 0.01 | 70 | 0.6851 | 0.4039 | 0.2915 | 0.5769 | 0.1125 | -157.3963 | -180.6157 | -2.3192 | -2.3543 | |
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| 0.7169 | 0.01 | 80 | 0.6853 | 0.5467 | 0.4175 | 0.5769 | 0.1291 | -156.1357 | -179.1884 | -2.3219 | -2.3564 | |
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| 0.6324 | 0.01 | 90 | 0.7046 | 0.5751 | 0.4602 | 0.5769 | 0.1149 | -155.7090 | -178.9038 | -2.3232 | -2.3580 | |
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| 0.5915 | 0.01 | 100 | 0.7175 | 0.5987 | 0.4947 | 0.5769 | 0.1040 | -155.3645 | -178.6683 | -2.3247 | -2.3598 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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