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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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- llama-factory |
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- generated_from_trainer |
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base_model: mistralai/Mistral-7B-Instruct-v0.3 |
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model-index: |
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- name: Mistral-7B-Instruct-v0.3-ORPO-SALT |
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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-7B-Instruct-v0.3-ORPO-SALT |
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This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co./mistralai/Mistral-7B-Instruct-v0.3) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8434 |
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- Rewards/chosen: -0.0777 |
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- Rewards/rejected: -0.0988 |
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- Rewards/accuracies: 0.5691 |
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- Rewards/margins: 0.0210 |
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- Logps/rejected: -0.9877 |
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- Logps/chosen: -0.7773 |
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- Logits/rejected: -3.1073 |
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- Logits/chosen: -3.0834 |
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- Sft Loss: 0.7773 |
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- Odds Ratio Loss: 0.6614 |
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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-06 |
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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: 8 |
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- total_train_batch_size: 16 |
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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_steps: 0.1 |
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- num_epochs: 3.0 |
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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 | Sft Loss | Odds Ratio Loss | |
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|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:---------------:| |
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| 0.8803 | 0.8082 | 500 | 0.8619 | -0.0796 | -0.0983 | 0.5655 | 0.0187 | -0.9834 | -0.7962 | -3.0746 | -3.0520 | 0.7962 | 0.6572 | |
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| 0.7341 | 1.6165 | 1000 | 0.8450 | -0.0779 | -0.0980 | 0.5673 | 0.0201 | -0.9804 | -0.7795 | -3.1194 | -3.0960 | 0.7795 | 0.6550 | |
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| 0.7691 | 2.4247 | 1500 | 0.8434 | -0.0777 | -0.0988 | 0.5691 | 0.0210 | -0.9877 | -0.7773 | -3.1073 | -3.0834 | 0.7773 | 0.6614 | |
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### Framework versions |
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- PEFT 0.10.0 |
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- Transformers 4.40.1 |
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- Pytorch 2.3.0 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
