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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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- llama-factory |
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- lora |
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- trl |
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- dpo |
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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-HALF |
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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-HALF |
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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 dpo_mix_en and the bct_non_cot_dpo_500 datasets. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8506 |
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- Rewards/chosen: -0.0787 |
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- Rewards/rejected: -0.0996 |
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- Rewards/accuracies: 0.5724 |
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- Rewards/margins: 0.0209 |
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- Logps/rejected: -0.9956 |
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- Logps/chosen: -0.7867 |
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- Logits/rejected: -3.1507 |
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- Logits/chosen: -3.1305 |
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- Sft Loss: 0.7867 |
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- Odds Ratio Loss: 0.6382 |
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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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| 0.8758 | 0.8467 | 500 | 0.8691 | -0.0805 | -0.1009 | 0.5705 | 0.0203 | -1.0086 | -0.8054 | -3.1276 | -3.1089 | 0.8054 | 0.6371 | |
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| 0.8098 | 1.6935 | 1000 | 0.8549 | -0.0791 | -0.0999 | 0.5676 | 0.0207 | -0.9985 | -0.7911 | -3.1170 | -3.0966 | 0.7911 | 0.6375 | |
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| 0.8135 | 2.5402 | 1500 | 0.8506 | -0.0787 | -0.0996 | 0.5724 | 0.0209 | -0.9956 | -0.7867 | -3.1507 | -3.1305 | 0.7867 | 0.6382 | |
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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 |
