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--- |
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license: llama2 |
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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: lmsys/vicuna-7b-v1.5 |
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model-index: |
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- name: Vicuna-7B-v1.5-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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# Vicuna-7B-v1.5-ORPO-SALT |
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This model is a fine-tuned version of [lmsys/vicuna-7b-v1.5](https://huggingface.co/lmsys/vicuna-7b-v1.5) on the dpo_mix_en and the bct_non_cot_dpo_1000 datasets. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9497 |
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- Rewards/chosen: -0.0879 |
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- Rewards/rejected: -0.0995 |
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- Rewards/accuracies: 0.5164 |
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- Rewards/margins: 0.0116 |
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- Logps/rejected: -0.9948 |
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- Logps/chosen: -0.8787 |
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- Logits/rejected: -0.3581 |
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- Logits/chosen: -0.3775 |
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- Sft Loss: 0.8787 |
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- Odds Ratio Loss: 0.7104 |
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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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| 1.0008 | 0.8082 | 500 | 0.9777 | -0.0907 | -0.1019 | 0.5055 | 0.0113 | -1.0193 | -0.9066 | -0.3689 | -0.3878 | 0.9066 | 0.7105 | |
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| 0.8458 | 1.6165 | 1000 | 0.9560 | -0.0885 | -0.1000 | 0.5191 | 0.0115 | -1.0000 | -0.8850 | -0.3578 | -0.3772 | 0.8850 | 0.7097 | |
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| 0.9219 | 2.4247 | 1500 | 0.9497 | -0.0879 | -0.0995 | 0.5164 | 0.0116 | -0.9948 | -0.8787 | -0.3581 | -0.3775 | 0.8787 | 0.7104 | |
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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 |
