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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 |
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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 |
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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 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0073 |
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- Rewards/chosen: -0.0940 |
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- Rewards/rejected: -0.1081 |
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- Rewards/accuracies: 0.5160 |
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- Rewards/margins: 0.0141 |
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- Logps/rejected: -1.0807 |
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- Logps/chosen: -0.9399 |
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- Logits/rejected: -0.2988 |
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- Logits/chosen: -0.3321 |
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- Sft Loss: 0.9399 |
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- Odds Ratio Loss: 0.6739 |
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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-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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| 1.0913 | 0.8891 | 500 | 1.0354 | -0.0968 | -0.1107 | 0.5180 | 0.0140 | -1.1075 | -0.9676 | -0.3176 | -0.3490 | 0.9676 | 0.6776 | |
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| 1.0328 | 1.7782 | 1000 | 1.0126 | -0.0945 | -0.1086 | 0.5160 | 0.0141 | -1.0856 | -0.9451 | -0.2979 | -0.3308 | 0.9451 | 0.6748 | |
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| 0.9998 | 2.6673 | 1500 | 1.0073 | -0.0940 | -0.1081 | 0.5160 | 0.0141 | -1.0807 | -0.9399 | -0.2988 | -0.3321 | 0.9399 | 0.6739 | |
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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 |
