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--- |
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license: gemma |
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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: google/gemma-2b-it |
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model-index: |
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- name: Gemma-2B-It-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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# Gemma-2B-It-ORPO-SALT |
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This model is a fine-tuned version of [google/gemma-2b-it](https://huggingface.co./google/gemma-2b-it) 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: 1.3294 |
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- Rewards/chosen: -0.1257 |
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- Rewards/rejected: -0.1400 |
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- Rewards/accuracies: 0.5345 |
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- Rewards/margins: 0.0142 |
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- Logps/rejected: -1.3996 |
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- Logps/chosen: -1.2573 |
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- Logits/rejected: -20.6959 |
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- Logits/chosen: -20.6644 |
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- Sft Loss: 1.2573 |
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- Odds Ratio Loss: 0.7207 |
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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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| 1.4057 | 0.8082 | 500 | 1.3871 | -0.1315 | -0.1452 | 0.5318 | 0.0137 | -1.4522 | -1.3148 | -21.9402 | -21.9144 | 1.3148 | 0.7223 | |
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| 1.2196 | 1.6165 | 1000 | 1.3397 | -0.1268 | -0.1408 | 0.5355 | 0.0140 | -1.4079 | -1.2678 | -20.9111 | -20.8823 | 1.2678 | 0.7187 | |
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| 1.2883 | 2.4247 | 1500 | 1.3294 | -0.1257 | -0.1400 | 0.5345 | 0.0142 | -1.3996 | -1.2573 | -20.6959 | -20.6644 | 1.2573 | 0.7207 | |
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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 |
