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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-7b-it |
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model-index: |
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- name: Gemma-7B-It-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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# Gemma-7B-It-ORPO-SALT-HALF |
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This model is a fine-tuned version of [google/gemma-7b-it](https://huggingface.co/google/gemma-7b-it) 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: 1.3159 |
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- Rewards/chosen: -0.1249 |
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- Rewards/rejected: -0.1471 |
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- Rewards/accuracies: 0.5619 |
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- Rewards/margins: 0.0222 |
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- Logps/rejected: -1.4709 |
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- Logps/chosen: -1.2488 |
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- Logits/rejected: 253.8645 |
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- Logits/chosen: 253.5439 |
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- Sft Loss: 1.2488 |
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- Odds Ratio Loss: 0.6713 |
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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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| 1.422 | 0.8467 | 500 | 1.3896 | -0.1322 | -0.1546 | 0.5752 | 0.0224 | -1.5459 | -1.3222 | 250.5634 | 250.2739 | 1.3222 | 0.6733 | |
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| 1.3103 | 1.6935 | 1000 | 1.3313 | -0.1264 | -0.1489 | 0.5695 | 0.0224 | -1.4886 | -1.2642 | 253.1350 | 252.8147 | 1.2642 | 0.6718 | |
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| 1.2057 | 2.5402 | 1500 | 1.3159 | -0.1249 | -0.1471 | 0.5619 | 0.0222 | -1.4709 | -1.2488 | 253.8645 | 253.5439 | 1.2488 | 0.6713 | |
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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 |
