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--- |
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license: mit |
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library_name: peft |
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tags: |
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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 |
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model-index: |
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- name: gemma-7b-lora-distilabel-intel-orca-dpo-pairs |
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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-lora-distilabel-intel-orca-dpo-pairs |
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This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4641 |
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- Rewards/chosen: -0.2842 |
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- Rewards/rejected: -2.0677 |
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- Rewards/accuracies: 0.8414 |
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- Rewards/margins: 1.7835 |
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- Logps/rejected: -294.6812 |
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- Logps/chosen: -246.1420 |
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- Logits/rejected: -29.7875 |
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- Logits/chosen: -27.6122 |
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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: 1e-05 |
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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: 4 |
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- total_train_batch_size: 8 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 250 |
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- num_epochs: 1 |
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- mixed_precision_training: Native AMP |
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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 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| |
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| 0.6333 | 0.19 | 250 | 0.5221 | -0.4649 | -1.1235 | 0.8196 | 0.6586 | -285.2397 | -247.9492 | -29.5102 | -27.3832 | |
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| 0.4697 | 0.39 | 500 | 0.4819 | -0.5572 | -2.0261 | 0.8394 | 1.4689 | -294.2652 | -248.8721 | -29.5979 | -27.4182 | |
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| 0.4471 | 0.58 | 750 | 0.4814 | -0.5104 | -2.3183 | 0.8418 | 1.8079 | -297.1878 | -248.4040 | -29.6888 | -27.5182 | |
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| 0.4477 | 0.78 | 1000 | 0.4744 | -0.3874 | -2.2429 | 0.8418 | 1.8555 | -296.4334 | -247.1736 | -29.7387 | -27.5680 | |
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| 0.458 | 0.97 | 1250 | 0.4641 | -0.2842 | -2.0677 | 0.8414 | 1.7835 | -294.6812 | -246.1420 | -29.7875 | -27.6122 | |
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### Framework versions |
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- PEFT 0.8.2 |
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- Transformers 4.38.0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.2 |
