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--- |
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library_name: transformers |
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license: gemma |
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base_model: google/gemma-7b |
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tags: |
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- alignment-handbook |
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- trl |
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- orpo |
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- generated_from_trainer |
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- trl |
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- orpo |
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- alignment-handbook |
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- generated_from_trainer |
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datasets: |
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- silviasapora/low_quality_dpo7k |
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model-index: |
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- name: gemma-7b-borpo-low-quality-v4 |
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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-borpo-low-quality-v4 |
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This model is a fine-tuned version of [google/gemma-7b](https://huggingface.co/google/gemma-7b) on the silviasapora/low_quality_dpo7k dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.8577 |
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- Rewards/chosen: -0.5993 |
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- Rewards/rejected: -0.7602 |
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- Rewards/accuracies: 0.6143 |
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- Rewards/margins: 0.1610 |
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- Logps/rejected: -1.5205 |
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- Logps/chosen: -1.1986 |
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- Logits/rejected: 240.3907 |
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- Logits/chosen: 301.1215 |
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- Nll Loss: 1.5532 |
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- Log Odds Ratio: -0.6421 |
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- Log Odds Chosen: 0.4396 |
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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: 1 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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- total_eval_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: inverse_sqrt |
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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 3 |
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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 | Nll Loss | Log Odds Ratio | Log Odds Chosen | |
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|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:--------------:|:---------------:| |
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| 1.8227 | 1.0 | 84 | 1.9616 | -0.6050 | -0.6743 | 0.5 | 0.0693 | -1.3486 | -1.2099 | 257.8447 | 315.1940 | 1.6719 | -0.6903 | 0.1646 | |
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| 1.4803 | 2.0 | 168 | 1.7681 | -0.5462 | -0.6508 | 0.5286 | 0.1046 | -1.3017 | -1.0924 | 274.3526 | 328.0207 | 1.4854 | -0.6718 | 0.2561 | |
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| 0.9109 | 3.0 | 252 | 1.8577 | -0.5993 | -0.7602 | 0.6143 | 0.1610 | -1.5205 | -1.1986 | 240.3907 | 301.1215 | 1.5532 | -0.6421 | 0.4396 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
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