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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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- 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 |
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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 |
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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: 1.5380 |
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- Rewards/chosen: -0.0547 |
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- Rewards/rejected: -0.0625 |
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- Rewards/accuracies: 0.5468 |
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- Rewards/margins: 0.0079 |
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- Logps/rejected: -1.2508 |
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- Logps/chosen: -1.0933 |
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- Logits/rejected: 267.2346 |
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- Logits/chosen: 296.6808 |
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- Nll Loss: 1.4703 |
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- Log Odds Ratio: -0.7039 |
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- Log Odds Chosen: 0.2721 |
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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: 4 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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- total_eval_batch_size: 4 |
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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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| 1.436 | 0.9955 | 167 | 1.4639 | -0.0502 | -0.0571 | 0.5540 | 0.0068 | -1.1413 | -1.0048 | 294.2689 | 322.9157 | 1.4152 | -0.6882 | 0.2192 | |
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| 1.0918 | 1.9970 | 335 | 1.4233 | -0.0501 | -0.0574 | 0.4964 | 0.0073 | -1.1475 | -1.0012 | 284.8744 | 313.3100 | 1.3661 | -0.7028 | 0.2209 | |
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| 0.576 | 2.9866 | 501 | 1.5380 | -0.0547 | -0.0625 | 0.5468 | 0.0079 | -1.2508 | -1.0933 | 267.2346 | 296.6808 | 1.4703 | -0.7039 | 0.2721 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
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