doplhin-2.1-mistral-7b-dpo-ultrafeedback-binarized-preferences-ipo
This model is a fine-tuned version of cognitivecomputations/dolphin-2.1-mistral-7b on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 13.6404
- Rewards/chosen: -0.4693
- Rewards/rejected: -0.7026
- Rewards/accuracies: 0.8234
- Rewards/margins: 0.2333
- Logps/rejected: -9.0933
- Logps/chosen: -6.2746
- Logits/rejected: -0.8214
- Logits/chosen: -0.8422
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 17.7871 | 0.25 | 700 | 16.4082 | -0.2243 | -0.3706 | 0.7903 | 0.1464 | -5.7735 | -3.8245 | -1.8423 | -1.8837 |
| 13.4212 | 0.51 | 1400 | 14.5490 | -0.4924 | -0.7383 | 0.8092 | 0.2459 | -9.4501 | -6.5058 | -0.9174 | -0.9510 |
| 13.2665 | 0.76 | 2100 | 13.6404 | -0.4693 | -0.7026 | 0.8234 | 0.2333 | -9.0933 | -6.2746 | -0.8214 | -0.8422 |
Framework versions
- PEFT 0.8.2
- Transformers 4.37.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.2
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