zephyr-7b-dpo-lora-pubmedqa-ultrafeedback
This model is a fine-tuned version of EllieS/zephyr-7b-dpo-lora-pubmedqa on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:
- Loss: 0.5835
- Rewards/chosen: -0.1486
- Rewards/rejected: -0.4853
- Rewards/accuracies: 0.7105
- Rewards/margins: 0.3368
- Logps/rejected: -314.4243
- Logps/chosen: -302.0460
- Logits/rejected: -2.5375
- Logits/chosen: -2.5889
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-06
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.5703 | 0.92 | 7000 | 0.5835 | -0.1500 | -0.4872 | 0.7140 | 0.3372 | -314.6089 | -302.1864 | -2.5236 | -2.5765 |
Framework versions
- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.1.1+cu121
- Datasets 2.14.6
- Tokenizers 0.15.0
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