selective-pairrm-33045197-mt0
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 on the snorkelai/Snorkel-Mistral-PairRM-DPO-Dataset dataset. It achieves the following results on the evaluation set:
- Loss: 0.6825
- Rewards/chosen: -0.2329
- Rewards/rejected: -0.2692
- Rewards/accuracies: 0.6055
- Rewards/margins: 0.0362
- Logps/rejected: -417.6746
- Logps/chosen: -401.4102
- Logits/rejected: -3.1643
- Logits/chosen: -3.1708
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-07
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- total_eval_batch_size: 32
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6786 | 0.32 | 100 | 0.6868 | -0.0869 | -0.1015 | 0.5547 | 0.0146 | -400.9028 | -386.8027 | -2.8786 | -2.8855 |
| 0.6615 | 0.64 | 200 | 0.6828 | -0.1851 | -0.2144 | 0.5938 | 0.0294 | -412.2021 | -396.6207 | -3.0607 | -3.0672 |
| 0.6539 | 0.96 | 300 | 0.6821 | -0.2322 | -0.2693 | 0.6055 | 0.0371 | -417.6892 | -401.3395 | -3.1645 | -3.1709 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.15.0