--- tags: - trl - dpo - alignment-handbook - generated_from_trainer model-index: - name: zephyr-7b-dpo-full results: [] --- # zephyr-7b-dpo-full This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set: - Logits/chosen: -0.9126 - Logits/rejected: -0.7601 - Logps/chosen: -361.4586 - Logps/rejected: -470.9522 - Loss: 0.4905 - Rewards/accuracies: 0.7539 - Rewards/chosen: -0.7983 - Rewards/margins: 1.0337 - Rewards/rejected: -1.8319 ## 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: 8 - eval_batch_size: 8 - seed: 42 - distributed_type: multi-GPU - num_devices: 8 - gradient_accumulation_steps: 2 - total_train_batch_size: 128 - total_eval_batch_size: 64 - 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 | Logits/chosen | Logits/rejected | Logps/chosen | Logps/rejected | Validation Loss | Rewards/accuracies | Rewards/chosen | Rewards/margins | Rewards/rejected | |:-------------:|:-----:|:----:|:-------------:|:---------------:|:------------:|:--------------:|:---------------:|:------------------:|:--------------:|:---------------:|:----------------:| | 0.5759 | 0.21 | 100 | -1.9151 | -1.8988 | -335.8161 | -395.6910 | 0.5723 | 0.7148 | -0.5418 | 0.5375 | -1.0793 | | 0.5391 | 0.42 | 200 | -1.6570 | -1.5774 | -321.1682 | -405.0056 | 0.5138 | 0.7461 | -0.3953 | 0.7771 | -1.1724 | | 0.4788 | 0.63 | 300 | -0.9864 | -0.8826 | -367.7277 | -475.5532 | 0.4939 | 0.7578 | -0.8609 | 1.0170 | -1.8779 | | 0.4937 | 0.84 | 400 | -0.9126 | -0.7601 | -361.4586 | -470.9522 | 0.4905 | 0.7539 | -0.7983 | 1.0337 | -1.8319 | ### Framework versions - Transformers 4.38.2 - Pytorch 2.1.2+cu118 - Datasets 2.16.1 - Tokenizers 0.15.2