--- license: apache-2.0 base_model: alignment-handbook/zephyr-7b-sft-full tags: - alignment-handbook - generated_from_trainer - trl - dpo - generated_from_trainer datasets: - HuggingFaceH4/ultrafeedback_binarized model-index: - name: zephyr-7b-dpo-full-repnew results: [] --- # zephyr-7b-dpo-full-repnew This model is a fine-tuned version of [alignment-handbook/zephyr-7b-sft-full](https://huggingface.co/alignment-handbook/zephyr-7b-sft-full) on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set: - Loss: 0.5036 - Rewards/chosen: -1.1057 - Rewards/rejected: -2.0459 - Rewards/accuracies: 0.7698 - Rewards/margins: 0.9402 - Logps/rejected: -466.3643 - Logps/chosen: -394.6778 - Logits/rejected: 0.8720 - Logits/chosen: 0.0385 ## 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: 4 - gradient_accumulation_steps: 4 - total_train_batch_size: 128 - 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 | Logits/chosen | Logits/rejected | Logps/chosen | Logps/rejected | Validation Loss | Rewards/accuracies | Rewards/chosen | Rewards/margins | Rewards/rejected | |:-------------:|:-----:|:----:|:-------------:|:---------------:|:------------:|:--------------:|:---------------:|:------------------:|:--------------:|:---------------:|:----------------:| | 0.5666 | 0.21 | 100 | -1.6453 | -1.5540 | -378.9401 | -411.0335 | 0.5780 | 0.7282 | -0.9484 | 0.5442 | -1.4926 | | 0.5107 | 0.42 | 200 | -0.1291 | 0.3999 | -386.8341 | -445.9254 | 0.5233 | 0.7480 | -1.0273 | 0.8142 | -1.8415 | | 0.5036 | 0.63 | 300 | -0.0425 | 0.7446 | -387.1995 | -449.6839 | 0.5109 | 0.7599 | -1.0310 | 0.8481 | -1.8791 | | 0.485 | 0.84 | 400 | 0.0635 | 0.9022 | -397.1799 | -468.7184 | 0.5047 | 0.7639 | -1.1308 | 0.9387 | -2.0694 | ### Framework versions - Transformers 4.36.2 - Pytorch 2.1.2+cu118 - Datasets 2.14.6 - Tokenizers 0.15.2