--- license: apache-2.0 library_name: peft tags: - alignment-handbook - generated_from_trainer - trl - dpo base_model: alignment-handbook/zephyr-7b-sft-full datasets: - updated - original model-index: - name: nash_dpo_rank4_iter_3 results: [] --- # nash_dpo_rank4_iter_3 This model is a fine-tuned version of [YYYYYYibo/nash_dpo_rank4_iter_2](https://huggingface.co/YYYYYYibo/nash_dpo_rank4_iter_2) on the updated and the original datasets. It achieves the following results on the evaluation set: - Loss: 0.5471 - Rewards/chosen: -0.3098 - Rewards/rejected: -0.8270 - Rewards/accuracies: 0.7140 - Rewards/margins: 0.5173 - Logps/rejected: -380.2009 - Logps/chosen: -346.7321 - Logits/rejected: -0.5385 - Logits/chosen: -0.9596 ## 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: 2 - eval_batch_size: 2 - seed: 42 - distributed_type: multi-GPU - num_devices: 4 - gradient_accumulation_steps: 16 - total_train_batch_size: 128 - total_eval_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 | |:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| | 0.5347 | 0.49 | 100 | 0.5570 | -0.3268 | -0.8259 | 0.7120 | 0.4991 | -380.0872 | -348.4370 | -0.5705 | -0.9798 | | 0.5154 | 0.98 | 200 | 0.5471 | -0.3098 | -0.8270 | 0.7140 | 0.5173 | -380.2009 | -346.7321 | -0.5385 | -0.9596 | ### Framework versions - PEFT 0.7.1 - Transformers 4.36.2 - Pytorch 2.1.2+cu121 - Datasets 2.14.6 - Tokenizers 0.15.2