--- license: apache-2.0 library_name: peft tags: - trl - dpo - generated_from_trainer base_model: mistralai/Mistral-7B-v0.1 model-index: - name: zephyr-7b-dpo-qlora results: [] --- # zephyr-7b-dpo-qlora This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.6813 - Rewards/chosen: -0.0009 - Rewards/rejected: -0.0252 - Rewards/accuracies: 0.2920 - Rewards/margins: 0.0243 - Logps/rejected: -71.3009 - Logps/chosen: -65.4449 - Logits/rejected: -2.4428 - Logits/chosen: -2.4444 ## 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: 4 - total_train_batch_size: 32 - 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 | |:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| | 0.69 | 0.26 | 100 | 0.6897 | 0.0232 | 0.0168 | 0.2680 | 0.0064 | -67.1001 | -63.0342 | -2.4904 | -2.4911 | | 0.6869 | 0.52 | 200 | 0.6849 | 0.0066 | -0.0092 | 0.3060 | 0.0159 | -69.7060 | -64.6950 | -2.4556 | -2.4573 | | 0.681 | 0.78 | 300 | 0.6815 | -0.0026 | -0.0264 | 0.2880 | 0.0238 | -71.4280 | -65.6224 | -2.4430 | -2.4446 | ### Framework versions - PEFT 0.7.1 - Transformers 4.36.2 - Pytorch 2.1.2+cu118 - Datasets 2.14.6 - Tokenizers 0.15.2