--- license: apache-2.0 base_model: mistralai/Mistral-7B-v0.1 tags: - generated_from_trainer - alignment-handbook model-index: - name: zephyr-7b-dpo-lora results: [] --- # zephyr-7b-dpo-lora This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the [HuggingFaceH4/ultrafeedback_binarized](https://huggingface.co/datasets/HuggingFaceH4/ultrafeedback_binarized) dataset. It achieves the following results on the evaluation set: - Loss: 0.5270 - Rewards/chosen: -0.1210 - Rewards/rejected: -0.9978 - Rewards/accuracies: 0.7812 - Rewards/margins: 0.8768 - Logps/rejected: -198.5849 - Logps/chosen: -248.6519 - Logits/rejected: -1.9190 - Logits/chosen: -2.0860 ## 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: 2 - eval_batch_size: 4 - seed: 42 - distributed_type: multi-GPU - num_devices: 32 - total_train_batch_size: 64 - total_eval_batch_size: 128 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | |:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| | 0.5491 | 1.0 | 969 | 0.5563 | -0.0962 | -0.7226 | 0.7812 | 0.6263 | -195.8333 | -248.4046 | -1.9755 | -2.1375 | | 0.5454 | 2.0 | 1938 | 0.5312 | -0.1249 | -0.9600 | 0.7969 | 0.8351 | -198.2077 | -248.6910 | -1.9316 | -2.0971 | | 0.5242 | 3.0 | 2907 | 0.5270 | -0.1210 | -0.9978 | 0.7812 | 0.8768 | -198.5849 | -248.6519 | -1.9190 | -2.0860 | ### Framework versions - Transformers 4.35.0 - Pytorch 2.1.0+cu118 - Datasets 2.14.6 - Tokenizers 0.14.1