--- license: apache-2.0 library_name: peft tags: - trl - sft - generated_from_trainer base_model: mistralai/Mistral-7B-Instruct-v0.1 model-index: - name: Mistral-7B-Medical-Finetune_QA_Choices_V2 results: [] --- # Mistral-7B-Medical-Finetune_QA_Choices_V2 This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.6574 ## 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: 0.00025 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 16 - total_train_batch_size: 128 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 1 - num_epochs: 1 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 0.7911 | 0.2 | 300 | 0.7404 | | 0.7311 | 0.39 | 600 | 0.7118 | | 0.7015 | 0.59 | 900 | 0.6815 | | 0.6824 | 0.78 | 1200 | 0.6623 | | 0.6686 | 0.98 | 1500 | 0.6574 | ### Framework versions - PEFT 0.9.0 - Transformers 4.38.2 - Pytorch 2.2.1+cu121 - Datasets 2.18.0 - Tokenizers 0.15.2