--- 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 results: [] --- # Mistral-7B-Medical-Finetune_QA 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: 0.6753 ## 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 | |:-------------:|:-----:|:----:|:---------------:| | 0.8304 | 0.15 | 300 | 0.7822 | | 0.7735 | 0.29 | 600 | 0.7528 | | 0.7522 | 0.44 | 900 | 0.7275 | | 0.7234 | 0.59 | 1200 | 0.7043 | | 0.7048 | 0.74 | 1500 | 0.6850 | | 0.6894 | 0.88 | 1800 | 0.6753 | ### Framework versions - PEFT 0.9.0 - Transformers 4.38.2 - Pytorch 2.2.1+cu121 - Datasets 2.18.0 - Tokenizers 0.15.2