--- license: apache-2.0 library_name: peft tags: - generated_from_trainer base_model: mistralai/Mistral-7B-v0.1 model-index: - name: mistral-sum-r8a16 results: [] --- [Visualize in Weights & Biases](https://wandb.ai/sebastien-roig/mistral-sum/runs/29fd7yh1) # mistral-sum-r8a16 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: 1.7038 ## 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: 0.0002 - train_batch_size: 4 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 16 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 20 - training_steps: 100 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 2.276 | 0.0033 | 20 | 1.7649 | | 1.7456 | 0.0067 | 40 | 1.7254 | | 1.7411 | 0.0100 | 60 | 1.7110 | | 1.7485 | 0.0134 | 80 | 1.7073 | | 1.7308 | 0.0167 | 100 | 1.7038 | ### Framework versions - PEFT 0.11.2.dev0 - Transformers 4.42.0.dev0 - Pytorch 2.1.2+cu121 - Datasets 2.19.1 - Tokenizers 0.19.1