--- license: cc-by-4.0 base_model: deepset/tinyroberta-squad2 tags: - generated_from_trainer model-index: - name: tinyroberta-squad2-finetuned-emrqa-msquad results: [] datasets: - Eladio/emrqa-msquad language: - en metrics: - exact_match - f1 - precision - recall - bleu - rouge pipeline_tag: question-answering --- # tinyroberta-squad2-finetuned-emrqa-msquad This model is a fine-tuned version of [deepset/tinyroberta-squad2](https://huggingface.co/deepset/tinyroberta-squad2) on medical dataset [Eladio/emrqa-msquad](https://huggingface.co/datasets/Eladio/emrqa-msquad). It achieves the following results on the evaluation set: - Loss: 0.0435 ## Model description [deepset/tinyroberta-squad2](https://huggingface.co/deepset/tinyroberta-squad2) on medical dataset [Eladio/emrqa-msquad](https://huggingface.co/datasets/Eladio/emrqa-msquad) ## 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: 2e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:-----:|:---------------:| | 0.2736 | 1.0 | 15878 | 0.1806 | | 0.1034 | 2.0 | 31756 | 0.0803 | | 0.0475 | 3.0 | 47634 | 0.0435 | ### Framework versions - Transformers 4.38.2 - Pytorch 2.1.0+cu121 - Datasets 2.18.0 - Tokenizers 0.15.2