--- license: cc-by-4.0 base_model: deepset/bert-base-cased-squad2 tags: - generated_from_trainer model-index: - name: bert-base-cased-squad2-finetuned-squad results: [] datasets: - Eladio/emrqa-msquad language: - en metrics: - precision - recall - exact_match - bleu - rouge pipeline_tag: question-answering --- # bert-base-cased-squad2-finetuned-squad This model is a fine-tuned version of [deepset/bert-base-cased-squad2](https://huggingface.co/deepset/bert-base-cased-squad2) on medical dataset [Eladio/emrqa-msquad](https://huggingface.co/datasets/Eladio/emrqa-msquad). It achieves the following results on the evaluation set: - Loss: 0.0217 ## Model description [deepset/bert-base-cased-squad2](https://huggingface.co/deepset/bert-base-cased-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 | |:-------------:|:-----:|:-----:|:---------------:| | 0.1755 | 1.0 | 17354 | 0.1014 | | 0.0599 | 2.0 | 34708 | 0.0344 | | 0.0278 | 3.0 | 52062 | 0.0217 | ### Framework versions - Transformers 4.35.0 - Pytorch 2.1.0+cu118 - Datasets 2.14.6 - Tokenizers 0.14.1