--- license: apache-2.0 base_model: bert-base-uncased tags: - generated_from_trainer datasets: - squad_v2 model-index: - name: bert-base-uncased-finetuned-squad_v2 results: - task: type: question-answering name: Question Answering dataset: name: squad_v2 type: squad_v2 config: squad_v2 split: validation metrics: - type: exact_match value: 71.6920 name: Exact Match - type: f1 value: 75.4437 name: F1 --- # bert-base-uncased-finetuned-squad_v2 This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co./bert-base-uncased) on the [SQuAD2.0](https://huggingface.co./datasets/squad_v2) dataset. It's been trained on question-answer pairs, including unanswerable questions, for the task of Question Answering. It achieves the following results on the evaluation set: - Loss: 1.7075 - Exact Match: 71.6920 - F1-score: 75.4437 ## Overview **Language model:** bert-base-uncased **Language:** English **Downstream-task:** Extractive QA **Training data:** SQuAD 2.0 **Eval data:** SQuAD 2.0 ## 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: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:-----:|:---------------:| | 1.0593 | 1.0 | 8235 | 1.1296 | | 0.7736 | 2.0 | 16470 | 1.1290 | | 0.5682 | 3.0 | 24705 | 1.1725 | | 0.4124 | 4.0 | 32940 | 1.4632 | | 0.3137 | 5.0 | 41175 | 1.7075 | ### Framework versions - Transformers 4.34.0 - Pytorch 1.12.1 - Datasets 2.14.5 - Tokenizers 0.14.1