| {} | |
| --- | |
| language: | |
| - en | |
| license: mit | |
| tags: | |
| - question-answering | |
| - SQuAD | |
| - BERT | |
| datasets: | |
| - squad | |
| metrics: | |
| - f1 | |
| - em | |
| model-index: | |
| - name: squad-v2-bert-base-finetuned | |
| results: | |
| - task: | |
| type: question-answering | |
| name: SQuAD Question Answering | |
| dataset: | |
| type: squad_v2 | |
| name: SQuAD v2 | |
| split: validation | |
| metrics: | |
| - type: f1 | |
| value: 26.869992349988973 | |
| name: F1 Score | |
| - type: em | |
| value: 23.347090036216628 | |
| name: Exact Match | |
| verified: true | |
| --- | |
| # distilbert-finetuned-uncased | |
| This model is fine-tuned on SQuAD v2 for question answering tasks. | |
| ## Training Procedure | |
| - Number of Epochs: 4 | |
| - Learning Rate: 2e-05 | |
| - Batch Size: 128 (per device) | |
| - Evaluation Strategy: Every 100 steps | |
| - Save Strategy: Every 100 steps | |
| - FP16 Training: Yes | |
| ## Evaluation Results | |
| - Exact Match: 23.347090036216628 | |
| - F1 Score: 26.869992349988973 | |
| - Total: 11873 | |
| - Has Answer Exact: 38.630229419703106 | |
| - Has Answer F1: 45.686136837283904 | |
| - Has Answer Total: 5928 | |
| - No Answer Exact: 8.107653490328007 | |
| - No Answer F1: 8.107653490328007 | |
| - No Answer Total: 5945 | |
| - Best Exact: 50.11370336056599 | |
| - Best Exact Threshold: 0.0 | |
| - Best F1: 50.11370336056599 | |
| - Best F1 Threshold: 0.0 | |