---
{}
---

    ---
    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