'question': 'Is this a test?',
                    'title': 'train test'
                }


    Return:
        Dictionary containing the F1 score, Exact match score for the batch.

    Example:
        >>> from torchmetrics.functional.text.squad import squad
        >>> preds = [{"prediction_text": "1976", "id": "56e10a3be3433e1400422b22"}]
        >>> target = [{"answers": {"answer_start": [97], "text": ["1976"]},"id": "56e10a3be3433e1400422b22"}]
        >>> squad(preds, target)
        {'exact_match': tensor(100.), 'f1': tensor(100.)}

    Raises:
        KeyError:
            If the required keys are missing in either predictions or targets.

    References:
        [1] SQuAD: 100,000+ Questions for Machine Comprehension of Text by Pranav Rajpurkar, Jian Zhang, Konstantin
        Lopyrev, Percy Liang `SQuAD Metric`_ .

    )