bertscore should be rescaled with a pre-computed baseline.
            When a pretrained model from ``transformers`` model is used, the corresponding baseline is downloaded
            from the original ``bert-score`` package from `BERT_score`_ if available.
            In other cases, please specify a path to the baseline csv/tsv file, which must follow the formatting
            of the files from `BERT_score`_
        baseline_path: A path to the user's own local csv/tsv file with the baseline scale.
        baseline_url: A url path to the user's own  csv/tsv file with the baseline scale.

    Returns:
        Python dictionary containing the keys ``precision``, ``recall`` and ``f1`` with corresponding values.

    Raises:
        ValueError:
            If ``len(preds) != len(target)``.
        ModuleNotFoundError:
            If `tqdm` package is required and not installed.
        ModuleNotFoundError:
            If ``transformers`` package is required and not installed.
        ValueError:
            If ``num_layer`` is larger than the number of the model layers.
        ValueError:
            If invalid input is provided.

    Example:
        >>> from pprint import pprint
        >>> from torchmetrics.functional.text.bert import bert_score
        >>> preds = ["hello there", "general kenobi"]
        >>> target = ["hello there", "master kenobi"]
        >>> pprint(bert_score(preds, target))
        {'f1': tensor([1.0000, 0.9961]), 'precision': tensor([1.0000, 0.9961]), 'recall': tensor([1.0000, 0.9961])}

    z=Number of predicted and reference sententes must be the same!zcAn argument `verbose = True` requires `tqdm` package be installed. Install with `pip install tqdm`.Nz®`bert_score` metric with default models requires `transformers` package be installed. Either install with `pip install transformers>=4.4` or `pip install torchmetrics[text]`.z«The argument `model_name_or_path` was not specified while it is required when default `transformers` model are used.It is, therefore, used the default recommended model - Ú