    def get_metrics(self, reset: bool = False) -> Dict[str, float]:
        """
        Returns a dictionary of metrics. This method will be called by
        `allennlp.training.Trainer` in order to compute and use model metrics for early
        stopping and model serialization.  We return an empty dictionary here rather than raising
        as it is not required to implement metrics for a new model.  A boolean `reset` parameter is
        passed, as frequently a metric accumulator will have some state which should be reset
        between epochs. This is also compatible with [`Metric`s](../training/metrics/metric.md). Metrics
        should be populated during the call to `forward`, with the `Metric` handling the accumulation of
        the metric until this method is called.
        """

        return {}
Returns a dictionary of metrics. This method will be called by
`allennlp.training.Trainer` in order to compute and use model metrics for early
stopping and model serialization.  We return an empty dictionary here rather than raising
as it is not required to implement metrics for a new model.  A boolean `reset` parameter is
passed, as frequently a metric accumulator will have some state which should be reset
between epochs. This is also compatible with [`Metric`s](../training/metrics/metric.md). Metrics
should be populated during the call to `forward`, with the `Metric` handling the accumulation of
the metric until this method is called.
allennlp/models/model.py