dn
            >>> # Example plotting multiple values
            >>> from torchmetrics.regression import CosineSimilarity
            >>> metric = CosineSimilarity()
            >>> values = []
            >>> for _ in range(10):
            ...     values.append(metric(randn(10,2), randn(10,2)))
            >>> fig, ax = metric.plot(values)

        )