def METHOD_NAME(self, averaging_snapshots_dict, validation_results_dict):
    """
    Determines if the new model is better according to the specified metrics
    :param averaging_snapshots_dict: snapshot dict
    :param validation_results_dict: latest model performance
    """
    snapshot_metric_array = averaging_snapshots_dict["snapshots_metric"]
    val = validation_results_dict[self.metric_to_watch]
    if self.greater_is_better:
        update_ind = np.argmin(snapshot_metric_array)
    else:
        update_ind = np.argmax(snapshot_metric_array)
    if (self.greater_is_better and val > snapshot_metric_array[update_ind]) or (not self.greater_is_better and val < snapshot_metric_array[update_ind]):
        return True, update_ind
    return False, None