def _score_for_model(meta):
    """ Returns mean score between tasks in pipeline that can be used for early stopping. """
    mean_acc = list()
    pipes = meta["pipeline"]
    acc = meta["accuracy"]
    if "tagger" in pipes:
        mean_acc.append(acc["tags_acc"])
    if "parser" in pipes:
        mean_acc.append((acc["uas"] + acc["las"]) / 2)
    if "ner" in pipes:
        mean_acc.append((acc["ents_p"] + acc["ents_r"] + acc["ents_f"]) / 3)
    return sum(mean_acc) / len(mean_acc)