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utils.py 317 Bytes
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from sklearn.metrics import f1_score

def doc_to_choice(doc):
    choices = eval(doc["choices"])
    return choices


def weighted_f1_score(items):
    unzipped_list = list(zip(*items))
    golds = unzipped_list[0]
    preds = unzipped_list[1]
    fscore = f1_score(golds, preds, average="weighted")
    return fscore