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import numpy as np
def process_docs(dataset):
def _detokenize(text):
text = text.replace(" '", "'")
text = text.replace(" \n", "\n")
text = text.replace("\n ", "\n")
text = text.replace(" n't", "n't")
text = text.replace("`` ", '"')
text = text.replace("''", '"')
# punctuation
text = text.replace(" :", ":")
text = text.replace(" ;", ";")
text = text.replace(" !", "!")
text = text.replace(" ?", "?")
text = text.replace(" ,", ",")
text = text.replace(" .", ".")
return text
def _process(doc):
return {
"article": _detokenize(doc["article"]),
"options": [_detokenize(option) for option in doc["options"]],
}
return dataset.map(_process)
def process_results(doc, results):
gold = ["A", "B", "C", "D"].index(doc["answers"])
r4_1 = np.argmax(results) == gold # r4_1 = accuracy
ranks = sorted(results, reverse=True)
r4_2 = (ranks.index(results[gold]) == 1) + r4_1
mrr = 1.0 / (ranks.index(results[gold]) + 1) # `+ 1` for index offset
return {"r@1": r4_1, "r@2": r4_2, "mrr": mrr}
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