added description
Browse files- agieval.py +11 -13
agieval.py
CHANGED
@@ -31,10 +31,6 @@ _CITATION = """\
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doi={10.1109/TASLP.2023.3293046}}
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"""
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_DESCRIPTION = """\
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The dataset is an amendment and re-annotation of LogiQA in 2020, a large-scale logical reasoning reading comprehension dataset adapted from the Chinese Civil Service Examination. We increase the data size, refine the texts with manual translation by professionals, and improve the quality by removing items with distinctive cultural features like Chinese idioms. Furthermore, we conduct a fine-grained annotation on the dataset and turn it into a two-way natural language inference (NLI) task, resulting in 35k premise-hypothesis pairs with gold labels, making it the first large-scale NLI dataset for complex logical reasoning
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"""
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_HOMEPAGE = "https://github.com/csitfun/LogiQA2.0/tree/main"
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_LICENSE = (
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@@ -42,6 +38,8 @@ _LICENSE = (
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)
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HEAD = 'https://raw.githubusercontent.com/microsoft/AGIEval/main/data/v1/'
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_URLS = {
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"sat_en": {
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"test": HEAD + 'sat-en.jsonl',
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@@ -86,47 +84,47 @@ class AgiEval(datasets.GeneratorBasedBuilder):
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datasets.BuilderConfig(
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name="aqua_rat",
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version=VERSION,
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description=
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),
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datasets.BuilderConfig(
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name="sat_en",
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version=VERSION,
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description=
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),
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datasets.BuilderConfig(
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name="sat_en_wop",
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version=VERSION,
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description=
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),
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datasets.BuilderConfig(
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name="sat_math",
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version=VERSION,
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description=
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),
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datasets.BuilderConfig(
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name="lsat_ar",
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version=VERSION,
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description=
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),
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datasets.BuilderConfig(
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name="lsat_lr",
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version=VERSION,
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description=
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),
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datasets.BuilderConfig(
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name="lsat_rc",
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version=VERSION,
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description=
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),
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datasets.BuilderConfig(
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name="logiqa",
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version=VERSION,
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description=
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),
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datasets.BuilderConfig(
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name="math_agieval",
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version=VERSION,
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description=
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),
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]
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DEFAULT_CONFIG_NAME = "aqua_rat"
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doi={10.1109/TASLP.2023.3293046}}
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"""
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_HOMEPAGE = "https://github.com/csitfun/LogiQA2.0/tree/main"
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_LICENSE = (
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)
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HEAD = 'https://raw.githubusercontent.com/microsoft/AGIEval/main/data/v1/'
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+
_DESCRIPTION = "AGIEval is a human-centric benchmark specifically designed to evaluate the general abilities of foundation models in tasks pertinent to human cognition and problem-solving. This benchmark is derived from 20 official, public, and high-standard admission and qualification exams intended for general human test-takers, such as general college admission tests"
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+
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_URLS = {
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"sat_en": {
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"test": HEAD + 'sat-en.jsonl',
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datasets.BuilderConfig(
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name="aqua_rat",
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version=VERSION,
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+
description=_DESCRIPTION,
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),
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datasets.BuilderConfig(
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name="sat_en",
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version=VERSION,
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+
description=_DESCRIPTION,
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),
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datasets.BuilderConfig(
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name="sat_en_wop",
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version=VERSION,
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+
description=_DESCRIPTION,
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),
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datasets.BuilderConfig(
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name="sat_math",
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version=VERSION,
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+
description=_DESCRIPTION,
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),
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datasets.BuilderConfig(
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name="lsat_ar",
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version=VERSION,
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+
description=_DESCRIPTION,
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),
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datasets.BuilderConfig(
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name="lsat_lr",
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version=VERSION,
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+
description=_DESCRIPTION,
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),
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datasets.BuilderConfig(
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name="lsat_rc",
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version=VERSION,
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description=_DESCRIPTION,
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),
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datasets.BuilderConfig(
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name="logiqa",
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version=VERSION,
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description=_DESCRIPTION,
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),
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datasets.BuilderConfig(
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name="math_agieval",
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version=VERSION,
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description=_DESCRIPTION,
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),
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]
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DEFAULT_CONFIG_NAME = "aqua_rat"
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