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https://github.com/hiyouga/LLaMA-Factory.git
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fix eval scripts
Former-commit-id: fc3743d0b82c28fbff1170761139e4fa5d2a8939
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@ -19,7 +19,7 @@ import pandas as pd
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_CITATION = """\
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_CITATION = """\
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@article{huang2023ceval,
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@article{huang2023ceval,
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title={C-Eval: A Multi-Level Multi-Discipline Chinese Evaluation Suite for Foundation Models},
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title={C-Eval: A Multi-Level Multi-Discipline Chinese Evaluation Suite for Foundation Models},
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author={Huang, Yuzhen and Bai, Yuzhuo and Zhu, Zhihao and Zhang, Junlei and Zhang, Jinghan and Su, Tangjun and Liu, Junteng and Lv, Chuancheng and Zhang, Yikai and Lei, Jiayi and Fu, Yao and Sun, Maosong and He, Junxian},
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author={Huang, Yuzhen and Bai, Yuzhuo and Zhu, Zhihao and Zhang, Junlei and Zhang, Jinghan and Su, Tangjun and Liu, Junteng and Lv, Chuancheng and Zhang, Yikai and Lei, Jiayi and Fu, Yao and Sun, Maosong and He, Junxian},
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journal={arXiv preprint arXiv:2305.08322},
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journal={arXiv preprint arXiv:2305.08322},
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year={2023}
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year={2023}
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@ -133,25 +133,19 @@ class Ceval(datasets.GeneratorBasedBuilder):
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datasets.SplitGenerator(
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datasets.SplitGenerator(
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name=datasets.Split.TEST,
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name=datasets.Split.TEST,
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gen_kwargs={
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gen_kwargs={
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"filepath": os.path.join(
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"filepath": os.path.join(data_dir, "test", f"{task_name}_test.csv"),
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data_dir, "test", f"{task_name}_test.csv"
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),
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},
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},
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),
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),
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datasets.SplitGenerator(
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datasets.SplitGenerator(
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name=datasets.Split.VALIDATION,
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name=datasets.Split.VALIDATION,
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gen_kwargs={
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gen_kwargs={
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"filepath": os.path.join(
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"filepath": os.path.join(data_dir, "val", f"{task_name}_val.csv"),
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data_dir, "val", f"{task_name}_val.csv"
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),
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},
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},
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),
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),
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datasets.SplitGenerator(
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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name=datasets.Split.TRAIN,
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gen_kwargs={
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gen_kwargs={
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"filepath": os.path.join(
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"filepath": os.path.join(data_dir, "dev", f"{task_name}_dev.csv"),
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data_dir, "dev", f"{task_name}_dev.csv"
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),
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},
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},
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),
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),
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]
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]
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@ -37,73 +37,73 @@ _LICENSE = "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 Internatio
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_URL = "cmmlu.zip"
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_URL = "cmmlu.zip"
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task_list = [
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task_list = [
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'agronomy',
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"agronomy",
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'anatomy',
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"anatomy",
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'ancient_chinese',
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"ancient_chinese",
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'arts',
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"arts",
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'astronomy',
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"astronomy",
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'business_ethics',
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"business_ethics",
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'chinese_civil_service_exam',
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"chinese_civil_service_exam",
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'chinese_driving_rule',
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"chinese_driving_rule",
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'chinese_food_culture',
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"chinese_food_culture",
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'chinese_foreign_policy',
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"chinese_foreign_policy",
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'chinese_history',
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"chinese_history",
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'chinese_literature',
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"chinese_literature",
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'chinese_teacher_qualification',
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"chinese_teacher_qualification",
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'clinical_knowledge',
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"clinical_knowledge",
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'college_actuarial_science',
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"college_actuarial_science",
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'college_education',
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"college_education",
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'college_engineering_hydrology',
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"college_engineering_hydrology",
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'college_law',
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"college_law",
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'college_mathematics',
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"college_mathematics",
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'college_medical_statistics',
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"college_medical_statistics",
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'college_medicine',
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"college_medicine",
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'computer_science',
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"computer_science",
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'computer_security',
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"computer_security",
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'conceptual_physics',
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"conceptual_physics",
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'construction_project_management',
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"construction_project_management",
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'economics',
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"economics",
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'education',
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"education",
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'electrical_engineering',
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"electrical_engineering",
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'elementary_chinese',
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"elementary_chinese",
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'elementary_commonsense',
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"elementary_commonsense",
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'elementary_information_and_technology',
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"elementary_information_and_technology",
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'elementary_mathematics',
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"elementary_mathematics",
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'ethnology',
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"ethnology",
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'food_science',
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"food_science",
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'genetics',
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"genetics",
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'global_facts',
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"global_facts",
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'high_school_biology',
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"high_school_biology",
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'high_school_chemistry',
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"high_school_chemistry",
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'high_school_geography',
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"high_school_geography",
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'high_school_mathematics',
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"high_school_mathematics",
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'high_school_physics',
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"high_school_physics",
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'high_school_politics',
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"high_school_politics",
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'human_sexuality',
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"human_sexuality",
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'international_law',
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"international_law",
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'journalism',
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"journalism",
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'jurisprudence',
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"jurisprudence",
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'legal_and_moral_basis',
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"legal_and_moral_basis",
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'logical',
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"logical",
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'machine_learning',
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"machine_learning",
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'management',
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"management",
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'marketing',
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"marketing",
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'marxist_theory',
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"marxist_theory",
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'modern_chinese',
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"modern_chinese",
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'nutrition',
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"nutrition",
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'philosophy',
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"philosophy",
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'professional_accounting',
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"professional_accounting",
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'professional_law',
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"professional_law",
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'professional_medicine',
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"professional_medicine",
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'professional_psychology',
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"professional_psychology",
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'public_relations',
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"public_relations",
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'security_study',
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"security_study",
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'sociology',
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"sociology",
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'sports_science',
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"sports_science",
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'traditional_chinese_medicine',
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"traditional_chinese_medicine",
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'virology',
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"virology",
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'world_history',
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"world_history",
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'world_religions',
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"world_religions",
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]
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]
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@ -136,25 +136,19 @@ class MMLU(datasets.GeneratorBasedBuilder):
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datasets.SplitGenerator(
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datasets.SplitGenerator(
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name=datasets.Split.TEST,
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name=datasets.Split.TEST,
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gen_kwargs={
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gen_kwargs={
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"filepath": os.path.join(
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"filepath": os.path.join(data_dir, "data", "test", f"{task_name}_test.csv"),
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data_dir, "data", "test", f"{task_name}_test.csv"
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),
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},
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},
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),
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),
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datasets.SplitGenerator(
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datasets.SplitGenerator(
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name=datasets.Split.VALIDATION,
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name=datasets.Split.VALIDATION,
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gen_kwargs={
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gen_kwargs={
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"filepath": os.path.join(
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"filepath": os.path.join(data_dir, "data", "val", f"{task_name}_val.csv"),
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data_dir, "data", "val", f"{task_name}_val.csv"
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),
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},
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},
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),
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),
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datasets.SplitGenerator(
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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name=datasets.Split.TRAIN,
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gen_kwargs={
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gen_kwargs={
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"filepath": os.path.join(
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"filepath": os.path.join(data_dir, "data", "dev", f"{task_name}_dev.csv"),
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data_dir, "data", "dev", f"{task_name}_dev.csv"
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),
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},
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},
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),
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),
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]
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]
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