{"kind":"task","effective_mode":"full","benchmark":{"kind":"benchmark","effective_mode":"full","slug":"mmlu-pro","formal_name":"MMLU-Pro","introduction":"MMLU-Pro rebuilds MMLU with ten answer options instead of four and removes items that no longer separate models. Questions span fourteen academic and professional subjects.","introduction_ja":"","introduction_en":"","category":"Category not supplied","task_count":null,"acquisition_status":"Acquisition status not supplied","official_url":"https://huggingface.co/datasets/TIGER-Lab/MMLU-Pro","indexing_mode":"index","profile":{"resources":[],"task_format":"","scoring":"","metric":"","size":"","answer_access":"","license":"","citation":"","maintainer":"","released":"","why_hard":"","related":[],"history":"","construction":"","limitations":"","saturation":"","scores":[]}},"task_id":"7f5625ac-6e19-5594-872b-cefc1e5a4872","task_key":"default--test--10665","task_revision_id":"1","upstream_id":"10665","short_description":"Statement 1| We learn a classifier f by boosting weak learners h. The functional…","config":"default","split":"test","body":"{\"category\":\"computer science\",\"options\":\"['The statement 1 is not clear, True', 'False, False', 'True, Statement 2 is not clear', 'False, Both are not related', 'True, False', 'True, True', 'Both statements are not clear', 'False, True', 'True, Cross validation is not needed', 'False, Cross validation increases overfitting']\",\"question\":\"Statement 1| We learn a classifier f by boosting weak learners h. The functional form of f’s decision boundary is the same as h’s, but with different parameters. (e.g., if h was a linear classifier, then f is also a linear classifier). Statement 2| Cross validation can be used to select the number of iterations in boosting; this procedure may help reduce overfitting.\",\"src\":\"ori_mmlu-machine_learning\"}","display_format":"text","language":"","answer_status":"published","assets":[],"source_url":"https://huggingface.co/datasets/TIGER-Lab/MMLU-Pro","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}