{"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":"a4b39a33-f3e9-591c-8097-645d19366dac","task_key":"default--test--10485","task_revision_id":"1","upstream_id":"10485","short_description":"Statement 1| RoBERTa pretrains on a corpus that is approximate 10x larger than…","config":"default","split":"test","body":"{\"category\":\"computer science\",\"options\":\"['False, False', 'False, True', 'True, True', 'Both are partially false', 'Both are partially true', 'Statement 1 is completely true, Statement 2 is partially false', 'Statement 1 is mostly true, Statement 2 is false', 'Statement 1 is completely false, Statement 2 is partially true', 'True, False', 'Statement 1 is false, Statement 2 is mostly true']\",\"question\":\"Statement 1| RoBERTa pretrains on a corpus that is approximate 10x larger than the corpus BERT pretrained on. Statement 2| ResNeXts in 2018 usually used tanh activation functions.\",\"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":[]}