MedMCQA : A Large-scale Multi-Subject Multi-Choice Dataset for Medical domain Question Answering

Benchmark Model Rank Results
multiple-choice-question-answering-mcqa-on-medmcqaPubmedBERT(Gu et al., 2022)#7Test Set (Acc-%): 0.41Dev Set (Acc-%): 0.40
multiple-choice-question-answering-mcqa-on-medmcqaSciBERT (Beltagy et al., 2019)#8Test Set (Acc-%): 0.39Dev Set (Acc-%): 0.39
multiple-choice-question-answering-mcqa-on-medmcqaBioBERT (Lee et al.,2020)#9Test Set (Acc-%): 0.37Dev Set (Acc-%): 0.38
multiple-choice-question-answering-mcqa-on-medmcqaBERT (Devlin et al., 2019)-Base#10Test Set (Acc-%): 0.33Dev Set (Acc-%): 0.35