Dataset · Hugging Face

mteb/medical_qa

Name: medical_qa
Creator: mteb
License: cc0-1.0
Keywords: task_categories:text-retrieval, task_ids:document-retrieval, annotations_creators:derived, multilinguality:monolingual, language:eng, license:cc0-1.0, size_categories:1K<n<10K, format:json, modality:text, library:datasets, library:pandas, library:mlcroissant, library:polars, arxiv:2502.13595, arxiv:2210.07316

MedicalQARetrieval An MTEB dataset Massive Text Embedding Benchmark The dataset consists 2048 medical question and answer pairs. Task category t2t Domains Medical, Written Reference https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-3119-4 How to evaluate on this task You can evaluate an embedding model on this dataset using the following code: import mteb task = mteb.get_tasks(["MedicalQARetrieval"]) evaluator =… See the full description on the dataset page: https://huggingface.co/datasets/mteb/medical_qa.

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Author / organization	mteb
License (as declared)	cc0-1.0
Downloads	551 (as reported by Hugging Face)
Likes	2
Created	10 April 2024
Last updated at source	4 May 2025

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17 Oct 2026 Description: MedicalQARetrieval An MTEB dataset Massive Text Embedding Benchmark The dataset consists 2048 medical question and answer pairs. Task category t2t Domains Medical, Written Reference https://bmcbioinformatics.biomedcentral.com/articles/10.11 → MedicalQARetrieval An MTEB dataset Massive Text Embedding Benchmark The dataset consists 2048 medical question and answer pairs. Task category t2t Domains Medical, Written Reference https://bmcbioinformatics.biomedcentral.com/articles/10.11

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