Datasetpublic

Layered-Labs/benchbase-pubmedqa

BenchBase PubMedQA PubMedQA normalized into the BenchBase unified schema. Every BenchBase dataset shares the same columns, so one loader and one evaluation loop cover all of them. Source: qiaojin/PubMedQA Code and converter: Layered-Labs/benchbase Items: 1,000 (train: 1,000) Rejected source rows: 0 (see rejected.json) Schema Field Type Description dataset_key str Benchmark identifier (pubmedqa) hash str SHA256(question + answer text), stable across… See the full description on the dataset page: https://huggingface.co/datasets/Layered-Labs/benchbase-pubmedqa.

sourceHugging Facemitupdated 2d agoView on Hugging Face

0likes28downloads

Dataset Card

BenchBase PubMedQA

PubMedQA normalized into the BenchBase unified schema. Every BenchBase dataset shares the same columns, so one loader and one evaluation loop cover all of them.

—Source: qiaojin/PubMedQA
—Code and converter: Layered-Labs/benchbase
—Items: 1,000 (train: 1,000)
—Rejected source rows: 0 (see rejected.json)

Schema

Field	Type	Description
`dataset_key`	str	Benchmark identifier (`pubmedqa`)
`hash`	str	SHA256(question + answer text), stable across option order
`split`	str	Source split
`question_type`	str	`mcq`
`question`	str	Question stem
`context`	str or null	Passage the question refers to, if any
`options`	list[dict]	`[{"original_key": "A", "text": "..."}]`
`answer`	dict	The matching option: `{"original_key": "D", "text": "..."}`
`metadata`	dict	Source fields that do not fit the schema

Usage

python

from datasets import load_dataset

ds = load_dataset("Layered-Labs/benchbase-pubmedqa")
print(ds["train"][0])