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---
license: agpl-3.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: val
path: data/val-*
- split: test
path: data/test-*
dataset_info:
features:
- name: input
dtype: string
splits:
- name: train
num_bytes: 136602851.95652175
num_examples: 7260
- name: val
num_bytes: 17065948.584650856
num_examples: 907
- name: test
num_bytes: 17084764.40447958
num_examples: 908
download_size: 82888007
dataset_size: 170753564.9456522
task_categories:
- text-generation
- question-answering
- summarization
language:
- en
tags:
- biology
- biomedicine
pretty_name: PubMed Referenced Question Answering Dataset
size_categories:
- 10M<n<100M
---
# Dataset description
The PQAref dataset is a dataset for fine-tuning large language models for referenced question-answering in biomedical domain.
The dataset contains 3 components:
- Instruction - question that is supposed to be answered
- Abstracts - set of 10 relevant abstracts retrieved from PubMed by an IR system. They contain the PubMed id, abstract title and the content of the abstract
- Answer - expected answer, with references in the form of PubMed IDs.
The dataset was created semi-automatically, utilizing questions available from PubMedQA dataset.
# arXiv paper
https://arxiv.org/abs/2407.05015 |