File size: 1,350 Bytes
0a6268a
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
21a09c0
0a6268a
 
 
 
 
 
 
21a09c0
 
0a6268a
772751c
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
---
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