Datasets:
File size: 1,905 Bytes
0992654 |
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 54 |
<br />
<div align="center">
<h2 align="center">AskDocs: A medical QA dataset</h2>
<img src="https://images.emojiterra.com/google/noto-emoji/v2.034/512px/1fa7a.png" alt="https://en.wikipedia.org/wiki/Stethoscope" width="250">
<br />
<img alt="GitHub release (latest by date)" src="https://img.shields.io/github/v/release/ju-resplande/askD">
<img alt="GitHub" src="https://img.shields.io/github/license/ju-resplande/askD">
<img alt="GitHub Repo stars" src="https://img.shields.io/github/stars/ju-resplande/askD?style=social">
<p align="center">
<b>
<a href="https://huggingface.co/datasets/eli5">ELI5 dataset</a> adapted on <a href="https://www.reddit.com/r/AskDocs/">Medical Questions (AskDocs)</a> subreddit.
</b>
</p>
</div>
## Getting Started
| Languages | Splits|
| --- | --- |
| en | train_en, validation_en, test_en, external_en |
| pt | train_pt, validation_pt, test_pt, external_pt |
We additionally translated to Portuguese and used <a href="https://github.com/LasseRegin/medical-question-answer-data"> external data from here<a>.
External data are from binary classification dataset "a QNLI medical-like", we adapted to value 5 or 0.
### Usage
#### Datasets :hugs
```python
from datasets import load_dataset
data = load_dataset("ju-resplande/askD", "train_pt")
# ['train_en', 'validation_en', 'test_en', 'external_en', 'train_pt', 'validation_pt', 'test_pt', 'external_pt']
```
## Citing
```bibtex
@misc{Gomes20202,
author = {GOMES, J. R. S.},
title = {PLUE: Portuguese Language Understanding Evaluation},
year = {2020},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\url{https://github.com/ju-resplande/askD}},
commit = {42060c4402c460e174cbb75a868b429c554ba2b7}
}
```
## Acknowledgments
[@viniciusplo](https://github.com/viniciusplo) and [@ruanchaves](https://github.com/ruanchaves) for giving the idea. :smiley:
|