How to load this dataset directly with the
π€/datasets
library:
from datasets import load_dataset dataset = load_dataset("qasc")
mrm8488/t5-base-finetuned-qasc
QASC is a question-answering dataset with a focus on sentence composition. It consists of 9,980 8-way multiple-choice questions about grade school science (8,134 train, 926 dev, 920 test), and comes with a corpus of 17M sentences.
We show detailed information for up to 5 configurations of the dataset.
An example of 'validation' looks as follows.
{
"answerKey": "F",
"choices": {
"label": ["A", "B", "C", "D", "E", "F", "G", "H"],
"text": ["sand", "occurs over a wide range", "forests", "Global warming", "rapid changes occur", "local weather conditions", "measure of motion", "city life"]
},
"combinedfact": "Climate is generally described in terms of local weather conditions",
"fact1": "Climate is generally described in terms of temperature and moisture.",
"fact2": "Fire behavior is driven by local weather conditions such as winds, temperature and moisture.",
"formatted_question": "Climate is generally described in terms of what? (A) sand (B) occurs over a wide range (C) forests (D) Global warming (E) rapid changes occur (F) local weather conditions (G) measure of motion (H) city life",
"id": "3NGI5ARFTT4HNGVWXAMLNBMFA0U1PG",
"question": "Climate is generally described in terms of what?"
}
The data fields are the same among all splits.
id
: a string
feature.question
: a string
feature.choices
: a dictionary feature containing:text
: a string
feature.label
: a string
feature.answerKey
: a string
feature.fact1
: a string
feature.fact2
: a string
feature.combinedfact
: a string
feature.formatted_question
: a string
feature.name | train | validation | test |
---|---|---|---|
default | 8134 | 926 | 920 |
@article{allenai:qasc,
author = {Tushar Khot and Peter Clark and Michal Guerquin and Peter Jansen and Ashish Sabharwal},
title = {QASC: A Dataset for Question Answering via Sentence Composition},
journal = {arXiv:1910.11473v2},
year = {2020},
}