annotations_creators:
- crowdsourced
language:
- en
language_creators:
- crowdsourced
- found
license:
- cc-by-4.0
multilinguality:
- monolingual
pretty_name: SQuAD-shifts
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- question-answering
task_ids:
- extractive-qa
paperswithcode_id: squad-shifts
dataset_info:
- config_name: new_wiki
features:
- name: id
dtype: string
- name: title
dtype: string
- name: context
dtype: string
- name: question
dtype: string
- name: answers
sequence:
- name: text
dtype: string
- name: answer_start
dtype: int32
splits:
- name: test
num_bytes: 7865203
num_examples: 7938
download_size: 16505623
dataset_size: 7865203
- config_name: nyt
features:
- name: id
dtype: string
- name: title
dtype: string
- name: context
dtype: string
- name: question
dtype: string
- name: answers
sequence:
- name: text
dtype: string
- name: answer_start
dtype: int32
splits:
- name: test
num_bytes: 10792550
num_examples: 10065
download_size: 16505623
dataset_size: 10792550
- config_name: reddit
features:
- name: id
dtype: string
- name: title
dtype: string
- name: context
dtype: string
- name: question
dtype: string
- name: answers
sequence:
- name: text
dtype: string
- name: answer_start
dtype: int32
splits:
- name: test
num_bytes: 9473946
num_examples: 9803
download_size: 16505623
dataset_size: 9473946
- config_name: amazon
features:
- name: id
dtype: string
- name: title
dtype: string
- name: context
dtype: string
- name: question
dtype: string
- name: answers
sequence:
- name: text
dtype: string
- name: answer_start
dtype: int32
splits:
- name: test
num_bytes: 9445004
num_examples: 9885
download_size: 16505623
dataset_size: 9445004
Dataset Card for "squadshifts"
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: https://modestyachts.github.io/squadshifts-website/index.html
- Repository: More Information Needed
- Paper: More Information Needed
- Point of Contact: More Information Needed
- Size of downloaded dataset files: 66.02 MB
- Size of the generated dataset: 37.56 MB
- Total amount of disk used: 103.58 MB
Dataset Summary
SquadShifts consists of four new test sets for the Stanford Question Answering Dataset (SQuAD) from four different domains: Wikipedia articles, New York
Times articles, Reddit comments, and Amazon product reviews. Each dataset was generated using the same data generating pipeline, Amazon Mechanical Turk interface, and data cleaning code as the original SQuAD v1.1 dataset. The "new-wikipedia" dataset measures overfitting on the original SQuAD v1.1 dataset. The "new-york-times", "reddit", and "amazon" datasets measure robustness to natural distribution shifts. We encourage SQuAD model developers to also evaluate their methods on these new datasets!
Supported Tasks and Leaderboards
Languages
Dataset Structure
Data Instances
amazon
- Size of downloaded dataset files: 16.50 MB
- Size of the generated dataset: 9.44 MB
- Total amount of disk used: 25.94 MB
An example of 'test' looks as follows.
{
"answers": {
"answer_start": [25],
"text": ["amazon"]
},
"context": "This is a paragraph from amazon.",
"id": "090909",
"question": "Where is this paragraph from?",
"title": "amazon dummy data"
}
new_wiki
- Size of downloaded dataset files: 16.50 MB
- Size of the generated dataset: 7.86 MB
- Total amount of disk used: 24.37 MB
An example of 'test' looks as follows.
{
"answers": {
"answer_start": [25],
"text": ["wikipedia"]
},
"context": "This is a paragraph from wikipedia.",
"id": "090909",
"question": "Where is this paragraph from?",
"title": "new_wiki dummy data"
}
nyt
- Size of downloaded dataset files: 16.50 MB
- Size of the generated dataset: 10.79 MB
- Total amount of disk used: 27.29 MB
An example of 'test' looks as follows.
{
"answers": {
"answer_start": [25],
"text": ["new york times"]
},
"context": "This is a paragraph from new york times.",
"id": "090909",
"question": "Where is this paragraph from?",
"title": "nyt dummy data"
}
- Size of downloaded dataset files: 16.50 MB
- Size of the generated dataset: 9.47 MB
- Total amount of disk used: 25.97 MB
An example of 'test' looks as follows.
{
"answers": {
"answer_start": [25],
"text": ["reddit"]
},
"context": "This is a paragraph from reddit.",
"id": "090909",
"question": "Where is this paragraph from?",
"title": "reddit dummy data"
}
Data Fields
The data fields are the same among all splits.
amazon
id
: astring
feature.title
: astring
feature.context
: astring
feature.question
: astring
feature.answers
: a dictionary feature containing:text
: astring
feature.answer_start
: aint32
feature.
new_wiki
id
: astring
feature.title
: astring
feature.context
: astring
feature.question
: astring
feature.answers
: a dictionary feature containing:text
: astring
feature.answer_start
: aint32
feature.
nyt
id
: astring
feature.title
: astring
feature.context
: astring
feature.question
: astring
feature.answers
: a dictionary feature containing:text
: astring
feature.answer_start
: aint32
feature.
id
: astring
feature.title
: astring
feature.context
: astring
feature.question
: astring
feature.answers
: a dictionary feature containing:text
: astring
feature.answer_start
: aint32
feature.
Data Splits
name | test |
---|---|
amazon | 9885 |
new_wiki | 7938 |
nyt | 10065 |
9803 |
Dataset Creation
Curation Rationale
Source Data
Initial Data Collection and Normalization
Who are the source language producers?
Annotations
Annotation process
Who are the annotators?
Personal and Sensitive Information
Considerations for Using the Data
Social Impact of Dataset
Discussion of Biases
Other Known Limitations
Additional Information
Dataset Curators
Licensing Information
All the datasets are distributed under the CC BY 4.0 license.
Citation Information
@InProceedings{pmlr-v119-miller20a,
title = {The Effect of Natural Distribution Shift on Question Answering Models},
author = {Miller, John and Krauth, Karl and Recht, Benjamin and Schmidt, Ludwig},
booktitle = {Proceedings of the 37th International Conference on Machine Learning},
pages = {6905--6916},
year = {2020},
editor = {III, Hal Daumé and Singh, Aarti},
volume = {119},
series = {Proceedings of Machine Learning Research},
month = {13--18 Jul},
publisher = {PMLR},
pdf = {http://proceedings.mlr.press/v119/miller20a/miller20a.pdf},
url = {https://proceedings.mlr.press/v119/miller20a.html},
}
Contributions
Thanks to @thomwolf, @lewtun, @millerjohnp, @albertvillanova for adding this dataset.