annotations_creators:
- no-annotation
language_creators:
- crowdsourced
languages:
- en
licenses:
- cc-by-sa-3-0
- gfdl-1-3-or-later
multilinguality:
- monolingual
paperswithcode_id: wikitext-2
pretty_name: WikiText
size_categories:
- 1M<n<10M
source_datasets:
- original
task_categories:
- sequence-modeling
task_ids:
- language-modeling
Dataset Card for "wikitext"
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: https://blog.einstein.ai/the-wikitext-long-term-dependency-language-modeling-dataset/
- Repository: More Information Needed
- Paper: Pointer Sentinel Mixture Models
- Point of Contact: Stephen Merity
- Size of downloaded dataset files: 373.28 MB
- Size of the generated dataset: 1072.25 MB
- Total amount of disk used: 1445.53 MB
Dataset Summary
The WikiText language modeling dataset is a collection of over 100 million tokens extracted from the set of verified Good and Featured articles on Wikipedia. The dataset is available under the Creative Commons Attribution-ShareAlike License.
Compared to the preprocessed version of Penn Treebank (PTB), WikiText-2 is over 2 times larger and WikiText-103 is over 110 times larger. The WikiText dataset also features a far larger vocabulary and retains the original case, punctuation and numbers - all of which are removed in PTB. As it is composed of full articles, the dataset is well suited for models that can take advantage of long term dependencies.
Supported Tasks and Leaderboards
Languages
Dataset Structure
We show detailed information for up to 5 configurations of the dataset.
Data Instances
wikitext-103-raw-v1
- Size of downloaded dataset files: 183.09 MB
- Size of the generated dataset: 523.97 MB
- Total amount of disk used: 707.06 MB
An example of 'validation' looks as follows.
This example was too long and was cropped:
{
"text": "\" The gold dollar or gold one @-@ dollar piece was a coin struck as a regular issue by the United States Bureau of the Mint from..."
}
wikitext-103-v1
- Size of downloaded dataset files: 181.42 MB
- Size of the generated dataset: 522.66 MB
- Total amount of disk used: 704.07 MB
An example of 'train' looks as follows.
This example was too long and was cropped:
{
"text": "\" Senjō no Valkyria 3 : <unk> Chronicles ( Japanese : 戦場のヴァルキュリア3 , lit . Valkyria of the Battlefield 3 ) , commonly referred to..."
}
wikitext-2-raw-v1
- Size of downloaded dataset files: 4.50 MB
- Size of the generated dataset: 12.91 MB
- Total amount of disk used: 17.41 MB
An example of 'train' looks as follows.
This example was too long and was cropped:
{
"text": "\" The Sinclair Scientific Programmable was introduced in 1975 , with the same case as the Sinclair Oxford . It was larger than t..."
}
wikitext-2-v1
- Size of downloaded dataset files: 4.27 MB
- Size of the generated dataset: 12.72 MB
- Total amount of disk used: 16.99 MB
An example of 'train' looks as follows.
This example was too long and was cropped:
{
"text": "\" Senjō no Valkyria 3 : <unk> Chronicles ( Japanese : 戦場のヴァルキュリア3 , lit . Valkyria of the Battlefield 3 ) , commonly referred to..."
}
Data Fields
The data fields are the same among all splits.
wikitext-103-raw-v1
text: astringfeature.
wikitext-103-v1
text: astringfeature.
wikitext-2-raw-v1
text: astringfeature.
wikitext-2-v1
text: astringfeature.
Data Splits
| name | train | validation | test |
|---|---|---|---|
| wikitext-103-raw-v1 | 1801350 | 3760 | 4358 |
| wikitext-103-v1 | 1801350 | 3760 | 4358 |
| wikitext-2-raw-v1 | 36718 | 3760 | 4358 |
| wikitext-2-v1 | 36718 | 3760 | 4358 |
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
The dataset is available under the Creative Commons Attribution-ShareAlike License (CC BY-SA 4.0).
Citation Information
@misc{merity2016pointer,
title={Pointer Sentinel Mixture Models},
author={Stephen Merity and Caiming Xiong and James Bradbury and Richard Socher},
year={2016},
eprint={1609.07843},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
Contributions
Thanks to @thomwolf, @lewtun, @patrickvonplaten, @mariamabarham for adding this dataset.