Datasets:
wikitext

Task Categories: sequence-modeling
Languages: en
Multilinguality: monolingual
Size Categories: 1M<n<10M
Language Creators: crowdsourced
Annotations Creators: no-annotation
Source Datasets: original
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Dataset Card for "wikitext"

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

More Information Needed

Languages

More Information Needed

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: a string feature.

wikitext-103-v1

  • text: a string feature.

wikitext-2-raw-v1

  • text: a string feature.

wikitext-2-v1

  • text: a string feature.

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

More Information Needed

Source Data

Initial Data Collection and Normalization

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Who are the source language producers?

More Information Needed

Annotations

Annotation process

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Who are the annotators?

More Information Needed

Personal and Sensitive Information

More Information Needed

Considerations for Using the Data

Social Impact of Dataset

More Information Needed

Discussion of Biases

More Information Needed

Other Known Limitations

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Additional Information

Dataset Curators

More Information Needed

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.

Models trained or fine-tuned on wikitext