annotations_creators:
- no-annotation
language_creators:
- crowdsourced
language:
- en
license:
- cc-by-sa-3.0
- gfdl
multilinguality:
- monolingual
size_categories:
- 1M<n<10M
source_datasets:
- original
task_categories:
- text-generation
- fill-mask
task_ids:
- language-modeling
- masked-language-modeling
paperswithcode_id: wikitext-2
pretty_name: WikiText
dataset_info:
- config_name: wikitext-103-raw-v1
features:
- name: text
dtype: string
splits:
- name: test
num_bytes: 1305088
num_examples: 4358
- name: train
num_bytes: 546500949
num_examples: 1801350
- name: validation
num_bytes: 1159288
num_examples: 3760
download_size: 315466397
dataset_size: 548965325
- config_name: wikitext-103-v1
features:
- name: text
dtype: string
splits:
- name: test
num_bytes: 1295575
num_examples: 4358
- name: train
num_bytes: 545141915
num_examples: 1801350
- name: validation
num_bytes: 1154751
num_examples: 3760
download_size: 313093838
dataset_size: 547592241
- config_name: wikitext-2-raw-v1
features:
- name: text
dtype: string
splits:
- name: test
num_bytes: 1305092
num_examples: 4358
- name: train
num_bytes: 11061733
num_examples: 36718
- name: validation
num_bytes: 1159292
num_examples: 3760
download_size: 4721645
dataset_size: 13526117
- config_name: wikitext-2-v1
features:
- name: text
dtype: string
splits:
- name: test
num_bytes: 1270947
num_examples: 4358
- name: train
num_bytes: 10918118
num_examples: 36718
- name: validation
num_bytes: 1134123
num_examples: 3760
download_size: 7371282
dataset_size: 13323188
configs:
- config_name: wikitext-103-raw-v1
data_files:
- split: test
path: wikitext-103-raw-v1/test-*
- split: train
path: wikitext-103-raw-v1/train-*
- split: validation
path: wikitext-103-raw-v1/validation-*
- config_name: wikitext-103-v1
data_files:
- split: test
path: wikitext-103-v1/test-*
- split: train
path: wikitext-103-v1/train-*
- split: validation
path: wikitext-103-v1/validation-*
- config_name: wikitext-2-v1
data_files:
- split: test
path: wikitext-2-v1/test-*
- split: train
path: wikitext-2-v1/train-*
- split: validation
path: wikitext-2-v1/validation-*
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: 391.41 MB
- Size of the generated dataset: 1.12 GB
- Total amount of disk used: 1.52 GB
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.
Each subset comes in two different variants:
- Raw (for character level work) contain the raw tokens, before the addition of the (unknown) tokens.
- Non-raw (for word level work) contain only the tokens in their vocabulary (wiki.train.tokens, wiki.valid.tokens, and wiki.test.tokens). The out-of-vocabulary tokens have been replaced with the the token.
Supported Tasks and Leaderboards
Languages
Dataset Structure
Data Instances
wikitext-103-raw-v1
- Size of downloaded dataset files: 191.98 MB
- Size of the generated dataset: 549.42 MB
- Total amount of disk used: 741.41 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: 190.23 MB
- Size of the generated dataset: 548.05 MB
- Total amount of disk used: 738.27 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: 4.72 MB
- Size of the generated dataset: 13.54 MB
- Total amount of disk used: 18.26 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: 4.48 MB
- Size of the generated dataset: 13.34 MB
- Total amount of disk used: 17.82 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
: astring
feature.
wikitext-103-v1
text
: astring
feature.
wikitext-2-raw-v1
text
: astring
feature.
wikitext-2-v1
text
: astring
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
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.