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metadata
annotations_creators:
  - no-annotation
language_creators:
  - found
language:
  - cs
  - de
  - en
  - et
  - fi
  - kk
  - ru
  - tr
  - zh
license:
  - unknown
multilinguality:
  - translation
size_categories:
  - 10M<n<100M
source_datasets:
  - extended|europarl_bilingual
  - extended|news_commentary
  - extended|opus_paracrawl
  - extended|setimes
  - extended|un_multi
task_categories:
  - translation
task_ids: []
paperswithcode_id: wmt-2018
pretty_name: WMT18
dataset_info:
  - config_name: cs-en
    features:
      - name: translation
        dtype:
          translation:
            languages:
              - cs
              - en
    splits:
      - name: train
        num_bytes: 1461007346
        num_examples: 11046024
      - name: validation
        num_bytes: 674422
        num_examples: 3005
      - name: test
        num_bytes: 696221
        num_examples: 2983
    download_size: 738874648
    dataset_size: 1462377989
  - config_name: de-en
    features:
      - name: translation
        dtype:
          translation:
            languages:
              - de
              - en
    splits:
      - name: train
        num_bytes: 8187518284
        num_examples: 42271874
      - name: validation
        num_bytes: 729511
        num_examples: 3004
      - name: test
        num_bytes: 757641
        num_examples: 2998
    download_size: 4436297213
    dataset_size: 8189005436
  - config_name: et-en
    features:
      - name: translation
        dtype:
          translation:
            languages:
              - et
              - en
    splits:
      - name: train
        num_bytes: 647990923
        num_examples: 2175873
      - name: validation
        num_bytes: 459390
        num_examples: 2000
      - name: test
        num_bytes: 489386
        num_examples: 2000
    download_size: 283931426
    dataset_size: 648939699
  - config_name: fi-en
    features:
      - name: translation
        dtype:
          translation:
            languages:
              - fi
              - en
    splits:
      - name: train
        num_bytes: 857169249
        num_examples: 3280600
      - name: validation
        num_bytes: 1388820
        num_examples: 6004
      - name: test
        num_bytes: 691833
        num_examples: 3000
    download_size: 488708706
    dataset_size: 859249902
  - config_name: kk-en
    features:
      - name: translation
        dtype:
          translation:
            languages:
              - kk
              - en
    splits:
      - name: train
      - name: validation
      - name: test
    download_size: 0
    dataset_size: 0
  - config_name: ru-en
    features:
      - name: translation
        dtype:
          translation:
            languages:
              - ru
              - en
    splits:
      - name: train
        num_bytes: 13665338159
        num_examples: 36858512
      - name: validation
        num_bytes: 1040187
        num_examples: 3001
      - name: test
        num_bytes: 1085588
        num_examples: 3000
    download_size: 6130744133
    dataset_size: 13667463934
  - config_name: tr-en
    features:
      - name: translation
        dtype:
          translation:
            languages:
              - tr
              - en
    splits:
      - name: train
        num_bytes: 60416449
        num_examples: 205756
      - name: validation
        num_bytes: 752765
        num_examples: 3007
      - name: test
        num_bytes: 770305
        num_examples: 3000
    download_size: 37733844
    dataset_size: 61939519
  - config_name: zh-en
    features:
      - name: translation
        dtype:
          translation:
            languages:
              - zh
              - en
    splits:
      - name: train
        num_bytes: 6342987000
        num_examples: 25160346
      - name: validation
        num_bytes: 540339
        num_examples: 2001
      - name: test
        num_bytes: 1107514
        num_examples: 3981
    download_size: 3581074494
    dataset_size: 6344634853
configs:
  - config_name: cs-en
    data_files:
      - split: train
        path: cs-en/train-*
      - split: validation
        path: cs-en/validation-*
      - split: test
        path: cs-en/test-*
  - config_name: de-en
    data_files:
      - split: train
        path: de-en/train-*
      - split: validation
        path: de-en/validation-*
      - split: test
        path: de-en/test-*
  - config_name: et-en
    data_files:
      - split: train
        path: et-en/train-*
      - split: validation
        path: et-en/validation-*
      - split: test
        path: et-en/test-*
  - config_name: fi-en
    data_files:
      - split: train
        path: fi-en/train-*
      - split: validation
        path: fi-en/validation-*
      - split: test
        path: fi-en/test-*
  - config_name: ru-en
    data_files:
      - split: train
        path: ru-en/train-*
      - split: validation
        path: ru-en/validation-*
      - split: test
        path: ru-en/test-*
  - config_name: tr-en
    data_files:
      - split: train
        path: tr-en/train-*
      - split: validation
        path: tr-en/validation-*
      - split: test
        path: tr-en/test-*
  - config_name: zh-en
    data_files:
      - split: train
        path: zh-en/train-*
      - split: validation
        path: zh-en/validation-*
      - split: test
        path: zh-en/test-*

Dataset Card for "wmt18"

Table of Contents

Dataset Description

Dataset Summary

Warning: There are issues with the Common Crawl corpus data (training-parallel-commoncrawl.tgz):

  • Non-English files contain many English sentences.
  • Their "parallel" sentences in English are not aligned: they are uncorrelated with their counterpart.

We have contacted the WMT organizers, and in response, they have indicated that they do not have plans to update the Common Crawl corpus data. Their rationale pertains to the expectation that such data has been superseded, primarily by CCMatrix, and to some extent, by ParaCrawl datasets.

Translation dataset based on the data from statmt.org.

Versions exist for different years using a combination of data sources. The base wmt allows you to create a custom dataset by choosing your own data/language pair. This can be done as follows:

from datasets import inspect_dataset, load_dataset_builder

inspect_dataset("wmt18", "path/to/scripts")
builder = load_dataset_builder(
    "path/to/scripts/wmt_utils.py",
    language_pair=("fr", "de"),
    subsets={
        datasets.Split.TRAIN: ["commoncrawl_frde"],
        datasets.Split.VALIDATION: ["euelections_dev2019"],
    },
)

# Standard version
builder.download_and_prepare()
ds = builder.as_dataset()

# Streamable version
ds = builder.as_streaming_dataset()

Supported Tasks and Leaderboards

More Information Needed

Languages

More Information Needed

Dataset Structure

Data Instances

cs-en

  • Size of downloaded dataset files: 2.03 GB
  • Size of the generated dataset: 1.46 GB
  • Total amount of disk used: 3.49 GB

An example of 'validation' looks as follows.


Data Fields

The data fields are the same among all splits.

cs-en

  • translation: a multilingual string variable, with possible languages including cs, en.

Data Splits

name train validation test
cs-en 11046024 3005 2983

Dataset Creation

Curation Rationale

More Information Needed

Source Data

Initial Data Collection and Normalization

More Information Needed

Who are the source language producers?

More Information Needed

Annotations

Annotation process

More Information Needed

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

More Information Needed

Additional Information

Dataset Curators

More Information Needed

Licensing Information

More Information Needed

Citation Information

@InProceedings{bojar-EtAl:2018:WMT1,
  author    = {Bojar, Ond
{r}ej  and  Federmann, Christian  and  Fishel, Mark
    and Graham, Yvette  and  Haddow, Barry  and  Huck, Matthias  and
    Koehn, Philipp  and  Monz, Christof},
  title     = {Findings of the 2018 Conference on Machine Translation (WMT18)},
  booktitle = {Proceedings of the Third Conference on Machine Translation,
    Volume 2: Shared Task Papers},
  month     = {October},
  year      = {2018},
  address   = {Belgium, Brussels},
  publisher = {Association for Computational Linguistics},
  pages     = {272--307},
  url       = {http://www.aclweb.org/anthology/W18-6401}
}

Contributions

Thanks to @thomwolf, @patrickvonplaten for adding this dataset.