Dataset Card for "wmt15"

Dataset Summary

Translate dataset based on the data from

Versions exists for the different years using a combination of multiple data sources. The base wmt_translate allows you to create your own config to choose your own data/language pair by creating a custom datasets.translate.wmt.WmtConfig.

config = datasets.wmt.WmtConfig(
    language_pair=("fr", "de"),
        datasets.Split.TRAIN: ["commoncrawl_frde"],
        datasets.Split.VALIDATION: ["euelections_dev2019"],
builder = datasets.builder("wmt_translate", config=config)

Supported Tasks and Leaderboards

More Information Needed


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Dataset Structure

We show detailed information for up to 5 configurations of the dataset.

Data Instances


  • Size of downloaded dataset files: 1659.14 MB
  • Size of the generated dataset: 271.17 MB
  • Total amount of disk used: 1930.31 MB

An example of 'validation' looks as follows.

Data Fields

The data fields are the same among all splits.


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

Data Splits

name train validation test
cs-en 959768 3003 2656

Dataset Creation

Curation Rationale

More Information Needed

Source Data

Initial Data Collection and Normalization

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Who are the source language producers?

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Annotation process

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Who are the annotators?

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Personal and Sensitive Information

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Considerations for Using the Data

Social Impact of Dataset

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Discussion of Biases

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Other Known Limitations

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Additional Information

Dataset Curators

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Licensing Information

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Citation Information

  author    = {Bojar, Ond{r}ej  and  Chatterjee, Rajen  and  Federmann, Christian  and  Haddow, Barry  and  Huck, Matthias  and  Hokamp, Chris  and  Koehn, Philipp  and  Logacheva, Varvara  and  Monz, Christof  and  Negri, Matteo  and  Post, Matt  and  Scarton, Carolina  and  Specia, Lucia  and  Turchi, Marco},
  title     = {Findings of the 2015 Workshop on Statistical Machine Translation},
  booktitle = {Proceedings of the Tenth Workshop on Statistical Machine Translation},
  month     = {September},
  year      = {2015},
  address   = {Lisbon, Portugal},
  publisher = {Association for Computational Linguistics},
  pages     = {1--46},
  url       = {}


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

Models trained or fine-tuned on wmt15

None yet