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wmt16_translate

Translate dataset based on the data from statmt.org.

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 tfds.translate.wmt.WmtConfig.

config = tfds.translate.wmt.WmtConfig(
    version="0.0.1",
    language_pair=("fr", "de"),
    subsets={
        tfds.Split.TRAIN: ["commoncrawl_frde"],
        tfds.Split.VALIDATION: ["euelections_dev2019"],
    },
)
builder = tfds.builder("wmt_translate", config=config)

wmt16_translate is configured with tfds.translate.wmt.WmtConfig and has the following configurations predefined (defaults to the first one):

  • cs-en (v0.0.3) (Size: 1.57 GiB): WMT 2016 cs-en translation task dataset.

  • de-en (v0.0.3) (Size: 1.57 GiB): WMT 2016 de-en translation task dataset.

  • fi-en (v0.0.3) (Size: 260.51 MiB): WMT 2016 fi-en translation task dataset.

  • ro-en (v0.0.3) (Size: 273.83 MiB): WMT 2016 ro-en translation task dataset.

  • ru-en (v0.0.3) (Size: 993.38 MiB): WMT 2016 ru-en translation task dataset.

  • tr-en (v0.0.3) (Size: 59.32 MiB): WMT 2016 tr-en translation task dataset.

wmt16_translate/cs-en

WMT 2016 cs-en translation task dataset.

Versions:

  • 0.0.3 (default):

Statistics

Split Examples
ALL 52,341,306
TRAIN 52,335,651
TEST 2,999
VALIDATION 2,656

Features

Translation({
    'cs': Text(shape=(), dtype=tf.string),
    'en': Text(shape=(), dtype=tf.string),
})

Urls

Supervised keys (for as_supervised=True)

(u'cs', u'en')

wmt16_translate/de-en

WMT 2016 de-en translation task dataset.

Versions:

  • 0.0.3 (default):

Statistics

Split Examples
ALL 4,554,053
TRAIN 4,548,885
TEST 2,999
VALIDATION 2,169

Features

Translation({
    'de': Text(shape=(), dtype=tf.string),
    'en': Text(shape=(), dtype=tf.string),
})

Urls

Supervised keys (for as_supervised=True)

(u'de', u'en')

wmt16_translate/fi-en

WMT 2016 fi-en translation task dataset.

Versions:

  • 0.0.3 (default):

Statistics

Split Examples
ALL 2,080,764
TRAIN 2,073,394
TEST 6,000
VALIDATION 1,370

Features

Translation({
    'en': Text(shape=(), dtype=tf.string),
    'fi': Text(shape=(), dtype=tf.string),
})

Urls

Supervised keys (for as_supervised=True)

(u'fi', u'en')

wmt16_translate/ro-en

WMT 2016 ro-en translation task dataset.

Versions:

  • 0.0.3 (default):

Statistics

Split Examples
ALL 614,318
TRAIN 610,320
TEST 1,999
VALIDATION 1,999

Features

Translation({
    'en': Text(shape=(), dtype=tf.string),
    'ro': Text(shape=(), dtype=tf.string),
})

Urls

Supervised keys (for as_supervised=True)

(u'ro', u'en')

wmt16_translate/ru-en

WMT 2016 ru-en translation task dataset.

Versions:

  • 0.0.3 (default):

Statistics

Split Examples
ALL 2,521,978
TRAIN 2,516,162
TEST 2,998
VALIDATION 2,818

Features

Translation({
    'en': Text(shape=(), dtype=tf.string),
    'ru': Text(shape=(), dtype=tf.string),
})

Urls

Supervised keys (for as_supervised=True)

(u'ru', u'en')

wmt16_translate/tr-en

WMT 2016 tr-en translation task dataset.

Versions:

  • 0.0.3 (default):

Statistics

Split Examples
ALL 209,757
TRAIN 205,756
TEST 3,000
VALIDATION 1,001

Features

Translation({
    'en': Text(shape=(), dtype=tf.string),
    'tr': Text(shape=(), dtype=tf.string),
})

Urls

Supervised keys (for as_supervised=True)

(u'tr', u'en')

Citation

@InProceedings{bojar-EtAl:2016:WMT1,
  author    = {Bojar, Ond
{r}ej  and  Chatterjee, Rajen  and  Federmann, Christian  and  Graham, Yvette  and  Haddow, Barry  and  Huck, Matthias  and  Jimeno Yepes, Antonio  and  Koehn, Philipp  and  Logacheva, Varvara  and  Monz, Christof  and  Negri, Matteo  and  Neveol, Aurelie  and  Neves, Mariana  and  Popel, Martin  and  Post, Matt  and  Rubino, Raphael  and  Scarton, Carolina  and  Specia, Lucia  and  Turchi, Marco  and  Verspoor, Karin  and  Zampieri, Marcos},
  title     = {Findings of the 2016 Conference on Machine Translation},
  booktitle = {Proceedings of the First Conference on Machine Translation},
  month     = {August},
  year      = {2016},
  address   = {Berlin, Germany},
  publisher = {Association for Computational Linguistics},
  pages     = {131--198},
  url       = {http://www.aclweb.org/anthology/W/W16/W16-2301}
}