README.md

metadata

annotations_creators:
  - no-annotation
language_creators:
  - found
language:
  - de
  - en
license:
  - unknown
multilinguality:
  - translation
size_categories:
  - 10M<n<100M
source_datasets:
  - extended|europarl_bilingual
  - extended|news_commentary
  - extended|opus_paracrawl
  - extended|un_multi
task_categories:
  - translation
task_ids: []
pretty_name: WMT T2T
dataset_info:
  config_name: de-en
  features:
    - name: translation
      dtype:
        translation:
          languages:
            - de
            - en
  splits:
    - name: train
      num_bytes: 1385106499
      num_examples: 4592289
    - name: validation
      num_bytes: 736407
      num_examples: 3000
    - name: test
      num_bytes: 777326
      num_examples: 3003
  download_size: 835031826
  dataset_size: 1386620232
configs:
  - config_name: de-en
    data_files:
      - split: train
        path: de-en/train-*
      - split: validation
        path: de-en/validation-*
      - split: test
        path: de-en/test-*
    default: true

Dataset Card for "wmt_t2t"

Table of Contents

• Dataset Description
  • Dataset Summary
  • Supported Tasks and Leaderboards
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits
• Dataset Creation
  • Curation Rationale
  • Source Data
  • Annotations
  • 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
  • Citation Information
  • Contributions

Dataset Description

• Homepage: https://github.com/tensorflow/tensor2tensor/blob/master/tensor2tensor/data_generators/translate_ende.py
• Repository: More Information Needed
• Paper: More Information Needed
• Point of Contact: More Information Needed
• Size of downloaded dataset files: 1.73 GB
• Size of the generated dataset: 1.39 GB
• Total amount of disk used: 3.11 GB

Dataset Summary

The WMT EnDe Translate dataset used by the Tensor2Tensor library.

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("wmt_t2t", "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

de-en

• Size of downloaded dataset files: 1.73 GB
• Size of the generated dataset: 1.39 GB
• Total amount of disk used: 3.11 GB

An example of 'validation' looks as follows.

{
    "translation": {
        "de": "Just a test sentence.",
        "en": "Just a test sentence."
    }
}

Data Fields

The data fields are the same among all splits.

de-en

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

Data Splits

name	train	validation	test
de-en	4592289	3000	3003

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:2014:W14-33,
  author    = {Bojar, Ondrej  and  Buck, Christian  and  Federmann, Christian  and  Haddow, Barry  and  Koehn, Philipp  and  Leveling, Johannes  and  Monz, Christof  and  Pecina, Pavel  and  Post, Matt  and  Saint-Amand, Herve  and  Soricut, Radu  and  Specia, Lucia  and  Tamchyna, Ale
{s}},
  title     = {Findings of the 2014 Workshop on Statistical Machine Translation},
  booktitle = {Proceedings of the Ninth Workshop on Statistical Machine Translation},
  month     = {June},
  year      = {2014},
  address   = {Baltimore, Maryland, USA},
  publisher = {Association for Computational Linguistics},
  pages     = {12--58},
  url       = {http://www.aclweb.org/anthology/W/W14/W14-3302}
}

Contributions

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