Datasets:
wmt
/

Modalities:
Text
Formats:
parquet
Libraries:
Datasets
Dask
License:
File size: 2,996 Bytes
f05cef3
1
{"de-en": {"description": "Translate dataset based on the data from statmt.org.\n\nVersions exists for the different years using a combination of multiple data\nsources. The base `wmt_translate` allows you to create your own config to choose\nyour own data/language pair by creating a custom `datasets.translate.wmt.WmtConfig`.\n\n```\nconfig = datasets.wmt.WmtConfig(\n    version=\"0.0.1\",\n    language_pair=(\"fr\", \"de\"),\n    subsets={\n        datasets.Split.TRAIN: [\"commoncrawl_frde\"],\n        datasets.Split.VALIDATION: [\"euelections_dev2019\"],\n    },\n)\nbuilder = datasets.builder(\"wmt_translate\", config=config)\n```\n\n", "citation": "\n@InProceedings{bojar-EtAl:2014:W14-33,\n  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\u000b{s}},\n  title     = {Findings of the 2014 Workshop on Statistical Machine Translation},\n  booktitle = {Proceedings of the Ninth Workshop on Statistical Machine Translation},\n  month     = {June},\n  year      = {2014},\n  address   = {Baltimore, Maryland, USA},\n  publisher = {Association for Computational Linguistics},\n  pages     = {12--58},\n  url       = {http://www.aclweb.org/anthology/W/W14/W14-3302}\n}\n", "homepage": "https://github.com/tensorflow/tensor2tensor/blob/master/tensor2tensor/data_generators/translate_ende.py", "license": "", "features": {"translation": {"languages": ["de", "en"], "id": null, "_type": "Translation"}}, "supervised_keys": {"input": "de", "output": "en"}, "builder_name": "wmt_t2t", "config_name": "de-en", "version": {"version_str": "1.0.0", "description": null, "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"test": {"name": "test", "num_bytes": 777334, "num_examples": 3003, "dataset_name": "wmt_t2t"}, "train": {"name": "train", "num_bytes": 1385124761, "num_examples": 4592289, "dataset_name": "wmt_t2t"}, "validation": {"name": "validation", "num_bytes": 736415, "num_examples": 3000, "dataset_name": "wmt_t2t"}}, "download_checksums": {"http://www.statmt.org/wmt13/training-parallel-europarl-v7.tgz": {"num_bytes": 657632379, "checksum": "0224c7c710c8a063dfd893b0cc0830202d61f4c75c17eb8e31836103d27d96e7"}, "http://www.statmt.org/wmt13/training-parallel-commoncrawl.tgz": {"num_bytes": 918311367, "checksum": "c7a74e2ea01ac6c920123108627e35278d4ccb5701e15428ffa34de86fa3a9e5"}, "http://data.statmt.org/wmt18/translation-task/training-parallel-nc-v13.tgz": {"num_bytes": 113157482, "checksum": "17992b7e919cfb754c60f4e754148bc23b80706ad0ed7b34150831a554b40c91"}, "http://data.statmt.org/wmt19/translation-task/dev.tgz": {"num_bytes": 38654961, "checksum": "7a7deccf82ebb05ba508dba5eb21356492224e8f630ec4f992132b029b4b25e7"}}, "download_size": 1727756189, "dataset_size": 1386638510, "size_in_bytes": 3114394699}}