数据集:
wmt14
Warning: There are issues with the Common Crawl corpus data ( training-parallel-commoncrawl.tgz ):
We have contacted the WMT organizers.
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("wmt14", "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()
An example of 'train' looks as follows.
The data fields are the same among all splits.
cs-enname | train | validation | test |
---|---|---|---|
cs-en | 953621 | 3000 | 3003 |
@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}
}
Thanks to @thomwolf , @patrickvonplaten for adding this dataset.