数据集:
wmt14
警告:Common Crawl语料库数据存在问题( training-parallel-commoncrawl.tgz ):
我们已经联系了WMT组织者。
基于statmt.org数据的翻译数据集。
不同年份的版本使用了多个数据源的组合。基于wmt基础可以通过选择自己的数据/语言对来创建自定义数据集。可以按照以下方式进行:
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()
'train'的一个示例如下所示。
数据字段在所有拆分之间相同。
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} }
感谢 @thomwolf , @patrickvonplaten 添加了这个数据集。