MLDoc

Multilingual Document Classification Corpus

Multilingual Document Classification Corpus (MLDoc) is a cross-lingual document classification dataset covering English, German, French, Spanish, Italian, Russian, Japanese and Chinese. It is a subset of the Reuters Corpus Volume 2 selected according to the following design choices: * uniform class coverage: same number of examples for each class and language, * official train / development / test split: for each language a training data of different sizes (1K, 2K, 5K and 10K stories), a development (1K) and a test corpus (4K) are provided (with exception of Spanish and Russian with 9458 and 5216 training documents respectively. Source: A Corpus for Multilingual Document Classification in Eight Languages

Texts EnglishFrenchSpanishGermanItalianChineseMultilingualJapaneseRussian

벤치마크

Cross-Lingual Document Classification on MLDoc Zero-Shot English-to-French 결과 12개

Cross-Lingual Document Classification on MLDoc Zero-Shot English-to-Spanish 결과 12개

Cross-Lingual Document Classification on MLDoc Zero-Shot English-to-Chinese 결과 10개

Cross-Lingual Document Classification on MLDoc Zero-Shot English-to-German 결과 10개

Cross-Lingual Document Classification on MLDoc Zero-Shot English-to-Russian 결과 10개

Cross-Lingual Document Classification on MLDoc Zero-Shot English-to-Italian 결과 8개

Cross-Lingual Document Classification on MLDoc Zero-Shot English-to-Japanese 결과 6개

Cross-Lingual Document Classification on MLDoc Zero-Shot German-to-French 결과 2개