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• W3136336051 abstract "This paper describes the training process of the first Czech monolingual language representation models based on BERT and ALBERT architectures. We pre-train our models on more than 340K of sentences, which is 50 times more than multilingual models that include Czech data. We outperform the multilingual models on 9 out of 11 datasets. In addition, we establish the new state-of-the-art results on nine datasets. At the end, we discuss properties of monolingual and multilingual models based upon our results. We publish all the pre-trained and fine-tuned models freely for the research community." @default.
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• W3136336051 date "2021-03-24" @default.
• W3136336051 modified "2023-09-27" @default.
• W3136336051 title "Czert -- Czech BERT-like Model for Language Representation" @default.
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