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arXiv 2008.00805cs.CL

LT@Helsinki at SemEval-2020 Task 12: Multilingual or language-specific BERT?

University of Helsinki(赫尔辛基大学)

Marc Pàmies, Emily Öhman, Kaisla Kajava, Jörg Tiedemann

英文摘要:

This paper presents the different models submitted by the LT@Helsinki team for the SemEval 2020 Shared Task 12. Our team participated in sub-tasks A and C; titled offensive language identification and offense target identification, respectively. In both cases we used the so-called Bidirectional Encoder Representation from Transformer (BERT), a model pre-trained by Google and fine-tuned by us on the OLID and SOLID datasets. The results show that offensive tweet classification is one of several language-based tasks where BERT can achieve state-of-the-art results.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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