ZYJ123@DravidianLangTech-EACL2021: Offensive Language Identification based on XLM-RoBERTa with DPCNN
Abstract
The development of online media platforms has given users more opportunities to post and comment freely, but the negative impact of offensive language has become increasingly apparent. It is very necessary for the automatic identification system of offensive language. This paper describes our work on the task of Offensive Language Identification in Dravidian language-EACL 2021. To complete this task, we propose a system based on the multilingual model XLM-Roberta and DPCNN. The test results on the official test data set confirm the effectiveness of our system. The weighted average F1-score of Kannada, Malayalam, and Tami language are 0.69, 0.92, and 0.76 respectively, ranked 6th, 6th, and 3rd- Anthology ID:
- 2021.dravidianlangtech-1.29
- Volume:
- Proceedings of the First Workshop on Speech and Language Technologies for Dravidian Languages
- Month:
- April
- Year:
- 2021
- Address:
- Kyiv
- Editors:
- Bharathi Raja Chakravarthi, Ruba Priyadharshini, Anand Kumar M, Parameswari Krishnamurthy, Elizabeth Sherly
- Venue:
- DravidianLangTech
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 216–221
- Language:
- URL:
- https://aclanthology.org/2021.dravidianlangtech-1.29
- DOI:
- Cite (ACL):
- Yingjia Zhao and Xin Tao. 2021. ZYJ123@DravidianLangTech-EACL2021: Offensive Language Identification based on XLM-RoBERTa with DPCNN. In Proceedings of the First Workshop on Speech and Language Technologies for Dravidian Languages, pages 216–221, Kyiv. Association for Computational Linguistics.
- Cite (Informal):
- ZYJ123@DravidianLangTech-EACL2021: Offensive Language Identification based on XLM-RoBERTa with DPCNN (Zhao & Tao, DravidianLangTech 2021)
- PDF:
- https://preview.aclanthology.org/proper-vol2-ingestion/2021.dravidianlangtech-1.29.pdf