DN at SemEval-2023 Task 12: Low-Resource Language Text Classification via Multilingual Pretrained Language Model Fine-tuning

Daniil Homskiy, Narek Maloyan


Abstract
In our work, a model is implemented that solves the task, based on multilingual pre-trained models. We also consider various methods of data preprocessing
Anthology ID:
2023.semeval-1.212
Volume:
Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
Month:
July
Year:
2023
Address:
Toronto, Canada
Editors:
Atul Kr. Ojha, A. Seza Doğruöz, Giovanni Da San Martino, Harish Tayyar Madabushi, Ritesh Kumar, Elisa Sartori
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
1537–1541
Language:
URL:
https://aclanthology.org/2023.semeval-1.212
DOI:
10.18653/v1/2023.semeval-1.212
Bibkey:
Cite (ACL):
Daniil Homskiy and Narek Maloyan. 2023. DN at SemEval-2023 Task 12: Low-Resource Language Text Classification via Multilingual Pretrained Language Model Fine-tuning. In Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023), pages 1537–1541, Toronto, Canada. Association for Computational Linguistics.
Cite (Informal):
DN at SemEval-2023 Task 12: Low-Resource Language Text Classification via Multilingual Pretrained Language Model Fine-tuning (Homskiy & Maloyan, SemEval 2023)
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PDF:
https://aclanthology.org/2023.semeval-1.212.pdf