@inproceedings{perez-etal-2020-andes,
title = "{ANDES} at {S}em{E}val-2020 Task 12: A Jointly-trained {BERT} Multilingual Model for Offensive Language Detection",
author = "P{\'e}rez, Juan Manuel and
Arango, Aym{\'e} and
Luque, Franco",
editor = "Herbelot, Aurelie and
Zhu, Xiaodan and
Palmer, Alexis and
Schneider, Nathan and
May, Jonathan and
Shutova, Ekaterina",
booktitle = "Proceedings of the Fourteenth Workshop on Semantic Evaluation",
month = dec,
year = "2020",
address = "Barcelona (online)",
publisher = "International Committee for Computational Linguistics",
url = "https://aclanthology.org/2020.semeval-1.199/",
doi = "10.18653/v1/2020.semeval-1.199",
pages = "1524--1531",
abstract = "This paper describes our participation in SemEval-2020 Task 12: Multilingual Offensive Language Detection. We jointly-trained a single model by fine-tuning Multilingual BERT to tackle the task across all the proposed languages: English, Danish, Turkish, Greek and Arabic. Our single model had competitive results, with a performance close to top-performing systems in spite of sharing the same parameters across all languages. Zero-shot and few-shot experiments were also conducted to analyze the transference performance among these languages. We make our code public for further research"
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<abstract>This paper describes our participation in SemEval-2020 Task 12: Multilingual Offensive Language Detection. We jointly-trained a single model by fine-tuning Multilingual BERT to tackle the task across all the proposed languages: English, Danish, Turkish, Greek and Arabic. Our single model had competitive results, with a performance close to top-performing systems in spite of sharing the same parameters across all languages. Zero-shot and few-shot experiments were also conducted to analyze the transference performance among these languages. We make our code public for further research</abstract>
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%0 Conference Proceedings
%T ANDES at SemEval-2020 Task 12: A Jointly-trained BERT Multilingual Model for Offensive Language Detection
%A Pérez, Juan Manuel
%A Arango, Aymé
%A Luque, Franco
%Y Herbelot, Aurelie
%Y Zhu, Xiaodan
%Y Palmer, Alexis
%Y Schneider, Nathan
%Y May, Jonathan
%Y Shutova, Ekaterina
%S Proceedings of the Fourteenth Workshop on Semantic Evaluation
%D 2020
%8 December
%I International Committee for Computational Linguistics
%C Barcelona (online)
%F perez-etal-2020-andes
%X This paper describes our participation in SemEval-2020 Task 12: Multilingual Offensive Language Detection. We jointly-trained a single model by fine-tuning Multilingual BERT to tackle the task across all the proposed languages: English, Danish, Turkish, Greek and Arabic. Our single model had competitive results, with a performance close to top-performing systems in spite of sharing the same parameters across all languages. Zero-shot and few-shot experiments were also conducted to analyze the transference performance among these languages. We make our code public for further research
%R 10.18653/v1/2020.semeval-1.199
%U https://aclanthology.org/2020.semeval-1.199/
%U https://doi.org/10.18653/v1/2020.semeval-1.199
%P 1524-1531
Markdown (Informal)
[ANDES at SemEval-2020 Task 12: A Jointly-trained BERT Multilingual Model for Offensive Language Detection](https://aclanthology.org/2020.semeval-1.199/) (Pérez et al., SemEval 2020)
ACL