YoungSheldon at SemEval-2021 Task 5: Fine-tuning Pre-trained Language Models for Toxic Spans Detection using Token classification Objective

Mayukh Sharma, Ilanthenral Kandasamy, W.b. Vasantha


Abstract
In this paper, we describe our system used for SemEval 2021 Task 5: Toxic Spans Detection. Our proposed system approaches the problem as a token classification task. We trained our model to find toxic words and concatenate their spans to predict the toxic spans within a sentence. We fine-tuned Pre-trained Language Models (PLMs) for identifying the toxic words. For fine-tuning, we stacked the classification layer on top of the PLM features of each word to classify if it is toxic or not. PLMs are pre-trained using different objectives and their performance may differ on downstream tasks. We, therefore, compare the performance of BERT, ELECTRA, RoBERTa, XLM-RoBERTa, T5, XLNet, and MPNet for identifying toxic spans within a sentence. Our best performing system used RoBERTa. It performed well, achieving an F1 score of 0.6841 and secured a rank of 16 on the official leaderboard.
Anthology ID:
2021.semeval-1.130
Volume:
Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021)
Month:
August
Year:
2021
Address:
Online
Editors:
Alexis Palmer, Nathan Schneider, Natalie Schluter, Guy Emerson, Aurelie Herbelot, Xiaodan Zhu
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
953–959
Language:
URL:
https://aclanthology.org/2021.semeval-1.130
DOI:
10.18653/v1/2021.semeval-1.130
Bibkey:
Cite (ACL):
Mayukh Sharma, Ilanthenral Kandasamy, and W.b. Vasantha. 2021. YoungSheldon at SemEval-2021 Task 5: Fine-tuning Pre-trained Language Models for Toxic Spans Detection using Token classification Objective. In Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021), pages 953–959, Online. Association for Computational Linguistics.
Cite (Informal):
YoungSheldon at SemEval-2021 Task 5: Fine-tuning Pre-trained Language Models for Toxic Spans Detection using Token classification Objective (Sharma et al., SemEval 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.semeval-1.130.pdf
Code
 04mayukh/YoungSheldon-at-SemEval-2021-Task-5-Toxic-Spans-Detection