@inproceedings{hassan-etal-2023-firc,
title = "{F}i{RC} at {S}em{E}val-2023 Task 10: Fine-grained Classification of Online Sexism Content Using {D}e{BERT}a",
author = "Hassan, Fadi and
Bouchekif, Abdessalam and
Aransa, Walid",
editor = {Ojha, Atul Kr. and
Do{\u{g}}ru{\"o}z, A. Seza and
Da San Martino, Giovanni and
Tayyar Madabushi, Harish and
Kumar, Ritesh and
Sartori, Elisa},
booktitle = "Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.semeval-1.252",
doi = "10.18653/v1/2023.semeval-1.252",
pages = "1824--1832",
abstract = "The SemEval 2023 shared task 10 {``}Explainable Detection of Online Sexism{''} focuses on detecting and identifying comments and tweets containing sexist expressions and also explaining why it is sexist. This paper describes our system that we used to participate in this shared task. Our model is an ensemble of different variants of fine tuned DeBERTa models that employs a k-fold cross-validation. We have participated in the three tasks A, B and C. Our model ranked 2 nd position in tasks A, 7 th in task B and 4 th in task C.",
}
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<abstract>The SemEval 2023 shared task 10 “Explainable Detection of Online Sexism” focuses on detecting and identifying comments and tweets containing sexist expressions and also explaining why it is sexist. This paper describes our system that we used to participate in this shared task. Our model is an ensemble of different variants of fine tuned DeBERTa models that employs a k-fold cross-validation. We have participated in the three tasks A, B and C. Our model ranked 2 nd position in tasks A, 7 th in task B and 4 th in task C.</abstract>
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%0 Conference Proceedings
%T FiRC at SemEval-2023 Task 10: Fine-grained Classification of Online Sexism Content Using DeBERTa
%A Hassan, Fadi
%A Bouchekif, Abdessalam
%A Aransa, Walid
%Y Ojha, Atul Kr.
%Y Doğruöz, A. Seza
%Y Da San Martino, Giovanni
%Y Tayyar Madabushi, Harish
%Y Kumar, Ritesh
%Y Sartori, Elisa
%S Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada
%F hassan-etal-2023-firc
%X The SemEval 2023 shared task 10 “Explainable Detection of Online Sexism” focuses on detecting and identifying comments and tweets containing sexist expressions and also explaining why it is sexist. This paper describes our system that we used to participate in this shared task. Our model is an ensemble of different variants of fine tuned DeBERTa models that employs a k-fold cross-validation. We have participated in the three tasks A, B and C. Our model ranked 2 nd position in tasks A, 7 th in task B and 4 th in task C.
%R 10.18653/v1/2023.semeval-1.252
%U https://aclanthology.org/2023.semeval-1.252
%U https://doi.org/10.18653/v1/2023.semeval-1.252
%P 1824-1832
Markdown (Informal)
[FiRC at SemEval-2023 Task 10: Fine-grained Classification of Online Sexism Content Using DeBERTa](https://aclanthology.org/2023.semeval-1.252) (Hassan et al., SemEval 2023)
ACL