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UM6P at SemEval-2023 Task 12: Out-Of-Distribution Generalization Method for African Languages Sentiment Analysis
El Mahdaouy, Abdelkader; Alami, Hamza; LAMSIYAH, Salima et al.
2023In Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
Peer reviewed
 

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Abstract :
[en] This paper presents our submitted system to AfriSenti SemEval-2023 Task 12: Sentiment Analysis for African Languages. The AfriSenti consists of three different tasks, covering monolingual, multilingual, and zero-shot sentiment analysis scenarios for African languages. To improve model generalization, we have explored the following steps: 1) further pre-training of the AfroXLM Pre-trained Language Model (PLM), 2) combining AfroXLM and MARBERT PLMs using a residual layer, and 3) studying the impact of metric learning and two out-of-distribution generalization training objectives. The overall evaluation results show that our system has achieved promising results on several sub-tasks of Task A. For Tasks B and C, our system is ranked among the top six participating systems.
Disciplines :
Computer science
Author, co-author :
El Mahdaouy, Abdelkader
Alami, Hamza
LAMSIYAH, Salima  ;  University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)
Berrada, Ismail
External co-authors :
yes
Language :
English
Title :
UM6P at SemEval-2023 Task 12: Out-Of-Distribution Generalization Method for African Languages Sentiment Analysis
Publication date :
2023
Event name :
The 61st Annual Meeting of the Association for Computational Linguistics
Event date :
9-14 July 2023
Main work title :
Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
Publisher :
Association for Computational Linguistics, Toronto, Canada, Unknown/unspecified
Pages :
1004--1010
Peer reviewed :
Peer reviewed
Available on ORBilu :
since 16 October 2023

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