UM6P at SemEval-2023 Task 12: Out-Of-Distribution Generalization Method for African Languages Sentiment Analysis

Abdelkader El Mahdaouy, Hamza Alami, Salima Lamsiyah, Ismail Berrada

The 17th International Workshop on Semantic Evaluation (SemEval-2023) Task 12: afrisenti-semeval: sentiment analysis for low-resource african languages using twitter dataset Paper

TLDR: 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
You can open the #paper-SemEval_155 channel in a separate window.
Abstract: 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.