Dang Qui


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ABCD Team at SemEval-2023 Task 12: An Ensemble Transformer-based System for African Sentiment Analysis
Dang Thin | Dai Nguyen | Dang Qui | Duong Hao | Ngan Nguyen
Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)

This paper describes the system of the ABCD team for three main tasks in the SemEval-2023 Task 12: AfriSenti-SemEval for Low-resource African Languages using Twitter Dataset. We focus on exploring the performance of ensemble architectures based on the soft voting technique and different pre-trained transformer-based language models. The experimental results show that our system has achieved competitive performance in some Tracks in Task A: Monolingual Sentiment Analysis, where we rank the Top 3, Top 2, and Top 4 for the Hause, Igbo and Moroccan languages. Besides, our model achieved competitive results and ranked $14ˆ{th}$ place in Task B (multilingual) setting and $14ˆ{th}$ and $8ˆ{th}$ place in Track 17 and Track 18 of Task C (zero-shot) setting.