Abstract
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.- Anthology ID:
- 2023.semeval-1.44
- Volume:
- Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
- Month:
- July
- Year:
- 2023
- Address:
- Toronto, Canada
- Editors:
- Atul Kr. Ojha, A. Seza Doğruöz, Giovanni Da San Martino, Harish Tayyar Madabushi, Ritesh Kumar, Elisa Sartori
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 324–330
- Language:
- URL:
- https://aclanthology.org/2023.semeval-1.44
- DOI:
- 10.18653/v1/2023.semeval-1.44
- Cite (ACL):
- Dang Thin, Dai Nguyen, Dang Qui, Duong Hao, and Ngan Nguyen. 2023. ABCD Team at SemEval-2023 Task 12: An Ensemble Transformer-based System for African Sentiment Analysis. In Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023), pages 324–330, Toronto, Canada. Association for Computational Linguistics.
- Cite (Informal):
- ABCD Team at SemEval-2023 Task 12: An Ensemble Transformer-based System for African Sentiment Analysis (Thin et al., SemEval 2023)
- PDF:
- https://preview.aclanthology.org/corrections-2024-07/2023.semeval-1.44.pdf