iCompass at Arabic Hate Speech 2022: Detect Hate Speech Using QRNN and Transformers
Mohamed Aziz Bennessir, Malek Rhouma, Hatem Haddad, Chayma Fourati
Abstract
This paper provides a detailed overview of the system we submitted as part of the OSACT2022 Shared Tasks on Fine-Grained Hate Speech Detection on Arabic Twitter, its outcome, and limitations. Our submission is accomplished with a hard parameter sharing Multi-Task Model that consisted of a shared layer containing state-of-the-art contextualized text representation models such as MarBERT, AraBERT, ArBERT and task specific layers that were fine-tuned with Quasi-recurrent neural networks (QRNN) for each down-stream subtask. The results show that MARBERT fine-tuned with QRNN outperforms all of the previously mentioned models.- Anthology ID:
- 2022.osact-1.22
- Volume:
- Proceedinsg of the 5th Workshop on Open-Source Arabic Corpora and Processing Tools with Shared Tasks on Qur'an QA and Fine-Grained Hate Speech Detection
- Month:
- June
- Year:
- 2022
- Address:
- Marseille, France
- Editors:
- Hend Al-Khalifa, Tamer Elsayed, Hamdy Mubarak, Abdulmohsen Al-Thubaity, Walid Magdy, Kareem Darwish
- Venue:
- OSACT
- SIG:
- Publisher:
- European Language Resources Association
- Note:
- Pages:
- 176–180
- Language:
- URL:
- https://aclanthology.org/2022.osact-1.22
- DOI:
- Cite (ACL):
- Mohamed Aziz Bennessir, Malek Rhouma, Hatem Haddad, and Chayma Fourati. 2022. iCompass at Arabic Hate Speech 2022: Detect Hate Speech Using QRNN and Transformers. In Proceedinsg of the 5th Workshop on Open-Source Arabic Corpora and Processing Tools with Shared Tasks on Qur'an QA and Fine-Grained Hate Speech Detection, pages 176–180, Marseille, France. European Language Resources Association.
- Cite (Informal):
- iCompass at Arabic Hate Speech 2022: Detect Hate Speech Using QRNN and Transformers (Bennessir et al., OSACT 2022)
- PDF:
- https://preview.aclanthology.org/proper-vol2-ingestion/2022.osact-1.22.pdf