Abstract
Women are frequently targeted online with hate speech and misogyny using tweets, memes, and other forms of communication. This paper describes our system for Task 5 of SemEval-2022: Multimedia Automatic Misogyny Identification (MAMI). We participated in both the sub-tasks, where we used transformer-based architecture to combine features of images and text. We explore models with multi-modal pre-training (VisualBERT) and text-based pre-training (MMBT) while drawing comparative results. We also show how additional training with task-related external data can improve the model performance. We achieved sizable improvements over baseline models and the official evaluation ranked our system 3rd out of 83 teams on the binary classification task (Sub-task A) with an F1 score of 0.761, and 7th out of 48 teams on the multi-label classification task (Sub-task B) with an F1 score of 0.705.- Anthology ID:
- 2022.semeval-1.82
- Volume:
- Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)
- Month:
- July
- Year:
- 2022
- Address:
- Seattle, United States
- Editors:
- Guy Emerson, Natalie Schluter, Gabriel Stanovsky, Ritesh Kumar, Alexis Palmer, Nathan Schneider, Siddharth Singh, Shyam Ratan
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 597–604
- Language:
- URL:
- https://aclanthology.org/2022.semeval-1.82
- DOI:
- 10.18653/v1/2022.semeval-1.82
- Cite (ACL):
- Ailneni Rakshitha Rao and Arjun Rao. 2022. ASRtrans at SemEval-2022 Task 5: Transformer-based Models for Meme Classification. In Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022), pages 597–604, Seattle, United States. Association for Computational Linguistics.
- Cite (Informal):
- ASRtrans at SemEval-2022 Task 5: Transformer-based Models for Meme Classification (Rao & Rao, SemEval 2022)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/2022.semeval-1.82.pdf