I2C at SemEval-2022 Task 5: Identification of misogyny in internet memes
Pablo Cordon, Pablo Gonzalez Diaz, Jacinto Mata, Victoria Pachón
Abstract
In this paper we present our approach and system description on Task 5 A in MAMI: Multimedia Automatic Misogyny Identification. In our experiments we compared several architectures based on deep learning algorithms with various other approaches to binary classification using Transformers, combined with a nudity image detection algorithm to provide better results. With this approach, we achieved an F1-score of 0.665 in the evaluation process- Anthology ID:
- 2022.semeval-1.94
- 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:
- 689–694
- Language:
- URL:
- https://aclanthology.org/2022.semeval-1.94
- DOI:
- 10.18653/v1/2022.semeval-1.94
- Cite (ACL):
- Pablo Cordon, Pablo Gonzalez Diaz, Jacinto Mata, and Victoria Pachón. 2022. I2C at SemEval-2022 Task 5: Identification of misogyny in internet memes. In Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022), pages 689–694, Seattle, United States. Association for Computational Linguistics.
- Cite (Informal):
- I2C at SemEval-2022 Task 5: Identification of misogyny in internet memes (Cordon et al., SemEval 2022)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/2022.semeval-1.94.pdf