Sexism Identification in Social Networks using a Multi-Task Learning System

This paper describes the participation of SINAI-TL team at sEXism Identification in Social neTworks shared task at IberLEF 2021. In order to accomplish the task, we follow a Multi-Task Learning approach where multiple tasks related to sexism identification are learned in parallel while using a shared representation. Specifically, we test the performance of the combination of different tasks related to sentiment analysis and offensive language detection. Our team ranked second in subtask 1 and third in subtask 2, achieving 78% and 56.67% of accuracy, respectively, among the participants.

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