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This project is an individual task as a part of the coursework from CSE712: Symbolic Machine Learning-II. Here I applied a neural network approach to address the task of detecting online sexism. Specifically, by utilizing natural language processing (NLP) methods to analyze textual data and build predictive models.
The project focuses on identifying signs of sexism in texts through three tasks: identifying sexism, categorizing sexism, and sub-categorizing sexism. The best model used for completing these tasks is RoBERTa pre-trained on hate speech with the addition of data augmentation and learning rate scheduler techniques.