This project aims to develop machine learning models for automatic hate speech detection in low-resource languages, focusing on addressing the challenges posed by limited availability of labeled training data and linguistic tools.
The aim of the project is to Develop machine learning models tailored for hate speech detection in low-resource languages. Utilizes fine-tuning of pre-trained language models like BERT for hate speech detection.