Beyond Binary Classification: Fine-Grained Hate Speech Detection with Target and Identity Identification

A hate speech detection system that goes beyond yes or no by identifying the target and identity of the abuse.

A hate speech detection system that goes beyond yes or no by identifying the target and identity of the abuse. This reference project walks through the whole job, from the problem and the design to the build and the evaluation, so that a developer can study how it works, run it and extend it.

It suits learners who want to work with language models and text or speech: preparing text data, using or fine-tuning a model, evaluating it and building an interface around it.

The main parts are text or speech data preparation, model training, fine-tuning or prompting, evaluation with task-appropriate metrics, and a chat or web interface to use it. The reference build uses Speech Recognition API, Python, Hugging Face Transformers, spaCy, and PyTorch, with a clear project structure, setup instructions and sample data so that it can be run and extended.