In this liveProject, you’ll use the ALBERT variation of the BERT Transformer to detect occurrences of hate speech in a data set. The ALBERT model uses fewer parameters than BERT, making it more suitable to the unstructured and slang-heavy text of social media. You’ll load this powerful pretrained model using the Hugging Face library and fine-tune it for your specific needs with PyTorch Lightning. As falsely tagging hate speech can be a big problem, the success of your model will involve calculating and optimizing its precision score. Your final product will run as a notebook on a GPU in the Google Colab environment.
This project is designed for learning purposes and is not a complete, production-ready application or solution.