Fine-tuning MathBERT for Math Problem Classification
The goal of this project is to fine-tune a pre-trained language model, MathBERT, for the task of classifying math problems based on their topic. This involves using a labeled dataset of math problems, preprocessing the data, training the model, and evaluating its performance using various metrics such as accuracy, precision, recall, and F1-score. The end result is a robust classifier that can automatically categorize math problems into predefined topics.