The task at hand involves the classification of academic queries into multiple predefined categories, which include 'academic_servable', 'academic_non_servable', 'general', 'junk', and 'conversational'. The goal is to assign each query to its most appropriate category accurately. However, it's important to note that the training dataset for this task exhibits class imbalance, which means that some categories may have significantly fewer examples compared to others.

**Objective:** The goal of this task is to build a machine learning or natural language processing model that can accurately classify academic queries into predefined categories based on their content and intent.