geralto/codet-classy

Model Card for Model ID

<!-- Provide a quick summary of what the model is/does. --> Vilnius University Deep Neural Networks course project.

Model Details

A transformer-based query classification model.

Model Description

This model was developed as part of a Deep Neural Networks (DNN) course project at Vilnius University. It fine-tunes the Salesforce/codet5-base model for classifying student queries related to C programming into five categories: General Question, Question from Code, Help Fix Code, Help Write Code, and Explain Code.

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• —Developed by: Brigita Bruškytė, Artiom Hovhannisyan, Eglė Orinaitė Faculty of Mathematics and Informatics, Vilnius University

Dataset

• —Size: 6,776 student queries from a real C programming course.
• —Structure: JSON entries with user_id, time, feature type, feature version, input question, input code, input intention, input task description.
• —Note: Dataset does not include AI responses — only the student queries.

Challenges

• —Class imbalance: e.g., “General Question” is much more frequent.
• —Field-based hints: Some classes have unique fields (like input task description), inadvertently helping classification.
• —Token length: Some queries, especially with code snippets, can be very long, hitting transformer limits.
• —Structural inconsistency: Dataset descriptions sometimes did not match actual data.

Per-Category F1 Scores