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Distilhubert Finetuned Gtzan

Developed by Gyaneshere
This model is an audio classification model fine-tuned on the GTZAN music genre classification dataset based on DistilHuBERT, with an accuracy of 84%.
Downloads 5
Release Time : 2/8/2025

Model Overview

A lightweight audio classification model specifically designed for music genre recognition tasks, fine-tuned on the GTZAN dataset based on the DistilHuBERT architecture.

Model Features

Efficient and Lightweight
Based on the distilled architecture of DistilHuBERT, reducing model complexity while maintaining performance
High Accuracy
Achieved a classification accuracy of 84% on the GTZAN test set
Fast Training
Good performance can be achieved in just 10 epochs

Model Capabilities

Music Audio Classification
Genre Recognition
Audio Feature Extraction

Use Cases

Music Analysis
Automatic Music Genre Classification
Automatically classify music segments by genre
Classification accuracy of 84% for 10 music genres
Music Recommendation System
Serves as the front-end classification module of a music recommendation system
Audio Processing
Audio Content Analysis
Extract audio features for content analysis
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