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Distilhubert Finetuned Distilhubert
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Distilhubert Finetuned Distilhubert

Developed by JanLilan
This model is a fine-tuned version of DistilHuBERT on the GTZAN music classification dataset, primarily used for music genre classification tasks.
Audio Classification
Transformers
#Music Classification#High Accuracy#Lightweight Model
Downloads 14
Release Time : 7/31/2023

Model Overview

This is a DistilHuBERT model fine-tuned on the GTZAN dataset, specifically designed for music genre classification tasks. It achieves 90% accuracy on the evaluation set.

Model Features

Efficient Music Classification
Based on the DistilHuBERT architecture, it reduces computational complexity while maintaining high accuracy
High Accuracy
Achieves 90% classification accuracy on the GTZAN evaluation set
Lightweight
Compared to the original HuBERT model, the Distil version is more suitable for resource-constrained environments

Model Capabilities

Music Genre Classification
Audio Feature Extraction

Use Cases

Music Analysis
Music Streaming Service Classification
Automatically classify uploaded music files for music streaming platforms
Accuracy reaches 90%
Music Recommendation System
Serves as a front-end classifier for music recommendation systems
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