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Distilhubert Finetuned Gtzan
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Distilhubert Finetuned Gtzan

Developed by lewtun
A model fine-tuned on the GTZAN music classification dataset based on distilhubert, designed for music genre classification tasks
Audio Classification
Transformers
Open Source License:Apache-2.0#Music Classification#High Accuracy#Lightweight Audio Model
Downloads 20
Release Time : 3/14/2022

Model Overview

This model is a music classification model fine-tuned on the GTZAN dataset based on the distilhubert architecture, primarily used for identifying the music genre of audio clips

Model Features

Efficient Audio Feature Extraction
Based on the DistilHuBERT architecture, capable of efficiently extracting audio features
High Accuracy
Achieves 82% accuracy on the GTZAN evaluation set
Lightweight
As a distilled version, it is more lightweight compared to the original HuBERT

Model Capabilities

Music Genre Classification
Audio Feature Extraction

Use Cases

Music Analysis
Automatic Classification for Music Streaming Platforms
Automatically classifies uploaded music genres for music streaming platforms
82% accuracy
Preprocessing for Music Recommendation Systems
Serves as a preprocessing step for music recommendation systems to identify music features
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