AudioCourseU4-Music Classification: An Open-Source Music Classification Model - Free Deployment, Accurately Classifying Music with 88% Accuracy

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Audiocourseu4 MusicClassification

Developed by Imxxn

A music classification model fine-tuned on the GTZAN dataset based on distilhubert, achieving 88% accuracy

Audio Classification

Transformers

Open Source License:Apache-2.0 #Music Classification #High Accuracy #Audio Feature Extraction

Downloads 17

Release Time : 9/2/2023

Model Overview

This model is an audio classification model specifically designed for music genre classification tasks, fine-tuned on the GTZAN music dataset using the lightweight DistilHuBERT architecture.

Model Features

High Accuracy

Achieves 88% classification accuracy on the GTZAN test set

Lightweight Architecture

Based on the lightweight DistilHuBERT model, suitable for resource-limited environments

Fast Training

Only requires 15 training epochs to achieve good performance

Model Capabilities

Music Genre Classification

Audio Feature Extraction

Use Cases

Music Analysis

Music Streaming Classification

Automatically add genre labels to songs on music streaming platforms

88% accuracy

Music Recommendation System

Improve recommendation algorithms based on music genre features

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.7993	1.0	225	1.5770	0.4
1.0767	2.0	450	0.9900	0.7
0.8292	3.0	675	0.8554	0.73
0.5892	4.0	900	0.8991	0.74
0.1584	5.0	1125	0.8473	0.78
0.0082	6.0	1350	0.9282	0.8
0.0094	7.0	1575	1.0036	0.82
0.0581	8.0	1800	1.2186	0.82
0.0021	9.0	2025	1.0192	0.83
0.0011	10.0	2250	0.8804	0.88
0.002	11.0	2475	1.1519	0.83
0.0009	12.0	2700	0.9439	0.87
0.0006	13.0	2925	1.1227	0.84
0.0008	14.0	3150	1.0344	0.86
0.0006	15.0	3375	1.0209	0.86

Property	Details
Model Type	Fine - tuned version of ntu - spml/distilhubert
Training Data	marsyas/gtzan
Metrics	accuracy

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Audiocourseu4 MusicClassification

Model Overview

Model Features

Model Capabilities

Use Cases

🚀 AudioCourseU4-MusicClassification

🚀 Quick Start

📚 Documentation

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

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📄 License