DistilHubert Fine-tuned GTZAN v3 Fine-tuned GTZAN Open-source Model - Free and Accurate Music Genre Classification

Distilhubert Finetuned Gtzan V3 Finetuned Gtzan

Developed by J3

This model is a fine-tuned version based on the DistilHuBERT architecture on the GTZAN music classification dataset, primarily used for music genre classification tasks.

Audio Classification

Transformers

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

Downloads 13

Release Time : 7/11/2023

Model Overview

This is a fine-tuned DistilHuBERT model specifically designed for music genre classification tasks. It achieves 88% accuracy on the GTZAN dataset.

Model Features

High Accuracy

Achieves 88% accuracy on the GTZAN music classification dataset

Lightweight

Based on the DistilHuBERT architecture, making it more lightweight compared to the original HuBERT model

Music-Specific

Specially fine-tuned and optimized for music audio data

Model Capabilities

Music Genre Classification

Audio Feature Extraction

Use Cases

Music Analysis

Automatic Music Genre Classification

Classify music clips by genre

88% accuracy

Music Recommendation System

Serve as a feature extraction component for music recommendation systems

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.0791	0.99	56	0.5451	0.82
0.0677	2.0	113	0.4793	0.88
0.0329	2.97	168	0.4764	0.88

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Distilhubert Finetuned Gtzan V3 Finetuned Gtzan

Model Overview

Model Features

Model Capabilities

Use Cases

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