DistilHubert-Finetuned-GTzan Open-Source Audio Classification Model

Distilhubert Finetuned Gtzan

Developed by technaxx

An audio classification model based on the DistilHuBERT architecture, fine-tuned on the GTZAN music genre classification dataset

Audio Classification

Transformers

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

Downloads 20

Release Time : 7/22/2023

Model Overview

This model is a fine-tuned version of DistilHuBERT, specifically designed for music genre classification tasks, achieving 89% accuracy on the GTZAN dataset.

Model Features

Efficient Audio Feature Extraction

Based on the DistilHuBERT architecture, it provides efficient audio feature extraction capabilities.

High Accuracy

Achieves 89% accuracy on the GTZAN music genre classification task.

Lightweight

Compared to the original HuBERT model, the Distil version is more lightweight while maintaining good performance.

Model Capabilities

Audio Feature Extraction

Music Genre Classification

Audio Content Analysis

Use Cases

Music Analysis

Automatic Music Genre Classification

Classify music clips by genre

89% accuracy

Music Recommendation System

Recommendation system based on music features

Audio Processing

Audio Content Analysis

Extract audio features for further processing

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.2685	1.0	15	1.2199	0.71
1.1248	2.0	30	1.0805	0.75
1.0651	3.0	45	0.9617	0.8
0.9201	4.0	60	0.9439	0.76
0.805	5.0	75	0.8118	0.84
0.6815	6.0	90	0.7881	0.84
0.6421	7.0	105	0.7476	0.81
0.5956	8.0	120	0.6870	0.84
0.4791	9.0	135	0.6403	0.88
0.4411	10.0	150	0.6420	0.82
0.3855	11.0	165	0.5990	0.89
0.3592	12.0	180	0.5927	0.87
0.3254	13.0	195	0.5891	0.87
0.3478	14.0	210	0.5887	0.85
0.2985	15.0	225	0.5748	0.89

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Distilhubert Finetuned Gtzan

Model Overview

Model Features

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Use Cases

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