W

Wav2vec2 Base Finetuned Gtzan

Developed by wilson-wei
This model is an audio classification model fine-tuned on the GTZAN dataset based on facebook/wav2vec2-base, primarily used for music genre classification tasks.
Downloads 14
Release Time : 7/29/2023

Model Overview

An audio classification model based on the wav2vec2 architecture, fine-tuned on the GTZAN dataset, capable of recognizing 10 different music genres.

Model Features

High Accuracy
Achieves 84% accuracy on the GTZAN test set
Based on wav2vec2 Architecture
Utilizes a self-supervised learning pre-trained speech representation model
Lightweight
Based on the wav2vec2-base version, relatively small in size

Model Capabilities

Music Genre Classification
Audio Feature Extraction

Use Cases

Music Analysis
Automatic Music Genre Classification
Automatically classify music clips by genre
84% accuracy
Music Recommendation System
Serves as a feature extraction component for music recommendation systems
Featured Recommended AI Models
AIbase
Empowering the Future, Your AI Solution Knowledge Base
Š 2025AIbase