Hubert Base Ls960 Finetuned Gtzan
An audio classification model based on the HuBERT architecture, fine-tuned on the GTZAN music genre classification dataset with an accuracy of 88%
Downloads 15
Release Time : 7/29/2023
Model Overview
This model is an audio classification model fine-tuned on the GTZAN music dataset, based on the facebook/hubert-base-ls960 pre-trained model, specifically designed for music genre classification tasks.
Model Features
High Accuracy
Achieves 88% classification accuracy on the GTZAN test set
Pre-trained + Fine-tuning Architecture
Based on the large-scale pre-trained HuBERT model, fine-tuned for specific tasks
Efficient Training
Optimizes the training process using techniques like gradient accumulation
Model Capabilities
Music Genre Classification
Audio Feature Extraction
Music Content Analysis
Use Cases
Music Analysis
Automatic Music Genre Classification
Classifies music clips into genres (e.g., rock, jazz, classical)
88% Accuracy
Music Recommendation System
Serves as a feature extraction component for music recommendation systems
Audio Processing
Audio Content Analysis
Analyzes audio content features
Featured Recommended AI Models