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Distilhubert Finetuned Gtzan
This model is an audio classification model fine-tuned on the GTZAN music classification dataset based on ntu-spml/distilhubert, achieving an accuracy of 85%.
Downloads 3
Release Time : 10/16/2024
Model Overview
A lightweight audio classification model for music genre classification, based on the DistilHuBERT architecture and fine-tuned on the GTZAN dataset.
Model Features
High Accuracy
Achieves 85% accuracy on the GTZAN test set.
Lightweight
Based on the distilled version of HuBERT, offering higher computational efficiency.
Music Genre Classification
Optimized classification capabilities specifically for musical audio data.
Model Capabilities
Music Genre Recognition
Audio Feature Extraction
Music Classification
Use Cases
Music Analysis
Music Streaming Service Classification
Automatically adds genre labels to songs in a music library.
Accuracy reaches 85%.
Music Recommendation System
Recommends similar music based on content.
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