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Distilhubert Finetuned Gtzan
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Distilhubert Finetuned Gtzan
Developed by arham061
This model is a fine-tuned version of DistilHuBERT on the GTZAN music classification dataset, primarily used for music genre classification tasks.
Downloads 15
Release Time : 7/12/2023
Model Overview
This is a fine-tuned audio processing model based on the DistilHuBERT architecture, specifically designed for classifying music segments. The model is trained on the GTZAN dataset and can recognize 10 different music genres.
Model Features
Efficient Audio Feature Extraction
Based on the DistilHuBERT architecture, capable of efficiently extracting audio features
Music Genre Classification
Optimized music genre classification capability specifically for the GTZAN dataset
Lightweight Model
More lightweight and efficient compared to the original HuBERT model
Model Capabilities
Audio Feature Extraction
Music Genre Classification
Audio Signal Processing
Use Cases
Music Analysis
Automatic Classification for Music Streaming Platforms
Provides automatic genre classification functionality for music streaming platforms
Achieves 82% accuracy on the GTZAN dataset
Music Recommendation System
Serves as a front-end classification module for music recommendation systems
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