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Distilhubert Finetuned Gtzan
This model is an audio classification model based on the DistilHuBERT architecture, fine-tuned on the GTZAN music genre classification dataset, achieving an accuracy of 89%.
Downloads 15
Release Time : 8/18/2023
Model Overview
A lightweight audio classification model specifically designed for music genre recognition tasks, leveraging the DistilHuBERT architecture for efficient feature extraction.
Model Features
Efficient and Lightweight
Based on the DistilHuBERT architecture, reducing model complexity while maintaining performance.
High Accuracy
Achieves 89% classification accuracy on the GTZAN test set.
Fast Inference
Distilled architecture design is suitable for real-time applications.
Model Capabilities
Music genre classification
Audio feature extraction
Music content analysis
Use Cases
Music Recommendation Systems
Automatic Music Categorization
Automatically tags uploaded audio files with genre labels for music platforms.
89% accuracy in automatic classification
Music Analysis
Music Content Research
Analyzes audio feature differences between various music genres.
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