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Distilhubert Finetuned Gtzan
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Distilhubert Finetuned Gtzan

Developed by CornerINCorner
A lightweight audio classification model fine-tuned on the GTZAN music classification dataset based on the DistilHuBERT architecture
Audio Classification
Transformers
Open Source License:Apache-2.0#Music Classification#Lightweight Audio Model#GTZAN Fine-tuning
Downloads 20
Release Time : 7/21/2023

Model Overview

This model is a fine-tuned version of DistilHuBERT, specifically designed for music genre classification tasks, achieving 85% accuracy on the GTZAN dataset

Model Features

Lightweight Architecture
Based on the distilled architecture of DistilHuBERT, reducing computational resource requirements while maintaining performance
High Accuracy
Achieves 85% accuracy on the GTZAN music classification dataset
Efficient Training
Requires only 10 training epochs to achieve good performance

Model Capabilities

Music Genre Classification
Audio Feature Extraction

Use Cases

Music Analysis
Music Streaming Service Classification
Automatically tag music tracks with genre labels
85% classification accuracy
Music Recommendation System
Improve recommendation algorithms based on music genre features
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