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Distilhubert Finetuned Gtzan V2
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Distilhubert Finetuned Gtzan V2

Developed by MariaK
This model is a fine-tuned version of DistilHuBERT on the GTZAN music classification dataset, primarily used for music genre classification tasks.
Audio Classification
Transformers
Open Source License:Apache-2.0#Music Classification#High Accuracy#Lightweight Model
Downloads 17
Release Time : 6/8/2023

Model Overview

This is an audio classification model specifically designed to identify the genre categories of music clips. Based on the lightweight DistilHuBERT architecture, it achieves 87% accuracy after fine-tuning on the GTZAN dataset.

Model Features

Efficient and Lightweight
Based on the DistilHuBERT architecture, it reduces model complexity while maintaining performance.
High Accuracy
Achieves 87% classification accuracy on the GTZAN test set.
Fast Inference
Faster inference speed compared to the full HuBERT model.

Model Capabilities

Music Genre Classification
Audio Feature Extraction

Use Cases

Music Classification
Music Streaming Services
Automatically add genre labels to uploaded music files
87% accuracy
Music Recommendation Systems
Preliminary classification based on music content
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