# Music genre classification

Music genre classification model fine-tuned on the GTZAN dataset with 93% accuracy

A music genre classification model based on the wav2vec2 architecture, fine-tuned on the GTZAN dataset with 98% accuracy

MAEST is a series of Transformer models based on PASST, focusing on music analysis applications, particularly excelling in music genre classification tasks.

MAEST is a series of Transformer models based on PASST, focusing on music analysis applications, particularly music genre classification tasks.

MAEST is a Transformer model family based on PASST, focusing on music analysis applications, particularly excelling in music genre classification tasks.

A music genre classification model fine-tuned on distilhubert, achieving 84% accuracy on the GTZAN dataset

This is an audio classification model based on the distilhubert architecture, specifically designed for music genre recognition, achieving 89.72% accuracy after fine-tuning on the GTZAN dataset.