# GTZAN Dataset

This model is an audio classification model based on the AST architecture and fine-tuned on the GTZAN music classification dataset, achieving an accuracy of 89%

Audio classification model based on wav2vec2 architecture, fine-tuned on the GTZAN dataset for music and speech classification tasks

A model fine-tuned on the GTZAN music classification dataset based on DistilHuBERT, used for music genre classification tasks

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%.

This model is trained on facebook/wav2vec2-base-960h for music genre classification tasks, supporting recognition of 10 genres.

This model is an audio classification model fine-tuned on the GTZAN dataset based on facebook/wav2vec2-base, primarily used for music genre classification tasks.

An audio classification model based on the HuBERT architecture, fine-tuned on the GTZAN music genre classification dataset with an accuracy of 88%

An audio classification model based on the DistilHuBERT architecture fine-tuned on the GTZAN music classification dataset

An audio classification model based on the DistilHuBERT architecture, fine-tuned on the GTZAN music genre classification dataset

A speech classification model fine-tuned on the GTZAN dataset based on OpenAI's whisper-base model, primarily used for music genre classification tasks.

A model fine-tuned on the GTZAN music classification dataset based on DistilHuBERT, achieving 88% accuracy

This model is a fine-tuned version of DistilHuBERT on the GTZAN music classification dataset, primarily used for music genre classification tasks.