beltrewilton
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README.md
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## Model description
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This model was generated as part of the [HF Audio course](https://huggingface.co/learn/audio-course/), I enjoyed it and currently this architecture achieves an amazing accuracy of 0.9 on
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The Audio Spectrogram Transformer is equivalent to [ViT](https://huggingface.co/docs/transformers/model_doc/vit), but applied on audio. Audio is first turned into an image (as a spectrogram), after which a Vision Transformer is applied. The model gets state-of-the-art results on several audio classification benchmarks.
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## Model description
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This model was generated as part of the [HF Audio course](https://huggingface.co/learn/audio-course/), I enjoyed it and currently this architecture achieves an amazing accuracy of 0.9 on music-genre classification task.
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The Audio Spectrogram Transformer is equivalent to [ViT](https://huggingface.co/docs/transformers/model_doc/vit), but applied on audio. Audio is first turned into an image (as a spectrogram), after which a Vision Transformer is applied. The model gets state-of-the-art results on several audio classification benchmarks.
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