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AST Audio Classifier

Audio Spectrogram Transformer model fine-tuned for music genre classification on noisy mashup data.

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330 MB
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vRevision 6204922
Updated
Oct 17, 2026
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Hugging Face

Source description

🎡 AST Music Genre Classifier

Audio Spectrogram Transformer model fine-tuned for music genre classification on noisy mashup data.

Model Description

This model is a fine-tuned version of MIT's Audio Spectrogram Transformer (AST) with custom Patchout regularization for robust music genre classification.

Key Features

  • 🎯 Classifies 10 music genres with high accuracy
  • πŸ”Š Robust to noise, tempo variations, and audio mashups
  • πŸš€ Achieves 98.19% F1-Score on public leaderboard
  • 🎨 Custom Patchout regularization for better generalization

Performance

MetricScore
Public Leaderboard0.98191 Macro F1
Private Leaderboard0.97634 Macro F1
CompetitionKaggle Messy Mashup Genre Classification

Model Architecture

  • Base Model: MIT/ast-finetuned-audioset-10-10-0.4593
  • Custom Components:
    • Patchout regularization (time=0.4, freq=0.2)
    • Custom classification head with LayerNorm and GELU activation
    • Dropout layers for regularization
  • Parameters: ~86.5M trainable parameters

Architecture Details

Input (Audio) β†’ AST Encoder β†’ Patchout β†’ Pooling β†’ Classification Head β†’ Genre (10 classes)

Classification Head:

LayerNorm(768) β†’ Dropout(0.15) β†’ Linear(768β†’384) β†’ GELU β†’ Dropout(0.1) β†’ Linear(384β†’10)

Citation

@misc{ast-genre-classifier-2026, author = {Neeraj Surin}, title = {AST Music Genre Classifier with Patchout Regularization}, year = {2026}, publisher = {HuggingFace}, journal = {HuggingFace Model Hub}, howpublished = {\url{https://huggingface.co/neerajs7/AST-audio-classifier}} }

Acknowledgments

  • Base AST model: MIT/ast-finetuned-audioset-10-10-0.4593
  • Competition: Kaggle Messy Mashup Genre Classification Challenge
  • Framework: Hugging Face Transformers

License

MIT License - See LICENSE file for details

Model Card Authors: Neeraj Surin Model Card Contact: https://huggingface.co/neerajs7

Sources

1 source
Hugging FacePrimaryVersion 620492243374a3248661385752dcb2a551e67cc1
huggingface.co/neerajs7/AST-audio-classifier/tree/620492243374a3248661385752dcb2a551e67cc1

Verified Aug 29

Model artifacts

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model.pth

pth Β· 330 MB Β· SHA-256 e2b49489c3a1…6960 Β· Hugging Face

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Source excerpts

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--- license: mit tags: - audio-classification - music-genre-classification - audio-spectrogram-transformer - pytorch datasets: - messy-mashup metrics: - f1 library_name: transformers pipeline_tag: audio-classification --- # 🎡 AST Music Genre Classifier Audio Spectrogram Transformer model fine-tuned for music genre classification on noisy mashup data. ## Model Description This model is a fine-tuned version of MIT's Audio Spectrogram Transformer (AST) with custom **Patchout regularization** for robust music genre classification. ### Key Features - 🎯 Classifies 10 music genres with high accuracy - πŸ”Š Robust to noise, tempo variations, and audio mashups - πŸš€ Achieves 98.19% F1-Score on public leaderboard - 🎨 Custom Patchout regularization for better generalization ## Performance | Metric | Score | |--------|-------| | **Public Leaderboard** | **0.98191** Macro F1 | | **Private Leaderboard** | **0.97634** Macro F1 | | Competition | Kaggle Messy Mashup Genre Classification | ## Model Architecture - **Base Model:** `MIT/ast-finetuned-audioset-10-10-0.4593` - **Custom Components:** - Patchout regularization (time=0.4, freq=0.2) - Custom classification head with LayerNorm and GELU activation - Dropout layers for regularization - **Parameters:** ~86.5M trainable parameters ### Architecture Details Input (Audio) β†’ AST Encoder β†’ Patchout β†’ Pooling β†’ Classification Head β†’ Genre (10 classes) **Classification Head:** LayerNorm(768) β†’ Dropout(0.15) β†’ Linear(768β†’384) β†’ GELU β†’ Dropout(0.1) β†’ Linear(384β†’10) ## Citation @misc{ast-genre-classifier-2026, author = {Neeraj Surin}, title = {AST Music Genre Classifier with Patchout Regularization}, year = {2026}, publisher = {HuggingFace}, journal = {HuggingFace Model Hub}, howpublished = {\url{https://huggingface.co/neerajs7/AST-audio-classifier}} } ## Acknowledgments - Base AST model: MIT/ast-finetuned-audioset-10-10-0.4593 - Competition: Kaggle Messy Mashup Genre Classification Challenge - Framework: Hugging Face Transformers ## License MIT License - See LICENSE file for details **Model Card Authors:** Neeraj Surin **Model Card Contact:** https://huggingface.co/neerajs7

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