AST Audio Classifier
Audio Spectrogram Transformer model fine-tuned for music genre classification on noisy mashup data.
Model source
- Kind
- Other
- File size
- 330 MB
- Version
- vRevision 6204922
- Updated
- Oct 17, 2026
- Downloads
- 0
- Source
- Hugging Face
Source description
π΅ 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
- π― Classifies 10 music genres with high accuracy
- π Robust to noise, tempo variations, and audio mashups
- π Achieves 98.19% F1-Score on public leaderboard
- π¨ 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(768β384) β GELU β Dropout(0.1) β Linear(384β10)
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
Sources
1 sourceVerified Aug 29
Model artifacts
1 artifact
Model artifacts
1 artifactSource excerpts
2 excerpts
Source excerpts
2 excerpts--- license: mit tags: - audio-classification - music-genre-classification - audio-spectrogram-transformer - pytorch datasets: - messy-mashup metrics: - f1 library_name: transformers pipeline_tag: audio-classification --- # π΅ 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 - π― Classifies 10 music genres with high accuracy - π Robust to noise, tempo variations, and audio mashups - π Achieves 98.19% F1-Score on public leaderboard - π¨ 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(768β384) β GELU β Dropout(0.1) β Linear(384β10) ## 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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