AST Audio Classifier
Audio Spectrogram Transformer model fine-tuned for music genre classification on noisy mashup data.
Fuente del modelo
- Tipo
- Other
- Tamaño del archivo
- 330 MB
- Versión
- vRevision 6204922
- Actualizado
- 17 oct 2026
- Descargas
- 0
- Fuente
- Hugging Face
Descripción de la fuente
🎵 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
- 🔊 Robust to noise, tempo variations, and audio mashups
- 🚀 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) → AST Encoder → Patchout → Pooling → Classification Head → Genre (10 classes)
Classification Head:
LayerNorm(768) → Dropout(0.15) → Linear(768→384) → GELU → Dropout(0.1) → Linear(384→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
Fuentes
1 fuente
Fuentes
1 fuenteVerificado 29 ago
Artefactos del modelo
1 artefacto
Artefactos del modelo
1 artefactoExtractos de fuentes
2 extractos
Extractos de fuentes
2 extractos--- 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 - 🔊 Robust to noise, tempo variations, and audio mashups - 🚀 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) → AST Encoder → Patchout → Pooling → Classification Head → Genre (10 classes) **Classification Head:** LayerNorm(768) → Dropout(0.15) → Linear(768→384) → GELU → Dropout(0.1) → Linear(384→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
Source context: 0 downloads · 0 likes · Pipeline audio-classification · Library transformers · Repo neerajs7/AST-audio-classifier
