---
language: en
license: mit
tags:
- audio-classification
- music-genre-classification
- transformer
- cqt
- mel-spectrogram
datasets:
- synthetic-mashups-gtzan
metrics:
- accuracy
- f1-score
---

# Music Genre Classifier - 23f2000254-t12026

Hierarchical Vision Transformer for music genre classification using Mel spectrogram and CQT features.

## Model Architecture

- **Type**: Hierarchical Vision Transformer (ViT)
- **Input**: 7-second audio segments with 2-second overlap (6 segments)
- **Features**: 
  - Mel spectrogram (128 bins)
  - Constant-Q Transform (84 bins)
- **Encoder**: Factorized attention with 256 embed dim, 8 heads, 4 layers
- **Temporal**: Transformer encoder with CLS token aggregation

## Training Details

- **Dataset**: 10,000 synthetic mashups (GTZAN-based)
- **Classes**: 10 genres (blues, classical, country, disco, hiphop, jazz, metal, pop, reggae, rock)
- **Best Val F1**: 0.763
- **Best Val Accuracy**: 76.6%

## Files

- `best_model.pt`: Model checkpoint with weights, config, and genre mapping
- `history.json`: Training history