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Ast Fine Tuned Music Genre 10

This model is a fine-tuned Audio Spectrogram Transformer (AST) for music genre classification.

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Kind
Other
File size
329 MB
Version
vRevision 8f50d87
Updated
Nov 5, 2026
Downloads
54
Source
Hugging Face

Source description

🎵 Music Genre Classification using AST

📌 Model Overview

This model is a fine-tuned Audio Spectrogram Transformer (AST) for music genre classification.

It predicts one of the following 10 genres:

  • blues, classical, country, disco, hiphop
  • jazz, metal, pop, reggae, rock

🧠 Architecture

  • Base Model: MIT/ast-finetuned-audioset
  • Type: Transformer (Audio Spectrogram Transformer)
  • Framework: PyTorch + Hugging Face Transformers

🎯 Task

Audio Classification (Music Genre Classification)


📊 Dataset

  • Training Data: Clean instrument stems (drums, vocals, bass, others)
  • Test Data: Noisy mashups with:
    • cross-song mixing
    • tempo variation
    • ESC-50 noise injection

⚙️ Preprocessing

  • Sampling rate: 16kHz
  • Fixed duration: 15 seconds
  • Padding / truncation applied
  • Feature extraction using ASTFeatureExtractor

📈 Performance

  • Metric: Macro F1 Score
  • Achieved: 0.87

🔗 Live Demo

Try the model here:
👉 https://huggingface.co/spaces/msaligs/music-genre-classifier

🚀 Usage

from transformers import ASTForAudioClassification, ASTFeatureExtractor

model = ASTForAudioClassification.from_pretrained("msaligs/ast_fine_tuned_music_genre_10")
feature_extractor = ASTFeatureExtractor.from_pretrained("msaligs/ast_fine_tuned_music_genre_10")

Sources

1 source
Hugging FacePrimaryVersion 8f50d87ce23eefb449348abc6bfef5a3bbcb17af
huggingface.co/msaligs/ast_fine_tuned_music_genre_10/tree/8f50d87ce23eefb449348abc6bfef5a3bbcb17af

Verified Nov 5

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model.safetensors

safetensors · FP32 (tensor header) · 329 MB · SHA-256 3e360fd195fa…6030 · Hugging Face

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Source excerpts

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--- language: en license: mit tags: - audio-classification - music - transformer - ast - pytorch pipeline_tag: audio-classification model-index: - name: Music Genre AST results: - task: type: audio-classification dataset: name: Messy Mashup Dataset type: custom # ✅ REQUIRED FIX metrics: - type: f1 value: 0.XX demo: https://huggingface.co/spaces/msaligs/music-genre-classifier --- # 🎵 Music Genre Classification using AST ## 📌 Model Overview This model is a fine-tuned Audio Spectrogram Transformer (AST) for music genre classification. It predicts one of the following 10 genres: - blues, classical, country, disco, hiphop - jazz, metal, pop, reggae, rock --- ## 🧠 Architecture - Base Model: MIT/ast-finetuned-audioset - Type: Transformer (Audio Spectrogram Transformer) - Framework: PyTorch + Hugging Face Transformers --- ## 🎯 Task Audio Classification (Music Genre Classification) --- ## 📊 Dataset - Training Data: Clean instrument stems (drums, vocals, bass, others) - Test Data: Noisy mashups with: - cross-song mixing - tempo variation - ESC-50 noise injection --- ## ⚙️ Preprocessing - Sampling rate: 16kHz - Fixed duration: 15 seconds - Padding / truncation applied - Feature extraction using ASTFeatureExtractor --- ## 📈 Performance - Metric: Macro F1 Score - Achieved: 0.87 --- ## 🔗 Live Demo Try the model here: 👉 https://huggingface.co/spaces/msaligs/music-genre-classifier ## 🚀 Usage ```python from transformers import ASTForAudioClassification, ASTFeatureExtractor model = ASTForAudioClassification.from_pretrained("msaligs/ast_fine_tuned_music_genre_10") feature_extractor = ASTFeatureExtractor.from_pretrained("msaligs/ast_fine_tuned_music_genre_10")

Source context: 54 downloads · 1 likes · Pipeline audio-classification · Repo msaligs/ast_fine_tuned_music_genre_10

Source context: 7 downloads · 1 likes · Pipeline audio-classification · Repo msaligs/ast_fine_tuned_music_genre_10