Music Genre Classification Model ๐ถ
This model classifies music genres based on audio signals. It was fine-tuned on the model Wav2Vec2 and using the datasets music_genres_small.
You can find a GitHub repository with an interface hosted by a Flask API to test the model: music-classifier repository
Metrics
- Validation Accuracy: 75%
- F1 Score: 74%
- Validation Loss: 0.77
Example Usage
from transformers import Wav2Vec2ForSequenceClassification, Wav2Vec2FeatureExtractor
import torch
# Load model and feature extractor
model = Wav2Vec2ForSequenceClassification.from_pretrained("gastonduault/music-classifier")
feature_extractor = Wav2Vec2FeatureExtractor.from_pretrained("facebook/wav2vec2-large")
# Process audio file
audio_path = "path/to/audio.wav"
audio_input = feature_extractor(audio_array, sampling_rate=16000, return_tensors="pt", padding=True)
# Predict
with torch.no_grad():
logits = model(audio_input["input_values"])
predicted_class = torch.argmax(logits.logits, dim=-1)
print(predicted_class)
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Base model
facebook/wav2vec2-large