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--- |
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datasets: |
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- lewtun/music_genres_small |
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base_model: |
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- facebook/wav2vec2-large |
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--- |
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# My Music Genre Classification Model 🎶 |
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This model classifies music genres based on audio signals. It was fine-tuned on the `music_genres_small` dataset using the Wav2Vec2 architecture. |
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## Metrics |
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- **Validation Accuracy**: 69% |
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- **F1 Score**: 68% |
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- **Validation Loss**: 1.03 |
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## Usage |
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```python |
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from transformers import Wav2Vec2ForSequenceClassification, Wav2Vec2FeatureExtractor |
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import torch |
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# Load the model and feature extractor |
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model = Wav2Vec2ForSequenceClassification.from_pretrained("username/repo-name") |
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feature_extractor = Wav2Vec2FeatureExtractor.from_pretrained("username/repo-name") |
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# Prepare input |
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audio = ... # Your audio array |
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inputs = feature_extractor(audio, sampling_rate=16000, return_tensors="pt") |
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# Make predictions |
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logits = model(**inputs).logits |
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predicted_class = torch.argmax(logits, dim=-1).item() |
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print(predicted_class) |
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