Audio Classification
Transformers
TensorBoard
Safetensors
hubert
Generated from Trainer
Eval Results (legacy)
Instructions to use SLPL/Hubert-base-ShEMO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SLPL/Hubert-base-ShEMO with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="SLPL/Hubert-base-ShEMO")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("SLPL/Hubert-base-ShEMO") model = AutoModelForAudioClassification.from_pretrained("SLPL/Hubert-base-ShEMO") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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- Loss: 0.6161
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- F1: 0.8335
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## Model description
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More information needed
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- Loss: 0.6161
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- F1: 0.8335
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## Labels description
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- 0 : anger
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- 1 : happiness
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- 2 : neutral
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- 3 : sadness
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## Model description
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More information needed
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