marsyas/gtzan
Updated • 1.61k • 17
How to use caffeinatedwoof/ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("audio-classification", model="caffeinatedwoof/ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan") # Load model directly
from transformers import AutoFeatureExtractor, AutoModelForAudioClassification
extractor = AutoFeatureExtractor.from_pretrained("caffeinatedwoof/ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan")
model = AutoModelForAudioClassification.from_pretrained("caffeinatedwoof/ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan")This model is a fine-tuned version of MIT/ast-finetuned-audioset-10-10-0.4593 on the GTZAN dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.687 | 1.0 | 450 | 0.6688 | 0.76 |
| 1.393 | 2.0 | 900 | 0.5216 | 0.88 |
| 0.024 | 3.0 | 1350 | 0.5718 | 0.85 |
| 0.0004 | 4.0 | 1800 | 0.6104 | 0.89 |
Base model
MIT/ast-finetuned-audioset-10-10-0.4593