marsyas/gtzan
Updated • 1.61k • 17
How to use sabya87/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="sabya87/ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan") # Load model directly
from transformers import AutoFeatureExtractor, AutoModelForAudioClassification
extractor = AutoFeatureExtractor.from_pretrained("sabya87/ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan")
model = AutoModelForAudioClassification.from_pretrained("sabya87/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 |
|---|---|---|---|---|
| 0.6009 | 0.99 | 37 | 0.6286 | 0.8 |
| 0.2809 | 2.0 | 75 | 0.5013 | 0.85 |
| 0.0913 | 2.99 | 112 | 0.3566 | 0.88 |
| 0.0217 | 4.0 | 150 | 0.3274 | 0.89 |
| 0.0401 | 4.99 | 187 | 0.3379 | 0.91 |
| 0.0016 | 6.0 | 225 | 0.3839 | 0.9 |
| 0.0006 | 6.99 | 262 | 0.3449 | 0.9 |
| 0.0027 | 8.0 | 300 | 0.4207 | 0.9 |
| 0.0007 | 8.99 | 337 | 0.3600 | 0.92 |
| 0.0003 | 9.87 | 370 | 0.3414 | 0.91 |
Base model
MIT/ast-finetuned-audioset-10-10-0.4593