marsyas/gtzan
Updated • 1.85k • 17
How to use tsobolev/distil-ast-audioset-finetuned-gtzan with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("audio-classification", model="tsobolev/distil-ast-audioset-finetuned-gtzan") # Load model directly
from transformers import AutoFeatureExtractor, AutoModelForAudioClassification
extractor = AutoFeatureExtractor.from_pretrained("tsobolev/distil-ast-audioset-finetuned-gtzan")
model = AutoModelForAudioClassification.from_pretrained("tsobolev/distil-ast-audioset-finetuned-gtzan")This model is a fine-tuned version of bookbot/distil-ast-audioset 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 |
|---|---|---|---|---|
| 1.3117 | 1.0 | 113 | 1.0134 | 0.65 |
| 0.5748 | 2.0 | 226 | 0.4728 | 0.91 |
| 0.4554 | 3.0 | 339 | 0.5475 | 0.88 |
| 0.1809 | 4.0 | 452 | 0.5119 | 0.88 |
| 0.0564 | 5.0 | 565 | 0.4898 | 0.88 |
| 0.0014 | 6.0 | 678 | 0.4669 | 0.87 |
| 0.0484 | 7.0 | 791 | 0.5143 | 0.88 |
| 0.0002 | 8.0 | 904 | 0.4885 | 0.88 |
| 0.0562 | 9.0 | 1017 | 0.4628 | 0.88 |
| 0.0002 | 10.0 | 1130 | 0.4629 | 0.89 |
Base model
bookbot/distil-ast-audioset