marsyas/gtzan
Updated • 1.61k • 17
How to use saandman/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="saandman/ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan") # Load model directly
from transformers import AutoFeatureExtractor, AutoModelForAudioClassification
extractor = AutoFeatureExtractor.from_pretrained("saandman/ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan")
model = AutoModelForAudioClassification.from_pretrained("saandman/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 |
|---|---|---|---|---|
| 1.066 | 1.0 | 112 | 0.5999 | 0.83 |
| 0.4707 | 2.0 | 225 | 0.5077 | 0.81 |
| 0.363 | 3.0 | 337 | 0.5508 | 0.83 |
| 0.1067 | 4.0 | 450 | 0.6624 | 0.81 |
| 0.0072 | 5.0 | 562 | 0.6558 | 0.85 |
| 0.0047 | 6.0 | 675 | 0.4942 | 0.89 |
| 0.0006 | 7.0 | 787 | 0.4824 | 0.91 |
| 0.001 | 8.0 | 900 | 0.5176 | 0.89 |
| 0.1411 | 9.0 | 1012 | 0.5117 | 0.89 |
| 0.0002 | 9.96 | 1120 | 0.5045 | 0.89 |
Base model
MIT/ast-finetuned-audioset-10-10-0.4593