marsyas/gtzan
Updated • 1.61k • 17
How to use giocs2017/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="giocs2017/ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan") # Load model directly
from transformers import AutoFeatureExtractor, AutoModelForAudioClassification
extractor = AutoFeatureExtractor.from_pretrained("giocs2017/ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan")
model = AutoModelForAudioClassification.from_pretrained("giocs2017/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 |
|---|---|---|---|---|
| 0.9627 | 1.0 | 112 | 0.7284 | 0.75 |
| 0.3776 | 1.99 | 224 | 0.4641 | 0.83 |
| 0.4536 | 3.0 | 337 | 0.5534 | 0.85 |
| 0.0602 | 4.0 | 449 | 0.4999 | 0.86 |
| 0.1927 | 4.99 | 561 | 0.5989 | 0.85 |
| 0.0122 | 6.0 | 674 | 0.7778 | 0.85 |
| 0.0006 | 6.99 | 786 | 0.4095 | 0.9 |
| 0.0005 | 8.0 | 899 | 0.5149 | 0.9 |
| 0.1723 | 9.0 | 1011 | 0.4558 | 0.9 |
| 0.0001 | 9.99 | 1123 | 0.4700 | 0.9 |
Base model
MIT/ast-finetuned-audioset-10-10-0.4593