marsyas/gtzan
Updated • 4.37k • 18
How to use abdelnour131/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="abdelnour131/ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan") # Load model directly
from transformers import AutoFeatureExtractor, AutoModelForAudioClassification
extractor = AutoFeatureExtractor.from_pretrained("abdelnour131/ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan")
model = AutoModelForAudioClassification.from_pretrained("abdelnour131/ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan", device_map="auto")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 |
|---|---|---|---|---|
| 0.7242 | 1.0 | 113 | 0.6274 | 0.8 |
| 0.3691 | 2.0 | 226 | 0.6663 | 0.81 |
| 0.1866 | 3.0 | 339 | 0.6063 | 0.84 |
| 0.0344 | 4.0 | 452 | 0.6844 | 0.84 |
| 0.0022 | 5.0 | 565 | 0.5484 | 0.85 |
| 0.0021 | 6.0 | 678 | 0.4110 | 0.89 |
| 0.0002 | 7.0 | 791 | 0.4046 | 0.89 |
| 0.0001 | 8.0 | 904 | 0.3777 | 0.9 |
| 0.0001 | 9.0 | 1017 | 0.3854 | 0.9 |
| 0.0001 | 10.0 | 1130 | 0.3871 | 0.9 |
Base model
MIT/ast-finetuned-audioset-10-10-0.4593