marsyas/gtzan
Updated • 1.61k • 17
How to use lightborn3/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="lightborn3/ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan") # Load model directly
from transformers import AutoFeatureExtractor, AutoModelForAudioClassification
extractor = AutoFeatureExtractor.from_pretrained("lightborn3/ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan")
model = AutoModelForAudioClassification.from_pretrained("lightborn3/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 |
|---|---|---|---|---|
| 1.3114 | 1.0 | 225 | 0.6735 | 0.81 |
| 0.8219 | 2.0 | 450 | 0.9353 | 0.76 |
| 0.3919 | 3.0 | 675 | 0.5918 | 0.83 |
| 0.1734 | 4.0 | 900 | 0.7837 | 0.84 |
| 0.0006 | 5.0 | 1125 | 0.5700 | 0.88 |
| 0.0001 | 6.0 | 1350 | 0.6843 | 0.86 |
| 0.3299 | 7.0 | 1575 | 0.5534 | 0.88 |
| 0.0001 | 8.0 | 1800 | 0.5711 | 0.88 |
| 0.0001 | 9.0 | 2025 | 0.5704 | 0.88 |
| 0.0 | 10.0 | 2250 | 0.5683 | 0.88 |
Base model
MIT/ast-finetuned-audioset-10-10-0.4593