marsyas/gtzan
Updated • 2.48k • 18
How to use pppde/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="pppde/ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan") # pip install -U transformers accelerate
# Load model directly
from transformers import AutoFeatureExtractor, AutoModelForAudioClassification
extractor = AutoFeatureExtractor.from_pretrained("pppde/ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan")
model = AutoModelForAudioClassification.from_pretrained("pppde/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 |
|---|---|---|---|---|
| 0.6838 | 1.0 | 57 | 0.5120 | 0.87 |
| 0.2759 | 2.0 | 114 | 0.4558 | 0.84 |
| 0.166 | 3.0 | 171 | 0.5021 | 0.84 |
| 0.252 | 4.0 | 228 | 0.3866 | 0.91 |
| 0.0299 | 5.0 | 285 | 0.3424 | 0.87 |
| 0.1403 | 6.0 | 342 | 0.6292 | 0.89 |
| 0.135 | 7.0 | 399 | 0.6622 | 0.91 |
| 0.0 | 8.0 | 456 | 0.7631 | 0.9 |
| 0.0 | 9.0 | 513 | 0.7565 | 0.89 |
| 0.0 | 10.0 | 570 | 0.5774 | 0.9 |
| 0.0 | 11.0 | 627 | 0.5556 | 0.9 |
| 0.0 | 12.0 | 684 | 0.5274 | 0.9 |
Base model
MIT/ast-finetuned-audioset-10-10-0.4593