marsyas/gtzan
Updated • 1.61k • 17
How to use xiankai123/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="xiankai123/ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan") # Load model directly
from transformers import AutoFeatureExtractor, AutoModelForAudioClassification
extractor = AutoFeatureExtractor.from_pretrained("xiankai123/ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan")
model = AutoModelForAudioClassification.from_pretrained("xiankai123/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 |
|---|---|---|---|---|
| 1.1244 | 1.0 | 113 | 0.8034 | 0.72 |
| 0.5318 | 2.0 | 226 | 0.5882 | 0.83 |
| 0.3489 | 3.0 | 339 | 0.8427 | 0.8 |
| 0.021 | 4.0 | 452 | 0.8284 | 0.8 |
| 0.0944 | 5.0 | 565 | 0.6992 | 0.87 |
| 0.0102 | 6.0 | 678 | 0.6557 | 0.88 |
| 0.2053 | 7.0 | 791 | 0.5572 | 0.9 |
| 0.0012 | 8.0 | 904 | 0.4284 | 0.9 |
| 0.0953 | 9.0 | 1017 | 0.4035 | 0.9 |
| 0.0001 | 10.0 | 1130 | 0.3998 | 0.9 |
Base model
MIT/ast-finetuned-audioset-10-10-0.4593