marsyas/gtzan
Updated • 1.61k • 17
How to use alessio21/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="alessio21/ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan") # Load model directly
from transformers import AutoFeatureExtractor, AutoModelForAudioClassification
extractor = AutoFeatureExtractor.from_pretrained("alessio21/ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan")
model = AutoModelForAudioClassification.from_pretrained("alessio21/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:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.0671 | 1.0 | 450 | 0.6674 | 0.77 |
| 2.0161 | 2.0 | 900 | 0.6465 | 0.81 |
| 0.6629 | 3.0 | 1350 | 1.5574 | 0.72 |
| 0.0792 | 4.0 | 1800 | 0.7004 | 0.85 |
| 0.0437 | 5.0 | 2250 | 0.8645 | 0.86 |
| 0.0 | 6.0 | 2700 | 1.0612 | 0.88 |
| 0.8016 | 7.0 | 3150 | 0.7086 | 0.87 |
| 0.0 | 8.0 | 3600 | 0.7586 | 0.88 |
| 0.0 | 9.0 | 4050 | 0.7274 | 0.88 |
| 0.0 | 10.0 | 4500 | 0.7229 | 0.88 |
Base model
MIT/ast-finetuned-audioset-10-10-0.4593