marsyas/gtzan
Updated • 1.91k • 18
How to use sugarblock/music_genres_classification-finetuned-gtzan with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("audio-classification", model="sugarblock/music_genres_classification-finetuned-gtzan") # Load model directly
from transformers import AutoProcessor, AutoModelForAudioClassification
processor = AutoProcessor.from_pretrained("sugarblock/music_genres_classification-finetuned-gtzan")
model = AutoModelForAudioClassification.from_pretrained("sugarblock/music_genres_classification-finetuned-gtzan", device_map="auto")This model is a fine-tuned version of dima806/music_genres_classification 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 |
|---|---|---|---|---|
| 1.4625 | 1.0 | 113 | 1.2806 | 0.62 |
| 1.3333 | 2.0 | 226 | 0.6150 | 0.85 |
| 0.5933 | 3.0 | 339 | 1.0492 | 0.7 |
| 0.3719 | 4.0 | 452 | 0.7653 | 0.81 |
| 0.3841 | 5.0 | 565 | 0.7379 | 0.85 |
| 0.7695 | 6.0 | 678 | 0.7611 | 0.81 |
| 0.5149 | 7.0 | 791 | 0.3903 | 0.92 |
| 0.1148 | 8.0 | 904 | 0.3904 | 0.93 |
| 0.3073 | 9.0 | 1017 | 0.3303 | 0.93 |
| 0.0687 | 10.0 | 1130 | 0.3249 | 0.93 |