marsyas/gtzan
Updated • 1.71k • 17
How to use asutosh09/music_class with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("audio-classification", model="asutosh09/music_class") # Load model directly
from transformers import AutoProcessor, AutoModelForAudioClassification
processor = AutoProcessor.from_pretrained("asutosh09/music_class")
model = AutoModelForAudioClassification.from_pretrained("asutosh09/music_class")This model is a fine-tuned version of openai/whisper-medium.en 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 |
|---|---|---|---|---|
| 1.7711 | 1.0 | 112 | 1.6556 | 0.52 |
| 0.5477 | 2.0 | 225 | 0.4738 | 0.85 |
| 0.535 | 3.0 | 337 | 0.3137 | 0.92 |
| 0.231 | 4.0 | 450 | 0.3613 | 0.9 |
| 0.1923 | 5.0 | 562 | 0.2885 | 0.95 |
| 0.0584 | 6.0 | 675 | 0.6531 | 0.86 |
| 0.1783 | 7.0 | 787 | 0.5717 | 0.9 |
| 0.0022 | 8.0 | 900 | 0.4205 | 0.91 |
| 0.1032 | 9.0 | 1012 | 0.4984 | 0.91 |
| 0.0011 | 10.0 | 1125 | 0.3778 | 0.94 |
| 0.0104 | 11.0 | 1237 | 0.3709 | 0.94 |
| 0.0011 | 12.0 | 1350 | 0.4564 | 0.92 |
| 0.0009 | 13.0 | 1462 | 0.3796 | 0.94 |
| 0.0008 | 14.0 | 1575 | 0.3880 | 0.94 |
| 0.0008 | 15.0 | 1687 | 0.3930 | 0.94 |
| 0.0008 | 15.93 | 1792 | 0.3955 | 0.94 |
Base model
openai/whisper-medium.en