marsyas/gtzan
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How to use samuelleecong/whisper-tiny-finetuned-gtzan with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("audio-classification", model="samuelleecong/whisper-tiny-finetuned-gtzan") # Load model directly
from transformers import AutoProcessor, AutoModelForAudioClassification
processor = AutoProcessor.from_pretrained("samuelleecong/whisper-tiny-finetuned-gtzan")
model = AutoModelForAudioClassification.from_pretrained("samuelleecong/whisper-tiny-finetuned-gtzan")This model is a fine-tuned version of openai/whisper-tiny 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 |
|---|---|---|---|---|
| 0.988 | 1.0 | 57 | 1.4201 | 0.58 |
| 0.4825 | 2.0 | 114 | 0.7614 | 0.83 |
| 0.5993 | 3.0 | 171 | 0.5825 | 0.83 |
| 0.1427 | 4.0 | 228 | 0.4283 | 0.88 |
| 0.0461 | 5.0 | 285 | 0.3900 | 0.88 |
| 0.0438 | 6.0 | 342 | 0.4485 | 0.86 |
| 0.0171 | 7.0 | 399 | 0.3320 | 0.91 |
| 0.0182 | 8.0 | 456 | 0.3799 | 0.9 |
| 0.0066 | 9.0 | 513 | 0.3901 | 0.88 |
| 0.0077 | 10.0 | 570 | 0.4064 | 0.89 |
Base model
openai/whisper-tiny