marsyas/gtzan
Updated • 1.82k • 17
How to use ternikov/whisper-tiny-finetuned-gtzan with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("audio-classification", model="ternikov/whisper-tiny-finetuned-gtzan") # Load model directly
from transformers import AutoProcessor, AutoModelForAudioClassification
processor = AutoProcessor.from_pretrained("ternikov/whisper-tiny-finetuned-gtzan")
model = AutoModelForAudioClassification.from_pretrained("ternikov/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:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3867 | 1.0 | 150 | 0.4913 | 0.85 |
| 0.6883 | 2.0 | 300 | 0.9527 | 0.81 |
| 0.0056 | 3.0 | 450 | 0.6576 | 0.84 |
| 0.0021 | 4.0 | 600 | 0.7685 | 0.84 |
| 0.0007 | 5.0 | 750 | 0.7602 | 0.87 |
| 0.0005 | 6.0 | 900 | 0.8593 | 0.85 |
| 0.0005 | 7.0 | 1050 | 0.8438 | 0.84 |
| 0.0003 | 8.0 | 1200 | 0.6439 | 0.88 |
| 0.0003 | 9.0 | 1350 | 0.7370 | 0.88 |
| 0.0003 | 10.0 | 1500 | 0.7231 | 0.89 |
Base model
openai/whisper-tiny