marsyas/gtzan
Updated • 1.85k • 17
How to use rishabhsabnavis/wav2vec2-base-finetuned-gtzan with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("audio-classification", model="rishabhsabnavis/wav2vec2-base-finetuned-gtzan") # Load model directly
from transformers import AutoProcessor, AutoModelForAudioClassification
processor = AutoProcessor.from_pretrained("rishabhsabnavis/wav2vec2-base-finetuned-gtzan")
model = AutoModelForAudioClassification.from_pretrained("rishabhsabnavis/wav2vec2-base-finetuned-gtzan")This model is a fine-tuned version of facebook/wav2vec2-base 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 |
|---|---|---|---|---|
| 0.8396 | 1.0 | 113 | 1.6878 | 0.78 |
| 0.1548 | 2.0 | 226 | 2.0664 | 0.73 |
| 0.0015 | 3.0 | 339 | 1.6951 | 0.79 |
| 0.0006 | 4.0 | 452 | 1.4365 | 0.82 |
| 0.0007 | 5.0 | 565 | 1.5483 | 0.82 |
| 0.0001 | 6.0 | 678 | 1.3558 | 0.84 |
| 0.0002 | 7.0 | 791 | 1.4830 | 0.84 |
| 0.0002 | 8.0 | 904 | 1.4790 | 0.83 |
| 0.0002 | 9.0 | 1017 | 1.4712 | 0.84 |
Base model
facebook/wav2vec2-base