marsyas/gtzan
Updated • 4.55k • 18
How to use Adbhut/wav2vec2-base-finetuned-gtzan with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("audio-classification", model="Adbhut/wav2vec2-base-finetuned-gtzan") # Load model directly
from transformers import AutoProcessor, AutoModelForAudioClassification
processor = AutoProcessor.from_pretrained("Adbhut/wav2vec2-base-finetuned-gtzan")
model = AutoModelForAudioClassification.from_pretrained("Adbhut/wav2vec2-base-finetuned-gtzan", device_map="auto")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 |
|---|---|---|---|---|
| 0.4667 | 1.0 | 113 | 0.7013 | 0.79 |
| 0.6329 | 2.0 | 226 | 1.1081 | 0.69 |
| 0.151 | 3.0 | 339 | 0.6619 | 0.84 |
| 0.2903 | 4.0 | 452 | 0.8713 | 0.78 |
| 0.379 | 5.0 | 565 | 0.7113 | 0.85 |
| 0.1222 | 6.0 | 678 | 0.6789 | 0.87 |
| 0.292 | 7.0 | 791 | 0.6808 | 0.88 |
| 0.0305 | 8.0 | 904 | 0.5518 | 0.91 |
| 0.0073 | 9.0 | 1017 | 0.7742 | 0.88 |
| 0.007 | 10.0 | 1130 | 0.7251 | 0.88 |
Base model
facebook/wav2vec2-base