marsyas/gtzan
Updated • 1.85k • 17
How to use jjsprockel/wav2vec2-base-finetuned-gtzan with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("audio-classification", model="jjsprockel/wav2vec2-base-finetuned-gtzan") # Load model directly
from transformers import AutoProcessor, AutoModelForAudioClassification
processor = AutoProcessor.from_pretrained("jjsprockel/wav2vec2-base-finetuned-gtzan")
model = AutoModelForAudioClassification.from_pretrained("jjsprockel/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 |
|---|---|---|---|---|
| 2.2793 | 0.99 | 28 | 2.1814 | 0.28 |
| 1.9466 | 1.98 | 56 | 1.9110 | 0.41 |
| 1.7147 | 2.97 | 84 | 1.7353 | 0.47 |
| 1.5161 | 4.0 | 113 | 1.5839 | 0.53 |
| 1.3164 | 4.99 | 141 | 1.4552 | 0.62 |
| 1.2924 | 5.98 | 169 | 1.4023 | 0.68 |
| 1.1274 | 6.97 | 197 | 1.3962 | 0.65 |
| 1.0276 | 8.0 | 226 | 1.2685 | 0.74 |
| 0.967 | 8.99 | 254 | 1.2464 | 0.72 |
| 0.9227 | 9.91 | 280 | 1.2556 | 0.72 |
Base model
facebook/wav2vec2-base