marsyas/gtzan
Updated • 1.76k • 17
How to use ld76/wav2vec2-base-finetuned-gtzan-2 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("audio-classification", model="ld76/wav2vec2-base-finetuned-gtzan-2") # Load model directly
from transformers import AutoProcessor, AutoModelForAudioClassification
processor = AutoProcessor.from_pretrained("ld76/wav2vec2-base-finetuned-gtzan-2")
model = AutoModelForAudioClassification.from_pretrained("ld76/wav2vec2-base-finetuned-gtzan-2")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 |
|---|---|---|---|---|
| 2.0152 | 1.0 | 112 | 1.9017 | 0.52 |
| 1.6232 | 2.0 | 225 | 1.5400 | 0.53 |
| 1.2989 | 3.0 | 337 | 1.1494 | 0.65 |
| 1.2035 | 4.0 | 450 | 1.1189 | 0.69 |
| 0.6804 | 5.0 | 562 | 0.8873 | 0.69 |
| 0.7305 | 6.0 | 675 | 0.7527 | 0.81 |
| 0.4738 | 7.0 | 787 | 0.6880 | 0.78 |
| 0.2824 | 8.0 | 900 | 0.7893 | 0.73 |
| 0.3863 | 9.0 | 1012 | 0.5786 | 0.85 |
| 0.4061 | 10.0 | 1125 | 0.7070 | 0.81 |
| 0.1302 | 11.0 | 1237 | 0.5829 | 0.88 |
Base model
facebook/wav2vec2-base