marsyas/gtzan
Updated • 1.8k • 17
How to use alex-uv2/wav2vec2-base-finetuned-gtzan with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("audio-classification", model="alex-uv2/wav2vec2-base-finetuned-gtzan") # Load model directly
from transformers import AutoProcessor, AutoModelForAudioClassification
processor = AutoProcessor.from_pretrained("alex-uv2/wav2vec2-base-finetuned-gtzan")
model = AutoModelForAudioClassification.from_pretrained("alex-uv2/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 |
|---|---|---|---|---|
| 1.9774 | 1.0 | 113 | 1.9927 | 0.28 |
| 1.5184 | 2.0 | 226 | 1.4378 | 0.5 |
| 1.3158 | 3.0 | 339 | 1.1390 | 0.72 |
| 0.8236 | 4.0 | 452 | 1.0595 | 0.69 |
| 0.7644 | 5.0 | 565 | 1.0361 | 0.7 |
| 0.5783 | 6.0 | 678 | 0.6584 | 0.82 |
| 0.4597 | 7.0 | 791 | 0.5901 | 0.87 |
| 0.2232 | 8.0 | 904 | 0.5699 | 0.87 |
| 0.1191 | 9.0 | 1017 | 0.5567 | 0.88 |
| 0.0797 | 10.0 | 1130 | 0.5653 | 0.86 |
Base model
facebook/wav2vec2-base