s3prl/superb
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How to use SHENMU007/speechcommand-demo with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("audio-classification", model="SHENMU007/speechcommand-demo") # Load model directly
from transformers import AutoProcessor, AutoModelForAudioClassification
processor = AutoProcessor.from_pretrained("SHENMU007/speechcommand-demo")
model = AutoModelForAudioClassification.from_pretrained("SHENMU007/speechcommand-demo")This model is a fine-tuned version of facebook/wav2vec2-base on the superb 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 |
|---|---|---|---|---|
| 0.6433 | 1.0 | 399 | 0.4979 | 0.9112 |
| 0.2406 | 2.0 | 798 | 0.1455 | 0.9750 |
| 0.1563 | 3.0 | 1197 | 0.1032 | 0.9785 |
| 0.1144 | 4.0 | 1597 | 0.0919 | 0.9806 |
| 0.1254 | 5.0 | 1995 | 0.0873 | 0.9809 |