s3prl/superb
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How to use Jungwoo4021/wav2vec2-base-ks-linear_lrX10 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("audio-classification", model="Jungwoo4021/wav2vec2-base-ks-linear_lrX10") # Load model directly
from transformers import AutoProcessor, AutoModelForSequenceClassification
processor = AutoProcessor.from_pretrained("Jungwoo4021/wav2vec2-base-ks-linear_lrX10")
model = AutoModelForSequenceClassification.from_pretrained("Jungwoo4021/wav2vec2-base-ks-linear_lrX10")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 |
|---|---|---|---|---|
| 1.6226 | 1.0 | 50 | 1.7588 | 0.6209 |
| 1.382 | 2.0 | 100 | 1.5696 | 0.6209 |
| 1.2373 | 3.0 | 150 | 1.3818 | 0.6212 |
| 1.1019 | 4.0 | 200 | 1.2577 | 0.6228 |
| 0.9831 | 5.0 | 250 | 1.1826 | 0.6331 |
| 0.9241 | 6.0 | 300 | 1.1200 | 0.6481 |
| 0.8695 | 7.0 | 350 | 1.0821 | 0.6581 |
| 0.8529 | 8.0 | 400 | 1.0632 | 0.6652 |
| 0.8385 | 9.0 | 450 | 1.0494 | 0.6677 |
| 0.8162 | 10.0 | 500 | 1.0471 | 0.6686 |