s3prl/superb
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How to use Jungwoo4021/wav2vec2-base-ks-ept4 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("audio-classification", model="Jungwoo4021/wav2vec2-base-ks-ept4") # Load model directly
from transformers import AutoProcessor, AutoModelForSequenceClassification
processor = AutoProcessor.from_pretrained("Jungwoo4021/wav2vec2-base-ks-ept4")
model = AutoModelForSequenceClassification.from_pretrained("Jungwoo4021/wav2vec2-base-ks-ept4")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 |
|---|---|---|---|---|
| 1.5133 | 1.0 | 50 | 1.5663 | 0.6209 |
| 1.4819 | 2.0 | 100 | 1.5675 | 0.6169 |
| 1.4082 | 3.0 | 150 | 1.5372 | 0.5802 |
| 1.3536 | 4.0 | 200 | 1.6716 | 0.5338 |
| 1.296 | 5.0 | 250 | 1.7601 | 0.5399 |
| 1.3053 | 6.0 | 300 | 1.6778 | 0.5630 |
| 1.2734 | 7.0 | 350 | 1.6554 | 0.5734 |
| 1.2837 | 8.0 | 400 | 1.7338 | 0.5741 |
| 1.2682 | 9.0 | 450 | 1.7313 | 0.5774 |
| 1.2776 | 10.0 | 500 | 1.7083 | 0.5791 |