s3prl/superb
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How to use Jungwoo4021/wav2vec2-base-ks-padpt800 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("audio-classification", model="Jungwoo4021/wav2vec2-base-ks-padpt800") # Load model directly
from transformers import AutoProcessor, AutoModelForSequenceClassification
processor = AutoProcessor.from_pretrained("Jungwoo4021/wav2vec2-base-ks-padpt800")
model = AutoModelForSequenceClassification.from_pretrained("Jungwoo4021/wav2vec2-base-ks-padpt800")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 |
|---|---|---|---|---|
| 1.328 | 1.0 | 50 | 1.5281 | 0.6142 |
| 0.9328 | 2.0 | 100 | 1.3054 | 0.5853 |
| 0.8277 | 3.0 | 150 | 1.3858 | 0.4966 |
| 0.7689 | 4.0 | 200 | 1.4112 | 0.4975 |
| 0.7154 | 5.0 | 250 | 1.4042 | 0.5035 |
| 0.706 | 6.0 | 300 | 1.3635 | 0.5171 |
| 0.6878 | 7.0 | 350 | 1.4373 | 0.4873 |
| 0.6868 | 8.0 | 400 | 1.2890 | 0.5505 |
| 0.6705 | 9.0 | 450 | 1.3019 | 0.5405 |
| 0.6579 | 10.0 | 500 | 1.3337 | 0.5272 |