s3prl/superb
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How to use NhatPham/wav2vec2-base-finetuned-ks with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("audio-classification", model="NhatPham/wav2vec2-base-finetuned-ks") # Load model directly
from transformers import AutoProcessor, AutoModelForAudioClassification
processor = AutoProcessor.from_pretrained("NhatPham/wav2vec2-base-finetuned-ks")
model = AutoModelForAudioClassification.from_pretrained("NhatPham/wav2vec2-base-finetuned-ks")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 |
|---|---|---|---|---|
| 1.1561 | 1.0 | 399 | 1.1127 | 0.6643 |
| 0.4803 | 2.0 | 798 | 0.3547 | 0.9687 |
| 0.2855 | 3.0 | 1197 | 0.1663 | 0.9763 |
| 0.1987 | 4.0 | 1596 | 0.1258 | 0.9793 |
| 0.2097 | 5.0 | 1995 | 0.1171 | 0.9791 |