s3prl/superb
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How to use herbiel/wav2vec2-base-finetuned-ks with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("audio-classification", model="herbiel/wav2vec2-base-finetuned-ks") # Load model directly
from transformers import AutoProcessor, AutoModelForAudioClassification
processor = AutoProcessor.from_pretrained("herbiel/wav2vec2-base-finetuned-ks")
model = AutoModelForAudioClassification.from_pretrained("herbiel/wav2vec2-base-finetuned-ks", device_map="auto")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 |
|---|---|---|---|---|
| 0.2589 | 1.0 | 400 | 0.1578 | 0.9703 |
| 0.199 | 2.0 | 800 | 0.0960 | 0.9793 |
| 0.1723 | 3.0 | 1200 | 0.0853 | 0.9794 |
| 0.1514 | 4.0 | 1600 | 0.0796 | 0.9819 |
| 0.1038 | 5.0 | 2000 | 0.0758 | 0.9829 |
Base model
facebook/wav2vec2-base