s3prl/superb
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How to use riteshkr/wav2vec2-base-finetuned-ks with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("audio-classification", model="riteshkr/wav2vec2-base-finetuned-ks") # Load model directly
from transformers import AutoProcessor, AutoModelForAudioClassification
processor = AutoProcessor.from_pretrained("riteshkr/wav2vec2-base-finetuned-ks")
model = AutoModelForAudioClassification.from_pretrained("riteshkr/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 |
|---|---|---|---|---|
| 0.8512 | 0.9994 | 399 | 0.6921 | 0.8461 |
| 0.3088 | 1.9987 | 798 | 0.1814 | 0.9784 |
| 0.1642 | 2.9981 | 1197 | 0.1171 | 0.9815 |
| 0.1566 | 4.0 | 1597 | 0.1004 | 0.9804 |
| 0.1454 | 4.9969 | 1995 | 0.0978 | 0.9809 |
Base model
facebook/wav2vec2-base