s3prl/superb
Viewer • Updated • 304k • 2.09k • 33
How to use GabeNeves/wav2vec2-base-finetuned-ks with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("audio-classification", model="GabeNeves/wav2vec2-base-finetuned-ks") # Load model directly
from transformers import AutoProcessor, AutoModelForAudioClassification
processor = AutoProcessor.from_pretrained("GabeNeves/wav2vec2-base-finetuned-ks")
model = AutoModelForAudioClassification.from_pretrained("GabeNeves/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:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.2711 | 1.0 | 400 | 0.5021 | 0.9500 |
| 0.8888 | 2.0 | 800 | 0.1725 | 0.9773 |
| 0.7851 | 3.0 | 1200 | 0.1099 | 0.9819 |
| 0.6176 | 4.0 | 1600 | 0.0968 | 0.9810 |
| 0.5318 | 4.9894 | 1995 | 0.0886 | 0.9835 |
Base model
facebook/wav2vec2-base