google/speech_commands
Updated • 3.63k • 59
How to use Dc26/wav2vec2-base-finetuned-ks with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("audio-classification", model="Dc26/wav2vec2-base-finetuned-ks") # Load model directly
from transformers import AutoProcessor, AutoModelForAudioClassification
processor = AutoProcessor.from_pretrained("Dc26/wav2vec2-base-finetuned-ks")
model = AutoModelForAudioClassification.from_pretrained("Dc26/wav2vec2-base-finetuned-ks")This model is a fine-tuned version of facebook/wav2vec2-base on the speech_commands 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 |
|---|---|---|---|---|
| 0.6408 | 1.0 | 2651 | 0.2399 | 0.9609 |
| 0.4113 | 2.0 | 5303 | 0.1284 | 0.9686 |
| 0.3014 | 3.0 | 7954 | 0.1144 | 0.9706 |
| 0.2914 | 4.0 | 10606 | 0.0962 | 0.9760 |
| 0.1621 | 5.0 | 13255 | 0.0880 | 0.9780 |