google/speech_commands
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How to use realHarter/wav2vec2-base-finetuned-ks with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("audio-classification", model="realHarter/wav2vec2-base-finetuned-ks") # Load model directly
from transformers import AutoProcessor, AutoModelForAudioClassification
processor = AutoProcessor.from_pretrained("realHarter/wav2vec2-base-finetuned-ks")
model = AutoModelForAudioClassification.from_pretrained("realHarter/wav2vec2-base-finetuned-ks", device_map="auto")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:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.5366 | 1.0 | 83 | 2.2424 | 0.8575 |
| 1.963 | 2.0 | 166 | 1.6987 | 0.9537 |
| 1.7887 | 3.0 | 249 | 1.5562 | 0.9632 |
Base model
facebook/wav2vec2-base