legacy-datasets/common_voice
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How to use burakyldrm/wav2vec2-burak-v2.1 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="burakyldrm/wav2vec2-burak-v2.1") # pip install -U transformers accelerate
# Load model directly
from transformers import AutoProcessor, AutoModelForCTC
processor = AutoProcessor.from_pretrained("burakyldrm/wav2vec2-burak-v2.1")
model = AutoModelForCTC.from_pretrained("burakyldrm/wav2vec2-burak-v2.1", device_map="auto")This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice 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 | Wer |
|---|---|---|---|---|
| 3.763 | 7.02 | 400 | 0.7108 | 0.7190 |
| 0.299 | 14.03 | 800 | 0.5404 | 0.5564 |
| 0.1285 | 21.05 | 1200 | 0.5736 | 0.5050 |
| 0.0741 | 28.07 | 1600 | 0.5006 | 0.4605 |