legacy-datasets/common_voice
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How to use emre/wav2vec2-large-xlsr-53-sah-CV8 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="emre/wav2vec2-large-xlsr-53-sah-CV8") # Load model directly
from transformers import AutoProcessor, AutoModelForCTC
processor = AutoProcessor.from_pretrained("emre/wav2vec2-large-xlsr-53-sah-CV8")
model = AutoModelForCTC.from_pretrained("emre/wav2vec2-large-xlsr-53-sah-CV8")This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 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 |
|---|---|---|---|---|
| 4.6849 | 16.67 | 500 | 1.1135 | 0.9344 |
| 0.8223 | 33.33 | 1000 | 0.5148 | 0.5686 |
| 0.5477 | 50.0 | 1500 | 0.5089 | 0.5606 |