legacy-datasets/common_voice
Updated • 949 • 147
How to use Umer4/UrduAudio2Text with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="Umer4/UrduAudio2Text") # Load model directly
from transformers import AutoProcessor, AutoModelForCTC
processor = AutoProcessor.from_pretrained("Umer4/UrduAudio2Text")
model = AutoModelForCTC.from_pretrained("Umer4/UrduAudio2Text", 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 |
|---|---|---|---|---|
| 5.5558 | 15.98 | 400 | 1.4978 | 0.8376 |