legacy-datasets/common_voice
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How to use Maniac/wav2vec2-xls-r-60-urdu with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="Maniac/wav2vec2-xls-r-60-urdu") # Load model directly
from transformers import AutoProcessor, AutoModelForCTC
processor = AutoProcessor.from_pretrained("Maniac/wav2vec2-xls-r-60-urdu")
model = AutoModelForCTC.from_pretrained("Maniac/wav2vec2-xls-r-60-urdu", device_map="auto")YAML Metadata Error:"model-index[0].name" is not allowed to be empty
This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - UR 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 |
|---|---|---|---|---|
| 1.468 | 166.67 | 500 | 3.0262 | 1.0035 |
| 0.0572 | 333.33 | 1000 | 3.5352 | 0.9721 |
| 0.0209 | 500.0 | 1500 | 3.7266 | 0.9834 |
| 0.0092 | 666.67 | 2000 | 3.8433 | 0.9852 |