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Update README.md

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@@ -86,7 +86,7 @@ processor = Wav2Vec2Processor.from_pretrained("gchhablani/wav2vec2-large-xlsr-gu
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  model = Wav2Vec2ForCTC.from_pretrained("gchhablani/wav2vec2-large-xlsr-gu")
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  model.to("cuda")
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- chars_to_ignore_regex = '[\,\?\.\!\-\;\:\"\β€œ\%\β€˜\”\οΏ½\–\…\'\_\’]'
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  resampler = torchaudio.transforms.Resample(48_000, 16_000)
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  # Preprocessing the datasets.
@@ -115,7 +115,7 @@ result = test_dataset.map(evaluate, batched=True, batch_size=8)
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  print("WER: {:2f}".format(100 * wer.compute(predictions=result["pred_strings"], references=result["sentence"])))
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  ```
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- **Test Result**: 14.53 %
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  ## Training
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  model = Wav2Vec2ForCTC.from_pretrained("gchhablani/wav2vec2-large-xlsr-gu")
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  model.to("cuda")
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+ chars_to_ignore_regex = '[\\,\\?\\.\\!\\-\\;\\:\\"\\β€œ\\%\\β€˜\\”\\οΏ½\\–\\…\\'\\_\\’]'
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  resampler = torchaudio.transforms.Resample(48_000, 16_000)
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  # Preprocessing the datasets.
 
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  print("WER: {:2f}".format(100 * wer.compute(predictions=result["pred_strings"], references=result["sentence"])))
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  ```
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+ **Test Result**: 23.55 %
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  ## Training
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