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Update README.md

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  1. README.md +5 -5
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@@ -50,8 +50,8 @@ model-index:
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  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 15 dataset.
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  It achieves the following results on the evaluation set:
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- - Wer: 13.9913
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- - Cer: 5.8844
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@@ -67,8 +67,8 @@ test_dataset = load_dataset("mozilla-foundation/common_voice_13_0", "hi", split=
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  wer = load_metric("wer")
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  cer = load_metric("cer")
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- processor = WhisperProcessor.from_pretrained("kingabzpro/whisper-small-hi-cv")
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- model = WhisperForConditionalGeneration.from_pretrained("kingabzpro/whisper-small-hi-cv").to("cuda")
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  test_dataset = test_dataset.cast_column("audio", Audio(sampling_rate=16000))
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  def map_to_pred(batch):
@@ -89,5 +89,5 @@ print("CER: {:2f}".format(100 * cer.compute(predictions=result["prediction"], re
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  ```
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  ```bash
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  WER: 23.1361
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- CER: 10.4366
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  ```
 
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  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 15 dataset.
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  It achieves the following results on the evaluation set:
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+ - Wer: 14.0178
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+ - Cer: 05.8824
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  wer = load_metric("wer")
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  cer = load_metric("cer")
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+ processor = WhisperProcessor.from_pretrained("SakshiRathi77/whisper-hindi-kagglex")
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+ model = WhisperForConditionalGeneration.from_pretrained("SakshiRathi77/whisper-hindi-kagglex").to("cuda")
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  test_dataset = test_dataset.cast_column("audio", Audio(sampling_rate=16000))
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  def map_to_pred(batch):
 
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  ```
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  ```bash
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  WER: 23.1361
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+ CER: 10.4366
93
  ```