WER
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README.md
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@@ -22,7 +22,7 @@ model-index:
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metrics:
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- name: Test WER
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type: wer
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value:
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---
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# Wav2Vec2-Large-XLSR-53-German
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@@ -140,7 +140,7 @@ 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**:
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## Training
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metrics:
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- name: Test WER
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type: wer
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value: 15.93
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---
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# Wav2Vec2-Large-XLSR-53-German
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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**: 15.93 %
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## Training
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