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README.md
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@@ -23,7 +23,7 @@ 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-lg
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@@ -56,7 +56,7 @@ def speech_file_to_array_fn(batch):
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return batch
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test_dataset = test_dataset.map(speech_file_to_array_fn)
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inputs = processor(test_dataset["speech"]
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with torch.no_grad():
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logits = model(inputs.input_values, attention_mask=inputs.attention_mask).logits
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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: 30.23
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---
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# Wav2Vec2-Large-XLSR-53-lg
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return batch
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test_dataset = test_dataset.map(speech_file_to_array_fn)
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inputs = processor(test_dataset[:2]["speech"], sampling_rate=16_000, return_tensors="pt", padding=True)
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with torch.no_grad():
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logits = model(inputs.input_values, attention_mask=inputs.attention_mask).logits
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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**: 30.23 %
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## Training
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