SaraSadeghi
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Update README.md
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README.md
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@@ -76,6 +76,8 @@ print(prediction[0])
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```
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## Evaluation
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pip install datasets
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pip install transformers
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import torch
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@@ -103,6 +105,7 @@ def predict(batch):
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return_tensors="pt",
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padding=True
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)
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input_values = features.input_values
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attention_mask = features.attention_mask
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@@ -117,11 +120,9 @@ dataset = dataset.map(speech_file_to_array_fn)
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result = dataset.map(predict, batched=True, batch_size=4)
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wer = load_metric("wer")
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cer = load_metric("cer")
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print("WER: {:.2f}".format(100 * wer.compute(predictions=result["prediction"], references=result["reference"])))
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print("CER: {:.2f}".format(100 * cer.compute(predictions=result["prediction"], references=result["reference"])))
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-
For the evaluation use the code below:
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-
```python
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-
?
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```
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*Result (WER)*:
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```
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## Evaluation
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+
For the evaluation use the code below:
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```python
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pip install datasets
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pip install transformers
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import torch
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return_tensors="pt",
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padding=True
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)
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+
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input_values = features.input_values
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attention_mask = features.attention_mask
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result = dataset.map(predict, batched=True, batch_size=4)
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wer = load_metric("wer")
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cer = load_metric("cer")
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print("WER: {:.2f}".format(100 * wer.compute(predictions=result["prediction"], references=result["reference"])))
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print("CER: {:.2f}".format(100 * cer.compute(predictions=result["prediction"], references=result["reference"])))
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```
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*Result (WER)*:
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