Update README.md

README.md

@@ -90,6 +90,7 @@ predicted_ids = torch.argmax(logits, dim=-1)
 print("Prediction:", processor.batch_decode(predicted_ids))
 print("Reference:", test_dataset["sentence"][:2])
 ```
+
 ## Evaluation
 The model can be evaluated as follows on the Turkish test data of Common Voice. 
 ```python
@@ -103,10 +104,8 @@ wer = load_metric("wer")
 processor = Wav2Vec2Processor.from_pretrained("gorkemgoknar/wav2vec2-large-xlsr-53-turkish") 
 model = Wav2Vec2ForCTC.from_pretrained("gorkemgoknar/wav2vec2-large-xlsr-53-turkish") 
 model.to("cuda")
-
-#Note: Not ignoring "'"  on this one 
-chars_to_ignore_regex = '[\,\?\.\!\-\;\:\"\“\%\‘\”\�\#\>\<\_\’\[\]\{\}]'
-
+# Note: Not ignoring "'"  on this one 
+chars_to_ignore_regex = '[\\,\\?\\.\\!\\-\\;\\:\\"\\“\\%\\‘\\”\\�\\#\\>\\<\\_\\’\\[\\]\\{\\}]'
 resampler = torchaudio.transforms.Resample(48_000, 16_000)
 # Preprocessing the datasets.
 # We need to read the aduio files as arrays