Update README.md

README.md

@@ -69,7 +69,7 @@ model = Wav2Vec2ForCTC.from_pretrained("gorkemgoknar/wav2vec2-large-xlsr-53-turk
 model.to("cuda")
 
 #Note: Not ignoring "'"  on this one 
-chars_to_ignore_regex = '[\\\\\\\\,\\\\\\\\?\\\\\\\\.\\\\\\\\!\\\\\\\\-\\\\\\\\;\\\\\\\\:\\\\\\\\"\\\\\\\\“\\\\\\\\%\\\\\\\\‘\\\\\\\\”\\\\\\\\�]'
+chars_to_ignore_regex = '[\\\\\\\\\\\\\\\\,\\\\\\\\\\\\\\\\?\\\\\\\\\\\\\\\\.\\\\\\\\\\\\\\\\!\\\\\\\\\\\\\\\\-\\\\\\\\\\\\\\\\;\\\\\\\\\\\\\\\\:\\\\\\\\\\\\\\\\"\\\\\\\\\\\\\\\\“\\\\\\\\\\\\\\\\%\\\\\\\\\\\\\\\\‘\\\\\\\\\\\\\\\\”\\\\\\\\\\\\\\\\�]'
 
 resampler = torchaudio.transforms.Resample(48_000, 16_000)
 # Preprocessing the datasets.
@@ -95,4 +95,3 @@ print("WER: {:2f}".format(100 * wer.compute(predictions=result["pred_strings"],
 **Test Result**: TBD %  
 ## Training
 The Common Voice `train` and `validation` datasets were used for training. Additional 5 Turkish movies with subtitles also used 
-The script used for training can be found [here](https://colab.research.google.com/drive/1hesw9z_kFFINT93jBvGuFspOLrHx10AE?usp=sharing)