Update README.md

README.md

@@ -21,7 +21,7 @@ model-index:
     metrics:
        - name: Test WER
          type: wer
-         value:  26.156584
+         value:  25.284593
 ---
 
 # wav2vec2-large-xlsr-53-German
@@ -96,7 +96,7 @@ from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor
 
 import re
 
-test_dataset = load_dataset("common_voice", "de", split="test[:10%]")
+test_dataset = load_dataset("common_voice", "de", split="test[:15%]")
 
 wer = load_metric("wer")
 
@@ -106,7 +106,7 @@ model = Wav2Vec2ForCTC.from_pretrained("MehdiHosseiniMoghadam/wav2vec2-large-xls
 
 model.to("cuda")
 
-chars_to_ignore_regex = '[\\,\\?\\.\\!\\-\\;\\:\\"\\“\\%\\‘\\”\\�]'
+chars_to_ignore_regex = '[\,\?\.\!\-\;\:\"\“\%\‘\”\�]'
 
 resampler = torchaudio.transforms.Resample(48_000, 16_000)
 
@@ -166,7 +166,7 @@ print("WER: {:2f}".format(100 * wer.compute(predictions=result["pred_strings"],
 
 ```
 
-**Test Result**:  26.156584 %
+**Test Result**:  25.284593 %
 
 ## Training
 
@@ -174,4 +174,4 @@ print("WER: {:2f}".format(100 * wer.compute(predictions=result["pred_strings"],
 
 ## Testing
 
-10% of the Common Voice `Test` dataset were used for training.
+15% of the Common Voice `Test` dataset were used for training.