updated numbers for no_PC WERs based on conversion bug

README.md

@@ -35,7 +35,7 @@ model-index:
     metrics:
     - name: Test WER
       type: wer
-      value: 4.93
+      value: 5.1
   - task:
       type: Automatic Speech Recognition
       name: automatic-speech-recognition
@@ -49,7 +49,7 @@ model-index:
     metrics:
     - name: Test WER
       type: wer
-      value: 3.8
+      value: 3.87
   - task:
       type: Automatic Speech Recognition
       name: automatic-speech-recognition
@@ -63,7 +63,7 @@ model-index:
     metrics:
     - name: Test WER
       type: wer
-      value: 8.6
+      value: 8.88
   - task:
       name: Automatic Speech Recognition
       type: automatic-speech-recognition
@@ -206,7 +206,7 @@ The following tables summarizes the performance of the available models in this
 a) On data without Punctuation and Capitalization with Transducer decoder
 | **Version** |     **Tokenizer**     | **Vocabulary Size** | **MCV12 DEV** | **MCV12 TEST** | **MLS DEV** | **MLS TEST** | **VOXPOPULI DEV** | **VOXPOPULI TEST** |
 |:-----------:|:---------------------:|:-------------------:|:-------------:|:--------------:|:-----------:|:------------:|:-----------------:|:------------------:|
-|    1.18.0    | SentencePiece Unigram |         1024        |      4.18     |      4.93      |     3.3     |      3.8     |        10.8       |         8.6        |
+|    1.18.0    | SentencePiece Unigram |         1024        |      4.36     |      5.1      |     3.33     |      3.87     |        11.03       |         8.88        |
 
 
 b) On data with Punctuation and Capitalization with Transducer decoder