Update README.md

README.md

@@ -5,7 +5,7 @@ datasets:
 - NST Swedish ASR Database
 metrics:
 - wer
-#- cer
+- cer
 tags:
 - audio
 - automatic-speech-recognition
@@ -15,15 +15,15 @@ license: cc-by-nc-4.0
 model-index:
 - name: Wav2vec 2.0 large VoxPopuli-sv swedish
   results:
-  - task: 
-      name: Speech Recognition
-      type: automatic-speech-recognition
-    dataset:
-      name: NST Swedish ASR Database
-    metrics:
-       - name: Test WER
-         type: wer
-         value: 5.192353080009441
+#  - task: 
+#      name: Speech Recognition
+#      type: automatic-speech-recognition
+#    dataset:
+#      name: NST Swedish ASR Database
+#    metrics:
+#       - name: Test WER
+#         type: wer
+#         value: 5.192353080009441
   - task: 
       name: Speech Recognition
       type: automatic-speech-recognition
@@ -34,7 +34,10 @@ model-index:
     metrics:
        - name: Test WER
          type: wer
-         value: 17.37743757973392
+         value: 14.343744
+       - name: Test CER
+         type: cer
+         value: 4.936313
 ---
 # Wav2vec 2.0 large-voxpopuli-sv-swedish
 Finetuned version of Facebooks [VoxPopuli-sv large](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) model using NST and Common Voice data. Evalutation without a language model gives the following: WER for NST + Common Voice test set (2% of total sentences) is **5.19%**, WER for Common Voice test set is **17.38%**.