Update README.md

README.md

@@ -9,6 +9,24 @@ metrics:
 pipeline_tag: automatic-speech-recognition
 base_model:
 - jonatasgrosman/wav2vec2-large-xlsr-53-russian
+
+model-index:
+  - name: wav2vec2-aed-macedonian-asr
+    results:
+      - task:
+          name: Automatic Speech Recognition
+          type: automatic-speech-recognition
+        dataset:
+          name: Macedonian Common Voice V.18.0
+          type: macedonian-common-voice-v.18.0
+        metrics:
+          - name: Test WER
+            type: test-wer
+            value: 5.66
+          - name: Test CER
+            type: test-cer
+            value: 1.43
+
 ---
 
 # Fine-tuned XLSR-53-russian large model for speech recognition in Macedonian
@@ -35,25 +53,6 @@ In training of the model, we used the following data sources:
 
 This model is an attention-based encoder-decoder (AED). The encoder is a Wav2vec2 model and the decoder is RNN-based.
 
-## Results
----
-model-index:
-  - name: wav2vec2-aed-macedonian-asr
-    results:
-      - task:
-          type: speech recognition
-        dataset:
-          name: Macedonian Common Voice V.18.0
-          type: Macedonian Common Voice V.18.0
-        metrics:
-          - name: WER
-            type: WER
-            value: 64.59
-          - name: CER
-            type: CER
-            value: 64.59
----
-
 
 ## Usage