Librarian Bot: Add base_model information to model

README.md

@@ -1,30 +1,31 @@
 ---
 language: ja
+license: apache-2.0
+tags:
+- audio
+- automatic-speech-recognition
+- speech
+- xlsr-fine-tuning-week
 datasets:
-  - common_voice
+- common_voice
 metrics:
-  - wer
-  - cer
-tags:
-  - audio
-  - automatic-speech-recognition
-  - speech
-  - xlsr-fine-tuning-week
-license: apache-2.0
+- wer
+- cer
+base_model: facebook/wav2vec2-large-xlsr-53
 model-index:
-  - name: Japanese XLSR Wav2Vec2 Large 53
-    results:
-      - task:
-          name: Speech Recognition
-          type: automatic-speech-recognition
-        dataset:
-          name: Common Voice ja
-          type: common_voice
-          args: ja
-        metrics:
-          - name: Test WER
-            type: wer
-            value: { wer_result_on_test } #TODO (IMPORTANT): replace {wer_result_on_test} with the WER error rate you achieved on the common_voice test set. It should be in the format XX.XX (don't add the % sign here). **Please** remember to fill out this value after you evaluated your model, so that your model appears on the leaderboard. If you fill out this model card before evaluating your model, please remember to edit the model card afterward to fill in your value
+- name: Japanese XLSR Wav2Vec2 Large 53
+  results:
+  - task:
+      type: automatic-speech-recognition
+      name: Speech Recognition
+    dataset:
+      name: Common Voice ja
+      type: common_voice
+      args: ja
+    metrics:
+    - type: wer
+      value: {}
+      name: Test WER
 ---
 
 # Wav2Vec2-Large-XLSR-53-{language} #TODO: replace language with your {language}, _e.g._ French