Librarian Bot: Add base_model information to model

README.md

@@ -5,49 +5,49 @@ metrics:
 - f1
 - precision
 - recall
+pipeline_tag: token-classification
+widget:
+- text: Jacob Collier is a Grammy awarded artist from England.
+  example_title: NER Example 1
+base_model: microsoft/deberta-v3-large
 model-index:
 - name: tner/deberta-v3-large-ontonotes5
   results:
   - task:
-      name: Token Classification
       type: token-classification
+      name: Token Classification
     dataset:
       name: tner/ontonotes5
       type: tner/ontonotes5
       args: tner/ontonotes5
     metrics:
-    - name: F1
-      type: f1
+    - type: f1
       value: 0.9069623608411381
-    - name: Precision
-      type: precision
+      name: F1
+    - type: precision
       value: 0.902100360312857
-    - name: Recall
-      type: recall
+      name: Precision
+    - type: recall
       value: 0.9118770542773386
-    - name: F1 (macro)
-      type: f1_macro
+      name: Recall
+    - type: f1_macro
       value: 0.834586960779896
-    - name: Precision (macro)
-      type: precision_macro
+      name: F1 (macro)
+    - type: precision_macro
       value: 0.8237351069457466
-    - name: Recall (macro)
-      type: recall_macro
+      name: Precision (macro)
+    - type: recall_macro
       value: 0.8475169311172334
-    - name: F1 (entity span)
-      type: f1_entity_span
+      name: Recall (macro)
+    - type: f1_entity_span
       value: 0.9267538434352359
-    - name: Precision (entity span)
-      type: precision_entity_span
+      name: F1 (entity span)
+    - type: precision_entity_span
       value: 0.9217857456718517
-    - name: Recall (entity span)
-      type: recall_entity_span
+      name: Precision (entity span)
+    - type: recall_entity_span
       value: 0.9317757839566492
-
-pipeline_tag: token-classification
-widget:
-- text: "Jacob Collier is a Grammy awarded artist from England."
-  example_title: "NER Example 1"
+      name: Recall (entity span)
 ---
 # tner/deberta-v3-large-ontonotes5