Update README.md

README.md

@@ -11,9 +11,31 @@ metrics:
 - accuracy
 model-index:
 - name: camelbert-ner-arabic
-  results: []
+  results: 
+  - task: 
+      name: Named Entity Recognition
+      type: token-classification
+    dataset:
+      name: WikiAnn Arabic
+      type: unimelb-nlp/wikiann
+    metrics:
+      - name: Precision
+        type: precision
+        value: 0.8884
+      - name: Recall
+        type: recall
+        value: 0.8955
+      - name: F1
+        type: f1
+        value: 0.8919
+      - name: Accuracy
+        type: accuracy
+        value: 0.9513
 datasets:
 - unimelb-nlp/wikiann
+language:
+- ar
+pipeline_tag: token-classification
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -34,7 +56,7 @@ It achieves the following results on the evaluation set:
 - **Base Model:** CAMeL-Lab/bert-base-arabic-camelbert-mix
 - **Task:** Named Entity Recognition (NER)
 - **Language:** Arabic
-- **Training Data:** WikiAnn (PanX) dataset for Arabic
+- **Training Data:** WikiAnn dataset for Arabic
 
 
 ## Training procedure