update model card README.md

README.md

@@ -21,16 +21,16 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.9557004346372451
+      value: 0.9552512940390716
     - name: Recall
       type: recall
-      value: 0.9621339616290812
+      value: 0.9628071356445641
     - name: F1
       type: f1
-      value: 0.9589064072458906
+      value: 0.9590143324113654
     - name: Accuracy
       type: accuracy
-      value: 0.9925041859740664
+      value: 0.9926599431486313
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -40,11 +40,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-dec2021](https://huggingface.co/cardiffnlp/twitter-roberta-base-dec2021) on the conll2003 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0413
-- Precision: 0.9557
-- Recall: 0.9621
-- F1: 0.9589
-- Accuracy: 0.9925
+- Loss: 0.0412
+- Precision: 0.9553
+- Recall: 0.9628
+- F1: 0.9590
+- Accuracy: 0.9927
 
 ## Model description