update model card README.md

README.md

@@ -24,16 +24,16 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.7949828178694158
+      value: 0.9545986426398315
     - name: Recall
       type: recall
-      value: 0.8113207547169812
+      value: 0.9557169634489222
     - name: F1
       type: f1
-      value: 0.8030686985802062
+      value: 0.955157475705421
     - name: Accuracy
       type: accuracy
-      value: 0.9595964075839893
+      value: 0.9883703228112445
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -43,11 +43,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [klue/roberta-base](https://huggingface.co/klue/roberta-base) on the klue dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1434
-- Precision: 0.7950
-- Recall: 0.8113
-- F1: 0.8031
-- Accuracy: 0.9596
+- Loss: 0.0487
+- Precision: 0.9546
+- Recall: 0.9557
+- F1: 0.9552
+- Accuracy: 0.9884
 
 ## Model description
 
@@ -78,9 +78,9 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.1526        | 1.0   | 2626 | 0.1732          | 0.7105    | 0.7480 | 0.7288 | 0.9450   |
-| 0.1019        | 2.0   | 5252 | 0.1395          | 0.7717    | 0.7894 | 0.7804 | 0.9566   |
-| 0.0728        | 3.0   | 7878 | 0.1434          | 0.7950    | 0.8113 | 0.8031 | 0.9596   |
+| 0.0449        | 1.0   | 2626 | 0.0601          | 0.9361    | 0.9176 | 0.9267 | 0.9830   |
+| 0.0262        | 2.0   | 5252 | 0.0469          | 0.9484    | 0.9510 | 0.9497 | 0.9874   |
+| 0.0144        | 3.0   | 7878 | 0.0487          | 0.9546    | 0.9557 | 0.9552 | 0.9884   |
 
 
 ### Framework versions