update model card README.md

README.md

@@ -24,16 +24,16 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.5184780231795321
+      value: 0.6037969459347916
     - name: Recall
       type: recall
-      value: 0.5445567294441892
+      value: 0.6720257234726688
     - name: F1
       type: f1
-      value: 0.5311974907583735
+      value: 0.6360869565217391
     - name: Accuracy
       type: accuracy
-      value: 0.8905679788803479
+      value: 0.9488508424567125
 ---
 
 <!-- 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 [bert-base-cased](https://huggingface.co/bert-base-cased) on the xglue dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.8429
-- Precision: 0.5185
-- Recall: 0.5446
-- F1: 0.5312
-- Accuracy: 0.8906
+- Loss: 0.2202
+- Precision: 0.6038
+- Recall: 0.6720
+- F1: 0.6361
+- Accuracy: 0.9489
 
 ## Model description
 
@@ -78,9 +78,9 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.0782        | 1.0   | 1756 | 0.6432          | 0.4982    | 0.5420 | 0.5192 | 0.8972   |
-| 0.039         | 2.0   | 3512 | 0.7474          | 0.4994    | 0.5496 | 0.5233 | 0.8908   |
-| 0.0189        | 3.0   | 5268 | 0.8429          | 0.5185    | 0.5446 | 0.5312 | 0.8906   |
+| No log        | 1.0   | 191  | 0.2359          | 0.5659    | 0.6309 | 0.5967 | 0.9397   |
+| No log        | 2.0   | 382  | 0.2136          | 0.5754    | 0.6681 | 0.6183 | 0.9464   |
+| 0.1605        | 3.0   | 573  | 0.2202          | 0.6038    | 0.6720 | 0.6361 | 0.9489   |
 
 
 ### Framework versions