End of training

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9059633027522935
+      value: 0.9151376146788991
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [google/bert_uncased_L-6_H-768_A-12](https://huggingface.co/google/bert_uncased_L-6_H-768_A-12) on the glue dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2788
-- Accuracy: 0.9060
+- Loss: 0.3683
+- Accuracy: 0.9151
 
 ## Model description
 
@@ -65,13 +65,13 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.2402        | 1.0   | 527  | 0.2701          | 0.8979   |
-| 0.122         | 2.0   | 1054 | 0.2788          | 0.9060   |
-| 0.0795        | 3.0   | 1581 | 0.2892          | 0.9037   |
-| 0.0534        | 4.0   | 2108 | 0.3204          | 0.9014   |
-| 0.0362        | 5.0   | 2635 | 0.3766          | 0.9037   |
-| 0.0237        | 6.0   | 3162 | 0.4298          | 0.9048   |
-| 0.0159        | 7.0   | 3689 | 0.4998          | 0.9014   |
+| 0.2388        | 1.0   | 527  | 0.2575          | 0.9060   |
+| 0.1196        | 2.0   | 1054 | 0.2980          | 0.9002   |
+| 0.0789        | 3.0   | 1581 | 0.2825          | 0.9071   |
+| 0.0529        | 4.0   | 2108 | 0.3194          | 0.9071   |
+| 0.0364        | 5.0   | 2635 | 0.3683          | 0.9151   |
+| 0.0236        | 6.0   | 3162 | 0.4103          | 0.9094   |
+| 0.0154        | 7.0   | 3689 | 0.4751          | 0.9083   |
 
 
 ### Framework versions

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