update model card README.md

README.md

@@ -23,10 +23,10 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.8848039215686274
+      value: 0.8676470588235294
     - name: F1
       type: f1
-      value: 0.919104991394148
+      value: 0.9028776978417268
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -36,9 +36,9 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [neuralmind/bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) on the glue-ptpt dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.7884
-- Accuracy: 0.8848
-- F1: 0.9191
+- Loss: 1.2267
+- Accuracy: 0.8676
+- F1: 0.9029
 
 ## Model description
 
@@ -69,9 +69,16 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 0.1866        | 1.09  | 500  | 0.5935          | 0.8775   | 0.9104 |
-| 0.1791        | 2.18  | 1000 | 0.6557          | 0.8676   | 0.9062 |
-| 0.0676        | 3.27  | 1500 | 0.7884          | 0.8848   | 0.9191 |
+| No log        | 1.0   | 459  | 0.7241          | 0.8603   | 0.9012 |
+| 0.0658        | 2.0   | 918  | 0.7902          | 0.8725   | 0.9071 |
+| 0.1499        | 3.0   | 1377 | 0.7895          | 0.8676   | 0.9022 |
+| 0.0654        | 4.0   | 1836 | 0.9841          | 0.8676   | 0.9036 |
+| 0.018         | 5.0   | 2295 | 1.0520          | 0.8627   | 0.8989 |
+| 0.0144        | 6.0   | 2754 | 1.1002          | 0.8725   | 0.9081 |
+| 0.007         | 7.0   | 3213 | 1.1303          | 0.8652   | 0.9005 |
+| 0.0056        | 8.0   | 3672 | 1.2298          | 0.8725   | 0.9081 |
+| 0.0019        | 9.0   | 4131 | 1.2353          | 0.8701   | 0.9038 |
+| 0.0001        | 10.0  | 4590 | 1.2267          | 0.8676   | 0.9029 |
 
 
 ### Framework versions