update model card README.md

README.md

@@ -22,10 +22,10 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.8676470588235294
+      value: 0.8627450980392157
     - name: F1
       type: f1
-      value: 0.9052631578947367
+      value: 0.900709219858156
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -35,9 +35,9 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on the glue dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.3588
-- Accuracy: 0.8676
-- F1: 0.9053
+- Loss: 0.5610
+- Accuracy: 0.8627
+- F1: 0.9007
 
 ## Model description
 
@@ -59,18 +59,20 @@ The following hyperparameters were used during training:
 - learning_rate: 2e-05
 - train_batch_size: 32
 - eval_batch_size: 32
-- seed: 35
+- seed: 95
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 3
+- num_epochs: 5
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| No log        | 1.0   | 115  | 0.3543          | 0.8505   | 0.8847 |
-| No log        | 2.0   | 230  | 0.3077          | 0.8725   | 0.9088 |
-| No log        | 3.0   | 345  | 0.3588          | 0.8676   | 0.9053 |
+| No log        | 1.0   | 115  | 0.3358          | 0.8676   | 0.9004 |
+| No log        | 2.0   | 230  | 0.3140          | 0.8676   | 0.9029 |
+| No log        | 3.0   | 345  | 0.3763          | 0.8897   | 0.9201 |
+| No log        | 4.0   | 460  | 0.4980          | 0.8725   | 0.9085 |
+| 0.2512        | 5.0   | 575  | 0.5610          | 0.8627   | 0.9007 |
 
 
 ### Framework versions