update model card README.md

README.md

@@ -22,10 +22,10 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9285
+      value: 0.937
     - name: F1
       type: f1
-      value: 0.9287004068581184
+      value: 0.9371930654030473
 ---
 
 <!-- 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 [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the emotion dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1656
-- Accuracy: 0.9285
-- F1: 0.9287
+- Loss: 0.1698
+- Accuracy: 0.937
+- F1: 0.9372
 
 ## Model description
 
@@ -62,15 +62,17 @@ The following hyperparameters were used during training:
 - seed: 42
 - 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     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 0.7873        | 1.0   | 250  | 0.2724          | 0.9155   | 0.9145 |
-| 0.2141        | 2.0   | 500  | 0.1850          | 0.9265   | 0.9268 |
-| 0.1473        | 3.0   | 750  | 0.1656          | 0.9285   | 0.9287 |
+| 0.1395        | 1.0   | 250  | 0.1659          | 0.9355   | 0.9358 |
+| 0.0945        | 2.0   | 500  | 0.1657          | 0.935    | 0.9351 |
+| 0.0783        | 3.0   | 750  | 0.1832          | 0.937    | 0.9371 |
+| 0.0653        | 4.0   | 1000 | 0.1729          | 0.9335   | 0.9332 |
+| 0.053         | 5.0   | 1250 | 0.1698          | 0.937    | 0.9372 |
 
 
 ### Framework versions