update model card README.md

README.md

@@ -20,10 +20,10 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.92
+      value: 0.937
     - name: F1
       type: f1
-      value: 0.920013063298419
+      value: 0.9372331942198677
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -33,9 +33,9 @@ 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: 0.2215
-- Accuracy: 0.92
-- F1: 0.9200
+- Loss: 0.1413
+- Accuracy: 0.937
+- F1: 0.9372
 
 ## Model description
 
@@ -60,14 +60,17 @@ 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: 2
+- num_epochs: 5
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 0.8248        | 1.0   | 250  | 0.3126          | 0.905    | 0.9018 |
-| 0.2477        | 2.0   | 500  | 0.2215          | 0.92     | 0.9200 |
+| 0.7628        | 1.0   | 250  | 0.2489          | 0.9155   | 0.9141 |
+| 0.2014        | 2.0   | 500  | 0.1716          | 0.928    | 0.9283 |
+| 0.1351        | 3.0   | 750  | 0.1456          | 0.937    | 0.9374 |
+| 0.1046        | 4.0   | 1000 | 0.1440          | 0.9355   | 0.9349 |
+| 0.0877        | 5.0   | 1250 | 0.1413          | 0.937    | 0.9372 |
 
 
 ### Framework versions