Training completed!

README.md

@@ -23,10 +23,10 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.924
+      value: 0.922
     - name: F1
       type: f1
-      value: 0.9239410287844312
+      value: 0.9222071075426412
 ---
 
 <!-- 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 [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the emotion dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2150
-- Accuracy: 0.924
-- F1: 0.9239
+- Loss: 0.2170
+- Accuracy: 0.922
+- F1: 0.9222
 
 ## Model description
 
@@ -69,8 +69,8 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 0.8269        | 1.0   | 250  | 0.3180          | 0.908    | 0.9071 |
-| 0.2514        | 2.0   | 500  | 0.2150          | 0.924    | 0.9239 |
+| 0.8318        | 1.0   | 250  | 0.3211          | 0.9055   | 0.9047 |
+| 0.2506        | 2.0   | 500  | 0.2170          | 0.922    | 0.9222 |
 
 
 ### Framework versions