Training completed!

README.md

@@ -23,10 +23,10 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9205
+      value: 0.9245
     - name: F1
       type: f1
-      value: 0.9203433558731255
+      value: 0.9245690662037136
 ---
 
 <!-- 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: 0.2202
-- Accuracy: 0.9205
-- F1: 0.9203
+- Loss: 0.2192
+- Accuracy: 0.9245
+- F1: 0.9246
 
 ## Model description
 
@@ -69,8 +69,8 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 0.8689        | 1.0   | 250  | 0.3324          | 0.899    | 0.8969 |
-| 0.2595        | 2.0   | 500  | 0.2202          | 0.9205   | 0.9203 |
+| 0.8375        | 1.0   | 250  | 0.3221          | 0.907    | 0.9059 |
+| 0.255         | 2.0   | 500  | 0.2192          | 0.9245   | 0.9246 |
 
 
 ### Framework versions