training completed

README.md

@@ -22,10 +22,10 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9255
+      value: 0.9225
     - name: F1
       type: f1
-      value: 0.9255619616346218
+      value: 0.9225745663022739
 ---
 
 <!-- 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: 0.2163
-- Accuracy: 0.9255
-- F1: 0.9256
+- Loss: 0.2277
+- Accuracy: 0.9225
+- F1: 0.9226
 
 ## Model description
 
@@ -68,8 +68,8 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 0.787         | 1.0   | 250  | 0.3151          | 0.901    | 0.8991 |
-| 0.2464        | 2.0   | 500  | 0.2163          | 0.9255   | 0.9256 |
+| 0.8266        | 1.0   | 250  | 0.3283          | 0.903    | 0.9009 |
+| 0.2602        | 2.0   | 500  | 0.2277          | 0.9225   | 0.9226 |
 
 
 ### Framework versions