Training completed!

README.md

@@ -23,10 +23,10 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.924
+      value: 0.927
     - name: F1
       type: f1
-      value: 0.9240101271424108
+      value: 0.9269202905106245
 ---
 
 <!-- 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: 0.2195
-- Accuracy: 0.924
-- F1: 0.9240
+- Loss: 0.2158
+- Accuracy: 0.927
+- F1: 0.9269
 
 ## Model description
 
@@ -69,13 +69,13 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 0.8353        | 1.0   | 250  | 0.3211          | 0.9085   | 0.9078 |
-| 0.2527        | 2.0   | 500  | 0.2195          | 0.924    | 0.9240 |
+| 0.8289        | 1.0   | 250  | 0.3220          | 0.905    | 0.9041 |
+| 0.2507        | 2.0   | 500  | 0.2158          | 0.927    | 0.9269 |
 
 
 ### Framework versions
 
-- Transformers 4.31.0
+- Transformers 4.32.0
 - Pytorch 2.0.1+cu118
-- Datasets 2.14.3
+- Datasets 2.14.4
 - Tokenizers 0.13.3