Training completed!

README.md

@@ -23,10 +23,10 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.929
+      value: 0.9205
     - name: F1
       type: f1
-      value: 0.9287765318513745
+      value: 0.9200442708403018
 ---
 
 <!-- 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: 0.2110
-- Accuracy: 0.929
-- F1: 0.9288
+- Loss: 0.2206
+- Accuracy: 0.9205
+- F1: 0.9200
 
 ## Model description
 
@@ -69,13 +69,13 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 0.8022        | 1.0   | 250  | 0.3077          | 0.909    | 0.9082 |
-| 0.2491        | 2.0   | 500  | 0.2110          | 0.929    | 0.9288 |
+| 0.8268        | 1.0   | 250  | 0.3130          | 0.905    | 0.9044 |
+| 0.2529        | 2.0   | 500  | 0.2206          | 0.9205   | 0.9200 |
 
 
 ### Framework versions
 
-- Transformers 4.42.1
+- Transformers 4.37.2
 - Pytorch 2.3.0
 - Datasets 2.16.1
-- Tokenizers 0.19.1
+- Tokenizers 0.15.2