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README.md

@@ -23,10 +23,10 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9225
+      value: 0.9245
     - name: F1
       type: f1
-      value: 0.9226136286799401
+      value: 0.9244352025262078
 ---
 
 <!-- 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: 0.2209
-- Accuracy: 0.9225
-- F1: 0.9226
+- Loss: 0.2137
+- Accuracy: 0.9245
+- F1: 0.9244
 
 ## Model description
 
@@ -69,13 +69,13 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 0.8278        | 1.0   | 250  | 0.3228          | 0.9075   | 0.9065 |
-| 0.2483        | 2.0   | 500  | 0.2209          | 0.9225   | 0.9226 |
+| 0.8045        | 1.0   | 250  | 0.3023          | 0.91     | 0.9094 |
+| 0.2388        | 2.0   | 500  | 0.2137          | 0.9245   | 0.9244 |
 
 
 ### Framework versions
 
-- Transformers 4.39.3
-- Pytorch 2.2.2+cu118
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
 - Datasets 2.18.0
 - Tokenizers 0.15.2