Training completed! (Hugging Face NLP Course)

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.935
+      value: 0.937
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +32,8 @@ 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: 0.1469
-- Accuracy: 0.935
+- Loss: 0.1411
+- Accuracy: 0.937
 
 ## Model description
 
@@ -64,13 +64,13 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| No log        | 1.0   | 250  | 0.1910          | 0.9305   |
-| 0.3349        | 2.0   | 500  | 0.1469          | 0.935    |
+| No log        | 1.0   | 250  | 0.1860          | 0.929    |
+| 0.3337        | 2.0   | 500  | 0.1411          | 0.937    |
 
 
 ### Framework versions
 
-- Transformers 4.37.0
+- Transformers 4.35.2
 - Pytorch 2.1.0+cu121
 - Datasets 2.16.1
-- Tokenizers 0.15.0
+- Tokenizers 0.15.1