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README.md

@@ -23,10 +23,10 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.928
+      value: 0.9285
     - name: F1
       type: f1
-      value: 0.9280127121050973
+      value: 0.9285492269076098
 ---
 
 <!-- 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: 0.2160
-- Accuracy: 0.928
-- F1: 0.9280
+- Loss: 0.2136
+- Accuracy: 0.9285
+- F1: 0.9285
 
 ## Model description
 
@@ -69,13 +69,13 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 0.8381        | 1.0   | 250  | 0.3050          | 0.9125   | 0.9117 |
-| 0.2529        | 2.0   | 500  | 0.2160          | 0.928    | 0.9280 |
+| 0.8193        | 1.0   | 250  | 0.3166          | 0.909    | 0.9083 |
+| 0.2489        | 2.0   | 500  | 0.2136          | 0.9285   | 0.9285 |
 
 
 ### Framework versions
 
-- Transformers 4.40.1
-- Pytorch 2.1.0+cu118
-- Datasets 2.18.0
+- Transformers 4.40.2
+- Pytorch 1.13.1+cu117
+- Datasets 2.19.1
 - Tokenizers 0.19.1