Training completed!

README.md

@@ -23,10 +23,10 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9225
+      value: 0.923
     - name: F1
       type: f1
-      value: 0.9219461308150362
+      value: 0.92304659943046
 ---
 
 <!-- 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: 0.2232
-- Accuracy: 0.9225
-- F1: 0.9219
+- Loss: 0.2302
+- Accuracy: 0.923
+- F1: 0.9230
 
 ## Model description
 
@@ -69,13 +69,13 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 0.8269        | 1.0   | 250  | 0.3225          | 0.906    | 0.9046 |
-| 0.2546        | 2.0   | 500  | 0.2232          | 0.9225   | 0.9219 |
+| 0.8433        | 1.0   | 250  | 0.3194          | 0.911    | 0.9105 |
+| 0.2605        | 2.0   | 500  | 0.2302          | 0.923    | 0.9230 |
 
 
 ### Framework versions
 
-- Transformers 4.32.1
-- Pytorch 2.0.1+cu118
-- Datasets 2.14.4
-- Tokenizers 0.13.3
+- Transformers 4.41.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

runs/Jul07_05-34-23_7a56ca70b1a8/events.out.tfevents.1720330464.7a56ca70b1a8.1481.1

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