Training completed.

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9365
+      value: 0.9415
 ---
 
 <!-- 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: 0.1650
-- Accuracy: 0.9365
+- Loss: 0.1508
+- Accuracy: 0.9415
 
 ## Model description
 
@@ -64,11 +64,11 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| No log        | 1.0   | 250  | 0.1920          | 0.9255   |
-| 0.338         | 2.0   | 500  | 0.1590          | 0.936    |
-| 0.338         | 3.0   | 750  | 0.1571          | 0.9335   |
-| 0.0858        | 4.0   | 1000 | 0.1527          | 0.9415   |
-| 0.0858        | 5.0   | 1250 | 0.1650          | 0.9365   |
+| No log        | 1.0   | 250  | 0.1900          | 0.932    |
+| 0.3456        | 2.0   | 500  | 0.1357          | 0.936    |
+| 0.3456        | 3.0   | 750  | 0.1391          | 0.9445   |
+| 0.0865        | 4.0   | 1000 | 0.1422          | 0.9455   |
+| 0.0865        | 5.0   | 1250 | 0.1508          | 0.9415   |
 
 
 ### Framework versions

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:84c27d52594bf1be2a311ec6f870a24883a33c544da2f302f7f34479969e7f53
+oid sha256:992aeb236ef86a4c9765b902e360358c7babc738a6963e5c51cd51e26905fbf5
 size 267844872