End of training

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9622115215221093
+      value: 0.9660686103496968
 ---
 
 <!-- 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 [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the audiofolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1202
-- Accuracy: 0.9622
+- Loss: 0.0929
+- Accuracy: 0.9661
 
 ## Model description
 
@@ -67,11 +67,11 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.1929        | 1.0   | 532  | 0.1905          | 0.9402   |
-| 0.1862        | 2.0   | 1064 | 0.1467          | 0.9523   |
-| 0.1205        | 3.0   | 1596 | 0.1325          | 0.9578   |
-| 0.1128        | 4.0   | 2129 | 0.1279          | 0.9598   |
-| 0.1176        | 5.0   | 2660 | 0.1202          | 0.9622   |
+| 0.1867        | 1.0   | 564  | 0.1825          | 0.9286   |
+| 0.1732        | 2.0   | 1129 | 0.1284          | 0.9505   |
+| 0.1493        | 3.0   | 1693 | 0.1088          | 0.9588   |
+| 0.1064        | 4.0   | 2258 | 0.1011          | 0.9636   |
+| 0.115         | 5.0   | 2820 | 0.0929          | 0.9661   |
 
 
 ### Framework versions