Model save

README.md

@@ -20,7 +20,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9425649095200629
+      value: 0.9512195121951219
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -30,17 +30,17 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model was trained from scratch on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1359
-- Accuracy: 0.9426
-- Weighted f1: 0.9426
-- Micro f1: 0.9426
-- Macro f1: 0.9386
-- Weighted recall: 0.9426
-- Micro recall: 0.9426
-- Macro recall: 0.9404
-- Weighted precision: 0.9440
-- Micro precision: 0.9426
-- Macro precision: 0.9382
+- Loss: 0.1182
+- Accuracy: 0.9512
+- Weighted f1: 0.9515
+- Micro f1: 0.9512
+- Macro f1: 0.9473
+- Weighted recall: 0.9512
+- Micro recall: 0.9512
+- Macro recall: 0.9498
+- Weighted precision: 0.9527
+- Micro precision: 0.9512
+- Macro precision: 0.9458
 
 ## Model description
 
@@ -74,9 +74,9 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted f1 | Micro f1 | Macro f1 | Weighted recall | Micro recall | Macro recall | Weighted precision | Micro precision | Macro precision |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|:------------:|:------------------:|:---------------:|:---------------:|
-| 0.3093        | 0.98  | 38   | 0.2252          | 0.8891   | 0.8879      | 0.8891   | 0.8820   | 0.8891          | 0.8891       | 0.8738       | 0.8952             | 0.8891          | 0.8994          |
-| 0.2278        | 1.99  | 77   | 0.1648          | 0.9292   | 0.9292      | 0.9292   | 0.9220   | 0.9292          | 0.9292       | 0.9221       | 0.9310             | 0.9292          | 0.9241          |
-| 0.2066        | 2.94  | 114  | 0.1359          | 0.9426   | 0.9426      | 0.9426   | 0.9386   | 0.9426          | 0.9426       | 0.9404       | 0.9440             | 0.9426          | 0.9382          |
+| 0.1916        | 0.98  | 38   | 0.1396          | 0.9461   | 0.9465      | 0.9461   | 0.9408   | 0.9461          | 0.9461       | 0.9427       | 0.9487             | 0.9461          | 0.9412          |
+| 0.1597        | 1.99  | 77   | 0.1227          | 0.9520   | 0.9523      | 0.9520   | 0.9485   | 0.9520          | 0.9520       | 0.9515       | 0.9541             | 0.9520          | 0.9472          |
+| 0.1722        | 2.94  | 114  | 0.1182          | 0.9512   | 0.9515      | 0.9512   | 0.9473   | 0.9512          | 0.9512       | 0.9498       | 0.9527             | 0.9512          | 0.9458          |
 
 
 ### Framework versions