Model save

README.md

@@ -23,10 +23,10 @@ model-index:
     metrics:
     - name: F1
       type: f1
-      value: 0.95
+      value: 0.93
     - name: Accuracy
       type: accuracy
-      value: 0.94
+      value: 0.92
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -36,10 +36,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1643
-- F1: 0.95
-- Roc Auc: 0.96
-- Accuracy: 0.94
+- Loss: 0.1817
+- F1: 0.93
+- Roc Auc: 0.95
+- Accuracy: 0.92
 
 ## Model description
 
@@ -73,11 +73,11 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | F1   | Roc Auc | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:----:|:-------:|:--------:|
-| 0.523         | 1.0   | 122  | 0.5292          | 0.53 | 0.67    | 0.45     |
-| 0.3308        | 2.0   | 245  | 0.3331          | 0.82 | 0.86    | 0.79     |
-| 0.1989        | 3.0   | 367  | 0.2265          | 0.91 | 0.93    | 0.9      |
-| 0.1182        | 4.0   | 490  | 0.1949          | 0.92 | 0.94    | 0.92     |
-| 0.0936        | 4.98  | 610  | 0.1643          | 0.95 | 0.96    | 0.94     |
+| 0.5369        | 1.0   | 122  | 0.5339          | 0.53 | 0.67    | 0.41     |
+| 0.3995        | 2.0   | 245  | 0.3591          | 0.8  | 0.84    | 0.73     |
+| 0.2357        | 3.0   | 367  | 0.2492          | 0.89 | 0.92    | 0.88     |
+| 0.1409        | 4.0   | 490  | 0.2015          | 0.91 | 0.93    | 0.9      |
+| 0.1137        | 4.98  | 610  | 0.1817          | 0.93 | 0.95    | 0.92     |
 
 
 ### Framework versions