Model save

README.md

@@ -23,10 +23,10 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.592
+      value: 0.608
     - name: F1
       type: f1
-      value: 0.4602437417654809
+      value: 0.5096170704866357
 ---
 
 <!-- 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 [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.8401
-- Accuracy: 0.592
-- F1: 0.4602
+- Loss: 0.7362
+- Accuracy: 0.608
+- F1: 0.5096
 
 ## Model description
 
@@ -69,12 +69,12 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 3.5336        | 5.0   | 20   | 2.5430          | 0.472    | 0.2688 |
-| 1.952         | 10.0  | 40   | 1.4687          | 0.576    | 0.3690 |
-| 1.3471        | 15.0  | 60   | 1.2750          | 0.584    | 0.3858 |
-| 1.2688        | 20.0  | 80   | 1.2295          | 0.576    | 0.3823 |
-| 1.1444        | 25.0  | 100  | 0.9876          | 0.592    | 0.3849 |
-| 0.9511        | 30.0  | 120  | 0.8401          | 0.592    | 0.4602 |
+| 3.2255        | 5.0   | 20   | 1.9574          | 0.512    | 0.3083 |
+| 1.3773        | 10.0  | 40   | 0.8854          | 0.584    | 0.4617 |
+| 0.869         | 15.0  | 60   | 0.7880          | 0.608    | 0.4795 |
+| 0.7966        | 20.0  | 80   | 0.7732          | 0.6      | 0.4846 |
+| 0.8458        | 25.0  | 100  | 0.7795          | 0.576    | 0.4112 |
+| 0.8135        | 30.0  | 120  | 0.7362          | 0.608    | 0.5096 |
 
 
 ### Framework versions