Model save

README.md

@@ -25,16 +25,16 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9983008958912574
+      value: 0.9578378378378378
     - name: Precision
       type: precision
-      value: 1.0
+      value: 0.9542200618647813
     - name: Recall
       type: recall
-      value: 0.9979676674364896
+      value: 0.9974133949191686
     - name: F1
       type: f1
-      value: 0.9989828000739782
+      value: 0.9753387533875338
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -44,12 +44,12 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0052
-- Accuracy: 0.9983
-- Precision: 1.0
-- Recall: 0.9980
-- F1: 0.9990
-- Roc Auc: 1.0000
+- Loss: 0.1068
+- Accuracy: 0.9578
+- Precision: 0.9542
+- Recall: 0.9974
+- F1: 0.9753
+- Roc Auc: 0.9904
 
 ## Model description
 
@@ -83,7 +83,7 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Roc Auc |
 |:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|
-| 0.0172        | 0.9975 | 202  | 0.0052          | 0.9983   | 1.0       | 0.9980 | 0.9990 | 1.0000  |
+| 0.1402        | 0.9975 | 202  | 0.1068          | 0.9578   | 0.9542    | 0.9974 | 0.9753 | 0.9904  |
 
 
 ### Framework versions