Model save

README.md

@@ -25,16 +25,16 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9835503925216681
+      value: 0.9825634160729682
     - name: Precision
       type: precision
-      value: 0.9834235162758739
+      value: 0.9818833850066437
     - name: Recall
       type: recall
-      value: 0.995767625231911
+      value: 0.9961009972170687
     - name: F1
       type: f1
-      value: 0.9895570759812747
+      value: 0.9889410935150342
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -44,11 +44,11 @@ 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: 0.0446
-- Accuracy: 0.9836
-- Precision: 0.9834
-- Recall: 0.9958
-- F1: 0.9896
+- Loss: 0.0478
+- Accuracy: 0.9826
+- Precision: 0.9819
+- Recall: 0.9961
+- F1: 0.9889
 - Roc Auc: 0.9989
 
 ## 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 |
 |:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|
-| 0.0406        | 0.9996 | 1377 | 0.0446          | 0.9836   | 0.9834    | 0.9958 | 0.9896 | 0.9989  |
+| 0.0428        | 0.9996 | 1377 | 0.0478          | 0.9826   | 0.9819    | 0.9961 | 0.9889 | 0.9989  |
 
 
 ### Framework versions