update model card README.md

README.md

@@ -24,16 +24,16 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9911764705882353
+      value: 0.9977843426883308
     - name: F1
       type: f1
-      value: 0.9923273657289001
+      value: 0.9984067976633033
     - name: Recall
       type: recall
-      value: 0.9948717948717949
+      value: 0.9978768577494692
     - name: Precision
       type: precision
-      value: 0.9897959183673469
+      value: 0.9989373007438895
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -43,11 +43,11 @@ 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: 0.0484
-- Accuracy: 0.9912
-- F1: 0.9923
-- Recall: 0.9949
-- Precision: 0.9898
+- Loss: 0.0101
+- Accuracy: 0.9978
+- F1: 0.9984
+- Recall: 0.9979
+- Precision: 0.9989
 
 ## Model description
 
@@ -81,15 +81,15 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Recall | Precision |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
-| 0.3405        | 1.0   | 24   | 0.1137          | 0.9647   | 0.9688 | 0.9538 | 0.9841    |
-| 0.2449        | 2.0   | 48   | 0.0811          | 0.9735   | 0.9766 | 0.9641 | 0.9895    |
-| 0.1713        | 3.0   | 72   | 0.0613          | 0.9794   | 0.9818 | 0.9692 | 0.9947    |
-| 0.1615        | 4.0   | 96   | 0.0484          | 0.9912   | 0.9923 | 0.9949 | 0.9898    |
+| 0.1884        | 1.0   | 95   | 0.0706          | 0.9705   | 0.9787 | 0.9756 | 0.9818    |
+| 0.1134        | 2.0   | 190  | 0.0364          | 0.9889   | 0.9920 | 0.9883 | 0.9957    |
+| 0.1031        | 3.0   | 285  | 0.0116          | 0.9963   | 0.9973 | 0.9947 | 1.0       |
+| 0.0746        | 4.0   | 380  | 0.0101          | 0.9978   | 0.9984 | 0.9979 | 0.9989    |
 
 
 ### Framework versions
 
 - Transformers 4.23.1
-- Pytorch 1.12.1+cu113
+- Pytorch 1.12.1
 - Datasets 2.6.1
 - Tokenizers 0.13.1