Model save

README.md

@@ -24,13 +24,13 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.6343582887700535
+      value: 0.9966577540106952
     - name: Precision
       type: precision
-      value: 0.7715676584335054
+      value: 0.9966586895563994
     - name: Recall
       type: recall
-      value: 0.6343582887700535
+      value: 0.9966577540106952
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -40,11 +40,11 @@ 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: 3.3036
-- Accuracy: 0.6344
-- Precision: 0.7716
-- Recall: 0.6344
-- Confusion Matrix: [[1498, 14], [1080, 400]]
+- Loss: 0.0154
+- Accuracy: 0.9967
+- Precision: 0.9967
+- Recall: 0.9967
+- Confusion Matrix: [[1506, 6], [4, 1476]]
 
 ## Model description
 
@@ -76,11 +76,11 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | Confusion Matrix          |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:-------------------------:|
-| 0.1263        | 1.0   | 374  | 1.1458          | 0.7309   | 0.8125    | 0.7309 | [[1493, 19], [786, 694]]  |
-| 0.0301        | 2.0   | 748  | 3.0924          | 0.6330   | 0.7754    | 0.6330 | [[1502, 10], [1088, 392]] |
-| 0.0467        | 3.0   | 1122 | 3.3036          | 0.6344   | 0.7716    | 0.6344 | [[1498, 14], [1080, 400]] |
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | Confusion Matrix        |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:-----------------------:|
+| 0.0568        | 1.0   | 374  | 0.0186          | 0.9940   | 0.9940    | 0.9940 | [[1500, 12], [6, 1474]] |
+| 0.0516        | 2.0   | 748  | 0.0191          | 0.9960   | 0.9960    | 0.9960 | [[1504, 8], [4, 1476]]  |
+| 0.0719        | 3.0   | 1122 | 0.0154          | 0.9967   | 0.9967    | 0.9967 | [[1506, 6], [4, 1476]]  |
 
 
 ### Framework versions