update model card README.md

README.md

@@ -21,7 +21,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.4017094017094017
+      value: 0.782051282051282
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -31,8 +31,8 @@ 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: 1.4448
-- Accuracy: 0.4017
+- Loss: 0.5657
+- Accuracy: 0.7821
 
 ## Model description
 
@@ -60,15 +60,32 @@ The following hyperparameters were used during training:
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 3
+- num_epochs: 20
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 2.0067        | 0.97  | 16   | 1.7825          | 0.2393   |
-| 1.6122        | 2.0   | 33   | 1.4736          | 0.4274   |
-| 1.5137        | 2.91  | 48   | 1.4448          | 0.4017   |
+| 2.1465        | 0.97  | 16   | 1.8341          | 0.3462   |
+| 1.7722        | 2.0   | 33   | 1.5865          | 0.4017   |
+| 1.6005        | 2.97  | 49   | 1.4867          | 0.4060   |
+| 1.429         | 4.0   | 66   | 1.3933          | 0.4487   |
+| 1.2294        | 4.97  | 82   | 1.2696          | 0.5385   |
+| 1.1224        | 6.0   | 99   | 1.2842          | 0.5641   |
+| 0.9776        | 6.97  | 115  | 0.9923          | 0.6197   |
+| 0.8678        | 8.0   | 132  | 1.1118          | 0.6368   |
+| 0.8125        | 8.97  | 148  | 0.8974          | 0.6624   |
+| 0.7022        | 10.0  | 165  | 0.8582          | 0.6838   |
+| 0.6047        | 10.97 | 181  | 0.7019          | 0.7393   |
+| 0.6223        | 12.0  | 198  | 0.6818          | 0.7308   |
+| 0.5331        | 12.97 | 214  | 0.8265          | 0.7051   |
+| 0.4995        | 14.0  | 231  | 0.6365          | 0.7521   |
+| 0.4132        | 14.97 | 247  | 0.6585          | 0.7308   |
+| 0.3978        | 16.0  | 264  | 0.5789          | 0.7692   |
+| 0.3388        | 16.97 | 280  | 0.6038          | 0.7650   |
+| 0.3376        | 18.0  | 297  | 0.5306          | 0.7821   |
+| 0.3455        | 18.97 | 313  | 0.5797          | 0.7692   |
+| 0.3207        | 19.39 | 320  | 0.5657          | 0.7821   |
 
 
 ### Framework versions