update model card README.md

README.md

@@ -21,7 +21,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9497354497354498
+      value: 0.9801587301587301
 ---
 
 <!-- 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 [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.9702
-- Accuracy: 0.9497
+- Loss: 0.3394
+- Accuracy: 0.9802
 
 ## Model description
 
@@ -60,14 +60,17 @@ 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: 2
+- num_epochs: 5
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.5256        | 0.98  | 33   | 1.3147          | 0.9180   |
-| 0.9811        | 1.98  | 66   | 0.9702          | 0.9497   |
+| 0.7076        | 0.98  | 33   | 0.6119          | 0.9696   |
+| 0.4469        | 1.98  | 66   | 0.4190          | 0.9788   |
+| 0.3497        | 2.98  | 99   | 0.3555          | 0.9788   |
+| 0.3048        | 3.98  | 132  | 0.3394          | 0.9802   |
+| 0.2983        | 4.98  | 165  | 0.3394          | 0.9802   |
 
 
 ### Framework versions