update model card README.md

README.md

@@ -21,7 +21,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9995570321151717
+      value: 0.9805094130675526
 ---
 
 <!-- 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/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0011
-- Accuracy: 0.9996
+- Loss: 0.0474
+- Accuracy: 0.9805
 
 ## Model description
 
@@ -51,7 +51,7 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 5e-05
+- learning_rate: 0.0005
 - train_batch_size: 16
 - eval_batch_size: 16
 - seed: 42
@@ -66,11 +66,11 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.0508        | 0.99  | 93   | 0.0634          | 0.9756   |
-| 0.0909        | 1.99  | 187  | 0.0222          | 0.9911   |
-| 0.0641        | 3.0   | 281  | 0.0228          | 0.9914   |
-| 0.0717        | 4.0   | 375  | 0.0050          | 0.9982   |
-| 0.0012        | 4.96  | 465  | 0.0011          | 0.9996   |
+| 0.2312        | 0.99  | 93   | 0.1822          | 0.9453   |
+| 0.3817        | 1.99  | 187  | 0.2106          | 0.9183   |
+| 0.2217        | 3.0   | 281  | 0.1902          | 0.9285   |
+| 0.1667        | 4.0   | 375  | 0.1127          | 0.9584   |
+| 0.0572        | 4.96  | 465  | 0.0474          | 0.9805   |
 
 
 ### Framework versions