update model card README.md

README.md

@@ -19,7 +19,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.6819923371647509
+      value: 0.6879136189481017
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -29,8 +29,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on the image_folder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.8754
-- Accuracy: 0.6820
+- Loss: 0.8504
+- Accuracy: 0.6879
 
 ## Model description
 
@@ -58,15 +58,16 @@ 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: 4
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.1701        | 1.0   | 202  | 1.0163          | 0.6179   |
-| 1.0447        | 2.0   | 404  | 0.9237          | 0.6569   |
-| 0.9712        | 3.0   | 606  | 0.8754          | 0.6820   |
+| 1.1617        | 1.0   | 202  | 1.0081          | 0.6270   |
+| 1.0604        | 2.0   | 404  | 0.9516          | 0.6524   |
+| 0.998         | 3.0   | 606  | 0.8857          | 0.6809   |
+| 0.9971        | 4.0   | 808  | 0.8504          | 0.6879   |
 
 
 ### Framework versions