update model card README.md

README.md

@@ -19,7 +19,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.6862635831707997
+      value: 0.7220674282529953
 ---
 
 <!-- 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: 0.8497
-- Accuracy: 0.6863
+- Loss: 0.7881
+- Accuracy: 0.7221
 
 ## Model description
 
@@ -58,15 +58,22 @@ 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: 10
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.1607        | 1.0   | 224  | 1.0029          | 0.6239   |
-| 1.0262        | 2.0   | 448  | 0.9090          | 0.6612   |
-| 0.9666        | 3.0   | 672  | 0.8497          | 0.6863   |
+| 1.2307        | 1.0   | 224  | 1.0863          | 0.5874   |
+| 1.0893        | 2.0   | 448  | 0.9700          | 0.6362   |
+| 1.0244        | 3.0   | 672  | 0.8859          | 0.6757   |
+| 1.016         | 4.0   | 896  | 0.8804          | 0.6787   |
+| 0.9089        | 5.0   | 1120 | 0.8611          | 0.6897   |
+| 0.8935        | 6.0   | 1344 | 0.8283          | 0.7028   |
+| 0.8403        | 7.0   | 1568 | 0.8116          | 0.7102   |
+| 0.8179        | 8.0   | 1792 | 0.7934          | 0.7166   |
+| 0.7764        | 9.0   | 2016 | 0.7865          | 0.7208   |
+| 0.771         | 10.0  | 2240 | 0.7881          | 0.7221   |
 
 
 ### Framework versions