update model card README.md

README.md

@@ -21,7 +21,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9722507708119219
+      value: 0.9753340184994861
 ---
 
 <!-- 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/swinv2-large-patch4-window12to16-192to256-22kto1k-ft](https://huggingface.co/microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0966
-- Accuracy: 0.9723
+- Loss: 0.0909
+- Accuracy: 0.9753
 
 ## Model description
 
@@ -51,31 +51,33 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 1e-05
+- learning_rate: 5e-06
 - train_batch_size: 16
 - eval_batch_size: 16
 - seed: 42
-- gradient_accumulation_steps: 4
-- total_train_batch_size: 64
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- lr_scheduler_warmup_ratio: 0.5
-- num_epochs: 10
+- lr_scheduler_warmup_ratio: 0.9
+- num_epochs: 12
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.9035        | 1.0   | 61   | 1.8946          | 0.2713   |
-| 1.4731        | 2.0   | 122  | 1.2931          | 0.5560   |
-| 0.9549        | 3.0   | 183  | 0.7530          | 0.6999   |
-| 0.7375        | 4.0   | 244  | 0.4989          | 0.8129   |
-| 0.615         | 5.0   | 305  | 0.3545          | 0.8746   |
-| 0.4751        | 6.0   | 366  | 0.2399          | 0.9168   |
-| 0.3778        | 7.0   | 427  | 0.1628          | 0.9558   |
-| 0.3054        | 8.0   | 488  | 0.1202          | 0.9620   |
-| 0.2787        | 9.0   | 549  | 0.0988          | 0.9733   |
-| 0.253         | 10.0  | 610  | 0.0966          | 0.9723   |
+| 2.0236        | 1.0   | 122  | 1.9878          | 0.1305   |
+| 1.88          | 2.0   | 244  | 1.7957          | 0.2867   |
+| 1.5421        | 3.0   | 366  | 1.3813          | 0.5149   |
+| 0.9489        | 4.0   | 488  | 0.9015          | 0.7030   |
+| 0.8734        | 5.0   | 610  | 0.6616          | 0.7667   |
+| 0.6562        | 6.0   | 732  | 0.5095          | 0.8140   |
+| 0.5788        | 7.0   | 854  | 0.4036          | 0.8520   |
+| 0.6737        | 8.0   | 976  | 0.3157          | 0.8921   |
+| 0.4687        | 9.0   | 1098 | 0.2146          | 0.9281   |
+| 0.3775        | 10.0  | 1220 | 0.2020          | 0.9353   |
+| 0.3226        | 11.0  | 1342 | 0.1549          | 0.9558   |
+| 0.2452        | 12.0  | 1464 | 0.0909          | 0.9753   |
 
 
 ### Framework versions