update model card README.md

README.md

@@ -21,7 +21,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 1.0
+      value: 0.8795454545454545
 ---
 
 <!-- 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: 0.0013
-- Accuracy: 1.0
+- Loss: 0.3293
+- Accuracy: 0.8795
 
 ## Model description
 
@@ -51,7 +51,7 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 5e-05
+- learning_rate: 1e-05
 - train_batch_size: 16
 - eval_batch_size: 16
 - seed: 42
@@ -60,27 +60,18 @@ 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: 0.5
-- num_epochs: 15
+- num_epochs: 6
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.8968        | 1.0   | 55   | 1.5220          | 0.4795   |
-| 1.0158        | 2.0   | 110  | 0.6740          | 0.7386   |
-| 0.67          | 3.0   | 165  | 0.5239          | 0.8      |
-| 0.4638        | 4.0   | 220  | 0.2628          | 0.8977   |
-| 0.3936        | 5.0   | 275  | 0.1238          | 0.9568   |
-| 0.3105        | 6.0   | 330  | 0.0565          | 0.9818   |
-| 0.2625        | 7.0   | 385  | 0.1136          | 0.9568   |
-| 0.2518        | 8.0   | 440  | 0.0339          | 0.9818   |
-| 0.2099        | 9.0   | 495  | 0.0273          | 0.9909   |
-| 0.1293        | 10.0  | 550  | 0.0166          | 0.9932   |
-| 0.1565        | 11.0  | 605  | 0.0150          | 0.9966   |
-| 0.0976        | 12.0  | 660  | 0.0047          | 1.0      |
-| 0.1049        | 13.0  | 715  | 0.0047          | 0.9977   |
-| 0.0678        | 14.0  | 770  | 0.0031          | 0.9989   |
-| 0.0775        | 15.0  | 825  | 0.0013          | 1.0      |
+| 1.8498        | 1.0   | 55   | 1.7348          | 0.3273   |
+| 1.1886        | 2.0   | 110  | 1.0198          | 0.6102   |
+| 0.8636        | 3.0   | 165  | 0.6859          | 0.7398   |
+| 0.576         | 4.0   | 220  | 0.4357          | 0.8477   |
+| 0.5875        | 5.0   | 275  | 0.4188          | 0.8386   |
+| 0.4677        | 6.0   | 330  | 0.3293          | 0.8795   |
 
 
 ### Framework versions