update model card README.md

README.md

@@ -15,12 +15,12 @@ should probably proofread and complete it, then remove this comment. -->
 
 # swin-tiny-patch4-window7-224-finetuned-ai-not
 
-This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the None dataset.
+This model is a fine-tuned version of [lukee/swin-tiny-patch4-window7-224-finetuned-ai-not](https://huggingface.co/lukee/swin-tiny-patch4-window7-224-finetuned-ai-not) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1248
-- Accuracy: 0.9554
-- F1: 0.9543
-- Log Loss: 1.5396
+- Loss: 0.0827
+- Accuracy: 0.9796
+- F1: 0.9794
+- Log Loss: 0.7049
 
 ## Model description
 
@@ -48,15 +48,22 @@ 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 | F1     | Log Loss |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|
-| 0.1872        | 1.0   | 131  | 0.1355          | 0.9463   | 0.9450 | 1.8550   |
-| 0.1163        | 2.0   | 262  | 0.1463          | 0.9425   | 0.9408 | 1.9848   |
-| 0.0988        | 3.0   | 393  | 0.1248          | 0.9554   | 0.9543 | 1.5396   |
+| 0.1026        | 1.0   | 131  | 0.0761          | 0.9715   | 0.9713 | 0.9831   |
+| 0.1111        | 2.0   | 262  | 0.1050          | 0.9597   | 0.9591 | 1.3912   |
+| 0.0736        | 3.0   | 393  | 0.0736          | 0.9748   | 0.9745 | 0.8718   |
+| 0.0708        | 4.0   | 524  | 0.0888          | 0.9694   | 0.9690 | 1.0573   |
+| 0.0439        | 5.0   | 655  | 0.0998          | 0.9683   | 0.9679 | 1.0944   |
+| 0.0514        | 6.0   | 786  | 0.0854          | 0.9705   | 0.9701 | 1.0202   |
+| 0.0361        | 7.0   | 917  | 0.0737          | 0.9780   | 0.9778 | 0.7605   |
+| 0.0256        | 8.0   | 1048 | 0.0764          | 0.9801   | 0.9799 | 0.6863   |
+| 0.0375        | 9.0   | 1179 | 0.0740          | 0.9785   | 0.9783 | 0.7420   |
+| 0.0257        | 10.0  | 1310 | 0.0827          | 0.9796   | 0.9794 | 0.7049   |
 
 
 ### Framework versions