update model card README.md

README.md

@@ -31,7 +31,7 @@ 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: 0.0076
+- Loss: 0.0013
 - Accuracy: 1.0
 
 ## Model description
@@ -51,7 +51,7 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 3e-05
+- learning_rate: 5e-05
 - train_batch_size: 16
 - eval_batch_size: 16
 - seed: 42
@@ -59,43 +59,28 @@ The following hyperparameters were used during training:
 - total_train_batch_size: 64
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- lr_scheduler_warmup_ratio: 0.05
-- num_epochs: 30
+- lr_scheduler_warmup_ratio: 0.5
+- num_epochs: 15
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.5952        | 1.0   | 55   | 0.8490          | 0.6693   |
-| 0.7582        | 2.0   | 110  | 0.4561          | 0.8386   |
-| 0.4359        | 3.0   | 165  | 0.2408          | 0.9227   |
-| 0.318         | 4.0   | 220  | 0.1294          | 0.9568   |
-| 0.2414        | 5.0   | 275  | 0.0346          | 0.9909   |
-| 0.1888        | 6.0   | 330  | 0.0419          | 0.9864   |
-| 0.1717        | 7.0   | 385  | 0.0238          | 0.9943   |
-| 0.1785        | 8.0   | 440  | 0.0230          | 0.9943   |
-| 0.1654        | 9.0   | 495  | 0.0076          | 1.0      |
-| 0.1322        | 10.0  | 550  | 0.0046          | 1.0      |
-| 0.1123        | 11.0  | 605  | 0.0035          | 1.0      |
-| 0.0953        | 12.0  | 660  | 0.0025          | 1.0      |
-| 0.0864        | 13.0  | 715  | 0.0033          | 1.0      |
-| 0.0984        | 14.0  | 770  | 0.0033          | 0.9989   |
-| 0.0952        | 15.0  | 825  | 0.0015          | 1.0      |
-| 0.0678        | 16.0  | 880  | 0.0022          | 1.0      |
-| 0.0592        | 17.0  | 935  | 0.0013          | 1.0      |
-| 0.0729        | 18.0  | 990  | 0.0037          | 0.9989   |
-| 0.0672        | 19.0  | 1045 | 0.0041          | 0.9989   |
-| 0.0615        | 20.0  | 1100 | 0.0010          | 1.0      |
-| 0.058         | 21.0  | 1155 | 0.0009          | 1.0      |
-| 0.0571        | 22.0  | 1210 | 0.0021          | 0.9989   |
-| 0.0755        | 23.0  | 1265 | 0.0022          | 0.9989   |
-| 0.0688        | 24.0  | 1320 | 0.0025          | 0.9989   |
-| 0.0417        | 25.0  | 1375 | 0.0003          | 1.0      |
-| 0.0589        | 26.0  | 1430 | 0.0007          | 1.0      |
-| 0.0563        | 27.0  | 1485 | 0.0007          | 1.0      |
-| 0.0603        | 28.0  | 1540 | 0.0010          | 0.9989   |
-| 0.0469        | 29.0  | 1595 | 0.0005          | 1.0      |
-| 0.0525        | 30.0  | 1650 | 0.0004          | 1.0      |
+| 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      |
 
 
 ### Framework versions