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Train-Test-Augmentation-V3D-swinv2-base

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ahmedesmail16 commited on Jun 1

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End of training

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README.md +13 -8
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@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window12-192-22k](https://huggingface.co/microsoft/swinv2-base-patch4-window12-192-22k) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.5903
-- Accuracy: 0.8165
 ## Model description
@@ -46,17 +46,22 @@ 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: 5
 ### Training results
 | Training Loss | Epoch  | Step | Validation Loss | Accuracy |
 |:-------------:|:------:|:----:|:---------------:|:--------:|
-| 1.2842        | 0.9825 | 28   | 0.7731          | 0.7538   |
-| 0.4531        | 2.0    | 57   | 0.6122          | 0.7883   |
-| 0.2334        | 2.9825 | 85   | 0.6159          | 0.8131   |
-| 0.1364        | 4.0    | 114  | 0.6249          | 0.8018   |
-| 0.0778        | 4.9123 | 140  | 0.5903          | 0.8165   |
 ### Framework versions

 This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window12-192-22k](https://huggingface.co/microsoft/swinv2-base-patch4-window12-192-22k) on an unknown dataset.
 It achieves the following results on the evaluation set:
+- Loss: 0.7725
+- Accuracy: 0.8142
 ## Model description
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 10
 ### Training results
 | Training Loss | Epoch  | Step | Validation Loss | Accuracy |
 |:-------------:|:------:|:----:|:---------------:|:--------:|
+| 1.8252        | 0.9825 | 28   | 0.9390          | 0.7273   |
+| 0.5282        | 2.0    | 57   | 0.6414          | 0.7804   |
+| 0.2556        | 2.9825 | 85   | 0.6210          | 0.7815   |
+| 0.1633        | 4.0    | 114  | 0.7030          | 0.8142   |
+| 0.0869        | 4.9825 | 142  | 0.7398          | 0.7877   |
+| 0.0524        | 6.0    | 171  | 0.8167          | 0.7962   |
+| 0.0277        | 6.9825 | 199  | 0.6993          | 0.8176   |
+| 0.0245        | 8.0    | 228  | 0.7444          | 0.8210   |
+| 0.0232        | 8.9825 | 256  | 0.8129          | 0.8142   |
+| 0.017         | 9.8246 | 280  | 0.7725          | 0.8142   |
 ### Framework versions

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