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mansee
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swin-tiny-patch4-window7-224-img_orientation

Image Classification
Transformers
PyTorch
swin
Generated from Trainer
Eval Results
Inference Endpoints
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  1. README.md +13 -13
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.9661252256004442
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [mansee/swin-tiny-patch4-window7-224](https://huggingface.co/mansee/swin-tiny-patch4-window7-224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1087
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- - Accuracy: 0.9661
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 0.5043 | 1.0 | 506 | 0.3764 | 0.8426 |
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- | 0.3557 | 2.0 | 1013 | 0.2068 | 0.9245 |
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- | 0.315 | 3.0 | 1519 | 0.1581 | 0.9442 |
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- | 0.2674 | 4.0 | 2026 | 0.1468 | 0.9490 |
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- | 0.2615 | 5.0 | 2532 | 0.1245 | 0.9561 |
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- | 0.2115 | 6.0 | 3039 | 0.1236 | 0.9560 |
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- | 0.2121 | 7.0 | 3545 | 0.1144 | 0.9624 |
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- | 0.2053 | 8.0 | 4052 | 0.1143 | 0.9614 |
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- | 0.1576 | 9.0 | 4558 | 0.1087 | 0.9661 |
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- | 0.2054 | 9.99 | 5060 | 0.1086 | 0.9657 |
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  ### Framework versions
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9644592530889907
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  This model is a fine-tuned version of [mansee/swin-tiny-patch4-window7-224](https://huggingface.co/mansee/swin-tiny-patch4-window7-224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1069
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+ - Accuracy: 0.9645
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.5605 | 1.0 | 506 | 0.3984 | 0.8341 |
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+ | 0.3828 | 2.0 | 1013 | 0.1944 | 0.9271 |
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+ | 0.3092 | 3.0 | 1519 | 0.1862 | 0.9339 |
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+ | 0.3234 | 4.0 | 2026 | 0.1415 | 0.9510 |
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+ | 0.2471 | 5.0 | 2532 | 0.1355 | 0.9517 |
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+ | 0.251 | 6.0 | 3039 | 0.1170 | 0.9606 |
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+ | 0.2276 | 7.0 | 3545 | 0.1136 | 0.9627 |
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+ | 0.2182 | 8.0 | 4052 | 0.1121 | 0.9628 |
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+ | 0.1386 | 9.0 | 4558 | 0.1116 | 0.9632 |
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+ | 0.1466 | 9.99 | 5060 | 0.1069 | 0.9645 |
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  ### Framework versions