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bliebfl
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swin-tiny-patch4-window7-224-finetuned-kuzushiji

Image Classification
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swin
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  1. README.md +13 -13
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@@ -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: 0.9676750216076059
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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 [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/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: 0.1772
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- - Accuracy: 0.9677
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  ## Model description
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@@ -67,16 +67,16 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 0.7629 | 1.0 | 406 | 0.3326 | 0.9312 |
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- | 0.8118 | 2.0 | 813 | 0.2958 | 0.9450 |
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- | 0.7189 | 3.0 | 1220 | 0.2502 | 0.9516 |
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- | 0.7529 | 4.0 | 1627 | 0.2301 | 0.9566 |
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- | 0.6746 | 5.0 | 2033 | 0.2146 | 0.9575 |
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- | 0.546 | 6.0 | 2440 | 0.2027 | 0.9609 |
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- | 0.5983 | 7.0 | 2847 | 0.1919 | 0.9640 |
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- | 0.5653 | 8.0 | 3254 | 0.1862 | 0.9653 |
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- | 0.5361 | 9.0 | 3660 | 0.1815 | 0.9659 |
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- | 0.5017 | 9.98 | 4060 | 0.1772 | 0.9677 |
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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: 0.9718236819360415
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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 [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/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: 0.1356
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+ - Accuracy: 0.9718
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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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+ | 0.5595 | 1.0 | 406 | 0.1957 | 0.9628 |
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+ | 0.6314 | 2.0 | 813 | 0.1814 | 0.9654 |
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+ | 0.5433 | 3.0 | 1220 | 0.1723 | 0.9658 |
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+ | 0.488 | 4.0 | 1627 | 0.1588 | 0.9677 |
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+ | 0.5789 | 5.0 | 2033 | 0.1572 | 0.9689 |
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+ | 0.4526 | 6.0 | 2440 | 0.1496 | 0.9701 |
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+ | 0.4538 | 7.0 | 2847 | 0.1447 | 0.9708 |
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+ | 0.447 | 8.0 | 3254 | 0.1414 | 0.9710 |
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+ | 0.3809 | 9.0 | 3660 | 0.1385 | 0.9715 |
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+ | 0.4515 | 9.98 | 4060 | 0.1356 | 0.9718 |
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  ### Framework versions