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  1. README.md +11 -11
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@@ -24,13 +24,13 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.8993647609495152
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  - name: Precision
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  type: precision
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- value: 0.914936979126043
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  - name: Recall
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  type: recall
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- value: 0.8993647609495152
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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
@@ -40,11 +40,11 @@ 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: 0.2879
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- - Accuracy: 0.8994
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- - Precision: 0.9149
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- - Recall: 0.8994
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- - Confusion Matrix: [[1506, 5], [296, 1184]]
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  ## Model description
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@@ -78,9 +78,9 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | Confusion Matrix |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------------------------:|
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- | 0.0727 | 1.0 | 374 | 0.2915 | 0.9057 | 0.9199 | 0.9057 | [[1508, 3], [279, 1201]] |
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- | 0.0635 | 2.0 | 748 | 0.1764 | 0.9305 | 0.9379 | 0.9305 | [[1505, 6], [202, 1278]] |
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- | 0.0396 | 3.0 | 1122 | 0.2879 | 0.8994 | 0.9149 | 0.8994 | [[1506, 5], [296, 1184]] |
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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: 0.9883021390374331
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  - name: Precision
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  type: precision
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+ value: 0.9883071765108582
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  - name: Recall
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  type: recall
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+ value: 0.9883021390374331
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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: 0.0394
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+ - Accuracy: 0.9883
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+ - Precision: 0.9883
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+ - Recall: 0.9883
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+ - Confusion Matrix: [[1497, 15], [20, 1460]]
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | Confusion Matrix |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------------------------:|
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+ | 0.1107 | 1.0 | 374 | 0.0641 | 0.9786 | 0.9787 | 0.9786 | [[1488, 24], [40, 1440]] |
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+ | 0.1079 | 2.0 | 748 | 0.0560 | 0.9773 | 0.9776 | 0.9773 | [[1498, 14], [54, 1426]] |
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+ | 0.0624 | 3.0 | 1122 | 0.0394 | 0.9883 | 0.9883 | 0.9883 | [[1497, 15], [20, 1460]] |
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  ### Framework versions