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segformer-class-classWeights-augmentation

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update model card README.md

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@@ -21,7 +21,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.9545454545454546
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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
@@ -31,8 +31,8 @@ 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: 0.0927
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- - Accuracy: 0.9545
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  ## Model description
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@@ -66,16 +66,16 @@ 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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- | No log | 0.96 | 6 | 0.9944 | 0.4773 |
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- | 1.0159 | 1.92 | 12 | 0.6948 | 0.75 |
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- | 1.0159 | 2.88 | 18 | 0.3417 | 0.9318 |
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- | 0.5444 | 4.0 | 25 | 0.2642 | 0.9091 |
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- | 0.2331 | 4.96 | 31 | 0.0986 | 0.9545 |
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- | 0.2331 | 5.92 | 37 | 0.1735 | 0.9545 |
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- | 0.2596 | 6.88 | 43 | 0.1091 | 0.9545 |
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- | 0.1737 | 8.0 | 50 | 0.0685 | 0.9545 |
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- | 0.1737 | 8.96 | 56 | 0.0995 | 0.9545 |
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- | 0.1716 | 9.6 | 60 | 0.0927 | 0.9545 |
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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: 0.9772727272727273
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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: 0.0991
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+ - Accuracy: 0.9773
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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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+ | No log | 0.96 | 6 | 1.0191 | 0.6364 |
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+ | 1.0551 | 1.92 | 12 | 0.8644 | 0.7273 |
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+ | 1.0551 | 2.88 | 18 | 0.5563 | 0.8636 |
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+ | 0.7192 | 4.0 | 25 | 0.2687 | 0.9545 |
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+ | 0.4056 | 4.96 | 31 | 0.1921 | 0.9545 |
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+ | 0.4056 | 5.92 | 37 | 0.1246 | 0.9545 |
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+ | 0.267 | 6.88 | 43 | 0.1010 | 0.9773 |
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+ | 0.2547 | 8.0 | 50 | 0.1442 | 0.9773 |
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+ | 0.2547 | 8.96 | 56 | 0.1188 | 0.9773 |
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+ | 0.189 | 9.6 | 60 | 0.0991 | 0.9773 |
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  ### Framework versions