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Yogesh1p
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swin-tiny-patch4-window7-224-finetuned-eurosat

Image Classification
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  1. README.md +13 -13
  2. model.safetensors +1 -1
  3. runs/Nov17_09-35-47_5aafc1ba1313/events.out.tfevents.1700213853.5aafc1ba1313.3404.1 +2 -2
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: 0.7777777777777778
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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: 0.5789
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- - Accuracy: 0.7778
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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 | 0.92 | 3 | 0.8976 | 0.6 |
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- | No log | 1.85 | 6 | 0.9456 | 0.4889 |
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- | No log | 2.77 | 9 | 0.7695 | 0.6222 |
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- | 0.8575 | 4.0 | 13 | 0.5789 | 0.7778 |
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- | 0.8575 | 4.92 | 16 | 0.5423 | 0.7333 |
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- | 0.8575 | 5.85 | 19 | 0.5269 | 0.7111 |
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- | 0.5728 | 6.77 | 22 | 0.4836 | 0.7556 |
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- | 0.5728 | 8.0 | 26 | 0.4813 | 0.7556 |
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- | 0.5728 | 8.92 | 29 | 0.4823 | 0.7556 |
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- | 0.504 | 9.23 | 30 | 0.4821 | 0.7556 |
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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: 0.8666666666666667
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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: 0.3718
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+ - Accuracy: 0.8667
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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 | 0.92 | 3 | 0.6033 | 0.6889 |
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+ | No log | 1.85 | 6 | 0.5412 | 0.7111 |
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+ | No log | 2.77 | 9 | 0.4459 | 0.7778 |
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+ | 0.5428 | 4.0 | 13 | 0.4544 | 0.8444 |
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+ | 0.5428 | 4.92 | 16 | 0.3929 | 0.9111 |
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+ | 0.5428 | 5.85 | 19 | 0.3823 | 0.8667 |
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+ | 0.4248 | 6.77 | 22 | 0.3531 | 0.8889 |
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+ | 0.4248 | 8.0 | 26 | 0.3560 | 0.8889 |
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+ | 0.4248 | 8.92 | 29 | 0.3694 | 0.8667 |
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+ | 0.382 | 9.23 | 30 | 0.3718 | 0.8667 |
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  ### Framework versions
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