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Safawat
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Electrcical-IMAGE-finetuned-eurosat

Image Classification
Transformers
TensorBoard
Safetensors
swin
Generated from Trainer
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  1. README.md +23 -23
  2. model.safetensors +1 -1
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: 0.8787128712871287
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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: 0.3505
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- - Accuracy: 0.8787
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  ## Model description
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@@ -67,26 +67,26 @@ 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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- | 1.5532 | 0.98 | 28 | 1.1704 | 0.6163 |
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- | 0.8115 | 2.0 | 57 | 0.6827 | 0.7673 |
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- | 0.5513 | 2.98 | 85 | 0.4525 | 0.8416 |
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- | 0.455 | 4.0 | 114 | 0.4012 | 0.8540 |
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- | 0.3901 | 4.98 | 142 | 0.3824 | 0.8614 |
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- | 0.4042 | 6.0 | 171 | 0.3797 | 0.8639 |
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- | 0.3591 | 6.98 | 199 | 0.3505 | 0.8787 |
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- | 0.2989 | 8.0 | 228 | 0.3551 | 0.8614 |
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- | 0.3029 | 8.98 | 256 | 0.3625 | 0.8663 |
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- | 0.2606 | 10.0 | 285 | 0.3615 | 0.8490 |
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- | 0.2413 | 10.98 | 313 | 0.3435 | 0.8787 |
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- | 0.2051 | 12.0 | 342 | 0.3371 | 0.8663 |
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- | 0.2477 | 12.98 | 370 | 0.3451 | 0.8639 |
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- | 0.2271 | 14.0 | 399 | 0.3364 | 0.8738 |
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- | 0.2112 | 14.98 | 427 | 0.3559 | 0.8639 |
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- | 0.1902 | 16.0 | 456 | 0.3630 | 0.8738 |
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- | 0.1739 | 16.98 | 484 | 0.3630 | 0.8713 |
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- | 0.195 | 18.0 | 513 | 0.3625 | 0.8663 |
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- | 0.1621 | 18.98 | 541 | 0.3571 | 0.8762 |
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- | 0.154 | 19.65 | 560 | 0.3555 | 0.8738 |
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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: 0.8861386138613861
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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: 0.3726
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+ - Accuracy: 0.8861
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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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+ | 1.6143 | 0.98 | 28 | 1.2882 | 0.5347 |
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+ | 0.8597 | 2.0 | 57 | 0.7302 | 0.7649 |
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+ | 0.5858 | 2.98 | 85 | 0.4849 | 0.8465 |
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+ | 0.4332 | 4.0 | 114 | 0.4274 | 0.8614 |
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+ | 0.4054 | 4.98 | 142 | 0.3687 | 0.8787 |
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+ | 0.3826 | 6.0 | 171 | 0.3788 | 0.8614 |
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+ | 0.3561 | 6.98 | 199 | 0.3700 | 0.8936 |
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+ | 0.2838 | 8.0 | 228 | 0.3550 | 0.8812 |
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+ | 0.2897 | 8.98 | 256 | 0.3698 | 0.8886 |
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+ | 0.2519 | 10.0 | 285 | 0.3459 | 0.8837 |
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+ | 0.2194 | 10.98 | 313 | 0.3583 | 0.8960 |
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+ | 0.1955 | 12.0 | 342 | 0.3442 | 0.8886 |
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+ | 0.2443 | 12.98 | 370 | 0.3801 | 0.8787 |
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+ | 0.207 | 14.0 | 399 | 0.3499 | 0.8861 |
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+ | 0.2078 | 14.98 | 427 | 0.3701 | 0.8837 |
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+ | 0.1873 | 16.0 | 456 | 0.3773 | 0.8861 |
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+ | 0.1697 | 16.98 | 484 | 0.3753 | 0.8861 |
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+ | 0.1812 | 18.0 | 513 | 0.3747 | 0.8911 |
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+ | 0.151 | 18.98 | 541 | 0.3736 | 0.8861 |
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+ | 0.1567 | 19.65 | 560 | 0.3726 | 0.8861 |
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  ### Framework versions
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