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bombshelll
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swin-brain-abnormalities-classification

Image Classification
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swin
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  2. model.safetensors +1 -1
README.md CHANGED
@@ -18,8 +18,8 @@ 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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1960
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- - Accuracy: 0.8983
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  ## Model description
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@@ -53,26 +53,31 @@ 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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- | 1.2657 | 0.8 | 2 | 0.9887 | 0.4746 |
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- | 0.6946 | 2.0 | 5 | 0.7099 | 0.7458 |
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- | 0.9218 | 2.8 | 7 | 0.6812 | 0.7458 |
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- | 0.5285 | 4.0 | 10 | 0.6193 | 0.7458 |
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- | 0.7932 | 4.8 | 12 | 0.5760 | 0.7458 |
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- | 0.4643 | 6.0 | 15 | 0.5008 | 0.7458 |
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- | 0.6529 | 6.8 | 17 | 0.4584 | 0.7627 |
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- | 0.415 | 8.0 | 20 | 0.3877 | 0.8305 |
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- | 0.4994 | 8.8 | 22 | 0.3337 | 0.8814 |
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- | 0.2865 | 10.0 | 25 | 0.2837 | 0.8983 |
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- | 0.3765 | 10.8 | 27 | 0.2686 | 0.8983 |
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- | 0.2434 | 12.0 | 30 | 0.2400 | 0.8983 |
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- | 0.2945 | 12.8 | 32 | 0.2282 | 0.8983 |
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- | 0.2019 | 14.0 | 35 | 0.2115 | 0.8983 |
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- | 0.3041 | 14.8 | 37 | 0.2084 | 0.8983 |
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- | 0.1708 | 16.0 | 40 | 0.2003 | 0.8983 |
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- | 0.2602 | 16.8 | 42 | 0.2007 | 0.8983 |
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- | 0.1499 | 18.0 | 45 | 0.1952 | 0.8983 |
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- | 0.2706 | 18.8 | 47 | 0.1970 | 0.8983 |
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- | 0.1809 | 20.0 | 50 | 0.1960 | 0.8983 |
 
 
 
 
 
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  ### Framework versions
 
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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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2291
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+ - Accuracy: 0.9262
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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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+ | 1.2609 | 1.0 | 6 | 0.9906 | 0.6779 |
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+ | 0.8038 | 2.0 | 12 | 0.6710 | 0.7718 |
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+ | 0.7211 | 3.0 | 18 | 0.5718 | 0.7785 |
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+ | 0.5931 | 4.0 | 24 | 0.4404 | 0.8255 |
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+ | 0.4773 | 5.0 | 30 | 0.3184 | 0.8859 |
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+ | 0.4233 | 6.0 | 36 | 0.2672 | 0.9396 |
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+ | 0.3331 | 7.0 | 42 | 0.2489 | 0.9262 |
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+ | 0.2819 | 8.0 | 48 | 0.2307 | 0.9396 |
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+ | 0.2437 | 9.0 | 54 | 0.2180 | 0.9262 |
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+ | 0.2231 | 10.0 | 60 | 0.2301 | 0.9128 |
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+ | 0.2023 | 11.0 | 66 | 0.1972 | 0.9262 |
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+ | 0.1873 | 12.0 | 72 | 0.2396 | 0.9128 |
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+ | 0.1627 | 13.0 | 78 | 0.1933 | 0.9262 |
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+ | 0.1372 | 14.0 | 84 | 0.2708 | 0.9195 |
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+ | 0.1559 | 15.0 | 90 | 0.2443 | 0.9128 |
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+ | 0.1455 | 16.0 | 96 | 0.2369 | 0.9195 |
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+ | 0.1064 | 17.0 | 102 | 0.2470 | 0.9128 |
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+ | 0.1152 | 18.0 | 108 | 0.2397 | 0.9128 |
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+ | 0.0994 | 19.0 | 114 | 0.2626 | 0.9128 |
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+ | 0.1046 | 20.0 | 120 | 0.2738 | 0.9195 |
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+ | 0.1056 | 21.0 | 126 | 0.2384 | 0.9195 |
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+ | 0.0902 | 22.0 | 132 | 0.2373 | 0.9195 |
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+ | 0.0735 | 23.0 | 138 | 0.2268 | 0.9329 |
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+ | 0.096 | 24.0 | 144 | 0.2240 | 0.9329 |
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+ | 0.1087 | 25.0 | 150 | 0.2291 | 0.9262 |
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  ### Framework versions
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