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swinv2-tiny-patch4-window8-256-dmae-va-U5-42B

Image Classification
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swinv2
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  1. README.md +40 -40
  2. model.safetensors +1 -1
  3. runs/Apr19_07-34-21_DESKTOP-SKBE9FB/events.out.tfevents.1713533662.DESKTOP-SKBE9FB.5900.0 +2 -2
README.md CHANGED
@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.8386
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- - Accuracy: 0.65
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  ## Model description
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@@ -52,44 +52,44 @@ 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 | 0.9 | 7 | 6.1748 | 0.1167 |
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- | 5.327 | 1.94 | 15 | 6.0660 | 0.1167 |
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- | 5.327 | 2.97 | 23 | 5.4902 | 0.1167 |
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- | 5.0963 | 4.0 | 31 | 4.2768 | 0.1167 |
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- | 3.9193 | 4.9 | 38 | 3.0013 | 0.1167 |
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- | 3.9193 | 5.94 | 46 | 1.9289 | 0.1167 |
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- | 2.2222 | 6.97 | 54 | 1.3857 | 0.1167 |
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- | 1.4465 | 8.0 | 62 | 1.3423 | 0.4333 |
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- | 1.4465 | 8.9 | 69 | 1.2786 | 0.45 |
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- | 1.3709 | 9.94 | 77 | 1.2654 | 0.4667 |
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- | 1.3511 | 10.97 | 85 | 1.2605 | 0.4667 |
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- | 1.3511 | 12.0 | 93 | 1.2184 | 0.4667 |
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- | 1.2749 | 12.9 | 100 | 1.2894 | 0.5 |
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- | 1.222 | 13.94 | 108 | 1.2072 | 0.5167 |
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- | 1.222 | 14.97 | 116 | 1.1749 | 0.5167 |
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- | 1.1668 | 16.0 | 124 | 1.1988 | 0.5167 |
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- | 1.1668 | 16.9 | 131 | 1.2306 | 0.5167 |
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- | 1.101 | 17.94 | 139 | 1.1432 | 0.5333 |
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- | 1.029 | 18.97 | 147 | 1.0208 | 0.55 |
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- | 1.029 | 20.0 | 155 | 0.9577 | 0.6167 |
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- | 0.9403 | 20.9 | 162 | 0.9479 | 0.5 |
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- | 0.8887 | 21.94 | 170 | 0.8910 | 0.5833 |
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- | 0.8887 | 22.97 | 178 | 0.9442 | 0.5333 |
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- | 0.8506 | 24.0 | 186 | 0.8923 | 0.6 |
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- | 0.8064 | 24.9 | 193 | 0.8973 | 0.6 |
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- | 0.8064 | 25.94 | 201 | 0.9079 | 0.55 |
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- | 0.7434 | 26.97 | 209 | 0.8386 | 0.65 |
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- | 0.7404 | 28.0 | 217 | 0.8645 | 0.6167 |
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- | 0.7404 | 28.9 | 224 | 0.8599 | 0.5667 |
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- | 0.7215 | 29.94 | 232 | 0.8420 | 0.65 |
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- | 0.6743 | 30.97 | 240 | 0.8553 | 0.5667 |
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- | 0.6743 | 32.0 | 248 | 0.8355 | 0.6167 |
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- | 0.6767 | 32.9 | 255 | 0.8694 | 0.5833 |
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- | 0.6767 | 33.94 | 263 | 0.8559 | 0.65 |
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- | 0.6606 | 34.97 | 271 | 0.8351 | 0.6167 |
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- | 0.6488 | 36.0 | 279 | 0.8287 | 0.6333 |
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- | 0.6488 | 36.9 | 286 | 0.8377 | 0.6167 |
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- | 0.6544 | 37.94 | 294 | 0.8406 | 0.6 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.8899
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+ - Accuracy: 0.6
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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 | 0.9 | 7 | 7.8663 | 0.1167 |
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+ | 6.936 | 1.94 | 15 | 7.7572 | 0.1167 |
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+ | 6.936 | 2.97 | 23 | 7.1790 | 0.1167 |
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+ | 6.7016 | 4.0 | 31 | 5.9033 | 0.1167 |
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+ | 5.5439 | 4.9 | 38 | 4.6116 | 0.1167 |
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+ | 5.5439 | 5.94 | 46 | 3.2830 | 0.1167 |
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+ | 3.6477 | 6.97 | 54 | 2.2014 | 0.1167 |
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+ | 2.2506 | 8.0 | 62 | 1.5647 | 0.45 |
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+ | 2.2506 | 8.9 | 69 | 1.3160 | 0.45 |
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+ | 1.5088 | 9.94 | 77 | 1.3676 | 0.3333 |
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+ | 1.3868 | 10.97 | 85 | 1.3390 | 0.45 |
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+ | 1.3868 | 12.0 | 93 | 1.3223 | 0.3833 |
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+ | 1.351 | 12.9 | 100 | 1.3156 | 0.45 |
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+ | 1.3271 | 13.94 | 108 | 1.3485 | 0.4833 |
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+ | 1.3271 | 14.97 | 116 | 1.2646 | 0.4833 |
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+ | 1.2322 | 16.0 | 124 | 1.2308 | 0.4833 |
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+ | 1.2322 | 16.9 | 131 | 1.2160 | 0.5 |
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+ | 1.22 | 17.94 | 139 | 1.2015 | 0.5 |
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+ | 1.1899 | 18.97 | 147 | 1.2008 | 0.5 |
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+ | 1.1899 | 20.0 | 155 | 1.1606 | 0.5 |
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+ | 1.109 | 20.9 | 162 | 1.1182 | 0.5667 |
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+ | 1.0603 | 21.94 | 170 | 1.0855 | 0.5333 |
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+ | 1.0603 | 22.97 | 178 | 1.0763 | 0.5667 |
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+ | 1.0264 | 24.0 | 186 | 1.1153 | 0.5833 |
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+ | 1.0086 | 24.9 | 193 | 1.0770 | 0.65 |
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+ | 1.0086 | 25.94 | 201 | 1.0041 | 0.6167 |
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+ | 0.9301 | 26.97 | 209 | 0.9637 | 0.6667 |
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+ | 0.9077 | 28.0 | 217 | 0.9824 | 0.5833 |
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+ | 0.9077 | 28.9 | 224 | 0.9485 | 0.6 |
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+ | 0.8725 | 29.94 | 232 | 0.9294 | 0.6167 |
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+ | 0.8203 | 30.97 | 240 | 0.9348 | 0.6167 |
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+ | 0.8203 | 32.0 | 248 | 0.9295 | 0.6 |
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+ | 0.8211 | 32.9 | 255 | 0.9167 | 0.6 |
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+ | 0.8211 | 33.94 | 263 | 0.9281 | 0.5833 |
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+ | 0.7916 | 34.97 | 271 | 0.8803 | 0.6333 |
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+ | 0.7822 | 36.0 | 279 | 0.8785 | 0.6333 |
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+ | 0.7822 | 36.9 | 286 | 0.8906 | 0.6 |
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+ | 0.7937 | 37.94 | 294 | 0.8899 | 0.6 |
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  ### Framework versions
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