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swin-tiny-patch4-window7-224-finetuned-isic217

Image Classification
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swin
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  1. README.md +50 -50
  2. model.safetensors +1 -1
README.md CHANGED
@@ -32,7 +32,7 @@ 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: 2.5371
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  - Accuracy: 0.5
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  ## Model description
@@ -67,55 +67,55 @@ 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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- | 2.2404 | 0.9796 | 24 | 2.1527 | 0.1364 |
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- | 2.0749 | 2.0 | 49 | 2.1159 | 0.1364 |
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- | 1.947 | 2.9796 | 73 | 2.1723 | 0.1364 |
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- | 1.732 | 4.0 | 98 | 2.1545 | 0.0909 |
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- | 1.446 | 4.9796 | 122 | 2.2918 | 0.1818 |
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- | 1.1175 | 6.0 | 147 | 1.9291 | 0.3182 |
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- | 1.1069 | 6.9796 | 171 | 1.9551 | 0.3636 |
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- | 0.7932 | 8.0 | 196 | 2.0534 | 0.4091 |
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- | 0.5994 | 8.9796 | 220 | 1.8135 | 0.3636 |
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- | 0.4671 | 10.0 | 245 | 1.7822 | 0.5455 |
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- | 0.4612 | 10.9796 | 269 | 2.2530 | 0.5 |
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- | 0.4016 | 12.0 | 294 | 1.8438 | 0.4091 |
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- | 0.3947 | 12.9796 | 318 | 1.8610 | 0.5 |
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- | 0.5033 | 14.0 | 343 | 1.8615 | 0.4545 |
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- | 0.2846 | 14.9796 | 367 | 1.5479 | 0.5 |
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- | 0.2828 | 16.0 | 392 | 1.6410 | 0.5455 |
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- | 0.3426 | 16.9796 | 416 | 1.9147 | 0.3636 |
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- | 0.3108 | 18.0 | 441 | 1.4794 | 0.5455 |
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- | 0.2129 | 18.9796 | 465 | 1.7765 | 0.4091 |
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- | 0.1946 | 20.0 | 490 | 2.1665 | 0.4545 |
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- | 0.1255 | 20.9796 | 514 | 1.8522 | 0.5455 |
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- | 0.2301 | 22.0 | 539 | 2.0289 | 0.4545 |
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- | 0.0909 | 22.9796 | 563 | 2.0512 | 0.4091 |
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- | 0.1724 | 24.0 | 588 | 2.3411 | 0.4091 |
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- | 0.2256 | 24.9796 | 612 | 2.1626 | 0.5 |
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- | 0.2471 | 26.0 | 637 | 2.0552 | 0.4091 |
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- | 0.0671 | 26.9796 | 661 | 1.9339 | 0.5455 |
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- | 0.2563 | 28.0 | 686 | 2.2507 | 0.4545 |
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- | 0.1865 | 28.9796 | 710 | 2.0704 | 0.5 |
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- | 0.0477 | 30.0 | 735 | 2.8395 | 0.3182 |
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- | 0.0931 | 30.9796 | 759 | 2.9484 | 0.3636 |
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- | 0.047 | 32.0 | 784 | 2.5486 | 0.4545 |
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- | 0.165 | 32.9796 | 808 | 2.6011 | 0.4545 |
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- | 0.0203 | 34.0 | 833 | 2.3598 | 0.5 |
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- | 0.0143 | 34.9796 | 857 | 2.5892 | 0.4091 |
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- | 0.0248 | 36.0 | 882 | 2.8362 | 0.4091 |
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- | 0.0812 | 36.9796 | 906 | 2.4658 | 0.4091 |
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- | 0.0662 | 38.0 | 931 | 2.6403 | 0.4091 |
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- | 0.1855 | 38.9796 | 955 | 2.6042 | 0.4545 |
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- | 0.03 | 40.0 | 980 | 2.5595 | 0.5 |
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- | 0.1117 | 40.9796 | 1004 | 2.4716 | 0.5 |
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- | 0.0466 | 42.0 | 1029 | 2.3257 | 0.5 |
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- | 0.1349 | 42.9796 | 1053 | 2.5545 | 0.4545 |
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- | 0.0069 | 44.0 | 1078 | 2.5815 | 0.5 |
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- | 0.0468 | 44.9796 | 1102 | 2.3667 | 0.5 |
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- | 0.1807 | 46.0 | 1127 | 2.4729 | 0.5 |
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- | 0.0667 | 46.9796 | 1151 | 2.4969 | 0.5 |
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- | 0.0199 | 48.0 | 1176 | 2.5521 | 0.5 |
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- | 0.2716 | 48.9796 | 1200 | 2.5371 | 0.5 |
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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 the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.7604
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  - Accuracy: 0.5
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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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+ | 2.2679 | 0.9796 | 24 | 2.1550 | 0.0909 |
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+ | 2.0504 | 2.0 | 49 | 2.0559 | 0.2727 |
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+ | 1.8943 | 2.9796 | 73 | 2.0186 | 0.2273 |
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+ | 1.5671 | 4.0 | 98 | 1.8154 | 0.2273 |
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+ | 1.3425 | 4.9796 | 122 | 2.0475 | 0.2273 |
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+ | 1.2758 | 6.0 | 147 | 2.1914 | 0.2273 |
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+ | 0.9808 | 6.9796 | 171 | 2.0478 | 0.3636 |
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+ | 0.7246 | 8.0 | 196 | 1.8840 | 0.4091 |
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+ | 0.7323 | 8.9796 | 220 | 2.1831 | 0.4091 |
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+ | 0.4881 | 10.0 | 245 | 2.2868 | 0.3636 |
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+ | 0.4346 | 10.9796 | 269 | 2.2312 | 0.4545 |
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+ | 0.5647 | 12.0 | 294 | 1.9897 | 0.4091 |
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+ | 0.1464 | 12.9796 | 318 | 2.0579 | 0.4545 |
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+ | 0.5575 | 14.0 | 343 | 2.1859 | 0.4545 |
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+ | 0.3894 | 14.9796 | 367 | 2.7353 | 0.3636 |
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+ | 0.4326 | 16.0 | 392 | 2.4455 | 0.3636 |
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+ | 0.3715 | 16.9796 | 416 | 2.3104 | 0.5455 |
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+ | 0.3966 | 18.0 | 441 | 2.4597 | 0.4545 |
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+ | 0.1855 | 18.9796 | 465 | 2.3335 | 0.3636 |
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+ | 0.1528 | 20.0 | 490 | 2.3630 | 0.4091 |
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+ | 0.2036 | 20.9796 | 514 | 2.3520 | 0.4545 |
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+ | 0.2026 | 22.0 | 539 | 2.7012 | 0.4091 |
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+ | 0.2127 | 22.9796 | 563 | 2.3724 | 0.5909 |
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+ | 0.2719 | 24.0 | 588 | 3.0376 | 0.3182 |
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+ | 0.1292 | 24.9796 | 612 | 2.5684 | 0.5 |
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+ | 0.2533 | 26.0 | 637 | 2.6974 | 0.4091 |
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+ | 0.1947 | 26.9796 | 661 | 2.6957 | 0.4091 |
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+ | 0.1805 | 28.0 | 686 | 2.8953 | 0.4091 |
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+ | 0.1123 | 28.9796 | 710 | 2.8240 | 0.4091 |
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+ | 0.2143 | 30.0 | 735 | 2.3880 | 0.4545 |
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+ | 0.1845 | 30.9796 | 759 | 2.6072 | 0.3636 |
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+ | 0.0921 | 32.0 | 784 | 2.7256 | 0.4545 |
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+ | 0.0276 | 32.9796 | 808 | 2.4074 | 0.4091 |
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+ | 0.0876 | 34.0 | 833 | 2.6043 | 0.4545 |
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+ | 0.0253 | 34.9796 | 857 | 2.7620 | 0.4545 |
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+ | 0.1904 | 36.0 | 882 | 2.6911 | 0.4091 |
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+ | 0.072 | 36.9796 | 906 | 2.6528 | 0.4545 |
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+ | 0.169 | 38.0 | 931 | 2.6454 | 0.4545 |
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+ | 0.0978 | 38.9796 | 955 | 2.6269 | 0.5 |
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+ | 0.069 | 40.0 | 980 | 2.4154 | 0.4545 |
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+ | 0.0159 | 40.9796 | 1004 | 2.7026 | 0.4545 |
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+ | 0.2046 | 42.0 | 1029 | 2.5213 | 0.4545 |
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+ | 0.0329 | 42.9796 | 1053 | 2.6399 | 0.5 |
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+ | 0.0166 | 44.0 | 1078 | 2.7787 | 0.4545 |
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+ | 0.0812 | 44.9796 | 1102 | 2.8176 | 0.4545 |
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+ | 0.0197 | 46.0 | 1127 | 2.8049 | 0.4545 |
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+ | 0.0989 | 46.9796 | 1151 | 2.7479 | 0.4545 |
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+ | 0.054 | 48.0 | 1176 | 2.7614 | 0.4545 |
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+ | 0.1095 | 48.9796 | 1200 | 2.7604 | 0.5 |
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  ### Framework versions
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