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vit-base-patch16-224-in21k-finetuned-biopsy

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  1. README.md +54 -54
  2. model.safetensors +1 -1
  3. runs/Oct17_14-32-01_634f3ddf7430/events.out.tfevents.1729175527.634f3ddf7430.627.0 +2 -2
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 [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1249
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- - Accuracy: 0.9682
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  ## Model description
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@@ -53,61 +53,61 @@ 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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- | 1.1332 | 1.0 | 42 | 1.0712 | 0.5494 |
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- | 0.6556 | 2.0 | 84 | 0.5742 | 0.8492 |
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- | 0.3987 | 3.0 | 126 | 0.3950 | 0.8894 |
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- | 0.2825 | 4.0 | 168 | 0.3924 | 0.8777 |
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- | 0.3662 | 5.0 | 210 | 0.3622 | 0.8861 |
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- | 0.2218 | 6.0 | 252 | 0.2706 | 0.9246 |
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- | 0.2236 | 7.0 | 294 | 0.2283 | 0.9347 |
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- | 0.2224 | 8.0 | 336 | 0.2367 | 0.9313 |
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- | 0.1754 | 9.0 | 378 | 0.2139 | 0.9296 |
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- | 0.1707 | 10.0 | 420 | 0.1829 | 0.9497 |
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- | 0.1619 | 11.0 | 462 | 0.2172 | 0.9464 |
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- | 0.1547 | 12.0 | 504 | 0.1960 | 0.9380 |
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- | 0.1213 | 13.0 | 546 | 0.1484 | 0.9581 |
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- | 0.1388 | 14.0 | 588 | 0.1689 | 0.9581 |
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- | 0.1009 | 15.0 | 630 | 0.1494 | 0.9581 |
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- | 0.124 | 16.0 | 672 | 0.1564 | 0.9581 |
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- | 0.1078 | 17.0 | 714 | 0.1728 | 0.9514 |
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- | 0.102 | 18.0 | 756 | 0.1669 | 0.9447 |
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- | 0.1006 | 19.0 | 798 | 0.1405 | 0.9581 |
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- | 0.0791 | 20.0 | 840 | 0.1179 | 0.9665 |
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- | 0.0694 | 21.0 | 882 | 0.1424 | 0.9631 |
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- | 0.0627 | 22.0 | 924 | 0.1224 | 0.9665 |
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- | 0.0883 | 23.0 | 966 | 0.1602 | 0.9447 |
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- | 0.074 | 24.0 | 1008 | 0.1315 | 0.9615 |
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- | 0.0708 | 25.0 | 1050 | 0.1331 | 0.9631 |
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- | 0.06 | 26.0 | 1092 | 0.1191 | 0.9665 |
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- | 0.083 | 27.0 | 1134 | 0.1583 | 0.9531 |
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- | 0.0584 | 28.0 | 1176 | 0.1348 | 0.9564 |
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- | 0.0627 | 29.0 | 1218 | 0.1270 | 0.9564 |
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- | 0.0627 | 30.0 | 1260 | 0.1411 | 0.9564 |
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- | 0.038 | 31.0 | 1302 | 0.1208 | 0.9665 |
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- | 0.0569 | 32.0 | 1344 | 0.1587 | 0.9514 |
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- | 0.0502 | 33.0 | 1386 | 0.1501 | 0.9497 |
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- | 0.0464 | 34.0 | 1428 | 0.1508 | 0.9615 |
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- | 0.0317 | 35.0 | 1470 | 0.1309 | 0.9631 |
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- | 0.0552 | 36.0 | 1512 | 0.1372 | 0.9598 |
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- | 0.031 | 37.0 | 1554 | 0.1258 | 0.9598 |
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- | 0.0383 | 38.0 | 1596 | 0.1249 | 0.9682 |
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- | 0.036 | 39.0 | 1638 | 0.1312 | 0.9665 |
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- | 0.0405 | 40.0 | 1680 | 0.1207 | 0.9665 |
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- | 0.0343 | 41.0 | 1722 | 0.1233 | 0.9648 |
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- | 0.0325 | 42.0 | 1764 | 0.1286 | 0.9631 |
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- | 0.0293 | 43.0 | 1806 | 0.1135 | 0.9682 |
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- | 0.0306 | 44.0 | 1848 | 0.1258 | 0.9615 |
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- | 0.0267 | 45.0 | 1890 | 0.1261 | 0.9648 |
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- | 0.0338 | 46.0 | 1932 | 0.1209 | 0.9665 |
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- | 0.0213 | 47.0 | 1974 | 0.1157 | 0.9665 |
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- | 0.0285 | 48.0 | 2016 | 0.1203 | 0.9631 |
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- | 0.0287 | 49.0 | 2058 | 0.1240 | 0.9648 |
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- | 0.0183 | 50.0 | 2100 | 0.1224 | 0.9665 |
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  ### Framework versions
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- - Transformers 4.44.2
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  - Pytorch 2.4.1+cu121
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  - Datasets 3.0.1
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- - Tokenizers 0.19.1
 
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  This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0848
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+ - Accuracy: 0.9782
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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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+ | 1.1862 | 1.0 | 42 | 1.1167 | 0.5611 |
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+ | 0.7235 | 2.0 | 84 | 0.6029 | 0.8543 |
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+ | 0.4286 | 3.0 | 126 | 0.3452 | 0.9280 |
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+ | 0.3612 | 4.0 | 168 | 0.3485 | 0.8945 |
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+ | 0.3015 | 5.0 | 210 | 0.2590 | 0.9296 |
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+ | 0.2917 | 6.0 | 252 | 0.2219 | 0.9414 |
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+ | 0.2312 | 7.0 | 294 | 0.2400 | 0.9280 |
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+ | 0.1708 | 8.0 | 336 | 0.2120 | 0.9414 |
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+ | 0.1806 | 9.0 | 378 | 0.1784 | 0.9514 |
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+ | 0.1703 | 10.0 | 420 | 0.1571 | 0.9481 |
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+ | 0.139 | 11.0 | 462 | 0.1544 | 0.9648 |
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+ | 0.1301 | 12.0 | 504 | 0.1431 | 0.9598 |
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+ | 0.122 | 13.0 | 546 | 0.1297 | 0.9631 |
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+ | 0.1104 | 14.0 | 588 | 0.1401 | 0.9598 |
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+ | 0.1075 | 15.0 | 630 | 0.1200 | 0.9665 |
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+ | 0.0986 | 16.0 | 672 | 0.1665 | 0.9581 |
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+ | 0.092 | 17.0 | 714 | 0.1399 | 0.9531 |
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+ | 0.1123 | 18.0 | 756 | 0.1122 | 0.9698 |
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+ | 0.0766 | 19.0 | 798 | 0.1337 | 0.9564 |
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+ | 0.0762 | 20.0 | 840 | 0.0974 | 0.9732 |
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+ | 0.0994 | 21.0 | 882 | 0.1023 | 0.9698 |
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+ | 0.0687 | 22.0 | 924 | 0.0976 | 0.9749 |
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+ | 0.0767 | 23.0 | 966 | 0.0952 | 0.9765 |
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+ | 0.0581 | 24.0 | 1008 | 0.1096 | 0.9665 |
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+ | 0.0544 | 25.0 | 1050 | 0.1123 | 0.9715 |
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+ | 0.079 | 26.0 | 1092 | 0.1040 | 0.9682 |
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+ | 0.0661 | 27.0 | 1134 | 0.0838 | 0.9799 |
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+ | 0.068 | 28.0 | 1176 | 0.1169 | 0.9715 |
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+ | 0.0722 | 29.0 | 1218 | 0.0897 | 0.9732 |
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+ | 0.048 | 30.0 | 1260 | 0.0864 | 0.9732 |
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+ | 0.0509 | 31.0 | 1302 | 0.0858 | 0.9749 |
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+ | 0.047 | 32.0 | 1344 | 0.0801 | 0.9782 |
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+ | 0.0411 | 33.0 | 1386 | 0.1221 | 0.9648 |
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+ | 0.0378 | 34.0 | 1428 | 0.1011 | 0.9648 |
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+ | 0.0358 | 35.0 | 1470 | 0.0834 | 0.9799 |
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+ | 0.0347 | 36.0 | 1512 | 0.0993 | 0.9715 |
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+ | 0.0434 | 37.0 | 1554 | 0.0938 | 0.9732 |
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+ | 0.0507 | 38.0 | 1596 | 0.0874 | 0.9782 |
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+ | 0.0466 | 39.0 | 1638 | 0.0932 | 0.9765 |
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+ | 0.0502 | 40.0 | 1680 | 0.1012 | 0.9698 |
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+ | 0.0289 | 41.0 | 1722 | 0.0841 | 0.9715 |
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+ | 0.0274 | 42.0 | 1764 | 0.0883 | 0.9682 |
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+ | 0.0251 | 43.0 | 1806 | 0.0843 | 0.9782 |
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+ | 0.0343 | 44.0 | 1848 | 0.0812 | 0.9782 |
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+ | 0.0289 | 45.0 | 1890 | 0.0805 | 0.9782 |
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+ | 0.0277 | 46.0 | 1932 | 0.0943 | 0.9698 |
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+ | 0.0332 | 47.0 | 1974 | 0.0807 | 0.9765 |
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+ | 0.0328 | 48.0 | 2016 | 0.0826 | 0.9749 |
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+ | 0.0257 | 49.0 | 2058 | 0.0852 | 0.9749 |
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+ | 0.0287 | 50.0 | 2100 | 0.0848 | 0.9782 |
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  ### Framework versions
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+ - Transformers 4.45.2
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  - Pytorch 2.4.1+cu121
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  - Datasets 3.0.1
113
+ - Tokenizers 0.20.1
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