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Image Classification
Transformers
Safetensors
resnet
Generated from Trainer
Eval Results (legacy)
Model card Files
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  1. README.md +53 -53
  2. model.safetensors +1 -1
README.md CHANGED
@@ -23,7 +23,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.9545454545454546
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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
@@ -33,8 +33,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [microsoft/resnet-18](https://huggingface.co/microsoft/resnet-18) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1433
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- - Accuracy: 0.9545
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  ## Model description
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@@ -68,56 +68,56 @@ 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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- | 3.3794 | 1.0 | 14 | 3.3306 | 0.0455 |
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- | 3.1945 | 2.0 | 28 | 3.0211 | 0.1045 |
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- | 2.9016 | 3.0 | 42 | 2.6297 | 0.1682 |
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- | 2.5174 | 4.0 | 56 | 2.1280 | 0.3636 |
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- | 1.8477 | 5.0 | 70 | 1.6542 | 0.5318 |
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- | 1.6209 | 6.0 | 84 | 1.2193 | 0.6136 |
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- | 1.3882 | 7.0 | 98 | 1.0877 | 0.6636 |
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- | 1.1235 | 8.0 | 112 | 0.8903 | 0.7318 |
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- | 1.0144 | 9.0 | 126 | 0.7754 | 0.7818 |
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- | 0.7593 | 10.0 | 140 | 0.6333 | 0.8 |
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- | 0.801 | 11.0 | 154 | 0.5506 | 0.8091 |
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- | 0.745 | 12.0 | 168 | 0.4354 | 0.8636 |
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- | 0.5987 | 13.0 | 182 | 0.4478 | 0.8636 |
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- | 0.5947 | 14.0 | 196 | 0.4014 | 0.8682 |
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- | 0.4595 | 15.0 | 210 | 0.4270 | 0.8591 |
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- | 0.5095 | 16.0 | 224 | 0.2876 | 0.9227 |
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- | 0.4554 | 17.0 | 238 | 0.3371 | 0.8727 |
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- | 0.3733 | 18.0 | 252 | 0.2550 | 0.9227 |
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- | 0.3888 | 19.0 | 266 | 0.3142 | 0.8818 |
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- | 0.4014 | 20.0 | 280 | 0.2550 | 0.9273 |
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- | 0.3493 | 21.0 | 294 | 0.2737 | 0.9091 |
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- | 0.3637 | 22.0 | 308 | 0.2399 | 0.9091 |
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- | 0.3479 | 23.0 | 322 | 0.1852 | 0.9455 |
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- | 0.3303 | 24.0 | 336 | 0.2029 | 0.9364 |
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- | 0.3147 | 25.0 | 350 | 0.2294 | 0.9318 |
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- | 0.2976 | 26.0 | 364 | 0.2396 | 0.9091 |
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- | 0.2937 | 27.0 | 378 | 0.2169 | 0.9455 |
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- | 0.2597 | 28.0 | 392 | 0.1885 | 0.9227 |
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- | 0.2685 | 29.0 | 406 | 0.1743 | 0.9545 |
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- | 0.2465 | 30.0 | 420 | 0.1985 | 0.9318 |
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- | 0.2753 | 31.0 | 434 | 0.1814 | 0.9364 |
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- | 0.224 | 32.0 | 448 | 0.1823 | 0.9182 |
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- | 0.2324 | 33.0 | 462 | 0.1634 | 0.9318 |
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- | 0.2163 | 34.0 | 476 | 0.1686 | 0.9364 |
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- | 0.2116 | 35.0 | 490 | 0.1502 | 0.9682 |
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- | 0.2511 | 36.0 | 504 | 0.1817 | 0.9364 |
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- | 0.238 | 37.0 | 518 | 0.1489 | 0.9318 |
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- | 0.2187 | 38.0 | 532 | 0.1455 | 0.9364 |
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- | 0.1822 | 39.0 | 546 | 0.1260 | 0.9591 |
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- | 0.1799 | 40.0 | 560 | 0.1632 | 0.95 |
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- | 0.2013 | 41.0 | 574 | 0.1442 | 0.9545 |
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- | 0.2065 | 42.0 | 588 | 0.1709 | 0.9409 |
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- | 0.2244 | 43.0 | 602 | 0.1692 | 0.9591 |
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- | 0.1965 | 44.0 | 616 | 0.1326 | 0.95 |
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- | 0.1694 | 45.0 | 630 | 0.1666 | 0.95 |
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- | 0.1755 | 46.0 | 644 | 0.1189 | 0.9591 |
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- | 0.1939 | 47.0 | 658 | 0.1444 | 0.95 |
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- | 0.192 | 48.0 | 672 | 0.1828 | 0.9364 |
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- | 0.178 | 49.0 | 686 | 0.1806 | 0.9273 |
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- | 0.1742 | 50.0 | 700 | 0.1433 | 0.9545 |
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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: 0.9681818181818181
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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/resnet-18](https://huggingface.co/microsoft/resnet-18) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1184
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+ - Accuracy: 0.9682
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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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+ | 3.3213 | 1.0 | 14 | 3.2453 | 0.0682 |
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+ | 3.1711 | 2.0 | 28 | 3.0051 | 0.1273 |
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+ | 2.8729 | 3.0 | 42 | 2.6285 | 0.2091 |
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+ | 2.562 | 4.0 | 56 | 2.1600 | 0.3773 |
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+ | 1.8675 | 5.0 | 70 | 1.6392 | 0.5364 |
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+ | 1.6359 | 6.0 | 84 | 1.2267 | 0.6682 |
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+ | 1.3499 | 7.0 | 98 | 1.0588 | 0.6818 |
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+ | 1.076 | 8.0 | 112 | 0.8791 | 0.6909 |
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+ | 0.9811 | 9.0 | 126 | 0.7573 | 0.7545 |
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+ | 0.7309 | 10.0 | 140 | 0.6195 | 0.7818 |
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+ | 0.7776 | 11.0 | 154 | 0.5426 | 0.8 |
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+ | 0.7365 | 12.0 | 168 | 0.4029 | 0.8773 |
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+ | 0.5767 | 13.0 | 182 | 0.4418 | 0.8364 |
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+ | 0.5838 | 14.0 | 196 | 0.3538 | 0.8818 |
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+ | 0.4491 | 15.0 | 210 | 0.3834 | 0.8636 |
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+ | 0.5056 | 16.0 | 224 | 0.2701 | 0.9227 |
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+ | 0.4364 | 17.0 | 238 | 0.3142 | 0.8818 |
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+ | 0.364 | 18.0 | 252 | 0.2617 | 0.9136 |
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+ | 0.3845 | 19.0 | 266 | 0.3092 | 0.8818 |
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+ | 0.3873 | 20.0 | 280 | 0.2309 | 0.9136 |
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+ | 0.3397 | 21.0 | 294 | 0.2267 | 0.9182 |
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+ | 0.3731 | 22.0 | 308 | 0.2205 | 0.9136 |
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+ | 0.329 | 23.0 | 322 | 0.1516 | 0.95 |
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+ | 0.3041 | 24.0 | 336 | 0.2081 | 0.9318 |
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+ | 0.2996 | 25.0 | 350 | 0.1876 | 0.9273 |
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+ | 0.2825 | 26.0 | 364 | 0.2241 | 0.9273 |
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+ | 0.2929 | 27.0 | 378 | 0.2055 | 0.9318 |
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+ | 0.2574 | 28.0 | 392 | 0.1667 | 0.9318 |
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+ | 0.2662 | 29.0 | 406 | 0.1586 | 0.9545 |
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+ | 0.2391 | 30.0 | 420 | 0.1782 | 0.9273 |
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+ | 0.2642 | 31.0 | 434 | 0.1590 | 0.9409 |
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+ | 0.2323 | 32.0 | 448 | 0.1662 | 0.9364 |
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+ | 0.2261 | 33.0 | 462 | 0.1549 | 0.9455 |
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+ | 0.2116 | 34.0 | 476 | 0.1538 | 0.95 |
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+ | 0.211 | 35.0 | 490 | 0.1497 | 0.9636 |
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+ | 0.2472 | 36.0 | 504 | 0.1579 | 0.9591 |
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+ | 0.2185 | 37.0 | 518 | 0.1227 | 0.9636 |
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+ | 0.2123 | 38.0 | 532 | 0.1389 | 0.95 |
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+ | 0.1691 | 39.0 | 546 | 0.1040 | 0.9727 |
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+ | 0.1805 | 40.0 | 560 | 0.1445 | 0.9545 |
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+ | 0.1828 | 41.0 | 574 | 0.1349 | 0.9455 |
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+ | 0.2005 | 42.0 | 588 | 0.1418 | 0.9455 |
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+ | 0.1986 | 43.0 | 602 | 0.1613 | 0.9455 |
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+ | 0.2012 | 44.0 | 616 | 0.1206 | 0.9591 |
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+ | 0.1494 | 45.0 | 630 | 0.1405 | 0.9591 |
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+ | 0.1891 | 46.0 | 644 | 0.1122 | 0.9727 |
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+ | 0.2012 | 47.0 | 658 | 0.1215 | 0.9636 |
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+ | 0.181 | 48.0 | 672 | 0.1784 | 0.9455 |
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+ | 0.1757 | 49.0 | 686 | 0.1703 | 0.9364 |
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+ | 0.1603 | 50.0 | 700 | 0.1184 | 0.9682 |
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  ### Framework versions
model.safetensors CHANGED
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