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Image Classification
Transformers
Safetensors
resnet
Generated from Trainer
Eval Results
Inference Endpoints
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  1. README.md +49 -49
  2. model.safetensors +1 -1
README.md CHANGED
@@ -33,7 +33,7 @@ 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: 0.0004
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  - Accuracy: 1.0
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  ## Model description
@@ -68,54 +68,54 @@ 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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- | 3.1555 | 0.9524 | 15 | 2.9808 | 0.12 |
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- | 2.6894 | 1.9683 | 31 | 2.3556 | 0.345 |
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- | 2.2726 | 2.9841 | 47 | 1.4728 | 0.725 |
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- | 1.3105 | 4.0 | 63 | 0.6794 | 0.91 |
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- | 0.906 | 4.9524 | 78 | 0.2580 | 0.96 |
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- | 0.3807 | 5.9683 | 94 | 0.1009 | 0.985 |
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- | 0.1963 | 6.9841 | 110 | 0.0539 | 0.99 |
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- | 0.1583 | 8.0 | 126 | 0.0152 | 1.0 |
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- | 0.1033 | 8.9524 | 141 | 0.0237 | 0.995 |
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- | 0.0969 | 9.9683 | 157 | 0.0082 | 1.0 |
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- | 0.0689 | 10.9841 | 173 | 0.0188 | 1.0 |
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- | 0.0593 | 12.0 | 189 | 0.0030 | 1.0 |
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- | 0.0433 | 12.9524 | 204 | 0.0136 | 1.0 |
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- | 0.0385 | 13.9683 | 220 | 0.0160 | 0.995 |
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- | 0.0352 | 14.9841 | 236 | 0.0023 | 1.0 |
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- | 0.0291 | 16.0 | 252 | 0.0026 | 1.0 |
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- | 0.0412 | 16.9524 | 267 | 0.0049 | 1.0 |
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- | 0.0311 | 17.9683 | 283 | 0.0102 | 0.995 |
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- | 0.0242 | 18.9841 | 299 | 0.0010 | 1.0 |
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- | 0.024 | 20.0 | 315 | 0.0085 | 1.0 |
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- | 0.0306 | 20.9524 | 330 | 0.0138 | 0.995 |
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- | 0.03 | 21.9683 | 346 | 0.0013 | 1.0 |
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- | 0.0106 | 22.9841 | 362 | 0.0007 | 1.0 |
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- | 0.0119 | 24.0 | 378 | 0.0288 | 0.99 |
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- | 0.0178 | 24.9524 | 393 | 0.0006 | 1.0 |
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- | 0.0109 | 25.9683 | 409 | 0.0348 | 0.99 |
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- | 0.0241 | 26.9841 | 425 | 0.0005 | 1.0 |
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- | 0.0225 | 28.0 | 441 | 0.0286 | 0.99 |
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- | 0.0144 | 28.9524 | 456 | 0.0009 | 1.0 |
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- | 0.0093 | 29.9683 | 472 | 0.0015 | 1.0 |
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- | 0.0138 | 30.9841 | 488 | 0.0004 | 1.0 |
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- | 0.0186 | 32.0 | 504 | 0.0004 | 1.0 |
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- | 0.01 | 32.9524 | 519 | 0.0012 | 1.0 |
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- | 0.0118 | 33.9683 | 535 | 0.0004 | 1.0 |
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- | 0.0146 | 34.9841 | 551 | 0.0089 | 0.995 |
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- | 0.0146 | 36.0 | 567 | 0.0015 | 1.0 |
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- | 0.0145 | 36.9524 | 582 | 0.0057 | 1.0 |
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- | 0.0115 | 37.9683 | 598 | 0.0194 | 0.995 |
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- | 0.0083 | 38.9841 | 614 | 0.0138 | 0.995 |
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- | 0.0123 | 40.0 | 630 | 0.0133 | 0.995 |
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- | 0.01 | 40.9524 | 645 | 0.0003 | 1.0 |
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- | 0.0121 | 41.9683 | 661 | 0.0134 | 0.995 |
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- | 0.0188 | 42.9841 | 677 | 0.0233 | 0.99 |
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- | 0.0077 | 44.0 | 693 | 0.0284 | 0.99 |
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- | 0.0145 | 44.9524 | 708 | 0.0003 | 1.0 |
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- | 0.0098 | 45.9683 | 724 | 0.0270 | 0.99 |
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- | 0.0166 | 46.9841 | 740 | 0.0004 | 1.0 |
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- | 0.016 | 47.6190 | 750 | 0.0004 | 1.0 |
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  ### Framework versions
 
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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: 0.0010
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  - Accuracy: 1.0
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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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+ | 3.2404 | 0.9524 | 15 | 3.1135 | 0.06 |
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+ | 2.7846 | 1.9683 | 31 | 2.4576 | 0.33 |
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+ | 2.3956 | 2.9841 | 47 | 1.7152 | 0.58 |
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+ | 1.6171 | 4.0 | 63 | 1.0931 | 0.775 |
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+ | 1.2882 | 4.9524 | 78 | 0.6347 | 0.85 |
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+ | 0.7191 | 5.9683 | 94 | 0.3957 | 0.94 |
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+ | 0.5196 | 6.9841 | 110 | 0.2080 | 0.965 |
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+ | 0.3999 | 8.0 | 126 | 0.1480 | 0.965 |
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+ | 0.2476 | 8.9524 | 141 | 0.0934 | 0.985 |
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+ | 0.2176 | 9.9683 | 157 | 0.0768 | 0.99 |
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+ | 0.194 | 10.9841 | 173 | 0.0365 | 0.995 |
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+ | 0.1572 | 12.0 | 189 | 0.0616 | 0.985 |
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+ | 0.1381 | 12.9524 | 204 | 0.0640 | 0.985 |
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+ | 0.1291 | 13.9683 | 220 | 0.0522 | 0.985 |
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+ | 0.094 | 14.9841 | 236 | 0.0442 | 0.99 |
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+ | 0.1037 | 16.0 | 252 | 0.0492 | 0.99 |
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+ | 0.1067 | 16.9524 | 267 | 0.0629 | 0.985 |
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+ | 0.0912 | 17.9683 | 283 | 0.0486 | 0.985 |
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+ | 0.0702 | 18.9841 | 299 | 0.0344 | 0.99 |
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+ | 0.0677 | 20.0 | 315 | 0.0242 | 0.995 |
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+ | 0.0566 | 20.9524 | 330 | 0.0295 | 0.99 |
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+ | 0.0742 | 21.9683 | 346 | 0.0300 | 0.99 |
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+ | 0.0675 | 22.9841 | 362 | 0.0159 | 1.0 |
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+ | 0.0501 | 24.0 | 378 | 0.0105 | 0.995 |
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+ | 0.0651 | 24.9524 | 393 | 0.0362 | 0.995 |
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+ | 0.0665 | 25.9683 | 409 | 0.0335 | 0.985 |
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+ | 0.0533 | 26.9841 | 425 | 0.0369 | 0.99 |
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+ | 0.0487 | 28.0 | 441 | 0.0296 | 0.99 |
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+ | 0.0384 | 28.9524 | 456 | 0.0177 | 0.995 |
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+ | 0.038 | 29.9683 | 472 | 0.0176 | 0.995 |
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+ | 0.0342 | 30.9841 | 488 | 0.0165 | 0.995 |
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+ | 0.055 | 32.0 | 504 | 0.0199 | 0.995 |
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+ | 0.0418 | 32.9524 | 519 | 0.0022 | 1.0 |
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+ | 0.0447 | 33.9683 | 535 | 0.0071 | 0.995 |
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+ | 0.0436 | 34.9841 | 551 | 0.0587 | 0.98 |
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+ | 0.0307 | 36.0 | 567 | 0.0244 | 0.995 |
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+ | 0.0413 | 36.9524 | 582 | 0.0227 | 0.99 |
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+ | 0.0351 | 37.9683 | 598 | 0.0323 | 0.99 |
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+ | 0.0267 | 38.9841 | 614 | 0.0510 | 0.985 |
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+ | 0.0259 | 40.0 | 630 | 0.0009 | 1.0 |
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+ | 0.0245 | 40.9524 | 645 | 0.0017 | 1.0 |
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+ | 0.0227 | 41.9683 | 661 | 0.0208 | 0.995 |
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+ | 0.0458 | 42.9841 | 677 | 0.0445 | 0.99 |
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+ | 0.0263 | 44.0 | 693 | 0.0339 | 0.99 |
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+ | 0.0458 | 44.9524 | 708 | 0.0124 | 0.995 |
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+ | 0.0374 | 45.9683 | 724 | 0.0253 | 0.995 |
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+ | 0.0413 | 46.9841 | 740 | 0.0025 | 1.0 |
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+ | 0.0413 | 47.6190 | 750 | 0.0010 | 1.0 |
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  ### Framework versions
model.safetensors CHANGED
@@ -1,3 +1,3 @@
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  size 44801272