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hkivancoral
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smids_1x_deit_tiny_adamax_001_fold2

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  1. README.md +53 -53
  2. model.safetensors +1 -1
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.8336106489184693
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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
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.3785
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- - Accuracy: 0.8336
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  ## Model description
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@@ -65,56 +65,56 @@ 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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- | 0.8106 | 1.0 | 75 | 0.7856 | 0.5657 |
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- | 0.8289 | 2.0 | 150 | 0.7551 | 0.7121 |
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- | 0.6607 | 3.0 | 225 | 0.6595 | 0.7288 |
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- | 0.5966 | 4.0 | 300 | 0.5724 | 0.7671 |
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- | 0.5316 | 5.0 | 375 | 0.5404 | 0.7854 |
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- | 0.3929 | 6.0 | 450 | 0.5052 | 0.7970 |
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- | 0.407 | 7.0 | 525 | 0.4685 | 0.8303 |
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- | 0.3944 | 8.0 | 600 | 0.4515 | 0.8236 |
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- | 0.2836 | 9.0 | 675 | 0.4807 | 0.8070 |
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- | 0.2744 | 10.0 | 750 | 0.4423 | 0.8469 |
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- | 0.2808 | 11.0 | 825 | 0.4896 | 0.7953 |
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- | 0.152 | 12.0 | 900 | 0.5241 | 0.8319 |
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- | 0.1786 | 13.0 | 975 | 0.4922 | 0.8486 |
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- | 0.1372 | 14.0 | 1050 | 0.6687 | 0.8220 |
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- | 0.1982 | 15.0 | 1125 | 0.7505 | 0.8253 |
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- | 0.1651 | 16.0 | 1200 | 0.8354 | 0.8236 |
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- | 0.1906 | 17.0 | 1275 | 1.1129 | 0.7737 |
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- | 0.0899 | 18.0 | 1350 | 1.0319 | 0.8003 |
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- | 0.0875 | 19.0 | 1425 | 1.0962 | 0.7987 |
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- | 0.0186 | 20.0 | 1500 | 0.9631 | 0.8270 |
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- | 0.0742 | 21.0 | 1575 | 1.2547 | 0.7887 |
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- | 0.0229 | 22.0 | 1650 | 0.9476 | 0.8303 |
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- | 0.0161 | 23.0 | 1725 | 1.3651 | 0.8070 |
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- | 0.0097 | 24.0 | 1800 | 1.0596 | 0.8286 |
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- | 0.0082 | 25.0 | 1875 | 0.9954 | 0.8386 |
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- | 0.0036 | 26.0 | 1950 | 0.9671 | 0.8353 |
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- | 0.0205 | 27.0 | 2025 | 1.0817 | 0.8253 |
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- | 0.0109 | 28.0 | 2100 | 0.9995 | 0.8353 |
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- | 0.007 | 29.0 | 2175 | 1.1573 | 0.8369 |
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- | 0.0048 | 30.0 | 2250 | 1.2320 | 0.8303 |
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- | 0.0312 | 31.0 | 2325 | 1.1062 | 0.8453 |
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- | 0.0003 | 32.0 | 2400 | 1.3037 | 0.8436 |
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- | 0.0002 | 33.0 | 2475 | 1.2278 | 0.8403 |
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- | 0.0041 | 34.0 | 2550 | 1.3384 | 0.8286 |
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- | 0.0096 | 35.0 | 2625 | 1.3396 | 0.8303 |
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- | 0.0049 | 36.0 | 2700 | 1.3638 | 0.8403 |
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- | 0.0054 | 37.0 | 2775 | 1.3303 | 0.8303 |
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- | 0.0 | 38.0 | 2850 | 1.3273 | 0.8303 |
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- | 0.0017 | 39.0 | 2925 | 1.3584 | 0.8336 |
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- | 0.0 | 40.0 | 3000 | 1.3526 | 0.8319 |
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- | 0.0031 | 41.0 | 3075 | 1.3529 | 0.8303 |
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- | 0.0029 | 42.0 | 3150 | 1.3744 | 0.8336 |
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- | 0.0052 | 43.0 | 3225 | 1.3603 | 0.8319 |
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- | 0.0041 | 44.0 | 3300 | 1.3711 | 0.8336 |
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- | 0.0 | 45.0 | 3375 | 1.3741 | 0.8353 |
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- | 0.0002 | 46.0 | 3450 | 1.3699 | 0.8336 |
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- | 0.0029 | 47.0 | 3525 | 1.3797 | 0.8336 |
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- | 0.0 | 48.0 | 3600 | 1.3781 | 0.8336 |
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- | 0.0022 | 49.0 | 3675 | 1.3784 | 0.8336 |
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- | 0.0022 | 50.0 | 3750 | 1.3785 | 0.8336 |
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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: 0.8935108153078203
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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 [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.8198
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+ - Accuracy: 0.8935
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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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+ | 0.6145 | 1.0 | 75 | 0.5428 | 0.7970 |
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+ | 0.3766 | 2.0 | 150 | 0.5726 | 0.7720 |
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+ | 0.4048 | 3.0 | 225 | 0.6119 | 0.7920 |
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+ | 0.3699 | 4.0 | 300 | 0.3532 | 0.8619 |
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+ | 0.3283 | 5.0 | 375 | 0.4734 | 0.8270 |
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+ | 0.2617 | 6.0 | 450 | 0.5747 | 0.8053 |
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+ | 0.2131 | 7.0 | 525 | 0.4492 | 0.8486 |
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+ | 0.1731 | 8.0 | 600 | 0.4339 | 0.8686 |
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+ | 0.1832 | 9.0 | 675 | 0.5654 | 0.8336 |
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+ | 0.1286 | 10.0 | 750 | 1.0166 | 0.7704 |
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+ | 0.0921 | 11.0 | 825 | 0.5592 | 0.8519 |
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+ | 0.0818 | 12.0 | 900 | 0.6074 | 0.8486 |
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+ | 0.1315 | 13.0 | 975 | 0.7091 | 0.8369 |
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+ | 0.0851 | 14.0 | 1050 | 0.6304 | 0.8436 |
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+ | 0.0354 | 15.0 | 1125 | 0.8000 | 0.8469 |
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+ | 0.0659 | 16.0 | 1200 | 0.7712 | 0.8586 |
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+ | 0.0297 | 17.0 | 1275 | 0.8136 | 0.8686 |
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+ | 0.058 | 18.0 | 1350 | 0.7968 | 0.8536 |
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+ | 0.0096 | 19.0 | 1425 | 0.7312 | 0.8719 |
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+ | 0.0206 | 20.0 | 1500 | 0.7618 | 0.8453 |
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+ | 0.0111 | 21.0 | 1575 | 1.0098 | 0.8336 |
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+ | 0.0053 | 22.0 | 1650 | 0.8487 | 0.8502 |
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+ | 0.0105 | 23.0 | 1725 | 0.7386 | 0.8702 |
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+ | 0.0094 | 24.0 | 1800 | 0.8515 | 0.8419 |
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+ | 0.0004 | 25.0 | 1875 | 0.8080 | 0.8636 |
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+ | 0.0177 | 26.0 | 1950 | 0.6472 | 0.8819 |
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+ | 0.0321 | 27.0 | 2025 | 0.6905 | 0.8785 |
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+ | 0.0096 | 28.0 | 2100 | 0.6932 | 0.8852 |
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+ | 0.0091 | 29.0 | 2175 | 0.7066 | 0.8869 |
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+ | 0.0059 | 30.0 | 2250 | 0.7159 | 0.8819 |
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+ | 0.0056 | 31.0 | 2325 | 0.7490 | 0.8869 |
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+ | 0.0 | 32.0 | 2400 | 0.7569 | 0.8885 |
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+ | 0.0 | 33.0 | 2475 | 0.7589 | 0.8869 |
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+ | 0.0003 | 34.0 | 2550 | 0.7519 | 0.8935 |
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+ | 0.01 | 35.0 | 2625 | 0.7808 | 0.8902 |
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+ | 0.0 | 36.0 | 2700 | 0.7653 | 0.8918 |
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+ | 0.0001 | 37.0 | 2775 | 0.7709 | 0.8902 |
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+ | 0.0 | 38.0 | 2850 | 0.7835 | 0.8885 |
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+ | 0.0016 | 39.0 | 2925 | 0.7996 | 0.8935 |
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+ | 0.0 | 40.0 | 3000 | 0.7825 | 0.8918 |
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+ | 0.0036 | 41.0 | 3075 | 0.7879 | 0.8918 |
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+ | 0.0 | 42.0 | 3150 | 0.7990 | 0.8935 |
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+ | 0.003 | 43.0 | 3225 | 0.8020 | 0.8935 |
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+ | 0.0034 | 44.0 | 3300 | 0.8080 | 0.8935 |
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+ | 0.0 | 45.0 | 3375 | 0.8073 | 0.8935 |
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+ | 0.0 | 46.0 | 3450 | 0.8161 | 0.8935 |
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+ | 0.0029 | 47.0 | 3525 | 0.8235 | 0.8918 |
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+ | 0.0 | 48.0 | 3600 | 0.8195 | 0.8935 |
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+ | 0.0023 | 49.0 | 3675 | 0.8192 | 0.8935 |
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+ | 0.0022 | 50.0 | 3750 | 0.8198 | 0.8935 |
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  ### Framework versions
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