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BilalMuftuoglu
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deit-base-distilled-patch16-224-65-fold4

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  1. README.md +96 -96
  2. model.safetensors +1 -1
  3. runs/May22_06-21-30_defc3061f818/events.out.tfevents.1716358891.defc3061f818.1801.0 +2 -2
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: 0.8732394366197183
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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-base-distilled-patch16-224](https://huggingface.co/facebook/deit-base-distilled-patch16-224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4832
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- - Accuracy: 0.8732
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  ## Model description
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@@ -67,99 +67,99 @@ 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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- | No log | 0.9231 | 3 | 0.7219 | 0.5493 |
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- | No log | 1.8462 | 6 | 0.6863 | 0.5493 |
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- | No log | 2.7692 | 9 | 0.6578 | 0.5493 |
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- | 0.6825 | 4.0 | 13 | 0.6293 | 0.6338 |
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- | 0.6825 | 4.9231 | 16 | 0.6186 | 0.6761 |
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- | 0.6825 | 5.8462 | 19 | 0.6135 | 0.7042 |
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- | 0.6206 | 6.7692 | 22 | 0.6163 | 0.6479 |
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- | 0.6206 | 8.0 | 26 | 0.6350 | 0.6479 |
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- | 0.6206 | 8.9231 | 29 | 0.6078 | 0.6901 |
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- | 0.5728 | 9.8462 | 32 | 0.6873 | 0.6761 |
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- | 0.5728 | 10.7692 | 35 | 0.6771 | 0.6761 |
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- | 0.5728 | 12.0 | 39 | 0.5912 | 0.6620 |
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- | 0.5329 | 12.9231 | 42 | 0.5524 | 0.7465 |
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- | 0.5329 | 13.8462 | 45 | 0.5923 | 0.7183 |
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- | 0.5329 | 14.7692 | 48 | 0.6650 | 0.6761 |
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- | 0.4279 | 16.0 | 52 | 0.5183 | 0.7746 |
86
- | 0.4279 | 16.9231 | 55 | 0.4761 | 0.7887 |
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- | 0.4279 | 17.8462 | 58 | 0.5590 | 0.7183 |
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- | 0.4055 | 18.7692 | 61 | 0.5320 | 0.7465 |
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- | 0.4055 | 20.0 | 65 | 0.6605 | 0.7183 |
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- | 0.4055 | 20.9231 | 68 | 0.5821 | 0.7465 |
91
- | 0.3478 | 21.8462 | 71 | 0.5589 | 0.7465 |
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- | 0.3478 | 22.7692 | 74 | 0.6247 | 0.7465 |
93
- | 0.3478 | 24.0 | 78 | 0.7006 | 0.6620 |
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- | 0.3769 | 24.9231 | 81 | 0.7575 | 0.7183 |
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- | 0.3769 | 25.8462 | 84 | 0.5367 | 0.7746 |
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- | 0.3769 | 26.7692 | 87 | 0.5335 | 0.7746 |
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- | 0.2957 | 28.0 | 91 | 0.5914 | 0.7606 |
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- | 0.2957 | 28.9231 | 94 | 0.6780 | 0.7465 |
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- | 0.2957 | 29.8462 | 97 | 0.5345 | 0.7746 |
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- | 0.2463 | 30.7692 | 100 | 0.6132 | 0.7606 |
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- | 0.2463 | 32.0 | 104 | 0.5758 | 0.7887 |
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- | 0.2463 | 32.9231 | 107 | 0.7236 | 0.7324 |
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- | 0.2323 | 33.8462 | 110 | 0.5247 | 0.8169 |
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- | 0.2323 | 34.7692 | 113 | 0.6018 | 0.7183 |
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- | 0.2323 | 36.0 | 117 | 0.5366 | 0.8028 |
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- | 0.1921 | 36.9231 | 120 | 0.6314 | 0.7465 |
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- | 0.1921 | 37.8462 | 123 | 0.5763 | 0.7746 |
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- | 0.1921 | 38.7692 | 126 | 0.5574 | 0.8028 |
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- | 0.1686 | 40.0 | 130 | 0.6261 | 0.7887 |
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- | 0.1686 | 40.9231 | 133 | 0.6525 | 0.7887 |
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- | 0.1686 | 41.8462 | 136 | 0.5726 | 0.8169 |
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- | 0.1686 | 42.7692 | 139 | 0.8200 | 0.7042 |
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- | 0.2073 | 44.0 | 143 | 0.4798 | 0.7887 |
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- | 0.2073 | 44.9231 | 146 | 0.5342 | 0.7887 |
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- | 0.2073 | 45.8462 | 149 | 0.4834 | 0.7887 |
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- | 0.1702 | 46.7692 | 152 | 0.6101 | 0.7465 |
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- | 0.1702 | 48.0 | 156 | 0.4779 | 0.8169 |
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- | 0.1702 | 48.9231 | 159 | 0.5048 | 0.7887 |
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- | 0.153 | 49.8462 | 162 | 0.6298 | 0.7465 |
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- | 0.153 | 50.7692 | 165 | 0.5995 | 0.7606 |
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- | 0.153 | 52.0 | 169 | 0.6475 | 0.7042 |
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- | 0.1508 | 52.9231 | 172 | 0.4888 | 0.8028 |
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- | 0.1508 | 53.8462 | 175 | 0.4954 | 0.8310 |
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- | 0.1508 | 54.7692 | 178 | 0.4390 | 0.8028 |
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- | 0.1293 | 56.0 | 182 | 0.4778 | 0.8592 |
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- | 0.1293 | 56.9231 | 185 | 0.4888 | 0.8310 |
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- | 0.1293 | 57.8462 | 188 | 0.4832 | 0.8732 |
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- | 0.1489 | 58.7692 | 191 | 0.5277 | 0.8310 |
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- | 0.1489 | 60.0 | 195 | 0.6217 | 0.7324 |
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- | 0.1489 | 60.9231 | 198 | 0.6090 | 0.7465 |
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- | 0.1487 | 61.8462 | 201 | 0.5424 | 0.8451 |
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- | 0.1487 | 62.7692 | 204 | 0.5570 | 0.8451 |
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- | 0.1487 | 64.0 | 208 | 0.7248 | 0.7183 |
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- | 0.1456 | 64.9231 | 211 | 0.5841 | 0.7887 |
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- | 0.1456 | 65.8462 | 214 | 0.5905 | 0.8310 |
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- | 0.1456 | 66.7692 | 217 | 0.5609 | 0.8310 |
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- | 0.1284 | 68.0 | 221 | 0.5470 | 0.8028 |
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- | 0.1284 | 68.9231 | 224 | 0.5473 | 0.8310 |
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- | 0.1284 | 69.8462 | 227 | 0.5813 | 0.8310 |
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- | 0.1225 | 70.7692 | 230 | 0.5683 | 0.8451 |
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- | 0.1225 | 72.0 | 234 | 0.5581 | 0.8310 |
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- | 0.1225 | 72.9231 | 237 | 0.5717 | 0.7887 |
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- | 0.1233 | 73.8462 | 240 | 0.6054 | 0.7606 |
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- | 0.1233 | 74.7692 | 243 | 0.5910 | 0.7887 |
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- | 0.1233 | 76.0 | 247 | 0.5707 | 0.8169 |
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- | 0.1234 | 76.9231 | 250 | 0.5733 | 0.8028 |
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- | 0.1234 | 77.8462 | 253 | 0.5748 | 0.8028 |
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- | 0.1234 | 78.7692 | 256 | 0.5723 | 0.7887 |
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- | 0.1219 | 80.0 | 260 | 0.5503 | 0.8169 |
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- | 0.1219 | 80.9231 | 263 | 0.5532 | 0.8028 |
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- | 0.1219 | 81.8462 | 266 | 0.5828 | 0.7746 |
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- | 0.1219 | 82.7692 | 269 | 0.6062 | 0.7746 |
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- | 0.1075 | 84.0 | 273 | 0.5752 | 0.8028 |
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- | 0.1075 | 84.9231 | 276 | 0.5748 | 0.8028 |
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- | 0.1075 | 85.8462 | 279 | 0.5776 | 0.8169 |
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- | 0.1013 | 86.7692 | 282 | 0.5844 | 0.8028 |
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- | 0.1013 | 88.0 | 286 | 0.5930 | 0.8028 |
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- | 0.1013 | 88.9231 | 289 | 0.6020 | 0.7887 |
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- | 0.1092 | 89.8462 | 292 | 0.6055 | 0.7746 |
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- | 0.1092 | 90.7692 | 295 | 0.6075 | 0.7746 |
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- | 0.1092 | 92.0 | 299 | 0.6080 | 0.7746 |
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- | 0.1096 | 92.3077 | 300 | 0.6081 | 0.7746 |
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  ### Framework versions
 
22
  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.704225352112676
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  ---
27
 
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
32
 
33
  This model is a fine-tuned version of [facebook/deit-base-distilled-patch16-224](https://huggingface.co/facebook/deit-base-distilled-patch16-224) on the imagefolder dataset.
34
  It achieves the following results on the evaluation set:
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+ - Loss: 0.9612
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+ - Accuracy: 0.7042
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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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+ | No log | 0.9231 | 3 | 0.7266 | 0.4648 |
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+ | No log | 1.8462 | 6 | 0.8116 | 0.5211 |
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+ | No log | 2.7692 | 9 | 0.7081 | 0.4648 |
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+ | 0.7173 | 4.0 | 13 | 0.6645 | 0.5634 |
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+ | 0.7173 | 4.9231 | 16 | 0.6441 | 0.5915 |
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+ | 0.7173 | 5.8462 | 19 | 0.6400 | 0.6761 |
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+ | 0.6351 | 6.7692 | 22 | 0.6055 | 0.6620 |
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+ | 0.6351 | 8.0 | 26 | 0.7770 | 0.5352 |
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+ | 0.6351 | 8.9231 | 29 | 0.6259 | 0.6901 |
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+ | 0.5434 | 9.8462 | 32 | 0.5889 | 0.7183 |
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+ | 0.5434 | 10.7692 | 35 | 0.7283 | 0.6479 |
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+ | 0.5434 | 12.0 | 39 | 0.6898 | 0.6479 |
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+ | 0.4861 | 12.9231 | 42 | 0.6429 | 0.7183 |
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+ | 0.4861 | 13.8462 | 45 | 0.6915 | 0.6620 |
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+ | 0.4861 | 14.7692 | 48 | 0.5702 | 0.7183 |
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+ | 0.4285 | 16.0 | 52 | 0.6356 | 0.7042 |
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+ | 0.4285 | 16.9231 | 55 | 0.6981 | 0.6761 |
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+ | 0.4285 | 17.8462 | 58 | 0.5218 | 0.7183 |
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+ | 0.3781 | 18.7692 | 61 | 0.5340 | 0.7183 |
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+ | 0.3781 | 20.0 | 65 | 0.7611 | 0.6761 |
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+ | 0.3781 | 20.9231 | 68 | 0.5939 | 0.7465 |
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+ | 0.3516 | 21.8462 | 71 | 0.6186 | 0.7887 |
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+ | 0.3516 | 22.7692 | 74 | 0.7122 | 0.7042 |
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+ | 0.3516 | 24.0 | 78 | 0.5931 | 0.7887 |
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+ | 0.296 | 24.9231 | 81 | 0.6305 | 0.6901 |
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+ | 0.296 | 25.8462 | 84 | 0.8947 | 0.7042 |
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+ | 0.296 | 26.7692 | 87 | 0.6217 | 0.7183 |
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+ | 0.2741 | 28.0 | 91 | 0.7218 | 0.8169 |
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+ | 0.2741 | 28.9231 | 94 | 0.6687 | 0.7887 |
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+ | 0.2741 | 29.8462 | 97 | 0.6648 | 0.8028 |
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+ | 0.2559 | 30.7692 | 100 | 0.6433 | 0.7746 |
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+ | 0.2559 | 32.0 | 104 | 0.6674 | 0.7324 |
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+ | 0.2559 | 32.9231 | 107 | 0.6643 | 0.7465 |
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+ | 0.2001 | 33.8462 | 110 | 0.6247 | 0.7465 |
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+ | 0.2001 | 34.7692 | 113 | 0.6344 | 0.6901 |
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+ | 0.2001 | 36.0 | 117 | 0.7072 | 0.7606 |
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+ | 0.1728 | 36.9231 | 120 | 0.7146 | 0.7465 |
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+ | 0.1728 | 37.8462 | 123 | 0.8212 | 0.7606 |
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+ | 0.1728 | 38.7692 | 126 | 0.7901 | 0.7324 |
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+ | 0.2109 | 40.0 | 130 | 0.8235 | 0.7465 |
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+ | 0.2109 | 40.9231 | 133 | 0.9196 | 0.6901 |
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+ | 0.2109 | 41.8462 | 136 | 0.7758 | 0.7606 |
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+ | 0.2109 | 42.7692 | 139 | 0.7692 | 0.7183 |
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+ | 0.1634 | 44.0 | 143 | 0.8310 | 0.7606 |
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+ | 0.1634 | 44.9231 | 146 | 0.7550 | 0.7465 |
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+ | 0.1634 | 45.8462 | 149 | 0.7646 | 0.7324 |
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+ | 0.148 | 46.7692 | 152 | 0.7208 | 0.7606 |
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+ | 0.148 | 48.0 | 156 | 0.7324 | 0.7606 |
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+ | 0.148 | 48.9231 | 159 | 0.7856 | 0.7606 |
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+ | 0.1568 | 49.8462 | 162 | 0.8033 | 0.7606 |
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+ | 0.1568 | 50.7692 | 165 | 0.9007 | 0.7746 |
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+ | 0.1568 | 52.0 | 169 | 0.8179 | 0.7606 |
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+ | 0.1659 | 52.9231 | 172 | 0.7775 | 0.7606 |
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+ | 0.1659 | 53.8462 | 175 | 0.7214 | 0.7606 |
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+ | 0.1659 | 54.7692 | 178 | 0.7385 | 0.7465 |
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+ | 0.1352 | 56.0 | 182 | 0.7434 | 0.7465 |
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+ | 0.1352 | 56.9231 | 185 | 0.8971 | 0.7042 |
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+ | 0.1352 | 57.8462 | 188 | 0.7821 | 0.7606 |
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+ | 0.1309 | 58.7692 | 191 | 0.7896 | 0.7465 |
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+ | 0.1309 | 60.0 | 195 | 0.8340 | 0.7465 |
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+ | 0.1309 | 60.9231 | 198 | 0.8154 | 0.7746 |
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+ | 0.1201 | 61.8462 | 201 | 0.8185 | 0.7606 |
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+ | 0.1201 | 62.7692 | 204 | 0.9640 | 0.7183 |
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+ | 0.1201 | 64.0 | 208 | 0.8485 | 0.7606 |
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+ | 0.1291 | 64.9231 | 211 | 0.8807 | 0.7324 |
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+ | 0.1291 | 65.8462 | 214 | 0.8653 | 0.7183 |
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+ | 0.1291 | 66.7692 | 217 | 0.8744 | 0.7324 |
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+ | 0.124 | 68.0 | 221 | 0.8723 | 0.7324 |
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+ | 0.124 | 68.9231 | 224 | 0.8948 | 0.7606 |
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+ | 0.124 | 69.8462 | 227 | 0.9777 | 0.7183 |
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+ | 0.1262 | 70.7692 | 230 | 0.9409 | 0.7746 |
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+ | 0.1262 | 72.0 | 234 | 0.9618 | 0.7465 |
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+ | 0.1262 | 72.9231 | 237 | 0.9642 | 0.7606 |
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+ | 0.1036 | 73.8462 | 240 | 0.9738 | 0.7465 |
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+ | 0.1036 | 74.7692 | 243 | 0.9788 | 0.7324 |
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+ | 0.1036 | 76.0 | 247 | 1.0114 | 0.7465 |
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+ | 0.1183 | 76.9231 | 250 | 1.0004 | 0.7465 |
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+ | 0.1183 | 77.8462 | 253 | 1.0407 | 0.7465 |
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+ | 0.1183 | 78.7692 | 256 | 1.1510 | 0.7324 |
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+ | 0.0981 | 80.0 | 260 | 1.0718 | 0.7465 |
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+ | 0.0981 | 80.9231 | 263 | 0.9988 | 0.7324 |
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+ | 0.0981 | 81.8462 | 266 | 1.0054 | 0.7042 |
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+ | 0.0981 | 82.7692 | 269 | 0.9896 | 0.7324 |
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+ | 0.106 | 84.0 | 273 | 0.9851 | 0.7324 |
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+ | 0.106 | 84.9231 | 276 | 0.9770 | 0.7465 |
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+ | 0.106 | 85.8462 | 279 | 0.9623 | 0.7183 |
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+ | 0.114 | 86.7692 | 282 | 0.9664 | 0.7042 |
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+ | 0.114 | 88.0 | 286 | 0.9780 | 0.7042 |
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+ | 0.114 | 88.9231 | 289 | 0.9670 | 0.7183 |
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+ | 0.1157 | 89.8462 | 292 | 0.9586 | 0.7324 |
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+ | 0.1157 | 90.7692 | 295 | 0.9587 | 0.7183 |
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+ | 0.1157 | 92.0 | 299 | 0.9611 | 0.7042 |
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+ | 0.0834 | 92.3077 | 300 | 0.9612 | 0.7042 |
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  ### Framework versions
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