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upload trashify box detection model trained on purely synthetic data

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  1. README.md +104 -104
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -4,18 +4,18 @@ base_model: microsoft/conditional-detr-resnet-50
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  tags:
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  - generated_from_trainer
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  model-index:
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- - name: trashify-box-detection-model-manual-and-synthetic-data
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  results: []
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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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  should probably proofread and complete it, then remove this comment. -->
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- # trashify-box-detection-model-manual-and-synthetic-data
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- This model is a fine-tuned version of [microsoft/conditional-detr-resnet-50](https://huggingface.co/microsoft/conditional-detr-resnet-50) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.8292
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  ## Model description
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@@ -48,106 +48,106 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:-----:|:---------------:|
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- | 47.9307 | 1.0 | 151 | 3.7270 |
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- | 2.9183 | 2.0 | 302 | 2.1431 |
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- | 2.0809 | 3.0 | 453 | 1.5949 |
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- | 1.6817 | 4.0 | 604 | 1.2977 |
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- | 1.5111 | 5.0 | 755 | 1.1754 |
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- | 1.4827 | 6.0 | 906 | 1.2093 |
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- | 1.4104 | 7.0 | 1057 | 1.1245 |
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- | 1.3974 | 8.0 | 1208 | 1.1345 |
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- | 1.3833 | 9.0 | 1359 | 1.0921 |
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- | 1.3964 | 10.0 | 1510 | 1.1397 |
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- | 1.3626 | 11.0 | 1661 | 1.0392 |
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- | 1.3321 | 12.0 | 1812 | 1.0339 |
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- | 1.3478 | 13.0 | 1963 | 1.0831 |
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- | 1.3223 | 14.0 | 2114 | 1.0881 |
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- | 1.3128 | 15.0 | 2265 | 1.0432 |
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- | 1.3079 | 16.0 | 2416 | 1.0585 |
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- | 1.2738 | 17.0 | 2567 | 1.0196 |
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- | 1.27 | 18.0 | 2718 | 0.9945 |
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- | 1.2396 | 19.0 | 2869 | 0.9707 |
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- | 1.2669 | 20.0 | 3020 | 1.0081 |
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- | 1.24 | 21.0 | 3171 | 0.9685 |
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- | 1.2028 | 22.0 | 3322 | 0.9739 |
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- | 1.2123 | 23.0 | 3473 | 0.9891 |
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- | 1.212 | 24.0 | 3624 | 0.9930 |
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- | 1.1998 | 25.0 | 3775 | 0.9591 |
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- | 1.1869 | 26.0 | 3926 | 0.9751 |
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- | 1.1942 | 27.0 | 4077 | 0.9734 |
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- | 1.1895 | 28.0 | 4228 | 0.9486 |
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- | 1.191 | 29.0 | 4379 | 0.9523 |
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- | 1.1749 | 30.0 | 4530 | 0.9293 |
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- | 1.1729 | 31.0 | 4681 | 0.9333 |
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- | 1.1641 | 32.0 | 4832 | 0.9146 |
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- | 1.1402 | 33.0 | 4983 | 0.9348 |
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- | 1.156 | 34.0 | 5134 | 0.9283 |
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- | 1.1562 | 35.0 | 5285 | 0.9428 |
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- | 1.1273 | 36.0 | 5436 | 0.9155 |
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- | 1.1258 | 37.0 | 5587 | 0.9424 |
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- | 1.1467 | 38.0 | 5738 | 0.9435 |
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- | 1.1284 | 39.0 | 5889 | 0.9089 |
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- | 1.1113 | 40.0 | 6040 | 0.9038 |
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- | 1.1025 | 41.0 | 6191 | 0.8817 |
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- | 1.0797 | 42.0 | 6342 | 0.8926 |
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- | 1.0803 | 43.0 | 6493 | 0.8805 |
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- | 1.0867 | 44.0 | 6644 | 0.8845 |
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- | 1.0646 | 45.0 | 6795 | 0.8696 |
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- | 1.0766 | 46.0 | 6946 | 0.8768 |
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- | 1.0653 | 47.0 | 7097 | 0.8643 |
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- | 1.0615 | 48.0 | 7248 | 0.8796 |
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- | 1.0514 | 49.0 | 7399 | 0.8712 |
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- | 1.0423 | 50.0 | 7550 | 0.8654 |
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- | 1.0291 | 51.0 | 7701 | 0.8345 |
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- | 1.046 | 52.0 | 7852 | 0.8521 |
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- | 1.0095 | 53.0 | 8003 | 0.8407 |
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- | 1.028 | 54.0 | 8154 | 0.8673 |
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- | 0.9932 | 55.0 | 8305 | 0.8398 |
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- | 0.9966 | 56.0 | 8456 | 0.8441 |
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- | 0.9961 | 57.0 | 8607 | 0.8362 |
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- | 0.9902 | 58.0 | 8758 | 0.8379 |
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- | 0.9802 | 59.0 | 8909 | 0.8337 |
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- | 0.9806 | 60.0 | 9060 | 0.8284 |
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- | 0.9671 | 61.0 | 9211 | 0.8259 |
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- | 0.9627 | 62.0 | 9362 | 0.8297 |
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- | 0.9535 | 63.0 | 9513 | 0.8434 |
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- | 0.953 | 64.0 | 9664 | 0.8236 |
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- | 0.9444 | 65.0 | 9815 | 0.8190 |
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- | 0.9329 | 66.0 | 9966 | 0.8189 |
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- | 0.9461 | 67.0 | 10117 | 0.8255 |
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- | 0.9235 | 68.0 | 10268 | 0.8205 |
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- | 0.9328 | 69.0 | 10419 | 0.8311 |
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- | 0.9128 | 70.0 | 10570 | 0.8234 |
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- | 0.9007 | 71.0 | 10721 | 0.8207 |
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- | 0.9064 | 72.0 | 10872 | 0.8331 |
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- | 0.8921 | 73.0 | 11023 | 0.8198 |
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- | 0.8883 | 74.0 | 11174 | 0.8236 |
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- | 0.8919 | 75.0 | 11325 | 0.8233 |
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- | 0.89 | 76.0 | 11476 | 0.8205 |
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- | 0.8815 | 77.0 | 11627 | 0.8196 |
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- | 0.8949 | 78.0 | 11778 | 0.8284 |
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- | 0.8816 | 79.0 | 11929 | 0.8186 |
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- | 0.8641 | 80.0 | 12080 | 0.8247 |
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- | 0.8697 | 81.0 | 12231 | 0.8133 |
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- | 0.8641 | 82.0 | 12382 | 0.8247 |
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- | 0.8437 | 83.0 | 12533 | 0.8293 |
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- | 0.8503 | 84.0 | 12684 | 0.8229 |
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- | 0.8446 | 85.0 | 12835 | 0.8158 |
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- | 0.835 | 86.0 | 12986 | 0.8099 |
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- | 0.8328 | 87.0 | 13137 | 0.8143 |
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- | 0.8332 | 88.0 | 13288 | 0.8273 |
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- | 0.8316 | 89.0 | 13439 | 0.8336 |
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- | 0.8223 | 90.0 | 13590 | 0.8273 |
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- | 0.8097 | 91.0 | 13741 | 0.8208 |
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- | 0.8063 | 92.0 | 13892 | 0.8248 |
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- | 0.7967 | 93.0 | 14043 | 0.8263 |
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- | 0.7916 | 94.0 | 14194 | 0.8302 |
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- | 0.7918 | 95.0 | 14345 | 0.8303 |
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- | 0.7935 | 96.0 | 14496 | 0.8321 |
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- | 0.8028 | 97.0 | 14647 | 0.8300 |
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- | 0.7961 | 98.0 | 14798 | 0.8301 |
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- | 0.7773 | 99.0 | 14949 | 0.8285 |
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- | 0.7741 | 100.0 | 15100 | 0.8292 |
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  ### Framework versions
 
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  tags:
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  - generated_from_trainer
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  model-index:
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+ - name: trashify-box-detection-model-synthetic-data-only
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  results: []
9
  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
12
  should probably proofread and complete it, then remove this comment. -->
13
 
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+ # trashify-box-detection-model-synthetic-data-only
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+ This model is a fine-tuned version of [microsoft/conditional-detr-resnet-50](https://huggingface.co/microsoft/conditional-detr-resnet-50) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.7824
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:-----:|:---------------:|
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+ | 67.3985 | 1.0 | 118 | 4.7679 |
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+ | 3.2012 | 2.0 | 236 | 2.1811 |
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+ | 2.1642 | 3.0 | 354 | 1.6674 |
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+ | 1.7756 | 4.0 | 472 | 1.3667 |
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+ | 1.5894 | 5.0 | 590 | 1.3178 |
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+ | 1.497 | 6.0 | 708 | 1.1129 |
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+ | 1.4228 | 7.0 | 826 | 1.1679 |
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+ | 1.4065 | 8.0 | 944 | 1.1444 |
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+ | 1.4096 | 9.0 | 1062 | 1.1029 |
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+ | 1.3762 | 10.0 | 1180 | 1.0651 |
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+ | 1.33 | 11.0 | 1298 | 1.0473 |
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+ | 1.3183 | 12.0 | 1416 | 1.0753 |
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+ | 1.3158 | 13.0 | 1534 | 1.0515 |
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+ | 1.2898 | 14.0 | 1652 | 0.9913 |
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+ | 1.292 | 15.0 | 1770 | 0.9918 |
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+ | 1.2323 | 16.0 | 1888 | 0.9896 |
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+ | 1.2356 | 17.0 | 2006 | 1.0034 |
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+ | 1.2407 | 18.0 | 2124 | 0.9813 |
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+ | 1.2384 | 19.0 | 2242 | 0.9685 |
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+ | 1.2229 | 20.0 | 2360 | 0.9606 |
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+ | 1.2011 | 21.0 | 2478 | 0.9410 |
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+ | 1.1809 | 22.0 | 2596 | 0.9628 |
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+ | 1.2145 | 23.0 | 2714 | 0.9707 |
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+ | 1.208 | 24.0 | 2832 | 0.9811 |
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+ | 1.2109 | 25.0 | 2950 | 0.9749 |
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+ | 1.2073 | 26.0 | 3068 | 0.9966 |
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+ | 1.1875 | 27.0 | 3186 | 0.9225 |
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+ | 1.1786 | 28.0 | 3304 | 0.9692 |
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+ | 1.1782 | 29.0 | 3422 | 0.9331 |
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+ | 1.1617 | 30.0 | 3540 | 0.9494 |
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+ | 1.1636 | 31.0 | 3658 | 0.9176 |
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+ | 1.1391 | 32.0 | 3776 | 0.9059 |
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+ | 1.1643 | 33.0 | 3894 | 0.9177 |
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+ | 1.1486 | 34.0 | 4012 | 0.9351 |
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+ | 1.1229 | 35.0 | 4130 | 0.9027 |
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+ | 1.11 | 36.0 | 4248 | 0.9060 |
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+ | 1.112 | 37.0 | 4366 | 0.8910 |
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+ | 1.1112 | 38.0 | 4484 | 0.8954 |
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+ | 1.0994 | 39.0 | 4602 | 0.8769 |
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+ | 1.0821 | 40.0 | 4720 | 0.9111 |
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+ | 1.088 | 41.0 | 4838 | 0.8496 |
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+ | 1.049 | 42.0 | 4956 | 0.8694 |
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+ | 1.0804 | 43.0 | 5074 | 0.8783 |
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+ | 1.0643 | 44.0 | 5192 | 0.8671 |
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+ | 1.06 | 45.0 | 5310 | 0.8707 |
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+ | 1.0558 | 46.0 | 5428 | 0.8754 |
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+ | 1.0448 | 47.0 | 5546 | 0.8606 |
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+ | 1.0341 | 48.0 | 5664 | 0.8649 |
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+ | 1.0433 | 49.0 | 5782 | 0.8479 |
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+ | 1.0211 | 50.0 | 5900 | 0.8530 |
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+ | 1.0186 | 51.0 | 6018 | 0.8419 |
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+ | 0.9921 | 52.0 | 6136 | 0.8340 |
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+ | 1.0261 | 53.0 | 6254 | 0.8279 |
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+ | 1.0006 | 54.0 | 6372 | 0.8395 |
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+ | 0.9926 | 55.0 | 6490 | 0.8368 |
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+ | 0.9965 | 56.0 | 6608 | 0.8197 |
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+ | 0.997 | 57.0 | 6726 | 0.8420 |
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+ | 0.9638 | 58.0 | 6844 | 0.8309 |
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+ | 0.9667 | 59.0 | 6962 | 0.8085 |
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+ | 0.9561 | 60.0 | 7080 | 0.8440 |
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+ | 0.9654 | 61.0 | 7198 | 0.8254 |
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+ | 0.969 | 62.0 | 7316 | 0.8226 |
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+ | 0.9621 | 63.0 | 7434 | 0.8033 |
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+ | 0.9466 | 64.0 | 7552 | 0.8182 |
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+ | 0.9406 | 65.0 | 7670 | 0.8176 |
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+ | 0.9365 | 66.0 | 7788 | 0.8037 |
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+ | 0.9163 | 67.0 | 7906 | 0.8124 |
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+ | 0.9133 | 68.0 | 8024 | 0.8080 |
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+ | 0.8986 | 69.0 | 8142 | 0.7981 |
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+ | 0.9227 | 70.0 | 8260 | 0.8112 |
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+ | 0.9212 | 71.0 | 8378 | 0.8031 |
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+ | 0.8991 | 72.0 | 8496 | 0.7998 |
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+ | 0.9026 | 73.0 | 8614 | 0.7971 |
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+ | 0.8794 | 74.0 | 8732 | 0.7959 |
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+ | 0.8874 | 75.0 | 8850 | 0.7961 |
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+ | 0.8922 | 76.0 | 8968 | 0.8009 |
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+ | 0.8905 | 77.0 | 9086 | 0.7930 |
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+ | 0.8785 | 78.0 | 9204 | 0.7991 |
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+ | 0.8723 | 79.0 | 9322 | 0.7887 |
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+ | 0.8634 | 80.0 | 9440 | 0.7800 |
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+ | 0.847 | 81.0 | 9558 | 0.7903 |
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+ | 0.8418 | 82.0 | 9676 | 0.7874 |
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+ | 0.852 | 83.0 | 9794 | 0.7950 |
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+ | 0.8322 | 84.0 | 9912 | 0.7967 |
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+ | 0.8489 | 85.0 | 10030 | 0.7806 |
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+ | 0.8359 | 86.0 | 10148 | 0.7919 |
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+ | 0.8279 | 87.0 | 10266 | 0.7896 |
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+ | 0.8453 | 88.0 | 10384 | 0.7926 |
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+ | 0.8029 | 89.0 | 10502 | 0.7913 |
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+ | 0.8088 | 90.0 | 10620 | 0.7843 |
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+ | 0.8269 | 91.0 | 10738 | 0.7820 |
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+ | 0.8201 | 92.0 | 10856 | 0.7880 |
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+ | 0.8177 | 93.0 | 10974 | 0.7847 |
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+ | 0.8224 | 94.0 | 11092 | 0.7869 |
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+ | 0.8134 | 95.0 | 11210 | 0.7869 |
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+ | 0.799 | 96.0 | 11328 | 0.7866 |
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+ | 0.8229 | 97.0 | 11446 | 0.7864 |
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+ | 0.7831 | 98.0 | 11564 | 0.7857 |
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+ | 0.7936 | 99.0 | 11682 | 0.7835 |
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+ | 0.7706 | 100.0 | 11800 | 0.7824 |
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  ### Framework versions
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