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ihsanahakiim
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videomae-base-finetuned-ucf101-subset

Video Classification
Transformers
TensorBoard
Safetensors
videomae
Generated from Trainer
Inference Endpoints
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  1. README.md +122 -122
  2. model.safetensors +1 -1
  3. runs/Jan20_13-17-28_GAN-SVR/events.out.tfevents.1737436793.GAN-SVR.864097.5 +3 -0
README.md CHANGED
@@ -18,8 +18,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.9989
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- - Accuracy: 0.5144
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  ## Model description
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@@ -51,126 +51,126 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
53
  |:-------------:|:--------:|:----:|:---------------:|:--------:|
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- | 4.2685 | 0.0083 | 16 | 4.2443 | 0.0144 |
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- | 4.2462 | 1.0083 | 32 | 4.2229 | 0.0165 |
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- | 4.2193 | 2.0083 | 48 | 4.2111 | 0.0129 |
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- | 4.2251 | 3.0083 | 64 | 4.2124 | 0.0136 |
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- | 4.231 | 4.0083 | 80 | 4.2131 | 0.0158 |
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- | 4.2197 | 5.0083 | 96 | 4.2091 | 0.0151 |
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- | 4.2239 | 6.0083 | 112 | 4.2100 | 0.0108 |
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- | 4.2246 | 7.0083 | 128 | 4.2119 | 0.0144 |
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- | 4.2131 | 8.0083 | 144 | 4.2030 | 0.0172 |
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- | 4.236 | 9.0083 | 160 | 4.1979 | 0.0129 |
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- | 4.177 | 10.0083 | 176 | 4.1328 | 0.0323 |
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- | 4.0656 | 11.0083 | 192 | 4.0373 | 0.0316 |
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- | 3.9339 | 12.0083 | 208 | 3.8848 | 0.0503 |
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- | 3.7197 | 13.0083 | 224 | 3.7681 | 0.0783 |
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- | 3.5657 | 14.0083 | 240 | 3.5790 | 0.1185 |
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- | 3.3108 | 15.0083 | 256 | 3.5642 | 0.1466 |
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- | 3.1687 | 16.0083 | 272 | 3.3210 | 0.1832 |
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- | 3.1376 | 17.0083 | 288 | 3.1950 | 0.2292 |
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- | 2.8366 | 18.0083 | 304 | 3.1270 | 0.2493 |
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- | 2.6811 | 19.0083 | 320 | 2.9997 | 0.2895 |
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- | 2.6104 | 20.0083 | 336 | 2.9776 | 0.2773 |
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- | 2.5156 | 21.0083 | 352 | 2.8625 | 0.3125 |
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- | 2.3804 | 22.0083 | 368 | 2.8223 | 0.2974 |
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- | 2.2389 | 23.0083 | 384 | 2.7042 | 0.3412 |
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- | 2.1889 | 24.0083 | 400 | 2.6846 | 0.3226 |
79
- | 1.9829 | 25.0083 | 416 | 2.6066 | 0.3592 |
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- | 1.9466 | 26.0083 | 432 | 2.5845 | 0.3642 |
81
- | 1.8991 | 27.0083 | 448 | 2.5150 | 0.3922 |
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- | 1.8629 | 28.0083 | 464 | 2.4958 | 0.3994 |
83
- | 1.8563 | 29.0083 | 480 | 2.5036 | 0.3994 |
84
- | 1.832 | 30.0083 | 496 | 2.4212 | 0.4037 |
85
- | 1.7148 | 31.0083 | 512 | 2.3891 | 0.4253 |
86
- | 1.6525 | 32.0083 | 528 | 2.3817 | 0.4109 |
87
- | 1.6489 | 33.0083 | 544 | 2.3351 | 0.4274 |
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- | 1.6928 | 34.0083 | 560 | 2.3495 | 0.4188 |
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- | 1.503 | 35.0083 | 576 | 2.2961 | 0.4274 |
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- | 1.5126 | 36.0083 | 592 | 2.2620 | 0.4454 |
91
- | 1.4732 | 37.0083 | 608 | 2.2635 | 0.4368 |
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- | 1.5553 | 38.0083 | 624 | 2.2326 | 0.4490 |
93
- | 1.7115 | 39.0083 | 640 | 2.2266 | 0.4404 |
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- | 1.4851 | 40.0083 | 656 | 2.2690 | 0.4274 |
95
- | 1.455 | 41.0083 | 672 | 2.1921 | 0.4569 |
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- | 1.4827 | 42.0083 | 688 | 2.2387 | 0.4504 |
97
- | 1.4839 | 43.0083 | 704 | 2.2020 | 0.4432 |
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- | 1.2879 | 44.0083 | 720 | 2.1959 | 0.4397 |
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- | 1.2722 | 45.0083 | 736 | 2.2158 | 0.4440 |
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- | 1.2225 | 46.0083 | 752 | 2.1568 | 0.4662 |
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- | 1.1821 | 47.0083 | 768 | 2.1312 | 0.4763 |
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- | 1.2406 | 48.0083 | 784 | 2.1162 | 0.4784 |
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- | 1.1717 | 49.0083 | 800 | 2.1368 | 0.4756 |
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- | 1.2366 | 50.0083 | 816 | 2.1134 | 0.4835 |
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- | 1.2534 | 51.0083 | 832 | 2.0964 | 0.4734 |
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- | 1.2322 | 52.0083 | 848 | 2.1506 | 0.4641 |
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- | 1.2742 | 53.0083 | 864 | 2.1719 | 0.4591 |
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- | 1.132 | 54.0083 | 880 | 2.1557 | 0.4648 |
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- | 1.1306 | 55.0083 | 896 | 2.1010 | 0.4878 |
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- | 1.2719 | 56.0083 | 912 | 2.1482 | 0.4619 |
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- | 1.1549 | 57.0083 | 928 | 2.0961 | 0.4813 |
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- | 1.1495 | 58.0083 | 944 | 2.1246 | 0.4763 |
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- | 1.2539 | 59.0083 | 960 | 2.1118 | 0.4806 |
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- | 1.1719 | 60.0083 | 976 | 2.0666 | 0.4935 |
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- | 1.1108 | 61.0083 | 992 | 2.0630 | 0.4835 |
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- | 1.0417 | 62.0083 | 1008 | 2.0635 | 0.4899 |
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- | 1.1755 | 63.0083 | 1024 | 2.0862 | 0.4720 |
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- | 1.0512 | 64.0083 | 1040 | 2.0730 | 0.4878 |
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- | 0.9824 | 65.0083 | 1056 | 2.0709 | 0.4907 |
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- | 1.0924 | 66.0083 | 1072 | 2.1638 | 0.4612 |
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- | 1.1027 | 67.0083 | 1088 | 2.0572 | 0.4777 |
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- | 1.0956 | 68.0083 | 1104 | 2.0502 | 0.4892 |
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- | 0.8823 | 69.0083 | 1120 | 2.1128 | 0.4756 |
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- | 1.0344 | 70.0083 | 1136 | 2.0950 | 0.4727 |
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- | 1.0887 | 71.0083 | 1152 | 2.0543 | 0.4943 |
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- | 1.0763 | 72.0083 | 1168 | 2.0535 | 0.4907 |
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- | 0.9652 | 73.0083 | 1184 | 2.0280 | 0.5 |
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- | 1.0445 | 74.0083 | 1200 | 2.0551 | 0.4820 |
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- | 0.9844 | 75.0083 | 1216 | 2.0514 | 0.5043 |
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- | 1.0809 | 76.0083 | 1232 | 2.0552 | 0.5022 |
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- | 1.1158 | 77.0083 | 1248 | 2.0469 | 0.4878 |
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- | 0.9017 | 78.0083 | 1264 | 2.0516 | 0.4907 |
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- | 1.0449 | 79.0083 | 1280 | 2.0770 | 0.4864 |
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- | 1.0167 | 80.0083 | 1296 | 2.0374 | 0.4943 |
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- | 0.975 | 81.0083 | 1312 | 2.0631 | 0.4943 |
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- | 0.9285 | 82.0083 | 1328 | 2.0499 | 0.4871 |
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- | 0.9762 | 83.0083 | 1344 | 2.0618 | 0.4964 |
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- | 0.9454 | 84.0083 | 1360 | 2.0462 | 0.4993 |
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- | 0.8665 | 85.0083 | 1376 | 2.0765 | 0.4892 |
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- | 0.9202 | 86.0083 | 1392 | 2.0513 | 0.4950 |
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- | 0.8186 | 87.0083 | 1408 | 2.0254 | 0.5093 |
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- | 0.8659 | 88.0083 | 1424 | 2.1060 | 0.4792 |
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- | 0.8789 | 89.0083 | 1440 | 2.0296 | 0.4964 |
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- | 0.8592 | 90.0083 | 1456 | 2.0757 | 0.4849 |
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- | 0.8093 | 91.0083 | 1472 | 2.0289 | 0.4986 |
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- | 0.9074 | 92.0083 | 1488 | 2.0539 | 0.4921 |
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- | 0.82 | 93.0083 | 1504 | 2.0481 | 0.5014 |
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- | 0.8318 | 94.0083 | 1520 | 2.0309 | 0.5022 |
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- | 0.8337 | 95.0083 | 1536 | 2.0335 | 0.5050 |
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- | 0.9089 | 96.0083 | 1552 | 2.0456 | 0.5022 |
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- | 0.8189 | 97.0083 | 1568 | 2.0107 | 0.4986 |
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- | 0.7603 | 98.0083 | 1584 | 2.0147 | 0.5072 |
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- | 0.9197 | 99.0083 | 1600 | 2.0438 | 0.5014 |
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- | 0.8021 | 100.0083 | 1616 | 2.0311 | 0.5 |
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- | 0.7474 | 101.0083 | 1632 | 2.0348 | 0.5007 |
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- | 0.9423 | 102.0083 | 1648 | 2.0177 | 0.5007 |
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- | 0.8135 | 103.0083 | 1664 | 2.0140 | 0.5029 |
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- | 0.8244 | 104.0083 | 1680 | 2.0124 | 0.4986 |
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- | 0.8446 | 105.0083 | 1696 | 2.0022 | 0.5065 |
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- | 0.7965 | 106.0083 | 1712 | 1.9957 | 0.5108 |
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- | 0.8256 | 107.0083 | 1728 | 1.9995 | 0.5108 |
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- | 0.8448 | 108.0083 | 1744 | 2.0056 | 0.5093 |
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- | 0.7144 | 109.0083 | 1760 | 2.0084 | 0.5072 |
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- | 0.7869 | 110.0083 | 1776 | 1.9967 | 0.5115 |
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- | 0.8149 | 111.0083 | 1792 | 1.9973 | 0.5115 |
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- | 0.7896 | 112.0083 | 1808 | 2.0014 | 0.5122 |
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- | 0.8189 | 113.0083 | 1824 | 1.9989 | 0.5144 |
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- | 0.6775 | 114.0083 | 1840 | 1.9957 | 0.5122 |
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- | 0.8642 | 115.0083 | 1856 | 2.0001 | 0.5101 |
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- | 0.7308 | 116.0083 | 1872 | 1.9895 | 0.5086 |
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- | 0.8616 | 117.0083 | 1888 | 1.9854 | 0.5079 |
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- | 0.7763 | 118.0083 | 1904 | 1.9896 | 0.5072 |
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- | 0.8009 | 119.0083 | 1920 | 1.9903 | 0.5072 |
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  ### Framework versions
 
18
 
19
  This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset.
20
  It achieves the following results on the evaluation set:
21
+ - Loss: 0.5552
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+ - Accuracy: 0.8630
23
 
24
  ## Model description
25
 
 
51
 
52
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:--------:|:----:|:---------------:|:--------:|
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+ | 0.4529 | 0.0083 | 16 | 1.0265 | 0.7074 |
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+ | 0.2409 | 1.0083 | 32 | 0.8731 | 0.7630 |
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+ | 0.21 | 2.0083 | 48 | 0.8199 | 0.7481 |
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+ | 0.149 | 3.0083 | 64 | 0.8314 | 0.7593 |
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+ | 0.1131 | 4.0083 | 80 | 0.7753 | 0.7741 |
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+ | 0.1177 | 5.0083 | 96 | 0.7645 | 0.7667 |
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+ | 0.1106 | 6.0083 | 112 | 0.8109 | 0.7407 |
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+ | 0.1346 | 7.0083 | 128 | 0.6663 | 0.7963 |
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+ | 0.1054 | 8.0083 | 144 | 0.7931 | 0.7852 |
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+ | 0.1302 | 9.0083 | 160 | 0.8380 | 0.7593 |
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+ | 0.1201 | 10.0083 | 176 | 0.7758 | 0.7704 |
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+ | 0.0992 | 11.0083 | 192 | 0.9272 | 0.7259 |
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+ | 0.11 | 12.0083 | 208 | 0.8363 | 0.7667 |
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+ | 0.122 | 13.0083 | 224 | 0.6285 | 0.8111 |
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+ | 0.1336 | 14.0083 | 240 | 0.6990 | 0.8185 |
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+ | 0.0996 | 15.0083 | 256 | 0.7357 | 0.8037 |
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+ | 0.0711 | 16.0083 | 272 | 0.6621 | 0.8222 |
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+ | 0.0839 | 17.0083 | 288 | 0.7744 | 0.7815 |
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+ | 0.0865 | 18.0083 | 304 | 0.6456 | 0.8222 |
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+ | 0.0607 | 19.0083 | 320 | 0.7278 | 0.7963 |
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+ | 0.0672 | 20.0083 | 336 | 0.7863 | 0.8 |
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+ | 0.0575 | 21.0083 | 352 | 0.6789 | 0.8185 |
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+ | 0.0527 | 22.0083 | 368 | 0.6201 | 0.8148 |
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+ | 0.0856 | 23.0083 | 384 | 0.6439 | 0.8 |
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+ | 0.0621 | 24.0083 | 400 | 0.8606 | 0.7704 |
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+ | 0.0725 | 25.0083 | 416 | 0.6359 | 0.8222 |
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+ | 0.0659 | 26.0083 | 432 | 0.6513 | 0.8259 |
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+ | 0.036 | 27.0083 | 448 | 0.6300 | 0.8111 |
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+ | 0.0337 | 28.0083 | 464 | 0.6411 | 0.8444 |
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+ | 0.0249 | 29.0083 | 480 | 0.5657 | 0.8593 |
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+ | 0.0236 | 30.0083 | 496 | 0.5585 | 0.8296 |
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+ | 0.0488 | 31.0083 | 512 | 0.6617 | 0.8148 |
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+ | 0.0327 | 32.0083 | 528 | 0.5680 | 0.8407 |
87
+ | 0.0367 | 33.0083 | 544 | 0.7030 | 0.7963 |
88
+ | 0.0226 | 34.0083 | 560 | 0.8866 | 0.7593 |
89
+ | 0.0277 | 35.0083 | 576 | 0.8434 | 0.7963 |
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+ | 0.0136 | 36.0083 | 592 | 0.7818 | 0.7778 |
91
+ | 0.017 | 37.0083 | 608 | 0.7851 | 0.7593 |
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+ | 0.0391 | 38.0083 | 624 | 1.0256 | 0.7481 |
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+ | 0.0211 | 39.0083 | 640 | 0.9225 | 0.7593 |
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+ | 0.0322 | 40.0083 | 656 | 0.7322 | 0.7926 |
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+ | 0.0203 | 41.0083 | 672 | 0.7956 | 0.7852 |
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+ | 0.0223 | 42.0083 | 688 | 0.8495 | 0.7704 |
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+ | 0.0228 | 43.0083 | 704 | 0.6640 | 0.8259 |
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+ | 0.0115 | 44.0083 | 720 | 0.9645 | 0.7593 |
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+ | 0.0222 | 45.0083 | 736 | 0.6595 | 0.8333 |
100
+ | 0.0165 | 46.0083 | 752 | 0.7120 | 0.7963 |
101
+ | 0.0165 | 47.0083 | 768 | 0.8027 | 0.8 |
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+ | 0.0166 | 48.0083 | 784 | 0.8485 | 0.7963 |
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+ | 0.0097 | 49.0083 | 800 | 0.8504 | 0.7926 |
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+ | 0.0257 | 50.0083 | 816 | 0.7934 | 0.7963 |
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+ | 0.0172 | 51.0083 | 832 | 0.7562 | 0.8037 |
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+ | 0.0064 | 52.0083 | 848 | 0.7097 | 0.8111 |
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+ | 0.0052 | 53.0083 | 864 | 0.7537 | 0.7963 |
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+ | 0.012 | 54.0083 | 880 | 0.7386 | 0.8074 |
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+ | 0.0174 | 55.0083 | 896 | 0.6894 | 0.8222 |
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+ | 0.0151 | 56.0083 | 912 | 0.9360 | 0.7667 |
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+ | 0.0081 | 57.0083 | 928 | 0.7102 | 0.8222 |
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+ | 0.0142 | 58.0083 | 944 | 0.7866 | 0.8111 |
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+ | 0.0169 | 59.0083 | 960 | 0.6516 | 0.8370 |
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+ | 0.0149 | 60.0083 | 976 | 1.0039 | 0.7556 |
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+ | 0.0106 | 61.0083 | 992 | 0.6570 | 0.8407 |
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+ | 0.005 | 62.0083 | 1008 | 0.7252 | 0.8037 |
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+ | 0.0115 | 63.0083 | 1024 | 0.6913 | 0.8333 |
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+ | 0.0059 | 64.0083 | 1040 | 0.6858 | 0.8481 |
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+ | 0.0225 | 65.0083 | 1056 | 0.7342 | 0.8148 |
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+ | 0.0151 | 66.0083 | 1072 | 0.6860 | 0.8259 |
121
+ | 0.0098 | 67.0083 | 1088 | 0.7041 | 0.8296 |
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+ | 0.0097 | 68.0083 | 1104 | 0.7321 | 0.8185 |
123
+ | 0.014 | 69.0083 | 1120 | 0.6251 | 0.8481 |
124
+ | 0.0252 | 70.0083 | 1136 | 0.6771 | 0.8370 |
125
+ | 0.0052 | 71.0083 | 1152 | 0.7527 | 0.8 |
126
+ | 0.0189 | 72.0083 | 1168 | 0.6936 | 0.8222 |
127
+ | 0.0038 | 73.0083 | 1184 | 0.6541 | 0.8296 |
128
+ | 0.0027 | 74.0083 | 1200 | 0.7257 | 0.8074 |
129
+ | 0.0028 | 75.0083 | 1216 | 0.6686 | 0.8185 |
130
+ | 0.0034 | 76.0083 | 1232 | 0.6239 | 0.8370 |
131
+ | 0.0111 | 77.0083 | 1248 | 0.7719 | 0.7926 |
132
+ | 0.009 | 78.0083 | 1264 | 0.6882 | 0.8185 |
133
+ | 0.0038 | 79.0083 | 1280 | 0.7040 | 0.8222 |
134
+ | 0.005 | 80.0083 | 1296 | 0.6955 | 0.8370 |
135
+ | 0.003 | 81.0083 | 1312 | 0.6797 | 0.8481 |
136
+ | 0.0035 | 82.0083 | 1328 | 0.6548 | 0.8370 |
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+ | 0.0029 | 83.0083 | 1344 | 0.6407 | 0.8370 |
138
+ | 0.0131 | 84.0083 | 1360 | 0.6152 | 0.8407 |
139
+ | 0.0026 | 85.0083 | 1376 | 0.5863 | 0.8444 |
140
+ | 0.0048 | 86.0083 | 1392 | 0.6048 | 0.8519 |
141
+ | 0.0032 | 87.0083 | 1408 | 0.6064 | 0.8481 |
142
+ | 0.0067 | 88.0083 | 1424 | 0.6492 | 0.8370 |
143
+ | 0.0077 | 89.0083 | 1440 | 0.7520 | 0.7852 |
144
+ | 0.012 | 90.0083 | 1456 | 0.7662 | 0.8037 |
145
+ | 0.0092 | 91.0083 | 1472 | 0.7106 | 0.8074 |
146
+ | 0.0034 | 92.0083 | 1488 | 0.7589 | 0.8111 |
147
+ | 0.0042 | 93.0083 | 1504 | 0.6382 | 0.8296 |
148
+ | 0.0053 | 94.0083 | 1520 | 0.6153 | 0.8519 |
149
+ | 0.0038 | 95.0083 | 1536 | 0.6227 | 0.8370 |
150
+ | 0.002 | 96.0083 | 1552 | 0.6424 | 0.8407 |
151
+ | 0.0063 | 97.0083 | 1568 | 0.6215 | 0.8481 |
152
+ | 0.0021 | 98.0083 | 1584 | 0.6355 | 0.8333 |
153
+ | 0.0022 | 99.0083 | 1600 | 0.6141 | 0.8407 |
154
+ | 0.002 | 100.0083 | 1616 | 0.5682 | 0.8519 |
155
+ | 0.0058 | 101.0083 | 1632 | 0.5804 | 0.8519 |
156
+ | 0.0027 | 102.0083 | 1648 | 0.5724 | 0.8556 |
157
+ | 0.0026 | 103.0083 | 1664 | 0.5557 | 0.8630 |
158
+ | 0.0016 | 104.0083 | 1680 | 0.5465 | 0.8593 |
159
+ | 0.0018 | 105.0083 | 1696 | 0.5636 | 0.8630 |
160
+ | 0.0022 | 106.0083 | 1712 | 0.5932 | 0.8519 |
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+ | 0.0018 | 107.0083 | 1728 | 0.5884 | 0.8593 |
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+ | 0.0018 | 108.0083 | 1744 | 0.5960 | 0.8519 |
163
+ | 0.0041 | 109.0083 | 1760 | 0.5984 | 0.8556 |
164
+ | 0.0019 | 110.0083 | 1776 | 0.6015 | 0.8519 |
165
+ | 0.0031 | 111.0083 | 1792 | 0.5941 | 0.8593 |
166
+ | 0.0056 | 112.0083 | 1808 | 0.5957 | 0.8593 |
167
+ | 0.0014 | 113.0083 | 1824 | 0.6007 | 0.8593 |
168
+ | 0.0145 | 114.0083 | 1840 | 0.6138 | 0.8444 |
169
+ | 0.002 | 115.0083 | 1856 | 0.6205 | 0.8407 |
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+ | 0.0046 | 116.0083 | 1872 | 0.6194 | 0.8444 |
171
+ | 0.0018 | 117.0083 | 1888 | 0.6189 | 0.8444 |
172
+ | 0.0023 | 118.0083 | 1904 | 0.6391 | 0.8444 |
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+ | 0.0021 | 119.0083 | 1920 | 0.6227 | 0.8481 |
174
 
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  ### Framework versions
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