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segformer-finetuned-sidewalk-10k-steps

Image Segmentation
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PyTorch
TensorBoard
segformer
vision
generated_from_trainer
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segformer-finetuned-sidewalk-10k-steps

This model is a fine-tuned version of nvidia/mit-b0 on the segments/sidewalk-semantic dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6468
  • Mean Iou: 0.2931
  • Mean Accuracy: 0.3665
  • Overall Accuracy: 0.8121
  • Accuracy Unlabeled: nan
  • Accuracy Flat-road: 0.6505
  • Accuracy Flat-sidewalk: 0.9345
  • Accuracy Flat-crosswalk: 0.9011
  • Accuracy Flat-cyclinglane: 0.7895
  • Accuracy Flat-parkingdriveway: 0.2382
  • Accuracy Flat-railtrack: 0.0
  • Accuracy Flat-curb: 0.4519
  • Accuracy Human-person: 0.5536
  • Accuracy Human-rider: 0.0
  • Accuracy Vehicle-car: 0.9509
  • Accuracy Vehicle-truck: 0.0
  • Accuracy Vehicle-bus: 0.0
  • Accuracy Vehicle-tramtrain: 0.0
  • Accuracy Vehicle-motorcycle: 0.0
  • Accuracy Vehicle-bicycle: 0.7507
  • Accuracy Vehicle-caravan: nan
  • Accuracy Vehicle-cartrailer: 0.0
  • Accuracy Construction-building: 0.8681
  • Accuracy Construction-door: 0.0
  • Accuracy Construction-wall: 0.6107
  • Accuracy Construction-fenceguardrail: 0.3192
  • Accuracy Construction-bridge: 0.0
  • Accuracy Construction-tunnel: nan
  • Accuracy Construction-stairs: 0.0
  • Accuracy Object-pole: 0.5156
  • Accuracy Object-trafficsign: 0.0
  • Accuracy Object-trafficlight: 0.0
  • Accuracy Nature-vegetation: 0.9183
  • Accuracy Nature-terrain: 0.8478
  • Accuracy Sky: 0.9246
  • Accuracy Void-ground: 0.0
  • Accuracy Void-dynamic: 0.1083
  • Accuracy Void-static: 0.3940
  • Accuracy Void-unclear: 0.0
  • Iou Unlabeled: nan
  • Iou Flat-road: 0.5472
  • Iou Flat-sidewalk: 0.8329
  • Iou Flat-crosswalk: 0.7961
  • Iou Flat-cyclinglane: 0.5266
  • Iou Flat-parkingdriveway: 0.2013
  • Iou Flat-railtrack: 0.0
  • Iou Flat-curb: 0.2863
  • Iou Human-person: 0.3887
  • Iou Human-rider: 0.0
  • Iou Vehicle-car: 0.7872
  • Iou Vehicle-truck: 0.0
  • Iou Vehicle-bus: 0.0
  • Iou Vehicle-tramtrain: 0.0
  • Iou Vehicle-motorcycle: 0.0
  • Iou Vehicle-bicycle: 0.4759
  • Iou Vehicle-caravan: nan
  • Iou Vehicle-cartrailer: 0.0
  • Iou Construction-building: 0.6992
  • Iou Construction-door: 0.0
  • Iou Construction-wall: 0.3924
  • Iou Construction-fenceguardrail: 0.2614
  • Iou Construction-bridge: 0.0
  • Iou Construction-tunnel: nan
  • Iou Construction-stairs: 0.0
  • Iou Object-pole: 0.3413
  • Iou Object-trafficsign: 0.0
  • Iou Object-trafficlight: 0.0
  • Iou Nature-vegetation: 0.8182
  • Iou Nature-terrain: 0.7517
  • Iou Sky: 0.8855
  • Iou Void-ground: 0.0
  • Iou Void-dynamic: 0.0963
  • Iou Void-static: 0.2896
  • Iou Void-unclear: 0.0

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 6e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 1337
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: polynomial
  • training_steps: 10000

Training results

Training Loss Epoch Step Accuracy Construction-bridge Accuracy Construction-building Accuracy Construction-door Accuracy Construction-fenceguardrail Accuracy Construction-stairs Accuracy Construction-tunnel Accuracy Construction-wall Accuracy Flat-crosswalk Accuracy Flat-curb Accuracy Flat-cyclinglane Accuracy Flat-parkingdriveway Accuracy Flat-railtrack Accuracy Flat-road Accuracy Flat-sidewalk Accuracy Human-person Accuracy Human-rider Accuracy Nature-terrain Accuracy Nature-vegetation Accuracy Object-pole Accuracy Object-trafficlight Accuracy Object-trafficsign Accuracy Sky Accuracy Unlabeled Accuracy Vehicle-bicycle Accuracy Vehicle-bus Accuracy Vehicle-car Accuracy Vehicle-caravan Accuracy Vehicle-cartrailer Accuracy Vehicle-motorcycle Accuracy Vehicle-tramtrain Accuracy Vehicle-truck Accuracy Void-dynamic Accuracy Void-ground Accuracy Void-static Accuracy Void-unclear Iou Construction-bridge Iou Construction-building Iou Construction-door Iou Construction-fenceguardrail Iou Construction-stairs Iou Construction-tunnel Iou Construction-wall Iou Flat-crosswalk Iou Flat-curb Iou Flat-cyclinglane Iou Flat-parkingdriveway Iou Flat-railtrack Iou Flat-road Iou Flat-sidewalk Iou Human-person Iou Human-rider Iou Nature-terrain Iou Nature-vegetation Iou Object-pole Iou Object-trafficlight Iou Object-trafficsign Iou Sky Iou Unlabeled Iou Vehicle-bicycle Iou Vehicle-bus Iou Vehicle-car Iou Vehicle-caravan Iou Vehicle-cartrailer Iou Vehicle-motorcycle Iou Vehicle-tramtrain Iou Vehicle-truck Iou Void-dynamic Iou Void-ground Iou Void-static Iou Void-unclear Validation Loss Mean Accuracy Mean Iou Overall Accuracy
2.5227 1.0 107 0.0 0.8334 0.0 0.0 0.0 nan 0.0000 0.0 0.0 0.0416 0.0001 nan 0.5390 0.9293 0.0 0.0 0.2834 0.9261 0.0 0.0 0.0 0.5133 nan 0.0 0.0 0.8875 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4909 0.0 0.0 0.0 nan 0.0000 0.0 0.0 0.0411 0.0001 nan 0.3808 0.7051 0.0 0.0 0.2534 0.5904 0.0 0.0 0.0 0.5116 nan 0.0 0.0 0.5403 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.7749 0.1548 0.1098 0.6606
1.7544 2.0 214 0.0 0.8141 0.0 0.0 0.0 nan 0.0024 0.0 0.0 0.2967 0.0009 nan 0.6039 0.9275 0.0 0.0 0.8832 0.8157 0.0 0.0 0.0 0.7111 nan 0.0 0.0 0.9009 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5356 0.0 0.0 0.0 nan 0.0024 0.0 0.0 0.2702 0.0009 nan 0.4296 0.7139 0.0 0.0 0.5124 0.6367 0.0 0.0 0.0 0.7016 nan 0.0 0.0 0.5653 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.4883 0.1861 0.1365 0.6975
1.523 3.0 321 0.0 0.8975 0.0 0.0 0.0 nan 0.0009 0.0 0.0003 0.5309 0.0063 nan 0.4954 0.9432 0.0 0.0 0.8476 0.8378 0.0 0.0 0.0 0.7705 nan 0.0 0.0 0.8567 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5155 0.0 0.0 0.0 nan 0.0009 0.0 0.0003 0.4164 0.0062 nan 0.4161 0.7219 0.0 0.0 0.5408 0.6765 0.0 0.0 0.0 0.7594 nan 0.0 0.0 0.6132 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.2403 0.1934 0.1459 0.7123
1.2744 4.0 428 0.0 0.8602 0.0 0.0 0.0 nan 0.0009 0.0 0.0015 0.4753 0.0069 nan 0.3731 0.9792 0.0 0.0 0.7062 0.8948 0.0 0.0 0.0 0.7488 nan 0.0 0.0 0.8857 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5565 0.0 0.0 0.0 nan 0.0009 0.0 0.0015 0.4431 0.0068 nan 0.3413 0.6728 0.0 0.0 0.5473 0.6788 0.0 0.0 0.0 0.7389 nan 0.0 0.0 0.6552 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.1870 0.1854 0.1451 0.7068
1.1579 5.0 535 0.0 0.7388 0.0 0.0 0.0 nan 0.0008 0.0 0.0040 0.6937 0.0681 nan 0.5908 0.9639 0.0 0.0 0.5152 0.9429 0.0 0.0 0.0 0.8365 nan 0.0 0.0 0.9525 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5687 0.0 0.0 0.0 nan 0.0008 0.0 0.0039 0.5783 0.0606 nan 0.4884 0.7434 0.0 0.0 0.4397 0.6660 0.0 0.0 0.0 0.8076 nan 0.0 0.0 0.5868 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0435 0.1971 0.1545 0.7340
1.0928 6.0 642 0.0 0.8126 0.0 0.0 0.0 nan 0.0127 0.1193 0.0326 0.7981 0.1432 nan 0.6767 0.9152 0.0 0.0 0.8393 0.8990 0.0115 0.0 0.0 0.8664 nan 0.0 0.0 0.9427 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0048 0.0 0.0 0.6031 0.0 0.0 0.0 nan 0.0126 0.1193 0.0298 0.6282 0.1206 nan 0.5205 0.7688 0.0 0.0 0.6037 0.6827 0.0113 0.0 0.0 0.8312 nan 0.0 0.0 0.5963 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0047 0.0 0.9777 0.2211 0.1729 0.7531
1.0371 7.0 749 0.0 0.8108 0.0 0.0 0.0 nan 0.0145 0.2878 0.0499 0.7673 0.1179 nan 0.5506 0.9510 0.0 0.0 0.8458 0.8788 0.0158 0.0 0.0 0.8125 nan 0.0 0.0 0.9351 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0032 0.0 0.0 0.5687 0.0 0.0 0.0 nan 0.0143 0.2871 0.0416 0.5650 0.1067 nan 0.4769 0.7722 0.0 0.0 0.5986 0.6729 0.0154 0.0 0.0 0.7949 nan 0.0 0.0 0.5910 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0032 0.0 0.9290 0.2200 0.1722 0.7457
0.9645 8.0 856 0.0 0.8913 0.0 0.0 0.0 nan 0.0530 0.3879 0.1304 0.8027 0.1244 nan 0.5733 0.9459 0.0 0.0 0.8434 0.8598 0.1344 0.0 0.0 0.8596 nan 0.0 0.0 0.9192 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0196 0.0 0.0 0.5899 0.0 0.0 0.0 nan 0.0518 0.3362 0.0872 0.6482 0.1137 nan 0.4887 0.7610 0.0 0.0 0.6153 0.7148 0.1144 0.0 0.0 0.8278 nan 0.0 0.0 0.6957 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0192 0.0 0.8855 0.2358 0.1895 0.7593
0.9171 9.0 963 0.0 0.8681 0.0 0.0 0.0 nan 0.2267 0.2895 0.1798 0.7741 0.2153 nan 0.6580 0.9264 0.0009 0.0 0.7788 0.8887 0.1800 0.0 0.0 0.8648 nan 0.0 0.0 0.9422 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0689 0.0 0.0 0.6112 0.0 0.0 0.0 nan 0.2013 0.2859 0.1173 0.6393 0.1769 nan 0.5251 0.7761 0.0009 0.0 0.6220 0.7328 0.1391 0.0 0.0 0.8329 nan 0.0 0.0 0.6550 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0622 0.0 0.8439 0.2457 0.1993 0.7676
0.8373 10.0 1070 0.0 0.8391 0.0 0.0000 0.0 nan 0.4409 0.3294 0.1364 0.7858 0.1023 nan 0.6096 0.9644 0.0756 0.0 0.6853 0.8993 0.1614 0.0 0.0 0.8876 nan 0.0 0.0 0.9315 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0874 0.0 0.0 0.6203 0.0 0.0000 0.0 nan 0.2914 0.3283 0.1050 0.6096 0.0951 nan 0.5427 0.7678 0.0740 0.0 0.5665 0.7403 0.1321 0.0 0.0 0.8500 nan 0.0 0.0 0.6756 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0767 0.0 0.8317 0.2480 0.2024 0.7710
0.8375 11.0 1177 0.0 0.8248 0.0 0.0000 0.0 nan 0.3739 0.3951 0.2834 0.7626 0.1777 nan 0.4734 0.9515 0.1276 0.0 0.7447 0.9010 0.1872 0.0 0.0 0.9018 nan 0.0 0.0 0.9378 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0591 0.0 0.0 0.6017 0.0 0.0000 0.0 nan 0.2379 0.3570 0.1503 0.6432 0.1533 nan 0.4411 0.7743 0.1234 0.0 0.5987 0.7041 0.1362 0.0 0.0 0.8576 nan 0.0 0.0 0.6553 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0518 0.0 0.8539 0.2532 0.2027 0.7577
0.8014 12.0 1284 0.0 0.8213 0.0 0.0002 0.0 nan 0.4219 0.5045 0.3125 0.8556 0.2246 nan 0.6546 0.8896 0.2522 0.0 0.7563 0.9184 0.2091 0.0 0.0 0.8852 nan 0.0 0.0 0.9338 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1150 0.0 0.0 0.6244 0.0 0.0002 0.0 nan 0.2819 0.4181 0.1371 0.5936 0.1892 nan 0.5497 0.7848 0.2332 0.0 0.6418 0.7339 0.1582 0.0 0.0 0.8537 nan 0.0 0.0 0.6887 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0936 0.0 0.7821 0.2736 0.2182 0.7698
0.7598 13.0 1391 0.0 0.7520 0.0 0.0 0.0 nan 0.5035 0.5241 0.2865 0.8708 0.1666 nan 0.6404 0.8870 0.2805 0.0 0.7662 0.9230 0.3694 0.0 0.0 0.8932 nan 0.0 0.0 0.9492 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2009 0.0 0.0 0.6246 0.0 0.0 0.0 nan 0.3111 0.4894 0.1504 0.5451 0.1555 nan 0.5227 0.7890 0.2569 0.0 0.6171 0.7275 0.1555 0.0 0.0 0.8569 nan 0.0 0.0 0.6889 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1265 0.0 0.7959 0.2817 0.2193 0.7653
0.7333 14.0 1498 0.0 0.7852 0.0 0.0005 0.0 nan 0.6099 0.5852 0.3890 0.8211 0.2961 nan 0.6321 0.9313 0.3684 0.0 0.6342 0.9311 0.2435 0.0 0.0 0.8845 nan 0.0 0.0 0.9298 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1712 0.0 0.0 0.6312 0.0 0.0005 0.0 nan 0.2920 0.4813 0.1830 0.6730 0.2504 nan 0.5405 0.8112 0.3183 0.0 0.5574 0.7360 0.1553 0.0 0.0 0.8543 nan 0.0 0.0 0.7520 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1219 0.0 0.7463 0.2879 0.2300 0.7815
0.7128 15.0 1605 0.0 0.7547 0.0 0.0126 0.0 nan 0.6715 0.6477 0.2623 0.8694 0.1131 0.0 0.7576 0.9015 0.5131 0.0 0.8870 0.8915 0.3275 0.0 0.0 0.9177 nan 0.0008 0.0 0.9290 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2520 0.0 0.0 0.5980 0.0 0.0126 0.0 nan 0.4000 0.3362 0.1721 0.4706 0.1069 0.0 0.6593 0.8212 0.2914 0.0 0.6797 0.7574 0.1981 0.0 0.0 0.8704 nan 0.0008 0.0 0.6431 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1881 0.0 0.7557 0.2942 0.2184 0.7786
0.6885 16.0 1712 0.0 0.8416 0.0 0.0086 0.0 nan 0.5907 0.7737 0.3100 0.7765 0.1341 0.0 0.6753 0.9522 0.5143 0.0 0.8466 0.8795 0.2986 0.0 0.0 0.9155 nan 0.0071 0.0 0.9178 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.3074 0.0 0.0 0.6078 0.0 0.0086 0.0 nan 0.4106 0.3222 0.1815 0.6082 0.1171 0.0 0.6206 0.8253 0.2609 0.0 0.6832 0.7692 0.1957 0.0 0.0 0.8691 nan 0.0071 0.0 0.6951 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2366 0.0 0.7262 0.2954 0.2248 0.7882
0.6627 17.0 1819 0.0 0.7096 0.0 0.0181 0.0 nan 0.7189 0.6110 0.3654 0.8153 0.1210 0.0 0.7156 0.9114 0.5562 0.0 0.8788 0.9226 0.3042 0.0 0.0 0.9273 nan 0.0002 0.0 0.9080 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.3069 0.0 0.0 0.5809 0.0 0.0179 0.0 nan 0.3488 0.3724 0.2149 0.5069 0.1137 0.0 0.6477 0.8079 0.2559 0.0 0.7100 0.7595 0.1837 0.0 0.0 0.8734 nan 0.0002 0.0 0.7016 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2201 0.0 0.7429 0.2967 0.2217 0.7786
0.6954 18.0 1926 0.0 0.8919 0.0 0.0031 0.0 nan 0.5763 0.5167 0.3013 0.7439 0.1958 0.0 0.7281 0.9530 0.4080 0.0 0.8497 0.8852 0.2874 0.0 0.0 0.8563 nan 0.0056 0.0 0.9222 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.3154 0.0 0.0 0.5730 0.0 0.0031 0.0 nan 0.3625 0.4887 0.1980 0.6038 0.1714 0.0 0.6684 0.8291 0.2599 0.0 0.7176 0.7922 0.2045 0.0 0.0 0.8322 nan 0.0056 0.0 0.6432 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2459 0.0 0.6984 0.2861 0.2303 0.7947
0.6592 19.0 2033 0.0 0.8433 0.0 0.0496 0.0 nan 0.5622 0.6415 0.3618 0.7738 0.1797 0.0 0.6474 0.9741 0.6289 0.0 0.6784 0.9279 0.3132 0.0 0.0 0.8985 nan 0.0019 0.0 0.9235 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2431 0.0 0.0 0.6155 0.0 0.0493 0.0 nan 0.3959 0.5424 0.2210 0.6568 0.1504 0.0 0.6217 0.8227 0.2586 0.0 0.6198 0.7658 0.2117 0.0 0.0 0.8686 nan 0.0019 0.0 0.6541 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1919 0.0 0.6999 0.2924 0.2318 0.7924
0.6682 20.0 2140 0.0 0.8071 0.0 0.0796 0.0 nan 0.5870 0.4899 0.4985 0.7638 0.2075 0.0 0.7505 0.9346 0.6505 0.0 0.8297 0.9187 0.3668 0.0 0.0 0.9157 nan 0.0082 0.0 0.9407 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2163 0.0 0.0 0.6144 0.0 0.0748 0.0 nan 0.3846 0.4807 0.2584 0.6083 0.1892 0.0 0.6719 0.8371 0.2436 0.0 0.7173 0.7842 0.1994 0.0 0.0 0.8798 nan 0.0082 0.0 0.6331 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1719 0.0 0.6756 0.3020 0.2351 0.7976
0.6249 21.0 2247 0.6678 0.2540 0.3195 0.7981 nan 0.6625 0.9563 0.8027 0.7398 0.1695 0.0 0.4050 0.7541 0.0 0.9306 0.0 0.0 0.0 0.0 0.0473 nan 0.0 0.8526 0.0 0.6384 0.1242 0.0 nan 0.0 0.3671 0.0 0.0 0.9185 0.7725 0.8706 0.0 0.0 0.2129 0.0 nan 0.5746 0.8111 0.7593 0.5842 0.1557 0.0 0.2176 0.3250 0.0 0.7386 0.0 0.0 0.0 0.0 0.0473 nan 0.0 0.6693 0.0 0.3844 0.1188 0.0 nan 0.0 0.2479 0.0 0.0 0.7914 0.7105 0.8285 0.0 0.0 0.1638 0.0
0.6278 22.0 2354 0.6800 0.2513 0.3216 0.7949 nan 0.6354 0.9558 0.8656 0.7557 0.1401 0.0 0.4619 0.6943 0.0 0.9333 0.0 0.0 0.0 0.0 0.0315 nan 0.0 0.8031 0.0 0.6422 0.1074 0.0 nan 0.0 0.4139 0.0 0.0 0.9114 0.8658 0.8302 0.0 0.0 0.2446 0.0 nan 0.5527 0.8215 0.7864 0.5887 0.1346 0.0 0.2336 0.3191 0.0 0.7265 0.0 0.0 0.0 0.0 0.0315 nan 0.0 0.6458 0.0 0.3638 0.1048 0.0 nan 0.0 0.2338 0.0 0.0 0.7831 0.7282 0.8001 0.0 0.0 0.1868 0.0
0.6375 23.0 2461 0.6680 0.2563 0.3186 0.7976 nan 0.6355 0.9595 0.8844 0.6403 0.2228 0.0 0.3772 0.5620 0.0 0.9094 0.0 0.0 0.0 0.0 0.0640 nan 0.0 0.8615 0.0 0.6510 0.1498 0.0 nan 0.0 0.3834 0.0 0.0 0.9024 0.8874 0.8627 0.0 0.0 0.2419 0.0 nan 0.5548 0.8086 0.7729 0.5236 0.2018 0.0 0.2287 0.3137 0.0 0.7398 0.0 0.0 0.0 0.0 0.0634 nan 0.0 0.6603 0.0 0.3896 0.1381 0.0 nan 0.0 0.2666 0.0 0.0 0.7881 0.7394 0.8256 0.0 0.0 0.1871 0.0
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0.3449 84.0 8988 0.6665 0.2911 0.3655 0.8080 nan 0.6208 0.9362 0.8933 0.7983 0.2167 0.0 0.4705 0.5213 0.0 0.9445 0.0 0.0 0.0 0.0 0.7528 nan 0.0 0.8565 0.0 0.6339 0.3453 0.0 nan 0.0 0.5227 0.0 0.0 0.9203 0.8327 0.9315 0.0 0.1078 0.3915 0.0 nan 0.5271 0.8305 0.8038 0.5352 0.1796 0.0 0.2901 0.3788 0.0 0.7816 0.0 0.0 0.0 0.0 0.4767 nan 0.0 0.6966 0.0 0.3857 0.2623 0.0 nan 0.0 0.3403 0.0 0.0 0.8154 0.7512 0.8876 0.0 0.0934 0.2779 0.0
0.3677 85.0 9095 0.6600 0.2914 0.3667 0.8089 nan 0.6430 0.9281 0.8959 0.7877 0.2441 0.0 0.5011 0.5246 0.0 0.9417 0.0 0.0 0.0 0.0 0.7416 nan 0.0 0.8635 0.0 0.6224 0.3337 0.0 nan 0.0 0.5238 0.0 0.0 0.9166 0.8404 0.9203 0.0 0.0966 0.4086 0.0 nan 0.5410 0.8368 0.8012 0.5221 0.1990 0.0 0.3032 0.3763 0.0 0.7839 0.0 0.0 0.0 0.0 0.4819 nan 0.0 0.6880 0.0 0.3785 0.2603 0.0 nan 0.0 0.3469 0.0 0.0 0.8166 0.7502 0.8825 0.0 0.0826 0.2728 0.0
0.3479 86.0 9202 0.6653 0.2925 0.3659 0.8083 nan 0.6215 0.9364 0.8955 0.8062 0.2438 0.0 0.4356 0.5749 0.0 0.9352 0.0 0.0 0.0 0.0 0.7572 nan 0.0 0.8647 0.0 0.5950 0.3194 0.0 nan 0.0 0.5181 0.0 0.0 0.9142 0.8559 0.9196 0.0010 0.1131 0.4024 0.0 nan 0.5305 0.8260 0.8026 0.5177 0.2000 0.0 0.2845 0.3964 0.0 0.8037 0.0 0.0 0.0 0.0 0.4777 nan 0.0 0.6850 0.0 0.3926 0.2605 0.0 nan 0.0 0.3443 0.0 0.0 0.8210 0.7590 0.8827 0.0010 0.0985 0.2760 0.0
0.373 87.0 9309 0.6488 0.2953 0.3681 0.8141 nan 0.6465 0.9404 0.8996 0.7934 0.2418 0.0 0.4875 0.5646 0.0 0.9394 0.0 0.0 0.0 0.0 0.7519 nan 0.0 0.8931 0.0 0.6325 0.3185 0.0 nan 0.0 0.5045 0.0 0.0 0.8982 0.8624 0.9196 0.0000 0.1086 0.3763 0.0 nan 0.5479 0.8347 0.7989 0.5439 0.2043 0.0 0.2952 0.3956 0.0 0.8041 0.0 0.0 0.0 0.0 0.4802 nan 0.0 0.6921 0.0 0.3919 0.2632 0.0 nan 0.0 0.3462 0.0 0.0 0.8219 0.7598 0.8803 0.0000 0.0954 0.2939 0.0
0.3509 88.0 9416 0.6508 0.2938 0.3690 0.8125 nan 0.6480 0.9359 0.8987 0.8023 0.2228 0.0 0.4828 0.5941 0.0 0.9355 0.0 0.0 0.0 0.0 0.7617 nan 0.0 0.8669 0.0 0.5964 0.3253 0.0 nan 0.0 0.5218 0.0 0.0 0.9249 0.8344 0.9275 0.0 0.1256 0.4037 0.0 nan 0.5517 0.8360 0.7990 0.5289 0.1923 0.0 0.2911 0.3969 0.0 0.7989 0.0 0.0 0.0 0.0 0.4790 nan 0.0 0.6967 0.0 0.3872 0.2572 0.0 nan 0.0 0.3400 0.0 0.0 0.8153 0.7499 0.8866 0.0 0.1061 0.2894 0.0
0.3249 89.0 9523 0.6380 0.2947 0.3653 0.8162 nan 0.6541 0.9527 0.9012 0.7578 0.2159 0.0 0.4779 0.5541 0.0 0.9496 0.0 0.0 0.0 0.0 0.7475 nan 0.0 0.8613 0.0 0.6083 0.3103 0.0 nan 0.0 0.5111 0.0 0.0 0.9215 0.8387 0.9247 0.0 0.1075 0.3965 0.0 nan 0.5525 0.8372 0.8023 0.5649 0.1893 0.0 0.2923 0.3918 0.0 0.7877 0.0 0.0 0.0 0.0 0.4774 nan 0.0 0.7001 0.0 0.3917 0.2583 0.0 nan 0.0 0.3406 0.0 0.0 0.8165 0.7519 0.8854 0.0 0.0954 0.2955 0.0
0.3507 90.0 9630 0.6552 0.2931 0.3681 0.8112 nan 0.6412 0.9316 0.9007 0.7940 0.2344 0.0 0.4845 0.5679 0.0 0.9438 0.0 0.0 0.0 0.0 0.7501 nan 0.0 0.8788 0.0 0.6209 0.3117 0.0 nan 0.0 0.5239 0.0 0.0 0.9155 0.8504 0.9231 0.0 0.1052 0.4019 0.0 nan 0.5432 0.8346 0.7967 0.5219 0.1977 0.0 0.2933 0.3922 0.0 0.7936 0.0 0.0 0.0 0.0 0.4792 nan 0.0 0.6958 0.0 0.3913 0.2588 0.0 nan 0.0 0.3429 0.0 0.0 0.8188 0.7511 0.8841 0.0 0.0910 0.2920 0.0
0.3327 91.0 9737 0.6568 0.2929 0.3687 0.8102 nan 0.6277 0.9380 0.8989 0.8059 0.2578 0.0 0.4617 0.5809 0.0 0.9460 0.0 0.0 0.0 0.0 0.7536 nan 0.0 0.8356 0.0 0.6285 0.3180 0.0 nan 0.0 0.5218 0.0 0.0 0.9181 0.8578 0.9230 0.0004 0.0976 0.4261 0.0 nan 0.5366 0.8321 0.7979 0.5259 0.2114 0.0 0.2900 0.3969 0.0 0.7969 0.0 0.0 0.0 0.0 0.4798 nan 0.0 0.6966 0.0 0.3832 0.2618 0.0 nan 0.0 0.3398 0.0 0.0 0.8184 0.7523 0.8857 0.0004 0.0849 0.2836 0.0
0.3428 92.0 9844 0.6481 0.2933 0.3672 0.8120 nan 0.6540 0.9343 0.9003 0.7727 0.2264 0.0 0.4777 0.5473 0.0 0.9437 0.0 0.0 0.0 0.0 0.7544 nan 0.0 0.8720 0.0 0.6385 0.3236 0.0 nan 0.0 0.5132 0.0 0.0 0.9136 0.8557 0.9224 0.0 0.1007 0.4012 0.0 nan 0.5486 0.8334 0.7997 0.5315 0.1937 0.0 0.2905 0.3891 0.0 0.7948 0.0 0.0 0.0 0.0 0.4778 nan 0.0 0.6974 0.0 0.3843 0.2628 0.0 nan 0.0 0.3480 0.0 0.0 0.8193 0.7522 0.8844 0.0 0.0885 0.2890 0.0
0.3483 93.0 9951 0.6642 0.2923 0.3664 0.8104 nan 0.6314 0.9384 0.9008 0.7929 0.2027 0.0 0.4565 0.5687 0.0 0.9355 0.0 0.0 0.0 0.0 0.7620 nan 0.0 0.8702 0.0 0.6443 0.3233 0.0 nan 0.0 0.5056 0.0 0.0 0.9195 0.8529 0.9224 0.0 0.1132 0.3833 0.0 nan 0.5395 0.8298 0.7942 0.5268 0.1771 0.0 0.2783 0.3974 0.0 0.8030 0.0 0.0 0.0 0.0 0.4790 nan 0.0 0.7001 0.0 0.3838 0.2612 0.0 nan 0.0 0.3438 0.0 0.0 0.8168 0.7498 0.8846 0.0 0.0996 0.2879 0.0
0.346 93.46 10000 0.6468 0.2931 0.3665 0.8121 nan 0.6505 0.9345 0.9011 0.7895 0.2382 0.0 0.4519 0.5536 0.0 0.9509 0.0 0.0 0.0 0.0 0.7507 nan 0.0 0.8681 0.0 0.6107 0.3192 0.0 nan 0.0 0.5156 0.0 0.0 0.9183 0.8478 0.9246 0.0 0.1083 0.3940 0.0 nan 0.5472 0.8329 0.7961 0.5266 0.2013 0.0 0.2863 0.3887 0.0 0.7872 0.0 0.0 0.0 0.0 0.4759 nan 0.0 0.6992 0.0 0.3924 0.2614 0.0 nan 0.0 0.3413 0.0 0.0 0.8182 0.7517 0.8855 0.0 0.0963 0.2896 0.0

Framework versions

  • Transformers 4.29.0.dev0
  • Pytorch 2.0.0+cu117
  • Datasets 2.11.0
  • Tokenizers 0.13.3
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