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segformer-finetuned-sidewalk-10k-steps

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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: 0.5890
  • Mean Iou: 0.3100
  • Mean Accuracy: 0.3785
  • Overall Accuracy: 0.8340
  • Accuracy Unlabeled: nan
  • Accuracy Flat-road: 0.7750
  • Accuracy Flat-sidewalk: 0.9476
  • Accuracy Flat-crosswalk: 0.7198
  • Accuracy Flat-cyclinglane: 0.8649
  • Accuracy Flat-parkingdriveway: 0.2833
  • Accuracy Flat-railtrack: nan
  • Accuracy Flat-curb: 0.4461
  • Accuracy Human-person: 0.6623
  • Accuracy Human-rider: 0.0
  • Accuracy Vehicle-car: 0.9432
  • Accuracy Vehicle-truck: 0.0
  • Accuracy Vehicle-bus: 0.0
  • Accuracy Vehicle-tramtrain: 0.0
  • Accuracy Vehicle-motorcycle: 0.0
  • Accuracy Vehicle-bicycle: 0.7612
  • Accuracy Vehicle-caravan: 0.0
  • Accuracy Vehicle-cartrailer: 0.0
  • Accuracy Construction-building: 0.8657
  • Accuracy Construction-door: 0.0
  • Accuracy Construction-wall: 0.5605
  • Accuracy Construction-fenceguardrail: 0.5325
  • Accuracy Construction-bridge: 0.0
  • Accuracy Construction-tunnel: nan
  • Accuracy Construction-stairs: 0.0
  • Accuracy Object-pole: 0.3362
  • Accuracy Object-trafficsign: 0.0
  • Accuracy Object-trafficlight: 0.0
  • Accuracy Nature-vegetation: 0.8960
  • Accuracy Nature-terrain: 0.8673
  • Accuracy Sky: 0.9590
  • Accuracy Void-ground: 0.0
  • Accuracy Void-dynamic: 0.3077
  • Accuracy Void-static: 0.3834
  • Accuracy Void-unclear: 0.0
  • Iou Unlabeled: nan
  • Iou Flat-road: 0.6597
  • Iou Flat-sidewalk: 0.8220
  • Iou Flat-crosswalk: 0.6669
  • Iou Flat-cyclinglane: 0.7094
  • Iou Flat-parkingdriveway: 0.2634
  • Iou Flat-railtrack: nan
  • Iou Flat-curb: 0.2962
  • Iou Human-person: 0.4612
  • Iou Human-rider: 0.0
  • Iou Vehicle-car: 0.8019
  • Iou Vehicle-truck: 0.0
  • Iou Vehicle-bus: 0.0
  • Iou Vehicle-tramtrain: 0.0
  • Iou Vehicle-motorcycle: 0.0
  • Iou Vehicle-bicycle: 0.4166
  • Iou Vehicle-caravan: 0.0
  • Iou Vehicle-cartrailer: 0.0
  • Iou Construction-building: 0.6806
  • Iou Construction-door: 0.0
  • Iou Construction-wall: 0.4268
  • Iou Construction-fenceguardrail: 0.4087
  • Iou Construction-bridge: 0.0
  • Iou Construction-tunnel: nan
  • Iou Construction-stairs: 0.0
  • Iou Object-pole: 0.2241
  • Iou Object-trafficsign: 0.0
  • Iou Object-trafficlight: 0.0
  • Iou Nature-vegetation: 0.8381
  • Iou Nature-terrain: 0.7739
  • Iou Sky: 0.9036
  • Iou Void-ground: 0.0
  • Iou Void-dynamic: 0.2473
  • Iou Void-static: 0.3211
  • 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: 3407
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: polynomial
  • training_steps: 10000

Training results

Training Loss Epoch Step Validation Loss Mean Iou Mean Accuracy Overall Accuracy Accuracy Unlabeled Accuracy Flat-road Accuracy Flat-sidewalk Accuracy Flat-crosswalk Accuracy Flat-cyclinglane Accuracy Flat-parkingdriveway Accuracy Flat-railtrack Accuracy Flat-curb Accuracy Human-person Accuracy Human-rider Accuracy Vehicle-car Accuracy Vehicle-truck Accuracy Vehicle-bus Accuracy Vehicle-tramtrain Accuracy Vehicle-motorcycle Accuracy Vehicle-bicycle Accuracy Vehicle-caravan Accuracy Vehicle-cartrailer Accuracy Construction-building Accuracy Construction-door Accuracy Construction-wall Accuracy Construction-fenceguardrail Accuracy Construction-bridge Accuracy Construction-tunnel Accuracy Construction-stairs Accuracy Object-pole Accuracy Object-trafficsign Accuracy Object-trafficlight Accuracy Nature-vegetation Accuracy Nature-terrain Accuracy Sky Accuracy Void-ground Accuracy Void-dynamic Accuracy Void-static Accuracy Void-unclear Iou Unlabeled Iou Flat-road Iou Flat-sidewalk Iou Flat-crosswalk Iou Flat-cyclinglane Iou Flat-parkingdriveway Iou Flat-railtrack Iou Flat-curb Iou Human-person Iou Human-rider Iou Vehicle-car Iou Vehicle-truck Iou Vehicle-bus Iou Vehicle-tramtrain Iou Vehicle-motorcycle Iou Vehicle-bicycle Iou Vehicle-caravan Iou Vehicle-cartrailer Iou Construction-building Iou Construction-door Iou Construction-wall Iou Construction-fenceguardrail Iou Construction-bridge Iou Construction-tunnel Iou Construction-stairs Iou Object-pole Iou Object-trafficsign Iou Object-trafficlight Iou Nature-vegetation Iou Nature-terrain Iou Sky Iou Void-ground Iou Void-dynamic Iou Void-static Iou Void-unclear
2.6262 1.0 107 1.8030 0.1150 0.1631 0.6678 nan 0.4682 0.9266 0.0 0.1510 0.0020 nan 0.0000 0.0 0.0 0.8961 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7523 0.0 0.0 0.0 0.0 nan 0.0 0.0000 0.0 0.0 0.9321 0.7060 0.3833 0.0 0.0 0.0 0.0 nan 0.3811 0.6887 0.0 0.1495 0.0020 nan 0.0000 0.0 0.0 0.4861 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4729 0.0 0.0 0.0 0.0 nan 0.0 0.0000 0.0 0.0 0.6066 0.5402 0.3543 0.0 0.0 0.0 0.0
1.8747 2.0 214 1.5625 0.1290 0.1774 0.6759 nan 0.5144 0.9502 0.0 0.2435 0.0107 nan 0.0000 0.0 0.0 0.8290 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8706 0.0 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.6522 0.8882 0.7181 0.0 0.0 0.0 0.0 nan 0.4081 0.6930 0.0 0.2399 0.0106 nan 0.0000 0.0 0.0 0.6241 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5101 0.0 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.5405 0.4174 0.6840 0.0 0.0 0.0 0.0
1.4981 3.0 321 1.2528 0.1500 0.2000 0.7230 nan 0.7317 0.9017 0.0 0.5385 0.0352 nan 0.0 0.0 0.0 0.9288 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7741 0.0 0.0001 0.0 0.0 nan 0.0 0.0000 0.0 0.0 0.8453 0.8460 0.7985 0.0 0.0 0.0 0.0 nan 0.4742 0.7460 0.0 0.4950 0.0322 nan 0.0 0.0 0.0 0.5423 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5264 0.0 0.0001 0.0 0.0 nan 0.0 0.0000 0.0 0.0 0.6792 0.5807 0.7242 0.0 0.0 0.0 0.0
1.3616 4.0 428 1.1121 0.1538 0.2064 0.7329 nan 0.6492 0.9195 0.0 0.6889 0.0578 nan 0.0 0.0 0.0 0.9435 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7840 0.0 0.0000 0.0 0.0 nan 0.0 0.0008 0.0 0.0 0.8478 0.8760 0.8387 0.0 0.0 0.0 0.0 nan 0.4697 0.7686 0.0 0.5062 0.0538 nan 0.0 0.0 0.0 0.5448 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5363 0.0 0.0000 0.0 0.0 nan 0.0 0.0008 0.0 0.0 0.6882 0.5835 0.7687 0.0 0.0 0.0 0.0
1.2402 5.0 535 0.9807 0.1617 0.2044 0.7432 nan 0.6175 0.9496 0.0 0.6074 0.0402 nan 0.0 0.0 0.0 0.9149 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9186 0.0 0.0000 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8532 0.7998 0.8388 0.0 0.0 0.0 0.0 nan 0.5019 0.7449 0.0 0.5470 0.0378 nan 0.0 0.0 0.0 0.6501 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5055 0.0 0.0000 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7337 0.6708 0.7837 0.0 0.0 0.0 0.0
1.1318 6.0 642 1.0385 0.1477 0.2019 0.7068 nan 0.4984 0.9470 0.0 0.7702 0.0691 nan 0.0 0.0 0.0 0.9543 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8840 0.0 0.0178 0.0 0.0 nan 0.0 0.0005 0.0 0.0 0.6212 0.8926 0.8047 0.0 0.0 0.0 0.0 nan 0.4191 0.7292 0.0 0.5835 0.0601 nan 0.0 0.0 0.0 0.6061 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5407 0.0 0.0177 0.0 0.0 nan 0.0 0.0005 0.0 0.0 0.5770 0.4410 0.7513 0.0 0.0 0.0 0.0
1.0574 7.0 749 0.9046 0.1690 0.2127 0.7531 nan 0.6171 0.9520 0.0115 0.7032 0.0985 nan 0.0020 0.0 0.0 0.9373 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8779 0.0 0.0486 0.0 0.0 nan 0.0 0.0169 0.0 0.0 0.8670 0.8317 0.8423 0.0 0.0 0.0 0.0 nan 0.4908 0.7535 0.0115 0.6164 0.0845 nan 0.0020 0.0 0.0 0.6419 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5622 0.0 0.0479 0.0 0.0 nan 0.0 0.0166 0.0 0.0 0.7327 0.6574 0.7922 0.0 0.0 0.0 0.0
0.9759 8.0 856 0.8881 0.1756 0.2189 0.7547 nan 0.5985 0.9566 0.1262 0.7070 0.0835 nan 0.0258 0.0 0.0 0.9402 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8847 0.0 0.1283 0.0001 0.0 nan 0.0 0.0597 0.0 0.0 0.8756 0.7936 0.8249 0.0 0.0 0.0 0.0 nan 0.5068 0.7552 0.1260 0.5858 0.0748 nan 0.0248 0.0 0.0 0.6569 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5553 0.0 0.1171 0.0001 0.0 nan 0.0 0.0558 0.0 0.0 0.7294 0.6463 0.7841 0.0 0.0 0.0 0.0
0.9478 9.0 963 0.8427 0.1792 0.2281 0.7627 nan 0.6444 0.9385 0.1576 0.8233 0.1084 nan 0.0637 0.0 0.0 0.9471 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9072 0.0 0.1206 0.0010 0.0 nan 0.0 0.0478 0.0 0.0 0.8482 0.8364 0.8557 0.0 0.0 0.0001 0.0 nan 0.5283 0.7850 0.1503 0.5470 0.0989 nan 0.0594 0.0 0.0 0.6174 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5622 0.0 0.1114 0.0010 0.0 nan 0.0 0.0438 0.0 0.0 0.7500 0.6754 0.8027 0.0 0.0 0.0001 0.0
0.9357 10.0 1070 0.8261 0.1919 0.2394 0.7663 nan 0.7330 0.9060 0.2756 0.7705 0.0660 nan 0.1561 0.0018 0.0 0.9329 0.0 0.0 0.0 0.0 0.0039 0.0 0.0 0.8534 0.0 0.2518 0.0002 0.0 nan 0.0 0.0967 0.0 0.0 0.9051 0.8362 0.8711 0.0 0.0 0.0002 0.0 nan 0.5551 0.7720 0.2581 0.6407 0.0623 nan 0.1264 0.0018 0.0 0.6682 0.0 0.0 0.0 0.0 0.0039 0.0 0.0 0.5674 0.0 0.2233 0.0002 0.0 nan 0.0 0.0776 0.0 0.0 0.7281 0.6464 0.8107 0.0 0.0 0.0002 0.0
0.8472 11.0 1177 0.7976 0.2078 0.2573 0.7708 nan 0.6694 0.9321 0.6020 0.7892 0.0857 nan 0.1836 0.0318 0.0 0.9266 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8658 0.0 0.4413 0.0004 0.0 nan 0.0 0.1099 0.0 0.0 0.8505 0.8369 0.9076 0.0 0.0 0.0022 0.0 nan 0.5349 0.7639 0.5201 0.6244 0.0777 nan 0.1394 0.0313 0.0 0.6994 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5838 0.0 0.3358 0.0004 0.0 nan 0.0 0.0885 0.0 0.0 0.7588 0.6643 0.8232 0.0 0.0 0.0022 0.0
0.8613 12.0 1284 0.7624 0.2053 0.2580 0.7782 nan 0.7226 0.9281 0.1215 0.7176 0.1899 nan 0.3386 0.0810 0.0 0.9500 0.0 0.0 0.0 0.0 0.0216 0.0 0.0 0.8083 0.0 0.5341 0.0030 0.0 nan 0.0 0.2061 0.0 0.0 0.8630 0.8930 0.8579 0.0 0.0 0.0188 0.0 nan 0.5747 0.7922 0.1206 0.6327 0.1671 nan 0.2062 0.0747 0.0 0.6546 0.0 0.0 0.0 0.0 0.0214 0.0 0.0 0.6156 0.0 0.3586 0.0030 0.0 nan 0.0 0.1199 0.0 0.0 0.7451 0.6452 0.8198 0.0 0.0 0.0183 0.0
0.7847 13.0 1391 0.7713 0.2170 0.2694 0.7725 nan 0.6374 0.9509 0.6615 0.5478 0.1946 nan 0.3358 0.2063 0.0 0.9425 0.0 0.0 0.0 0.0 0.0670 0.0 0.0 0.8683 0.0 0.4287 0.0321 0.0 nan 0.0 0.1353 0.0 0.0 0.8484 0.8816 0.8796 0.0 0.0 0.0039 0.0 nan 0.5472 0.7772 0.5301 0.4776 0.1689 nan 0.2091 0.1927 0.0 0.6819 0.0 0.0 0.0 0.0 0.0665 0.0 0.0 0.6125 0.0 0.3472 0.0320 0.0 nan 0.0 0.1017 0.0 0.0 0.7452 0.6313 0.8206 0.0 0.0 0.0039 0.0
0.8041 14.0 1498 0.7236 0.2310 0.2877 0.7880 nan 0.6190 0.9472 0.5927 0.8157 0.1877 nan 0.3897 0.3524 0.0 0.9307 0.0 0.0 0.0 0.0 0.1085 0.0 0.0 0.7989 0.0 0.5597 0.0130 0.0 nan 0.0 0.1964 0.0 0.0 0.9106 0.8640 0.9053 0.0 0.0 0.0136 0.0 nan 0.5518 0.7940 0.4508 0.6548 0.1720 nan 0.2188 0.3054 0.0 0.7232 0.0 0.0 0.0 0.0 0.1064 0.0 0.0 0.6219 0.0 0.3678 0.0129 0.0 nan 0.0 0.1153 0.0 0.0 0.7713 0.6756 0.8352 0.0 0.0 0.0133 0.0
0.74 15.0 1605 0.7429 0.2275 0.2771 0.7791 nan 0.6285 0.9519 0.4719 0.6291 0.1591 nan 0.3397 0.4511 0.0 0.9334 0.0 0.0 0.0 0.0 0.1813 0.0 0.0 0.8426 0.0 0.4337 0.0407 0.0 nan 0.0 0.1488 0.0 0.0 0.9095 0.8395 0.9037 0.0 0.0 0.0042 0.0 nan 0.5371 0.7690 0.4183 0.5169 0.1449 nan 0.2088 0.3547 0.0 0.7256 0.0 0.0 0.0 0.0 0.1607 0.0 0.0 0.6329 0.0 0.3753 0.0401 0.0 nan 0.0 0.1064 0.0 0.0 0.7613 0.6850 0.8378 0.0 0.0 0.0042 0.0
0.7184 16.0 1712 0.6646 0.2439 0.2964 0.8029 nan 0.7431 0.9484 0.4972 0.8103 0.2001 nan 0.3258 0.4629 0.0 0.9401 0.0 0.0 0.0 0.0 0.1821 0.0 0.0 0.8279 0.0 0.6112 0.0110 0.0 nan 0.0 0.2345 0.0 0.0 0.8917 0.8616 0.9063 0.0 0.0 0.0313 0.0 nan 0.6165 0.8048 0.4637 0.6925 0.1798 nan 0.2280 0.3680 0.0 0.7181 0.0 0.0 0.0 0.0 0.1722 0.0 0.0 0.6472 0.0 0.3937 0.0109 0.0 nan 0.0 0.1451 0.0 0.0 0.7831 0.7086 0.8424 0.0 0.0 0.0293 0.0
0.7496 17.0 1819 0.7000 0.2385 0.2948 0.7852 nan 0.6870 0.9552 0.5478 0.8104 0.2046 nan 0.3326 0.5163 0.0 0.9477 0.0 0.0 0.0 0.0 0.1966 0.0 0.0 0.8765 0.0 0.5327 0.0835 0.0 nan 0.0 0.2037 0.0 0.0 0.7682 0.8842 0.8746 0.0 0.0 0.0112 0.0 nan 0.6047 0.7973 0.4943 0.6625 0.1800 nan 0.2414 0.3971 0.0 0.7056 0.0 0.0 0.0 0.0 0.1848 0.0 0.0 0.6271 0.0 0.4151 0.0821 0.0 nan 0.0 0.1296 0.0 0.0 0.7041 0.5693 0.8255 0.0 0.0 0.0103 0.0
0.6723 18.0 1926 0.6689 0.2487 0.3028 0.8022 nan 0.7140 0.9462 0.5937 0.8259 0.1957 nan 0.3702 0.5214 0.0 0.9200 0.0 0.0 0.0 0.0 0.2293 0.0 0.0 0.8539 0.0 0.4865 0.1947 0.0 nan 0.0 0.1763 0.0 0.0 0.9082 0.8340 0.9089 0.0 0.0 0.0120 0.0 nan 0.5970 0.8087 0.4665 0.6640 0.1781 nan 0.2503 0.3889 0.0 0.7549 0.0 0.0 0.0 0.0 0.2088 0.0 0.0 0.6258 0.0 0.3857 0.1777 0.0 nan 0.0 0.1182 0.0 0.0 0.7836 0.6927 0.8458 0.0 0.0 0.0116 0.0
0.6711 19.0 2033 0.7171 0.2410 0.2989 0.7914 nan 0.6550 0.9565 0.2743 0.8302 0.1406 nan 0.2934 0.6023 0.0 0.9349 0.0 0.0 0.0 0.0 0.2585 0.0 0.0 0.8100 0.0 0.6473 0.1674 0.0 nan 0.0 0.2790 0.0 0.0 0.8745 0.8440 0.9106 0.0 0.0 0.0875 0.0 nan 0.5597 0.7818 0.2558 0.6593 0.1321 nan 0.1980 0.3907 0.0 0.7384 0.0 0.0 0.0 0.0 0.2201 0.0 0.0 0.6550 0.0 0.4454 0.1541 0.0 nan 0.0 0.1459 0.0 0.0 0.7737 0.6716 0.8494 0.0 0.0 0.0804 0.0
0.6843 20.0 2140 0.6734 0.2490 0.3017 0.7990 nan 0.6756 0.9455 0.4783 0.7881 0.2300 nan 0.3708 0.5272 0.0 0.9268 0.0 0.0 0.0 0.0 0.3415 0.0 0.0 0.8824 0.0 0.5309 0.1064 0.0 nan 0.0 0.1958 0.0 0.0 0.8984 0.8616 0.8828 0.0 0.0 0.0131 0.0 nan 0.5749 0.8016 0.4521 0.6371 0.2040 nan 0.2474 0.4068 0.0 0.7496 0.0 0.0 0.0 0.0 0.2855 0.0 0.0 0.6350 0.0 0.3958 0.1030 0.0 nan 0.0 0.1338 0.0 0.0 0.7849 0.6948 0.8482 0.0 0.0 0.0127 0.0
0.6635 21.0 2247 0.6890 0.2588 0.3264 0.7921 nan 0.8326 0.8628 0.5588 0.8419 0.2679 nan 0.3243 0.6557 0.0 0.9472 0.0 0.0 0.0 0.0 0.3776 0.0 0.0 0.7708 0.0 0.5574 0.1780 0.0 nan 0.0 0.3384 0.0 0.0 0.9255 0.8385 0.8964 0.0 0.0 0.2726 0.0 nan 0.5749 0.7876 0.4791 0.6054 0.2392 nan 0.1911 0.4287 0.0 0.7368 0.0 0.0 0.0 0.0 0.2660 0.0 0.0 0.6472 0.0 0.3842 0.1686 0.0 nan 0.0 0.2159 0.0 0.0 0.7949 0.7123 0.8570 0.0 0.0 0.1917 0.0
0.6789 22.0 2354 0.6569 0.2518 0.3098 0.8048 nan 0.6906 0.9488 0.2921 0.8276 0.2066 nan 0.3660 0.7073 0.0 0.9234 0.0 0.0 0.0 0.0 0.2937 0.0 0.0 0.8247 0.0 0.6251 0.1025 0.0 nan 0.0 0.2306 0.0 0.0 0.9155 0.8941 0.8789 0.0 0.0 0.1853 0.0 nan 0.5897 0.7929 0.2851 0.7088 0.1866 nan 0.2519 0.3796 0.0 0.7649 0.0 0.0 0.0 0.0 0.2501 0.0 0.0 0.6571 0.0 0.4087 0.0996 0.0 nan 0.0 0.1627 0.0 0.0 0.7933 0.7197 0.8451 0.0 0.0 0.1610 0.0
0.6454 23.0 2461 0.6744 0.2605 0.3209 0.8028 nan 0.7072 0.9467 0.5200 0.8210 0.1523 nan 0.3109 0.6300 0.0 0.8984 0.0 0.0 0.0 0.0 0.5537 0.0 0.0 0.8196 0.0 0.5994 0.2228 0.0 nan 0.0 0.3040 0.0 0.0 0.9410 0.7925 0.9118 0.0 0.0 0.1383 0.0 nan 0.5906 0.8004 0.4780 0.7242 0.1412 nan 0.2191 0.3835 0.0 0.7780 0.0 0.0 0.0 0.0 0.3617 0.0 0.0 0.6282 0.0 0.3930 0.2002 0.0 nan 0.0 0.1673 0.0 0.0 0.7889 0.7080 0.8552 0.0 0.0 0.1194 0.0
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0.3837 84.0 8988 0.6004 0.3036 0.3712 0.8292 nan 0.7741 0.9374 0.6093 0.8726 0.2691 nan 0.4232 0.6590 0.0 0.9410 0.0 0.0 0.0 0.0 0.7466 0.0 0.0 0.8726 0.0 0.5627 0.4905 0.0 nan 0.0 0.3329 0.0 0.0 0.9002 0.8601 0.9551 0.0 0.3032 0.3703 0.0 nan 0.6535 0.8166 0.5919 0.6585 0.2514 nan 0.2897 0.4643 0.0 0.8054 0.0 0.0 0.0 0.0 0.4115 0.0 0.0 0.6766 0.0 0.4207 0.3879 0.0 nan 0.0 0.2191 0.0 0.0 0.8380 0.7728 0.9020 0.0 0.2484 0.3078 0.0
0.3893 85.0 9095 0.5829 0.3084 0.3760 0.8340 nan 0.7840 0.9454 0.6141 0.8637 0.2819 nan 0.4197 0.6554 0.0 0.9299 0.0 0.0 0.0 0.0 0.7525 0.0 0.0 0.8579 0.0 0.5518 0.5349 0.0 nan 0.0 0.3574 0.0 0.0 0.9054 0.8711 0.9585 0.0 0.3114 0.4356 0.0 nan 0.6558 0.8246 0.5972 0.7109 0.2607 nan 0.2940 0.4619 0.0 0.8209 0.0 0.0 0.0 0.0 0.4206 0.0 0.0 0.6725 0.0 0.4299 0.4114 0.0 nan 0.0 0.2291 0.0 0.0 0.8388 0.7753 0.9033 0.0 0.2374 0.3259 0.0
0.3568 86.0 9202 0.5820 0.3080 0.3747 0.8325 nan 0.7903 0.9414 0.6354 0.8605 0.2640 nan 0.4273 0.6557 0.0 0.9349 0.0 0.0 0.0 0.0 0.7446 0.0 0.0 0.8585 0.0 0.5437 0.5643 0.0 nan 0.0 0.3338 0.0 0.0 0.9118 0.8567 0.9552 0.0 0.3089 0.4020 0.0 nan 0.6572 0.8189 0.6172 0.7005 0.2476 nan 0.2908 0.4655 0.0 0.8147 0.0 0.0 0.0 0.0 0.4183 0.0 0.0 0.6758 0.0 0.4228 0.4167 0.0 nan 0.0 0.2271 0.0 0.0 0.8392 0.7752 0.9050 0.0 0.2439 0.3209 0.0
0.3812 87.0 9309 0.5807 0.3103 0.3773 0.8331 nan 0.7822 0.9393 0.7419 0.8598 0.2849 nan 0.4434 0.6552 0.0 0.9438 0.0 0.0 0.0 0.0 0.6996 0.0 0.0 0.8562 0.0 0.5577 0.5600 0.0 nan 0.0 0.3260 0.0 0.0 0.9138 0.8579 0.9549 0.0 0.3072 0.3889 0.0 nan 0.6617 0.8195 0.6735 0.6867 0.2661 nan 0.2962 0.4633 0.0 0.8066 0.0 0.0 0.0 0.0 0.4183 0.0 0.0 0.6738 0.0 0.4195 0.4302 0.0 nan 0.0 0.2260 0.0 0.0 0.8401 0.7766 0.9048 0.0 0.2449 0.3213 0.0
0.3861 88.0 9416 0.5830 0.3086 0.3753 0.8326 nan 0.7898 0.9402 0.6848 0.8620 0.2609 nan 0.4195 0.6699 0.0 0.9395 0.0 0.0 0.0 0.0 0.7112 0.0 0.0 0.8726 0.0 0.5395 0.5290 0.0 nan 0.0 0.3415 0.0 0.0 0.9041 0.8616 0.9560 0.0 0.3120 0.4148 0.0 nan 0.6604 0.8180 0.6453 0.6906 0.2451 nan 0.2897 0.4600 0.0 0.8129 0.0 0.0 0.0 0.0 0.4175 0.0 0.0 0.6771 0.0 0.4296 0.4125 0.0 nan 0.0 0.2268 0.0 0.0 0.8392 0.7765 0.9045 0.0 0.2408 0.3276 0.0
0.3794 89.0 9523 0.5810 0.3097 0.3749 0.8352 nan 0.7929 0.9458 0.6782 0.8640 0.2715 nan 0.4132 0.6713 0.0 0.9444 0.0 0.0 0.0 0.0 0.6702 0.0 0.0 0.8568 0.0 0.5447 0.5202 0.0 nan 0.0 0.3659 0.0 0.0 0.9108 0.8647 0.9536 0.0 0.3065 0.4218 0.0 nan 0.6601 0.8260 0.6376 0.7196 0.2537 nan 0.2907 0.4658 0.0 0.7987 0.0 0.0 0.0 0.0 0.4120 0.0 0.0 0.6758 0.0 0.4326 0.4139 0.0 nan 0.0 0.2351 0.0 0.0 0.8374 0.7762 0.9056 0.0 0.2380 0.3327 0.0
0.3862 90.0 9630 0.5829 0.3101 0.3741 0.8360 nan 0.7848 0.9513 0.6485 0.8585 0.2785 nan 0.4155 0.6589 0.0 0.9368 0.0 0.0 0.0 0.0 0.7153 0.0 0.0 0.8629 0.0 0.5388 0.5348 0.0 nan 0.0 0.3483 0.0 0.0 0.9114 0.8631 0.9563 0.0 0.3089 0.3983 0.0 nan 0.6612 0.8226 0.6249 0.7241 0.2594 nan 0.2904 0.4605 0.0 0.8116 0.0 0.0 0.0 0.0 0.4253 0.0 0.0 0.6824 0.0 0.4310 0.4208 0.0 nan 0.0 0.2285 0.0 0.0 0.8396 0.7744 0.9050 0.0 0.2350 0.3275 0.0
0.3932 91.0 9737 0.5930 0.3098 0.3750 0.8355 nan 0.7909 0.9519 0.6784 0.8521 0.2627 nan 0.4139 0.6617 0.0 0.9373 0.0 0.0 0.0 0.0 0.7455 0.0 0.0 0.8494 0.0 0.5452 0.5494 0.0 nan 0.0 0.3350 0.0 0.0 0.9168 0.8574 0.9575 0.0 0.3072 0.3890 0.0 nan 0.6640 0.8206 0.6375 0.7287 0.2458 nan 0.2891 0.4614 0.0 0.8079 0.0 0.0 0.0 0.0 0.4162 0.0 0.0 0.6814 0.0 0.4299 0.4185 0.0 nan 0.0 0.2279 0.0 0.0 0.8395 0.7741 0.9051 0.0 0.2450 0.3209 0.0
0.3772 92.0 9844 0.5853 0.3107 0.3765 0.8360 nan 0.7945 0.9480 0.7226 0.8569 0.2856 nan 0.4213 0.6610 0.0 0.9426 0.0 0.0 0.0 0.0 0.7424 0.0 0.0 0.8737 0.0 0.5441 0.5365 0.0 nan 0.0 0.3261 0.0 0.0 0.9066 0.8428 0.9565 0.0 0.3083 0.3800 0.0 nan 0.6627 0.8247 0.6681 0.7259 0.2658 nan 0.2930 0.4638 0.0 0.8004 0.0 0.0 0.0 0.0 0.4139 0.0 0.0 0.6795 0.0 0.4294 0.4075 0.0 nan 0.0 0.2218 0.0 0.0 0.8407 0.7744 0.9051 0.0 0.2460 0.3197 0.0
0.3886 93.0 9951 0.5873 0.3101 0.3758 0.8353 nan 0.7940 0.9477 0.6976 0.8584 0.2758 nan 0.4271 0.6610 0.0 0.9388 0.0 0.0 0.0 0.0 0.7573 0.0 0.0 0.8781 0.0 0.5376 0.5151 0.0 nan 0.0 0.3348 0.0 0.0 0.9022 0.8517 0.9536 0.0 0.3092 0.3870 0.0 nan 0.6608 0.8232 0.6593 0.7203 0.2580 nan 0.2931 0.4603 0.0 0.8067 0.0 0.0 0.0 0.0 0.4182 0.0 0.0 0.6808 0.0 0.4315 0.4049 0.0 nan 0.0 0.2203 0.0 0.0 0.8401 0.7743 0.9055 0.0 0.2425 0.3223 0.0
0.3732 93.4579 10000 0.5890 0.3100 0.3785 0.8340 nan 0.7750 0.9476 0.7198 0.8649 0.2833 nan 0.4461 0.6623 0.0 0.9432 0.0 0.0 0.0 0.0 0.7612 0.0 0.0 0.8657 0.0 0.5605 0.5325 0.0 nan 0.0 0.3362 0.0 0.0 0.8960 0.8673 0.9590 0.0 0.3077 0.3834 0.0 nan 0.6597 0.8220 0.6669 0.7094 0.2634 nan 0.2962 0.4612 0.0 0.8019 0.0 0.0 0.0 0.0 0.4166 0.0 0.0 0.6806 0.0 0.4268 0.4087 0.0 nan 0.0 0.2241 0.0 0.0 0.8381 0.7739 0.9036 0.0 0.2473 0.3211 0.0

Framework versions

  • Transformers 4.46.3
  • Pytorch 2.5.1+cu124
  • Datasets 3.1.0
  • Tokenizers 0.20.3
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