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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: 0.5870
  • Mean Iou: 0.2962
  • Mean Accuracy: 0.3656
  • Overall Accuracy: 0.8302
  • Accuracy Unlabeled: nan
  • Accuracy Flat-road: 0.7752
  • Accuracy Flat-sidewalk: 0.9460
  • Accuracy Flat-crosswalk: 0.8223
  • Accuracy Flat-cyclinglane: 0.7550
  • Accuracy Flat-parkingdriveway: 0.2805
  • Accuracy Flat-railtrack: nan
  • Accuracy Flat-curb: 0.5378
  • Accuracy Human-person: 0.6477
  • Accuracy Human-rider: 0.0
  • Accuracy Vehicle-car: 0.9354
  • Accuracy Vehicle-truck: 0.0
  • Accuracy Vehicle-bus: 0.0
  • Accuracy Vehicle-tramtrain: 0.0
  • Accuracy Vehicle-motorcycle: 0.0
  • Accuracy Vehicle-bicycle: 0.5094
  • Accuracy Vehicle-caravan: 0.0
  • Accuracy Vehicle-cartrailer: 0.0
  • Accuracy Construction-building: 0.8737
  • Accuracy Construction-door: 0.0
  • Accuracy Construction-wall: 0.5689
  • Accuracy Construction-fenceguardrail: 0.5286
  • Accuracy Construction-bridge: 0.0
  • Accuracy Construction-tunnel: nan
  • Accuracy Construction-stairs: 0.0
  • Accuracy Object-pole: 0.4050
  • Accuracy Object-trafficsign: 0.0
  • Accuracy Object-trafficlight: 0.0
  • Accuracy Nature-vegetation: 0.9220
  • Accuracy Nature-terrain: 0.8417
  • Accuracy Sky: 0.9603
  • Accuracy Void-ground: 0.0
  • Accuracy Void-dynamic: 0.0091
  • Accuracy Void-static: 0.3817
  • Accuracy Void-unclear: 0.0
  • Iou Unlabeled: nan
  • Iou Flat-road: 0.6953
  • Iou Flat-sidewalk: 0.8257
  • Iou Flat-crosswalk: 0.6744
  • Iou Flat-cyclinglane: 0.5831
  • Iou Flat-parkingdriveway: 0.2594
  • Iou Flat-railtrack: nan
  • Iou Flat-curb: 0.3720
  • Iou Human-person: 0.4758
  • Iou Human-rider: 0.0
  • Iou Vehicle-car: 0.7439
  • Iou Vehicle-truck: 0.0
  • Iou Vehicle-bus: 0.0
  • Iou Vehicle-tramtrain: 0.0
  • Iou Vehicle-motorcycle: 0.0
  • Iou Vehicle-bicycle: 0.2578
  • Iou Vehicle-caravan: 0.0
  • Iou Vehicle-cartrailer: 0.0
  • Iou Construction-building: 0.6847
  • Iou Construction-door: 0.0
  • Iou Construction-wall: 0.4535
  • Iou Construction-fenceguardrail: 0.4437
  • Iou Construction-bridge: 0.0
  • Iou Construction-tunnel: nan
  • Iou Construction-stairs: 0.0
  • Iou Object-pole: 0.2822
  • Iou Object-trafficsign: 0.0
  • Iou Object-trafficlight: 0.0
  • Iou Nature-vegetation: 0.8452
  • Iou Nature-terrain: 0.7081
  • Iou Sky: 0.9161
  • Iou Void-ground: 0.0
  • Iou Void-dynamic: 0.0090
  • Iou Void-static: 0.2470
  • 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: Use 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 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
2.5976 1.0 107 0.0 0.8716 0.0 0.0 0.0 nan 0.0 0.0 0.0000 0.0340 0.0059 nan 0.7126 0.8829 0.0 0.0 0.7639 0.8401 0.0 0.0 0.0 0.5274 nan 0.0 0.0 0.7375 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.0 0.0 0.4078 0.0 0.0 0.0 nan 0.0 0.0 0.0000 0.0335 0.0058 nan 0.4342 0.7303 0.0 0.0 0.4971 0.6088 0.0 0.0 0.0 0.5238 nan 0.0 0.0 0.5006 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.0 1.8167 0.1734 0.1207 0.6649
1.7804 2.0 214 0.0 0.8645 0.0 0.0 0.0 nan 0.0 0.0 0.0000 0.4088 0.0091 nan 0.4849 0.9320 0.0 0.0 0.7240 0.8760 0.0 0.0 0.0 0.6529 nan 0.0 0.0 0.7975 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.0 0.0 0.4432 0.0 0.0 0.0 nan 0.0 0.0 0.0000 0.3873 0.0090 nan 0.3862 0.7022 0.0 0.0 0.5454 0.6380 0.0 0.0 0.0 0.6448 nan 0.0 0.0 0.5313 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.0 1.5213 0.1855 0.1383 0.6885
1.4506 3.0 321 0.0 0.8987 0.0 0.0 0.0 nan 0.0 0.0 0.0010 0.5240 0.0117 nan 0.5295 0.9284 0.0 0.0 0.8090 0.8123 0.0 0.0 0.0 0.8372 nan 0.0 0.0 0.8111 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.0 0.0 0.4566 0.0 0.0 0.0 nan 0.0 0.0 0.0010 0.4336 0.0116 nan 0.4384 0.7208 0.0 0.0 0.5342 0.6543 0.0 0.0 0.0 0.7963 nan 0.0 0.0 0.5375 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.0 1.3304 0.1988 0.1479 0.7053
1.2854 4.0 428 0.0 0.8395 0.0 0.0 0.0 nan 0.0 0.0 0.0013 0.5963 0.0190 nan 0.5613 0.9518 0.0 0.0 0.8063 0.7245 0.0 0.0 0.0 0.9043 nan 0.0 0.0 0.9129 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.0 0.0 0.5325 0.0 0.0 0.0 nan 0.0 0.0 0.0013 0.4682 0.0187 nan 0.4473 0.7302 0.0 0.0 0.4632 0.6076 0.0 0.0 0.0 0.8239 nan 0.0 0.0 0.5643 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.0 1.1582 0.2038 0.1502 0.7119
1.1642 5.0 535 0.0 0.8254 0.0 0.0 0.0 nan 0.0 0.0 0.0063 0.7528 0.0587 nan 0.6286 0.9087 0.0 0.0 0.8256 0.8157 0.0000 0.0 0.0 0.9404 nan 0.0 0.0 0.9277 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.0 0.0 0.5305 0.0 0.0 0.0 nan 0.0 0.0 0.0062 0.4925 0.0546 nan 0.4666 0.7665 0.0 0.0 0.5518 0.6739 0.0000 0.0 0.0 0.8213 nan 0.0 0.0 0.5415 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.0 1.1097 0.2158 0.1582 0.7293
1.0799 6.0 642 0.0 0.8431 0.0 0.0 0.0 nan 0.0 0.0 0.0122 0.6784 0.0697 nan 0.5980 0.9488 0.0 0.0 0.8225 0.8262 0.0008 0.0 0.0 0.9372 nan 0.0 0.0 0.9414 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.0 0.0 0.5299 0.0 0.0 0.0 nan 0.0 0.0 0.0117 0.5230 0.0649 nan 0.4718 0.7595 0.0 0.0 0.5885 0.7045 0.0008 0.0 0.0 0.8205 nan 0.0 0.0 0.5774 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.0 1.0014 0.2154 0.1630 0.7393
1.0072 7.0 749 0.0 0.8738 0.0 0.0 0.0 nan 0.0042 0.0070 0.2003 0.6716 0.1430 nan 0.6910 0.9306 0.0 0.0 0.8153 0.8074 0.0017 0.0 0.0 0.9013 nan 0.0 0.0 0.9354 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0003 0.0 0.0 0.5090 0.0 0.0 0.0 nan 0.0041 0.0070 0.1458 0.6067 0.1168 nan 0.5294 0.7917 0.0 0.0 0.5533 0.6821 0.0017 0.0 0.0 0.8340 nan 0.0 0.0 0.5637 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0003 0.0 0.9490 0.2253 0.1724 0.7464
0.984 8.0 856 0.0 0.8566 0.0 0.0 0.0 nan 0.0314 0.1486 0.1743 0.7371 0.1348 nan 0.6086 0.9221 0.0 0.0 0.6871 0.8991 0.0205 0.0 0.0 0.9047 nan 0.0 0.0 0.9382 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0001 0.0 0.0 0.5408 0.0 0.0 0.0 nan 0.0307 0.1485 0.1336 0.4415 0.1161 nan 0.4910 0.7736 0.0 0.0 0.6197 0.7323 0.0202 0.0 0.0 0.8432 nan 0.0 0.0 0.6013 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0001 0.0 0.9205 0.2278 0.1772 0.7460
0.915 9.0 963 0.0 0.8404 0.0 0.0 0.0 nan 0.1437 0.5864 0.3057 0.6835 0.1982 nan 0.7090 0.9415 0.0 0.0 0.8255 0.8329 0.0645 0.0 0.0 0.9328 nan 0.0 0.0 0.9341 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0053 0.0 0.0 0.5652 0.0 0.0 0.0 nan 0.1308 0.4699 0.1767 0.6121 0.1550 nan 0.5848 0.8019 0.0 0.0 0.5785 0.6993 0.0597 0.0 0.0 0.8524 nan 0.0 0.0 0.6370 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0051 0.0 0.8332 0.2582 0.2041 0.7702
0.8824 10.0 1070 0.0 0.8843 0.0 0.0 0.0 nan 0.0371 0.7441 0.2783 0.7581 0.1750 nan 0.8493 0.7731 0.0 0.0 0.7427 0.9100 0.1120 0.0 0.0 0.9336 nan 0.0 0.0 0.9236 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0131 0.0 0.0 0.5406 0.0 0.0 0.0 nan 0.0352 0.5175 0.1624 0.4615 0.1452 nan 0.5509 0.7306 0.0 0.0 0.6595 0.7475 0.0968 0.0 0.0 0.8444 nan 0.0 0.0 0.6323 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0123 0.0 0.9102 0.2624 0.1980 0.7420
0.8133 11.0 1177 0.0 0.8471 0.0 0.0001 0.0 nan 0.2570 0.6660 0.3263 0.7662 0.2418 nan 0.6984 0.9167 0.0308 0.0 0.7725 0.8677 0.1876 0.0 0.0 0.9201 nan 0.0 0.0 0.9386 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0227 0.0 0.0 0.5412 0.0 0.0001 0.0 nan 0.1887 0.5137 0.1982 0.5765 0.1849 nan 0.5743 0.7964 0.0299 0.0 0.6809 0.7657 0.1367 0.0 0.0 0.8434 nan 0.0 0.0 0.6371 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0212 0.0 0.8147 0.2729 0.2158 0.7737
0.8029 12.0 1284 0.0 0.8274 0.0 0.0001 0.0 nan 0.2257 0.7924 0.3257 0.8064 0.3262 nan 0.4170 0.9044 0.1800 0.0 0.8542 0.8370 0.1968 0.0 0.0 0.9124 nan 0.0 0.0 0.9401 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0575 0.0 0.0 0.5649 0.0 0.0001 0.0 nan 0.1804 0.4960 0.1876 0.4040 0.2183 nan 0.3817 0.7994 0.1545 0.0 0.5926 0.7280 0.1465 0.0 0.0 0.8639 nan 0.0 0.0 0.6549 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0486 0.0 0.8597 0.2775 0.2071 0.7427
0.8166 13.0 1391 0.0 0.8364 0.0 0.0 0.0 nan 0.2578 0.6942 0.2631 0.7621 0.2267 nan 0.5905 0.9075 0.2544 0.0 0.7529 0.9264 0.2317 0.0 0.0 0.9297 nan 0.0 0.0 0.9342 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0362 0.0 0.0 0.5759 0.0 0.0 0.0 nan 0.2117 0.5555 0.1845 0.4370 0.1793 nan 0.5142 0.7828 0.2029 0.0 0.6831 0.7646 0.1479 0.0 0.0 0.8628 nan 0.0 0.0 0.6656 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0336 0.0 0.8034 0.2775 0.2194 0.7655
0.7582 14.0 1498 0.0 0.8060 0.0 0.0022 0.0 nan 0.4223 0.7450 0.3414 0.7468 0.2863 nan 0.6522 0.9323 0.2355 0.0 0.8710 0.8169 0.2442 0.0 0.0 0.9435 nan 0.0 0.0 0.8890 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0539 0.0 0.0 0.5605 0.0 0.0022 0.0 nan 0.2575 0.5183 0.2118 0.5597 0.2211 nan 0.5628 0.8109 0.1857 0.0 0.5691 0.7164 0.1531 0.0 0.0 0.8665 nan 0.0 0.0 0.6934 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0498 0.0 0.7747 0.2900 0.2238 0.7727
0.7669 15.0 1605 0.0 0.7878 0.0 0.0034 0.0 nan 0.3742 0.7369 0.3506 0.6943 0.2288 nan 0.5781 0.9404 0.2633 0.0 0.8169 0.8762 0.3000 0.0 0.0 0.9231 nan 0.0 0.0 0.9461 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0484 0.0 0.0 0.5657 0.0 0.0034 0.0 nan 0.2425 0.4899 0.1978 0.4820 0.1886 nan 0.5133 0.8055 0.2088 0.0 0.6658 0.7638 0.1512 0.0 0.0 0.8597 nan 0.0 0.0 0.6478 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0436 0.0 0.7869 0.2861 0.2203 0.7690
0.6652 16.0 1712 0.0 0.8814 0.0 0.0004 0.0 nan 0.3337 0.8311 0.3079 0.7933 0.2521 nan 0.6354 0.9192 0.4108 0.0 0.7857 0.9223 0.2649 0.0 0.0 0.9252 nan 0.0 0.0 0.8721 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0474 0.0 0.0 0.5338 0.0 0.0004 0.0 nan 0.2333 0.5449 0.1959 0.5722 0.2055 nan 0.5614 0.8214 0.2604 0.0 0.7013 0.7777 0.1648 0.0 0.0 0.8747 nan 0.0 0.0 0.6819 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0437 0.0 0.7644 0.2962 0.2314 0.7832
0.6706 17.0 1819 0.0 0.8498 0.0 0.0101 0.0 nan 0.3778 0.7270 0.2322 0.8303 0.2801 nan 0.5029 0.9083 0.5548 0.0 0.8575 0.8799 0.2880 0.0 0.0 0.9585 nan 0.0 0.0 0.9107 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0766 0.0 0.0 0.5856 0.0 0.0101 0.0 nan 0.2506 0.5817 0.1612 0.4110 0.2289 nan 0.4506 0.7961 0.3049 0.0 0.6819 0.7806 0.1801 0.0 0.0 0.8821 nan 0.0 0.0 0.7249 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0693 0.0 0.7996 0.2982 0.2290 0.7649
0.6466 18.0 1926 0.0 0.8108 0.0 0.0262 0.0 nan 0.4841 0.8584 0.2654 0.8431 0.3039 nan 0.4422 0.8782 0.5326 0.0 0.8432 0.9130 0.2361 0.0 0.0 0.9411 nan 0.0 0.0 0.9447 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.1762 0.0 0.0 0.5962 0.0 0.0259 0.0 nan 0.2776 0.5696 0.1869 0.3526 0.2396 nan 0.4058 0.7978 0.3165 0.0 0.7060 0.7897 0.1815 0.0 0.0 0.8873 nan 0.0 0.0 0.6949 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.1423 0.0 0.8046 0.3064 0.2313 0.7562
0.652 19.0 2033 0.0 0.8059 0.0 0.0161 0.0 nan 0.5654 0.7580 0.2439 0.7384 0.2594 nan 0.4601 0.9339 0.6299 0.0 0.8739 0.8663 0.2749 0.0 0.0 0.9341 nan 0.0 0.0 0.9147 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.1054 0.0 0.0 0.6110 0.0 0.0161 0.0 nan 0.3079 0.5175 0.1772 0.4120 0.2180 nan 0.4140 0.7907 0.3186 0.0 0.6320 0.7572 0.1810 0.0 0.0 0.8871 nan 0.0 0.0 0.7379 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0937 0.0 0.8110 0.3026 0.2281 0.7623
0.6547 20.0 2140 0.0 0.8135 0.0 0.0793 0.0 nan 0.3920 0.8563 0.3291 0.7943 0.3934 nan 0.6505 0.9035 0.6328 0.0 0.8299 0.9087 0.3951 0.0 0.0 0.9350 nan 0.0 0.0 0.9440 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.1874 0.0 0.0 0.6299 0.0 0.0758 0.0 nan 0.2870 0.5098 0.2266 0.4864 0.2733 nan 0.5700 0.8166 0.3297 0.0 0.7015 0.7944 0.1770 0.0 0.0 0.8913 nan 0.0 0.0 0.7049 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.1436 0.0 0.7205 0.3240 0.2457 0.7885
0.6278 21.0 2247 0.0 0.7191 0.0 0.1114 0.0 nan 0.5394 0.7069 0.4743 0.8021 0.4035 nan 0.6842 0.9158 0.7155 0.0 0.8750 0.8706 0.3563 0.0 0.0 0.9442 nan 0.0 0.0 0.9386 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.2143 0.0 0.0 0.6040 0.0 0.1003 0.0 nan 0.3067 0.5481 0.2581 0.5635 0.2724 nan 0.5997 0.8250 0.3280 0.0 0.6375 0.7686 0.1893 0.0 0.0 0.8921 nan 0.0 0.0 0.7233 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.1503 0.0 0.7129 0.3313 0.2506 0.7905
0.5872 22.0 2354 0.0 0.7515 0.0 0.0535 0.0 nan 0.5099 0.7462 0.3655 0.7844 0.3205 nan 0.6225 0.9094 0.7130 0.0 0.8558 0.9015 0.2839 0.0 0.0 0.9401 nan 0.0 0.0 0.9209 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.2068 0.0 0.0 0.6130 0.0 0.0516 0.0 nan 0.2994 0.5161 0.2294 0.4419 0.2491 nan 0.5430 0.8100 0.3168 0.0 0.6703 0.7680 0.2037 0.0 0.0 0.8899 nan 0.0 0.0 0.7347 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.1663 0.0 0.7458 0.3189 0.2420 0.7798
0.6228 23.0 2461 0.0 0.7653 0.0 0.1850 0.0 nan 0.4119 0.7566 0.3355 0.8048 0.3356 nan 0.6472 0.8888 0.7324 0.0 0.8906 0.8384 0.3526 0.0 0.0 0.9624 nan 0.0 0.0 0.9423 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.2648 0.0 0.0 0.6293 0.0 0.1631 0.0 nan 0.2881 0.4781 0.2163 0.4550 0.2538 nan 0.5476 0.8075 0.3276 0.0 0.5909 0.7407 0.1998 0.0 0.0 0.8925 nan 0.0 0.0 0.7182 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.1918 0.0 0.7450 0.3263 0.2419 0.7736
0.6222 24.0 2568 0.0 0.8326 0.0 0.1325 0.0 nan 0.3981 0.7508 0.3212 0.7890 0.3020 nan 0.5528 0.9168 0.6682 0.0 0.8718 0.8591 0.2781 0.0 0.0 0.9459 nan 0.0 0.0 0.9338 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.1607 0.0 0.0 0.6097 0.0 0.1219 0.0 nan 0.2596 0.4342 0.2183 0.4341 0.2483 nan 0.4997 0.8057 0.3521 0.0 0.6371 0.7705 0.2118 0.0 0.0 0.8957 nan 0.0 0.0 0.7237 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.1366 0.0 0.7382 0.3133 0.2374 0.7739
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0.367 86.0 9202 0.0 0.8308 0.0 0.3721 0.0 nan 0.5010 0.7501 0.3935 0.7990 0.3061 nan 0.7232 0.9394 0.7348 0.0 0.8514 0.9168 0.4360 0.0 0.0 0.9648 nan 0.5879 0.0 0.9403 0.0 0.0 0.0 nan 0.0 0.0355 0.0 0.3496 0.0 0.0 0.6679 0.0 0.2828 0.0 nan 0.3430 0.5220 0.2826 0.5627 0.2552 nan 0.6224 0.8421 0.4371 0.0 0.7338 0.8289 0.2874 0.0 0.0 0.9221 nan 0.3584 0.0 0.7691 0.0 0.0 0.0 nan 0.0 0.0333 0.0 0.2610 0.0 0.6372 0.3688 0.2907 0.8210
0.3734 87.0 9309 0.0 0.8043 0.0 0.3589 0.0 nan 0.5449 0.7606 0.3835 0.8424 0.2978 nan 0.6983 0.9269 0.7200 0.0 0.8592 0.9303 0.4461 0.0 0.0 0.9686 nan 0.6134 0.0 0.9319 0.0 0.0 0.0 nan 0.0 0.0279 0.0 0.3541 0.0 0.0 0.6670 0.0 0.2750 0.0 nan 0.3561 0.4925 0.2822 0.5384 0.2517 nan 0.5999 0.8406 0.4360 0.0 0.7385 0.8269 0.2874 0.0 0.0 0.9218 nan 0.3487 0.0 0.7801 0.0 0.0 0.0 nan 0.0 0.0265 0.0 0.2623 0.0 0.6538 0.3700 0.2881 0.8167
0.3797 88.0 9416 0.0 0.8332 0.0 0.3706 0.0 nan 0.5229 0.7574 0.3755 0.8350 0.2962 nan 0.7156 0.9303 0.6916 0.0 0.8609 0.9256 0.4300 0.0 0.0 0.9661 nan 0.6016 0.0 0.9327 0.0 0.0 0.0 nan 0.0 0.0317 0.0 0.3311 0.0 0.0 0.6693 0.0 0.2822 0.0 nan 0.3464 0.4905 0.2794 0.5576 0.2512 nan 0.6087 0.8444 0.4313 0.0 0.7417 0.8312 0.2894 0.0 0.0 0.9224 nan 0.3525 0.0 0.7791 0.0 0.0 0.0 nan 0.0 0.0296 0.0 0.2515 0.0 0.6392 0.3680 0.2890 0.8199
0.3523 89.0 9523 0.0 0.8100 0.0 0.3879 0.0 nan 0.5601 0.7567 0.4019 0.8261 0.2994 nan 0.7119 0.9295 0.7163 0.0 0.8690 0.9203 0.4416 0.0 0.0 0.9635 nan 0.6151 0.0 0.9297 0.0 0.0 0.0 nan 0.0 0.0294 0.0 0.3684 0.0 0.0 0.6688 0.0 0.2803 0.0 nan 0.3612 0.4933 0.2870 0.5567 0.2535 nan 0.6092 0.8420 0.4330 0.0 0.7304 0.8258 0.2923 0.0 0.0 0.9239 nan 0.3519 0.0 0.7788 0.0 0.0 0.0 nan 0.0 0.0275 0.0 0.2654 0.0 0.6469 0.3722 0.2897 0.8184
0.3429 90.0 9630 0.0 0.8212 0.0 0.3724 0.0 nan 0.5217 0.7542 0.4025 0.8221 0.3092 nan 0.7147 0.9285 0.7163 0.0 0.8676 0.9360 0.4352 0.0 0.0 0.9629 nan 0.6058 0.0 0.9350 0.0 0.0 0.0 nan 0.0 0.0307 0.0 0.3475 0.0 0.0 0.6660 0.0 0.2753 0.0 nan 0.3474 0.5084 0.2873 0.5590 0.2577 nan 0.6147 0.8444 0.4320 0.0 0.7498 0.8323 0.2899 0.0 0.0 0.9232 nan 0.3492 0.0 0.7710 0.0 0.0 0.0 nan 0.0 0.0286 0.0 0.2584 0.0 0.6468 0.3704 0.2901 0.8205
0.3451 91.0 9737 0.0 0.8004 0.0 0.3826 0.0 nan 0.5398 0.7545 0.3806 0.8163 0.3028 nan 0.7044 0.9406 0.7114 0.0 0.8498 0.9192 0.4569 0.0 0.0 0.9683 nan 0.6080 0.0 0.9401 0.0 0.0 0.0 nan 0.0 0.0307 0.0 0.3752 0.0 0.0 0.6691 0.0 0.2814 0.0 nan 0.3585 0.5136 0.2804 0.5503 0.2537 nan 0.6068 0.8430 0.4304 0.0 0.7354 0.8300 0.2878 0.0 0.0 0.9227 nan 0.3453 0.0 0.7727 0.0 0.0 0.0 nan 0.0 0.0290 0.0 0.2686 0.0 0.6492 0.3704 0.2896 0.8192
0.3414 92.0 9844 0.0 0.8142 0.0 0.3795 0.0 nan 0.5216 0.7561 0.4008 0.8221 0.3113 nan 0.7151 0.9353 0.6918 0.0 0.8487 0.9201 0.4441 0.0 0.0 0.9681 nan 0.6002 0.0 0.9382 0.0 0.0 0.0 nan 0.0 0.0308 0.0 0.3497 0.0 0.0 0.6695 0.0 0.2835 0.0 nan 0.3499 0.5082 0.2868 0.5564 0.2581 nan 0.6108 0.8425 0.4276 0.0 0.7369 0.8308 0.2881 0.0 0.0 0.9221 nan 0.3509 0.0 0.7752 0.0 0.0 0.0 nan 0.0 0.0291 0.0 0.2613 0.0 0.6469 0.3693 0.2899 0.8197
0.3313 93.0 9951 0.0 0.8203 0.0 0.3932 0.0 nan 0.5104 0.7604 0.4028 0.8078 0.2869 nan 0.7376 0.9340 0.6909 0.0 0.8579 0.9290 0.4384 0.0 0.0 0.9618 nan 0.5972 0.0 0.9377 0.0 0.0 0.0 nan 0.0 0.0288 0.0 0.3603 0.0 0.0 0.6687 0.0 0.2859 0.0 nan 0.3457 0.5104 0.2881 0.5710 0.2444 nan 0.6219 0.8456 0.4244 0.0 0.7464 0.8328 0.2898 0.0 0.0 0.9233 nan 0.3474 0.0 0.7735 0.0 0.0 0.0 nan 0.0 0.0272 0.0 0.2651 0.0 0.6325 0.3695 0.2907 0.8223
0.3479 93.4579 10000 0.0 0.8226 0.0 0.3548 0.0 nan 0.5230 0.7581 0.3967 0.8054 0.3003 nan 0.7238 0.9385 0.6829 0.0 0.8618 0.9102 0.4428 0.0 0.0 0.9672 nan 0.6017 0.0 0.9452 0.0 0.0 0.0 nan 0.0 0.0271 0.0 0.3487 0.0 0.0 0.6692 0.0 0.2751 0.0 nan 0.3465 0.5049 0.2854 0.5664 0.2522 nan 0.6174 0.8440 0.4224 0.0 0.7310 0.8289 0.2844 0.0 0.0 0.9220 nan 0.3442 0.0 0.7668 0.0 0.0 0.0 nan 0.0 0.0257 0.0 0.2604 0.0 0.6392 0.3681 0.2886 0.8204
0.3479 93.4673 10001 0.0 0.8702 0.0 0.5326 0.0 nan 0.6362 0.7814 0.5120 0.7826 0.4144 nan 0.7943 0.9502 0.8395 0.0 0.8952 0.9156 0.5517 0.0 0.0 0.9616 nan 0.5202 0.0 0.9422 0.0 0.0 0.0 0.0 0.0 0.0065 0.0 0.3684 0.0 0.0 0.7275 0.0 0.4609 0.0 nan 0.5010 0.6564 0.3551 0.6281 0.3705 nan 0.6934 0.8442 0.5645 0.0 0.7594 0.8456 0.3953 0.0 0.0 0.9066 nan 0.3567 0.0 0.7782 0.0 0.0 0.0 0.0 0.0 0.0064 0.0 0.2362 0.0 0.5370 0.3836 0.3152 0.8446
0.3479 93.4766 10002 0.5870 0.2962 0.3656 0.8302 nan 0.7752 0.9460 0.8223 0.7550 0.2805 nan 0.5378 0.6477 0.0 0.9354 0.0 0.0 0.0 0.0 0.5094 0.0 0.0 0.8737 0.0 0.5689 0.5286 0.0 nan 0.0 0.4050 0.0 0.0 0.9220 0.8417 0.9603 0.0 0.0091 0.3817 0.0 nan 0.6953 0.8257 0.6744 0.5831 0.2594 nan 0.3720 0.4758 0.0 0.7439 0.0 0.0 0.0 0.0 0.2578 0.0 0.0 0.6847 0.0 0.4535 0.4437 0.0 nan 0.0 0.2822 0.0 0.0 0.8452 0.7081 0.9161 0.0 0.0090 0.2470 0.0

Framework versions

  • Transformers 4.46.0.dev0
  • Pytorch 2.4.1+cu118
  • Datasets 3.0.1
  • Tokenizers 0.20.0
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