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segformer-b0-scene-parse-150_epoch_1000_230609

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PyTorch
segformer
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segformer-b0-scene-parse-150_epoch_1000_230609

This model is a fine-tuned version of nvidia/mit-b0 on the scene_parse_150 dataset. It achieves the following results on the evaluation set:

  • Loss: 5.4540
  • Mean Iou: 0.0525
  • Mean Accuracy: 0.1687
  • Overall Accuracy: 0.3376
  • Per Category Iou: [0.3766819148826483, 0.14258576874205844, 0.7799514467840762, 0.27640218562139834, 0.03187365887441956, 0.46183688464364436, 8.260537347954484e-05, 0.0, 0.16884121607493832, 0.0, 0.000928765612453199, 0.2961475473758091, 0.019304084720121028, 0.0, 0.0, 0.03117903394095624, 0.17384245603038237, 0.5531024346603617, 0.029623504231929176, 0.13796048953221096, 0.0, 0.0, 0.013549354243542436, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.1413035211803179, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.12164318000531774, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, 0.01129511677282378, 0.0, 0.0, 0.009438414346389807, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan]
  • Per Category Accuracy: [0.8707401654875447, 0.149054586269418, 0.8042609005227754, 0.8328780623667663, 0.035533560317440226, 0.9776035834266518, 8.302889405513119e-05, nan, 0.24404617988394584, 0.0, 0.0024469820554649264, 0.3118285456212621, 0.13863537592351152, 0.0, 0.0, 0.06206475259621259, 0.9958745329971352, 0.7006516371878415, 0.052656608015217675, 0.15534880467288084, 0.0, nan, 0.025518514496688023, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.1846734917006262, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.17458500286204923, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.01804123711340206, nan, 0.0, 0.010752688172043012, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]

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: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 1000

Training results

Training Loss Epoch Step Validation Loss Mean Iou Mean Accuracy Overall Accuracy Per Category Iou Per Category Accuracy
3.0227 10.0 100 3.6663 0.0479 0.1167 0.3089 [0.34742291476339365, 0.11682178184421513, 0.6488149911585156, 0.24395151870068624, 0.0038975893900915063, 0.2624315443592552, 0.0, 0.0, 0.003999003708418664, 0.0, 0.0, 0.2084876239137377, 0.0, 0.0, 0.0, 0.0, 0.17567339198032164, 0.0, 0.0, 0.0002956110454197677, 0.0, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan] [0.9653016393833345, 0.2069947997263713, 0.7782570406040961, 0.8389412004156356, 0.003916108699229182, 0.6707726763717805, 0.0, nan, 0.004367142166344294, 0.0, 0.0, 0.20997276546825602, 0.0, 0.0, 0.0, 0.0, 0.9880790505485221, 0.0, 0.0, 0.00029730155121456426, 0.0, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]
2.2079 20.0 200 3.0660 0.0509 0.1141 0.3547 [0.3277553764364774, 0.11212165664270696, 0.6227345433051882, 0.24943070621530583, 0.20160312675963035, 0.2070142029675474, 0.0, 0.0, 0.0018593899190914116, 0.0, 0.0, 0.28490518995700864, 0.0, 0.0, 0.0, 0.0, 0.23135691718894483, 0.0, 0.0, 1.7485574401119076e-05, 0.0, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan] [0.9470249184677904, 0.18274678054579627, 0.9001967434278326, 0.7345288213302482, 0.23111623020744998, 0.32462361577703125, 0.0, nan, 0.002236460348162476, 0.0, 0.0, 0.28931899984945736, 0.0, 0.0, 0.0, 0.0, 0.9512666833885596, 0.0, 0.0, 1.7488326542033193e-05, 0.0, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]
2.2655 30.0 300 3.2252 0.0516 0.1118 0.3176 [0.34654207145176147, 0.10961883599692333, 0.6480130599758802, 0.23789457365433603, 0.019519038544723335, 0.30059939609716524, 0.0, 0.0, 0.08029291003310444, 0.0, 0.0, 0.2952283694082718, 0.0, 0.0, 0.0, 0.0, 0.17821266282944562, 0.0, 0.0, 0.004796163069544364, 0.0, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan] [0.9370543534823489, 0.17037371570509202, 0.8255916355936967, 0.7232809503915331, 0.021132304732492058, 0.4149558292895359, 0.0, nan, 0.10372340425531915, 0.0, 0.0, 0.29871422901640915, 0.0, 0.0, 0.0, 0.0, 0.970771891378104, 0.0, 0.0, 0.004826778125601161, 0.0, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]
1.7239 40.0 400 3.4332 0.0522 0.1164 0.3285 [0.3615225644621691, 0.15078978527581602, 0.6560130190081128, 0.25270168573148705, 0.015148556924808489, 0.13458035277913538, 0.0, 0.0, 0.22189647766323023, 0.0, 0.0, 0.31770931389688284, 0.0, 0.0, 0.0, 0.04104692250801216, 0.18085997478600319, 0.005868782126522848, 0.0, 0.0617946505608283, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan] [0.9297730604073234, 0.2385152322191155, 0.8172647042290468, 0.7194138252402223, 0.016694723252370043, 0.18844096055742193, 0.0, nan, 0.3122431092843327, 0.0, 0.0, 0.32333137171714404, 0.0, 0.0, 0.0, 0.06102626756261454, 0.9819799601314869, 0.005868782126522848, 0.0, 0.06262569734702086, 0.0, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]
1.4338 50.0 500 3.3707 0.0563 0.1209 0.3279 [0.3392892370591683, 0.0981899864148101, 0.6562610223960014, 0.27138383523022924, 0.024682122498268545, 0.15488985070271846, 0.0, 0.0, 0.1919966575367903, 0.0, 0.0, 0.3236490627799368, 0.0023455824863174357, 0.0, 0.0, 0.023590786797033927, 0.18483053925694884, 0.19751801749720585, 0.0, 0.17555746269780328, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan] [0.9428062969480537, 0.14544826624338345, 0.8157881916468361, 0.6145622435753233, 0.028146873061880594, 0.19814607440587284, 0.0, nan, 0.3124848887814313, 0.0, 0.0, 0.3288159137253829, 0.009126466753585397, 0.0, 0.0, 0.04392180818570556, 0.9841252029729766, 0.20743109240296273, 0.0, 0.20391388748010703, 0.0, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]
0.5298 60.0 600 3.3318 0.0704 0.1491 0.3468 [0.36499310395332657, 0.14479774696062758, 0.6805358338076979, 0.29754918881601655, 0.017696161051990702, 0.2820369110052444, 0.0, 0.0, 0.19892317883044314, 0.0, 0.0001810669783213445, 0.32470403950222554, 0.01597612359550562, 0.0, 0.0, 0.003308354591836735, 0.1800528058886567, 0.6432694442388811, 0.0, 0.3602002071108043, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0038770685579196215, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan] [0.9503179855486392, 0.20692838499292682, 0.8153984522850344, 0.6648455828003985, 0.01905653929398661, 0.43828542988677366, 0.0, nan, 0.3539651837524178, 0.0, 0.0002803833605220228, 0.34468447631690596, 0.03954802259887006, 0.0, 0.0, 0.0050702504581551615, 0.9803891800551823, 0.7036467397903429, 0.0, 0.43797764991867927, 0.0, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.003911467277237168, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]
0.9622 70.0 700 3.5274 0.0772 0.1603 0.3515 [0.35969490899603457, 0.1576561556119367, 0.6520208897601268, 0.27905377709019263, 0.02266644063102148, 0.3181774021179442, 0.0, 0.0, 0.22944150190260004, 0.02593375869237938, 0.00025690901750651446, 0.327821179977907, 0.024130996839988508, 0.0, 0.0, 0.007516913054372337, 0.18275124331195527, 0.71161668886569, 0.0, 0.4430519569071321, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.04174388844762157, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan] [0.9364704199951538, 0.21666478491588573, 0.8164402555790815, 0.6782144808304142, 0.024030782082600274, 0.6112355356476297, 0.0, nan, 0.3161720261121857, 0.028621726402405255, 0.0005352773246329527, 0.3370991802269088, 0.03650586701434159, 0.0, 0.0, 0.012828344532681736, 0.9850229045928, 0.8000971384627839, 0.0, 0.5681782410241164, 0.0, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.045124976149589775, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]
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0.1402 210.0 2100 4.3218 0.0629 0.1698 0.3424 [0.3663535744203041, 0.12269097951800625, 0.7567037348622491, 0.2798874144360869, 0.031058010881433614, 0.35930590710865784, 0.0, 0.0, 0.2085140562248996, 0.0, 0.00356760231412042, 0.30730718452117717, 0.04588045234248788, 0.0, 0.0, 0.04151223128243143, 0.17212693647544516, 0.6636440821871286, 0.0197592778335005, 0.1625016354834489, 0.0, 0.0, 0.002651385562777968, 0.003097921249943878, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, 0.0, 0.0976978998384491, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, 0.1922110552763819, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan] [0.8981651777024799, 0.13379248052387943, 0.8022372538364968, 0.806375935983546, 0.03355398888706064, 0.7329849446310812, 0.0, nan, 0.35305851063829785, 0.0, 0.008487969004893963, 0.32572294680370606, 0.12342459800086919, 0.0, 0.0, 0.10946854001221747, 0.9885477036000475, 0.7909094588578136, 0.02555012753447754, 0.19548451408684703, 0.0, nan, 0.003366272125095016, 0.0032392845406318954, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.12021667826259815, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.3357183743560389, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]
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0.058 990.0 9900 5.4776 0.0524 0.1681 0.3379 [0.377366941374273, 0.14381370292622475, 0.7799895328298431, 0.2784017031734465, 0.03184976704988154, 0.4614188931577558, 0.00018568952711067095, 0.0, 0.17021298540560054, 0.0, 0.0008786230999775463, 0.2964662912601204, 0.015051851851851853, 0.0, 0.0, 0.032230626689753634, 0.1738196485667161, 0.5534110880332321, 0.029619112895329484, 0.13546313917574018, 0.0, 0.0, 0.013934663197455913, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.13990869681973375, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.11775301888051237, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, 0.011112032506841363, 0.0, 0.0, 0.010879848628192999, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan] [0.8701800660202351, 0.1510603112194409, 0.8042534055350484, 0.8348919668776982, 0.035493057577176704, 0.9787856165235784, 0.00018681501162404516, nan, 0.24938044003868473, 0.0, 0.0022940456769983686, 0.31270785148284497, 0.11038678835289005, 0.0, 0.0, 0.06481368356750153, 0.9961385628853187, 0.7009754320637875, 0.0523107518049371, 0.15186862769101625, 0.0, nan, 0.026170051037028994, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.18124440910446277, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.1683838962030147, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.01817688551275095, nan, 0.0, 0.012365591397849462, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]
0.0205 1000.0 10000 5.4540 0.0525 0.1687 0.3376 [0.3766819148826483, 0.14258576874205844, 0.7799514467840762, 0.27640218562139834, 0.03187365887441956, 0.46183688464364436, 8.260537347954484e-05, 0.0, 0.16884121607493832, 0.0, 0.000928765612453199, 0.2961475473758091, 0.019304084720121028, 0.0, 0.0, 0.03117903394095624, 0.17384245603038237, 0.5531024346603617, 0.029623504231929176, 0.13796048953221096, 0.0, 0.0, 0.013549354243542436, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.1413035211803179, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.12164318000531774, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, 0.01129511677282378, 0.0, 0.0, 0.009438414346389807, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan] [0.8707401654875447, 0.149054586269418, 0.8042609005227754, 0.8328780623667663, 0.035533560317440226, 0.9776035834266518, 8.302889405513119e-05, nan, 0.24404617988394584, 0.0, 0.0024469820554649264, 0.3118285456212621, 0.13863537592351152, 0.0, 0.0, 0.06206475259621259, 0.9958745329971352, 0.7006516371878415, 0.052656608015217675, 0.15534880467288084, 0.0, nan, 0.025518514496688023, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.1846734917006262, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.17458500286204923, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.01804123711340206, nan, 0.0, 0.010752688172043012, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]

Framework versions

  • Transformers 4.29.2
  • Pytorch 2.0.1
  • Datasets 2.12.0
  • Tokenizers 0.13.3
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Dataset used to train manadopeee/segformer-b0-scene-parse-150_epoch_1000_230609

Evaluation results

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