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segformer-b0-scene-parse-150

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segformer
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segformer-b0-scene-parse-150

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: 2.2758
  • Mean Iou: 0.1546
  • Mean Accuracy: 0.2448
  • Overall Accuracy: 0.5711
  • Per Category Iou: [0.525845396578425, 0.6706121263475253, 0.5441146612860046, 0.570977465816495, 0.38965718028968627, 0.7229945780620047, 0.0, 0.5242459575781477, 0.0, 0.5679062909567497, 0.0, 0.02253717472118959, 0.6731798419567641, 0.0, 0.0, 0.0, nan, 0.17624107383867882, 0.002262699400384659, 0.0, nan, 0.0, 0.0, nan, 0.3305173012382826, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 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, nan, nan, nan, nan, nan, nan, nan, nan, 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, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0]
  • Per Category Accuracy: [0.7967704709890467, 0.9791603141724584, 0.9854669230944455, 0.6455993360082901, 0.5026996572609043, 0.84172618204625, nan, 0.5672605491054655, nan, 0.9016777214202107, nan, 0.06622667273554847, 0.9414837595315331, 0.0, 0.0, 0.0, nan, 0.20823427080313134, 0.0039032006245121, 0.0, nan, 0.0, 0.0, nan, 0.3918949823903398, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 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, nan, nan, nan, nan, nan, nan, nan, nan, 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, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 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: 2
  • eval_batch_size: 2
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 50

Training results

Training Loss Epoch Step Validation Loss Mean Iou Mean Accuracy Overall Accuracy Per Category Iou Per Category Accuracy
4.8281 1.0 20 4.8787 0.0110 0.0801 0.1810 [0.028302683213102076, 0.2202226322924318, 0.3600423878901779, 0.03708451073498995, 0.22719483042799601, 0.24371303934407088, nan, 0.03209526740775609, 0.0, 0.0, 0.0, 0.02450795565945253, 0.06250376637620374, 0.00026651806265597366, 0.0, 0.007155016491116076, 0.0, 0.004860342069644395, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.03825686515676701, 0.0028843682471989263, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.00016848568807682947, 0.0, 0.0, 0.0, nan, 0.0007499263465195383, 0.0, 0.0003362474781439139, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.030163030711164707, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] [0.02862399369847998, 0.2584913132927475, 0.8004777106336174, 0.0375116026657892, 0.32574299262876194, 0.5911546320836789, nan, 0.0328915936489677, nan, 0.0, nan, 0.07396449704142012, 0.07282582747047507, 0.00030378348522507595, 0.0, 0.06900266776113277, nan, 0.011452594955059438, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.21127018250011434, 0.0029144423604097534, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0014335775724753105, nan, nan, nan, nan, 0.0019353055017970694, nan, 0.00040584415584415587, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.04369625881979264, 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, nan, nan, nan, nan, nan, nan, nan, nan, 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, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0]
4.5554 2.0 40 4.4993 0.0295 0.1384 0.3351 [0.19675681977150852, 0.46595963137965224, 0.41480367238964677, 0.2876260437103618, 0.30453572309724863, 0.3634189140173906, nan, 0.1162275343869079, 0.0, 0.0, 0.0, 0.005260344876086528, 0.20000697131304682, 0.0, 0.0, 0.010060076072660054, 0.0, 0.005855729153348505, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.060538034445661984, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.00020534302552413806, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.018256002035512423, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0] [0.23242087984422466, 0.6473585890978932, 0.9628700386268748, 0.309595957115565, 0.5988387561231356, 0.7500354057498938, nan, 0.12577752832963027, nan, 0.0, nan, 0.042558033682294036, 0.2417323166364747, 0.0, 0.0, 0.0725938846706341, nan, 0.0066396056828066105, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.415679458445776, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0006911805363560963, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0227896635433446, 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, nan, nan, nan, nan, nan, nan, nan, nan, 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, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0]
4.0429 3.0 60 3.9628 0.0627 0.1719 0.4471 [0.5349072675967054, 0.5585340463327029, 0.5152604269800354, 0.4098607113041731, 0.39026186285426917, 0.38422708974025627, nan, 0.03402496294841348, 0.0, 0.008697524219590958, 0.0, 0.012294589350412968, 0.2851442522248182, 0.00048140846361927465, 0.0, 0.024549713169167563, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.03730952879182757, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, 0.00015832805573147562, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0014838781657927032, 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, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, 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, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0] [0.6693106610812285, 0.8518475681775964, 0.9568465891525842, 0.5810860586296822, 0.6801258275036387, 0.867016003398952, nan, 0.035354636411286396, nan, 0.00875709888585425, nan, 0.162949476558944, 0.3050652286865793, 0.000579950289975145, 0.0, 0.2011081469320747, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.17941270639893886, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.00015928639694170118, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.001508723370465322, 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, nan, nan, nan, nan, nan, nan, nan, nan, 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, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0]
4.2215 4.0 80 3.6208 0.0791 0.1804 0.4733 [0.5342977670285168, 0.5664723257846467, 0.5333716552985959, 0.4136706626909268, 0.3846476890012434, 0.42613561055043264, nan, 0.09061398318151133, 0.0, 0.029034059184812954, 0.0, 0.003527130487111765, 0.3407203216409466, 0.0042294475284166, 0.0, 0.03600522783329894, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.03686583217007254, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.003252509966458491, 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, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 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, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0] [0.6540636266239221, 0.8973051405259339, 0.9903839582946902, 0.6677094741598196, 0.7310515360658559, 0.9106561191251745, nan, 0.10086415229118639, nan, 0.029305934885334027, nan, 0.04802002730996814, 0.3974807262922863, 0.006628003314001657, 0.0, 0.18797455366304125, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.1473722727896446, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.003267010005218141, 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, nan, nan, nan, nan, nan, nan, nan, nan, 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, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0]
3.9988 5.0 100 3.3967 0.0886 0.1811 0.4941 [0.5775583187750488, 0.5992114251656236, 0.5283269343628252, 0.4287362887488728, 0.34817400110310404, 0.44993526584889515, nan, 0.11246408312133113, 0.0, 0.002164877034984413, 0.0, 0.009439468988175647, 0.29632098281382735, 0.0, 0.0, 0.019754450583179865, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.08137086080794868, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0036620899989796033, 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, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 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, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0] [0.7739494941983601, 0.9161400668019529, 0.9726129925577369, 0.7261819985561127, 0.6026417515689313, 0.8296679952252817, nan, 0.12672378204622728, nan, 0.0021675987341223395, nan, 0.1288120163859809, 0.31839182148825323, 0.0, 0.0, 0.08254668581982352, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.310158715638293, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.003664042471130068, 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, nan, nan, nan, nan, nan, nan, nan, nan, 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, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0]
3.1879 6.0 120 3.3499 0.0964 0.1881 0.5016 [0.5658327762636911, 0.6217913478443899, 0.5328723733003708, 0.3722624891944134, 0.3481118477947535, 0.5248120118077236, nan, 0.1891076331580741, 0.0, 0.0, 0.0, 0.02361914667706776, 0.29599673757901174, 0.0071870794078061915, 0.0, 0.002949351779159329, nan, 0.0, 0.0, 0.0014773776546629731, nan, 0.0, 0.0, 0.0, 0.08143261800921078, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0005785330217573791, 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, nan, nan, nan, nan, nan, nan, nan, nan, 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, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0] [0.7273463384808599, 0.8800543948745448, 0.9876049059710575, 0.7973302818526941, 0.6614708045761147, 0.8740566896635442, nan, 0.22906297689563843, nan, 0.0, nan, 0.24806554392353208, 0.30578141017539423, 0.007373653686826844, 0.0, 0.007131130720295506, nan, 0.0, 0.0, 0.0018652366519002097, nan, 0.0, 0.0, nan, 0.2899419109911723, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0005785330217573791, 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, nan, nan, nan, nan, nan, nan, nan, nan, 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, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0]
3.5834 7.0 140 3.0377 0.0972 0.1894 0.5118 [0.5108056284955569, 0.6108653859389123, 0.5206645157397449, 0.4472189084808175, 0.32259958487351875, 0.44224477462646133, nan, 0.17925331282485557, 0.0, 0.0017308524448290783, 0.0, 2.9571800331204164e-05, 0.4191510553819705, 0.0064555285808872214, 0.0, 0.001097432961160416, nan, 0.0, 0.0, 0.0005841121495327102, nan, 0.0, 0.0, 0.0, 0.13254004026563299, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 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, nan, nan, nan, nan, nan, nan, nan, nan, 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, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0] [0.7586473765240838, 0.9332471146533203, 0.9547151145952314, 0.8064159672325985, 0.6105294458268776, 0.8587209419952657, nan, 0.1924420303636119, nan, 0.0017340789872978715, nan, 0.0002275830678197542, 0.43139402620381684, 0.006462303231151615, 0.0, 0.002359942540529448, nan, 0.0, 0.0, 0.0006994637444625787, nan, 0.0, 0.0, nan, 0.5043681105063349, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 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, nan, nan, nan, nan, nan, nan, nan, nan, 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, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0]
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1.5924 50.0 1000 2.2758 0.1546 0.2448 0.5711 [0.525845396578425, 0.6706121263475253, 0.5441146612860046, 0.570977465816495, 0.38965718028968627, 0.7229945780620047, 0.0, 0.5242459575781477, 0.0, 0.5679062909567497, 0.0, 0.02253717472118959, 0.6731798419567641, 0.0, 0.0, 0.0, nan, 0.17624107383867882, 0.002262699400384659, 0.0, nan, 0.0, 0.0, nan, 0.3305173012382826, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 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, nan, nan, nan, nan, nan, nan, nan, nan, 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, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0] [0.7967704709890467, 0.9791603141724584, 0.9854669230944455, 0.6455993360082901, 0.5026996572609043, 0.84172618204625, nan, 0.5672605491054655, nan, 0.9016777214202107, nan, 0.06622667273554847, 0.9414837595315331, 0.0, 0.0, 0.0, nan, 0.20823427080313134, 0.0039032006245121, 0.0, nan, 0.0, 0.0, nan, 0.3918949823903398, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 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, nan, nan, nan, nan, nan, nan, nan, nan, 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, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0]

Framework versions

  • Transformers 4.42.4
  • Pytorch 2.3.1+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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