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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: 1.9189
  • Mean Iou: 0.1362
  • Mean Accuracy: 0.2014
  • Overall Accuracy: 0.5622
  • Per Category Iou: [0.5394486238576831, nan, nan, 0.5953296561678437, nan, 0.5305918700503232, nan, nan, 0.45864878291107797, nan, 0.2527963616569211, nan, nan, nan, 0.29357850916534417, 0.0, nan, nan, 0.10623097394858876, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.18785814116002794, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.15775911336081969, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.21968459188747602, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.15961103761497517, nan, nan, nan, nan, nan, nan, 0.4441676196699886, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.004493932281716791, 0.0, 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, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 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]
  • Per Category Accuracy: [0.7739608529583082, nan, nan, 0.7817504907601706, nan, 0.5577609008587373, nan, nan, 0.581178396072013, nan, 0.4749674205308391, nan, nan, nan, 0.3909988627966014, 0.0, nan, nan, 0.14556099872240696, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.28374527223150675, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.3724984638369137, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.3698572795407431, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.33803609248146843, nan, nan, nan, nan, nan, nan, 0.7644364258350224, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.004869009836582626, 0.0, 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, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 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]

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
4.6747 1.0 20 4.8597 0.0065 0.0375 0.2163 [0.3265714548058666, nan, nan, 0.03815267090202893, nan, 0.0, nan, nan, 0.0009106251745364918, nan, 0.08879199595125939, 0.0, 0.0, 0.0, 0.00016071449070725855, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0684388266126513, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, 0.07230662020905923, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, 0.007989604232562456, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.007686209630165788, 0.0, nan, 0.0, 0.0, 0.008133079302644787, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0019369634611212693, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0] [0.4868232668227273, nan, nan, 0.04002797897064465, nan, 0.0, nan, nan, 0.0009442276218053632, nan, 0.1881196285115719, nan, nan, nan, 0.0001608166422250897, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.1830679919078195, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.10341253388614256, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.012343363925167666, nan, nan, nan, nan, nan, nan, 0.010450226694940076, 0.0, nan, nan, nan, 0.04648258366669919, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.016110323495295786, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 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]
4.334 2.0 40 4.4109 0.0292 0.0904 0.3570 [0.40822193324211764, nan, nan, 0.4972948279565127, nan, 0.00677162341300753, nan, nan, 0.021716176263550612, nan, 0.20600620942703923, nan, nan, 0.0, 0.04702016385245008, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, 0.07608189236319103, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0248319641523525, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, 0.1290239135433433, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.007111797456008453, nan, nan, nan, nan, nan, nan, 0.08724145559119566, 0.0, nan, 0.0, nan, 0.00847684312426759, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0005462668513568879, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan] [0.62539352358344, nan, nan, 0.6582729754732733, nan, 0.00702732217187511, nan, nan, 0.023303537706156365, nan, 0.30100130317876644, nan, nan, nan, 0.04788506970635647, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.4021813703931744, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.025638863118832757, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.2684380481581885, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.013512619131662549, nan, nan, nan, nan, nan, nan, 0.22177442974799957, 0.0, nan, nan, nan, 0.02597326568445702, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0005519525320822409, 0.0, 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, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 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]
3.7046 3.0 60 3.8875 0.0540 0.1233 0.4073 [0.42447762223294944, nan, nan, 0.5596961061443035, nan, 0.014508170906673199, nan, nan, 0.0761798050625896, nan, 0.2211901122457286, nan, 0.0, 0.0, 0.19911595283640804, 0.0, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.07939833997356549, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.11004576381014093, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.1745264842754246, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.009196143783822528, nan, nan, nan, nan, nan, nan, 0.12928620315549433, 0.0, nan, 0.0, nan, 0.0002515602726434193, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0016980579681858104, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 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] [0.6149858176648253, nan, nan, 0.8783411178050047, nan, 0.01469993830706065, nan, nan, 0.07960468336900416, nan, 0.40340805991323136, nan, nan, nan, 0.21163470116821803, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.3682821708153751, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.13095338498054193, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.3520969542337745, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.014152400282386164, nan, nan, nan, nan, nan, nan, 0.5067891327014773, 0.0, nan, nan, nan, 0.00040979607766611375, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0017149953675412485, 0.0, 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, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 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]
3.7447 4.0 80 3.5751 0.0669 0.1409 0.4531 [0.45553073786639314, nan, nan, 0.5089103314226779, nan, 0.17654022857065982, nan, nan, 0.10651963305385784, nan, 0.22449823943661973, nan, nan, 0.0, 0.30572018678160917, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, 0.07968346267949343, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.11395532482154166, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.18828325532236148, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.08695018124748267, nan, nan, nan, nan, nan, nan, 0.15928904841484798, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0023818897637795274, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 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] [0.652654179817423, nan, nan, 0.9263295651977707, nan, 0.1861070337042001, nan, nan, 0.11212388266398086, nan, 0.4206957984856733, nan, nan, nan, 0.3389287314247206, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.3075996129826722, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.17560452535572718, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.372847233296125, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.1381155135898341, nan, nan, nan, nan, nan, nan, 0.45336644914886887, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.002385223442212541, 0.0, 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, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 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]
3.3946 5.0 100 3.3308 0.0755 0.1365 0.4706 [0.47825793108154574, nan, nan, 0.5095164268167514, nan, 0.18855495049817325, nan, nan, 0.15197077711659696, nan, 0.24498588309108021, nan, 0.0, 0.0, 0.30906703391730456, 0.0, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, 0.07518666666666667, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.09868151894967828, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.1753476126847209, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.027675953079178885, nan, nan, nan, nan, nan, nan, 0.21760887149161592, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.016221485669721192, 0.0, 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, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 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] [0.7282167024846812, nan, nan, 0.7459870484442338, nan, 0.21189751880925536, nan, nan, 0.16236938184565025, nan, 0.3864667359495884, nan, nan, nan, 0.3694953803505037, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.2975987333978362, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.12786901047000565, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.26419231382554614, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.03830965407695023, nan, nan, nan, nan, nan, nan, 0.6083039469522125, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.01640087523901516, 0.0, 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, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 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]
3.1622 6.0 120 3.0382 0.0808 0.1282 0.5014 [0.5027396406688129, nan, nan, 0.5289850095300239, nan, 0.18454429129290398, nan, nan, 0.06691391050583657, nan, 0.2852541675241819, nan, 0.0, nan, 0.23331035904306713, 0.0, nan, nan, 0.00045393770324028985, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.07002929119258877, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.09297910912421577, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.20443002433393648, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.038015874382328126, nan, nan, nan, nan, nan, nan, 0.20494239929494218, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.010389307184964688, 0.0, 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, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 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] [0.8463981664373714, nan, nan, 0.8341298314492656, nan, 0.1973819502059977, nan, nan, 0.06928112803726552, nan, 0.4572837795483413, nan, nan, nan, 0.2773742471292315, 0.0, nan, nan, 0.000465348461388769, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.18736916175565133, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.11802551837973951, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.3265428161377771, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.04871161313095658, nan, nan, nan, nan, nan, nan, 0.3432641728270675, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.010526523290425594, 0.0, 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, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 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]
3.3025 7.0 140 3.1524 0.1060 0.1674 0.5038 [0.4903212647056243, nan, nan, 0.5730280573974511, nan, 0.34883955536780514, nan, nan, 0.2538729876714406, nan, 0.31698155519425913, nan, nan, nan, 0.3404773678746281, 0.0, nan, nan, 0.06970904342585463, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0892728785451911, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.14084552219656146, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.13866976024748648, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.05071803412626088, nan, nan, nan, nan, nan, nan, 0.26098956242472904, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 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, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 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] [0.6700846144393057, nan, nan, 0.9152959227419392, nan, 0.39233163855028685, nan, nan, 0.29502706785849175, nan, 0.4663400471783705, nan, nan, nan, 0.503536051645116, 0.0, nan, nan, 0.07046221793537578, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.27747383235113027, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.26452125929228065, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.1786995694466592, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0890178256265443, nan, nan, nan, nan, nan, nan, 0.731187834623991, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 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, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 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]
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0.8229 48.0 960 1.9207 0.1370 0.2033 0.5613 [0.5370950646304242, nan, nan, 0.6015766777930628, nan, 0.5451042354180416, nan, nan, 0.45685997171145687, nan, 0.2515579650144248, nan, nan, nan, 0.29504979047977775, 0.0, nan, nan, 0.10680781799430922, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.1833671075085324, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.15836257065322534, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.225375833615915, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.16521674028599237, nan, nan, nan, nan, nan, nan, 0.4436385927211615, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.003923013168800073, 0.0, 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, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 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] [0.7649818711890282, nan, nan, 0.7913490827861639, nan, 0.5798001716056473, nan, nan, 0.5652398338159386, nan, 0.4761056399597499, nan, nan, nan, 0.38391144363568136, 0.0, nan, nan, 0.14545946814901303, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.30244524584396165, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.36490801093989084, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.39744458619040024, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.36513854571126014, nan, nan, nan, nan, nan, nan, 0.7546071206813735, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.004198781761911333, 0.0, 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, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 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]
1.1484 49.0 980 1.9097 0.1355 0.2011 0.5595 [0.5379186069232229, nan, nan, 0.5945120151660874, nan, 0.5255949799414508, nan, nan, 0.45422437885814315, nan, 0.251876614761539, nan, nan, nan, 0.29943005664467703, 0.0, nan, nan, 0.10638311114430461, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.18116246389662377, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.15605314727932793, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.21733286169083835, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.16492020475760313, nan, nan, nan, nan, nan, nan, 0.4350193418472789, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.00479151426481346, 0.0, 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, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 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] [0.7673877227635721, nan, nan, 0.7726979399354679, nan, 0.5499960998716503, nan, nan, 0.5586050610600529, nan, 0.4760231602909883, nan, nan, nan, 0.39347237591273015, 0.0, nan, nan, 0.14462184091851327, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.30730055413844665, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.35787178158773, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.36740551746132993, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.36249117543240383, nan, nan, nan, nan, nan, nan, 0.7694037981653525, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.005164698693055254, 0.0, 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, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 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]
0.6254 50.0 1000 1.9189 0.1362 0.2014 0.5622 [0.5394486238576831, nan, nan, 0.5953296561678437, nan, 0.5305918700503232, nan, nan, 0.45864878291107797, nan, 0.2527963616569211, nan, nan, nan, 0.29357850916534417, 0.0, nan, nan, 0.10623097394858876, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.18785814116002794, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.15775911336081969, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.21968459188747602, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.15961103761497517, nan, nan, nan, nan, nan, nan, 0.4441676196699886, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.004493932281716791, 0.0, 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, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 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] [0.7739608529583082, nan, nan, 0.7817504907601706, nan, 0.5577609008587373, nan, nan, 0.581178396072013, nan, 0.4749674205308391, nan, nan, nan, 0.3909988627966014, 0.0, nan, nan, 0.14556099872240696, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.28374527223150675, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.3724984638369137, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.3698572795407431, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.33803609248146843, nan, nan, nan, nan, nan, nan, 0.7644364258350224, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.004869009836582626, 0.0, 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, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 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]

Framework versions

  • Transformers 4.32.1
  • Pytorch 2.1.1+cpu
  • Datasets 2.12.0
  • Tokenizers 0.13.2
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