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segformer-b0-scene-parse-150

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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: 2.6066
  • Mean Iou: 0.0688
  • Mean Accuracy: 0.1262
  • Overall Accuracy: 0.5008
  • Per Category Iou: [0.43853467784626365, 0.24573297715749878, 0.6380510638879026, 0.4055319712687706, 0.39704872582170575, 0.3731125869306434, 0.2434579810174668, 0.0, 0.0, 0.6120472479537323, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.41646126174138964, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.01480455169405637, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 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, 0.0, 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]
  • Per Category Accuracy: [0.8826735992812765, 0.3043340877296272, 0.9976989832282037, 0.6216524065587666, 0.9707018877486381, 0.4822455259535185, 0.9546882874336703, nan, 0.0, 0.8994367536265288, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.5587433525494928, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.01480455169405637, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 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, 0.0, 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]

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
4.9836 1.0 20 4.8270 0.0124 0.0559 0.2326 [0.12345389372087832, 0.11147143096565497, 0.4150538794240512, 0.0, 0.293640108509997, 0.0004316952407802231, 0.1743424495064011, 0.0, 0.1276976560079854, 0.0007056565428474653, 0.0, 0.061583158696894645, 4.939552229590388e-05, 0.0, 0.0, 0.0, 0.0, 0.000493114015004755, 0.0, 0.0, 0.0, 0.0, 0.045756685731952386, 0.0, 0.0, 0.0, 0.0505284969399829, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.04502755997205186, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.012764610732118997, 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, nan, nan, 0.0, 0.0005076142131979696, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0] [0.18841535794035377, 0.14909229381485062, 0.9449891489174277, 0.0, 0.4628468263017864, 0.0004959915782654466, 0.59263925532861, nan, 0.18719882937659257, 0.0007202639046946801, 0.0, 0.11125770830345619, 0.006802721088435374, nan, 0.0, 0.0, 0.0, 0.0006256424006792689, nan, 0.0, 0.0, nan, 0.09346974864216244, 0.0, 0.0, 0.0, 0.11449794096139784, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.09154040404040405, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.018720990201134605, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0006021678040947411, 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, 0.0, 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]
4.688 2.0 40 4.3114 0.0170 0.0751 0.3110 [0.1784793666623604, 0.29020648660310755, 0.3967341143059993, 3.0891847641407435e-05, 0.2034361629960977, 0.008162343072599663, 0.2815558456255147, 0.0, 0.155603858659529, 0.05218973982730402, 0.0, 0.005494705432844511, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0069754894404193005, 0.0, 0.0, 0.0, 0.0, 0.052440097468525786, 0.0, 0.0, 0.0, 0.037968658793947285, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 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, nan, 0.00025331419403867264, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, 0.0] [0.320788946588342, 0.42139874795421767, 0.9844934960239391, 3.090425860683602e-05, 0.9593627264664893, 0.011701352336221556, 0.7449381910888447, nan, 0.2185331886873376, 0.053285123669312436, 0.0, 0.008661981930302596, 0.0, nan, 0.0, 0.0, 0.0, 0.008088662465924833, nan, 0.0, 0.0, nan, 0.19571807502841987, 0.0, 0.0, 0.0, 0.05424059320837984, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, 0.0002704530087897228, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 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, 0.0, 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]
4.2628 3.0 60 3.8641 0.0296 0.0768 0.3737 [0.2672464483195483, 0.30063989353452375, 0.46343013043315767, 0.0006310846712622577, 0.2152098765432099, 0.017871182607620207, 0.3743446908107241, 0.0, 0.0, 0.11977134437501705, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.015490085477502495, nan, 0.0, 0.0, nan, 0.05556126644736842, 0.0, 0.0, 0.0, 0.006406069436768327, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0] [0.6253046220083026, 0.48686378195606494, 0.9930141985014027, 0.000631329854396793, 0.9662359052324845, 0.020477366588387724, 0.7609907212521863, nan, 0.0, 0.12646393638629194, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.01595388121732136, nan, 0.0, 0.0, nan, 0.06827080965012, 0.0, 0.0, 0.0, 0.006542739483508448, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 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, 0.0, 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]
3.9402 4.0 80 3.8193 0.0295 0.0767 0.3659 [0.2834437731005024, 0.2261241333235565, 0.4999395656786774, 0.03137167210354625, 0.15235063300510845, 0.034387711222180706, 0.32747194719471945, 0.0, 0.0, 0.05056918263795778, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.023358697575650327, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.02178028516261313, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 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, 0.0, 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] [0.694789905754345, 0.2998239141824703, 0.9937082406831511, 0.03158856719027311, 0.9776700874192322, 0.04937646773018058, 0.9192037470725996, nan, 0.0, 0.05541710482720869, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.02359565625418957, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.022213241991558583, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 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, 0.0, 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]
3.5912 5.0 100 3.6448 0.0364 0.0844 0.3882 [0.3058604423164221, 0.21762328839300885, 0.5110845587230063, 0.06504290063659009, 0.17468867816748543, 0.056915544675642596, 0.3486286890567001, 0.0, 0.0, 0.29609841403847315, 0.0004989190088142358, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.02452937820878494, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.002005190651750417, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 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, 0.0, 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] [0.7690818698094906, 0.2732895099304839, 0.9979312204197888, 0.0674375071742029, 0.9686114278474598, 0.08566483116041784, 0.931328372810008, nan, 0.0, 0.3536639824831818, 0.0005012810515762504, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.024981007284265094, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.002026966349792813, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 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, 0.0, 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]
3.7503 6.0 120 3.5438 0.0379 0.0878 0.3915 [0.3003434283183761, 0.24077015199577623, 0.4792921923103039, 0.09790288306795357, 0.2083111892400147, 0.03344137652223869, 0.30019005561921797, 0.0, 0.0, 0.4232145412909689, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.002411898700254589, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 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, 0.0, 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] [0.7211691408954096, 0.3029729335573116, 0.9986519565316043, 0.10393985148296292, 0.9683580387685291, 0.04772653656166491, 0.955192244982658, nan, 0.0, 0.5537532952073639, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0024131921169057513, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 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, 0.0, 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]
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1.518 49.0 980 2.6536 0.0681 0.1246 0.4959 [0.43788100249764617, 0.2327002408765022, 0.6344844675799025, 0.39711397990519065, 0.399981744924437, 0.3702829804891543, 0.2332744666789456, 0.0, 0.0, 0.6118559477947978, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.41649069552593376, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.012463197326474192, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 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, 0.0, 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] [0.8951970087909084, 0.2877760793358432, 0.997899187703708, 0.5880462327708759, 0.9715887495248955, 0.46066483116041784, 0.9574155871105445, nan, 0.0, 0.8671257148619254, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.5641060016981723, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.01246327727103619, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 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, 0.0, 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]
1.3176 50.0 1000 2.6066 0.0688 0.1262 0.5008 [0.43853467784626365, 0.24573297715749878, 0.6380510638879026, 0.4055319712687706, 0.39704872582170575, 0.3731125869306434, 0.2434579810174668, 0.0, 0.0, 0.6120472479537323, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.41646126174138964, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.01480455169405637, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 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, 0.0, 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] [0.8826735992812765, 0.3043340877296272, 0.9976989832282037, 0.6216524065587666, 0.9707018877486381, 0.4822455259535185, 0.9546882874336703, nan, 0.0, 0.8994367536265288, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.5587433525494928, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.01480455169405637, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 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, 0.0, 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]

Framework versions

  • Transformers 4.32.0.dev0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.1
  • Tokenizers 0.13.3
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