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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: 2.6888
  • Mean Iou: 0.0707
  • Mean Accuracy: 0.1197
  • Overall Accuracy: 0.4906
  • Per Category Iou: [0.4415036020019309, 0.8523328409339264, 0.8177294034546972, 0.37529152669357374, 0.0, 0.3154792713672716, 0.05970276977493796, 0.01978970408954893, 0.07565132680664692, 0.0, 0.0, 0.0, 0.0, nan, 0.022858017135862913, 0.011225201550764839, nan, 0.10394415357766143, 1.7838667094794678e-05, 0.16320877381423485, 0.6260946260946261, nan, 0.0, 0.14388990770070173, nan, 0.0, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 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, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan]
  • Per Category Accuracy: [0.8267252999175692, 0.8635981633801915, 0.9887417989828797, 0.9322714395602334, nan, 0.4900028526231166, 0.0600910121875942, 0.019810149841560404, 0.11533410251374705, 0.0, nan, 0.0, 0.0, nan, 0.24348109517601044, 0.011353382225066037, nan, 0.10738497043127074, 1.7838667094794678e-05, 0.29308528863114347, 0.6652386371243055, nan, 0.0, 0.48672203424587307, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 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, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • 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
4.9131 1.0 20 4.9586 0.0057 0.0248 0.1072 [0.16271142875502467, 0.0631424958599855, 0.03674322786950773, 0.32088450014769804, 0.0, 0.014728138496179544, 0.0004536969822669294, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.032272752170459836, 0.0, 0.007284708509877251, 0.0, 0.07622521237572204, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0031753348185705873, 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, 0.0, 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, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 4.23570273838182e-05, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, 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, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, 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, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] [0.20155946522512833, 0.0636814035574504, 0.06958732870064832, 0.3423875724658074, nan, 0.015520863048157465, 0.0005024332122708546, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.15466522288395596, nan, 0.18065772392903506, 0.0, 0.23126023120947173, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, 0.003376630449582006, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0022417336073229962, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan]
4.6679 2.0 40 4.7798 0.0149 0.0684 0.2795 [0.41526403570202886, 0.14449589078692573, 0.17848105034386258, 0.3940437987677969, 0.0, 0.22606797630183972, 0.0, 0.0, 0.001112802417029913, 0.0, 0.0, 0.0, 0.002268233104571362, 0.0, 0.0, 0.1116395752431355, 0.0, 0.019478230213291026, 0.0, 0.08864065317991807, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.004505011825656042, 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, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.004554212646698196, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.000126098104325165, 0.0, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, 0.0006387735547748323, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan] [0.5800446471214635, 0.1516998871455289, 0.6982025699755425, 0.7132399016903999, nan, 0.33842483338087703, 0.0, 0.0, 0.0011844560094265515, 0.0, nan, 0.0, 0.0031097998564707757, nan, 0.0, 0.26649275647651394, nan, 0.20719746141641426, 0.0, 0.402281639023895, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, 0.008168822328114363, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.11657014758079581, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, 0.0028735632183908046, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0006563833278634722, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan]
4.2143 3.0 60 4.4674 0.0266 0.0795 0.3264 [0.40699175360204165, 0.24717396739971662, 0.5808947700063012, 0.3143815645901191, 0.0, 0.2822031097893167, 0.0, 2.7719643525384263e-05, 0.011830112198508498, 0.0, 0.0, 0.0, 0.0, 0.0, 0.034489593657086225, 0.08695104859893084, 0.0, 0.015396089712854936, 0.00030248033877797946, 0.1023186984622242, 0.0030932390631904553, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0022515446643627604, nan, 0.0, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.011604326273095988, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, nan] [0.6330286102433658, 0.27692566278657166, 0.8947164097985171, 0.725419785745108, nan, 0.40971447835896374, 0.0, 2.7735596558012466e-05, 0.012967645326001571, 0.0, nan, 0.0, 0.0, nan, 0.056714471968709254, 0.16998900756345262, nan, 0.08336939275926727, 0.0003032573406115095, 0.7282463865588874, 0.003280005355110784, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, 0.00292716133424098, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.05772464038856716, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan]
3.9013 4.0 80 4.2891 0.0286 0.0787 0.3321 [0.4317680732341701, 0.20177274765274097, 0.5845836505169069, 0.27795719583302836, 0.0, 0.28061718768460103, 0.0, 0.0, 0.02157439744750571, 0.0, 0.0, 0.0, 0.0, 0.0, 0.014417344173441735, 0.01803661947212026, 0.0, 0.010614812350681948, 0.0, 0.11278714853971505, 0.0, 0.0, 0.0, 0.020108683190791735, nan, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan] [0.7132572233169768, 0.20290860388614237, 0.924181839357118, 0.6840059285942103, nan, 0.46196934726796507, 0.0, 0.0, 0.024566722309505105, 0.0, nan, 0.0, 0.0, nan, 0.08670143415906127, 0.02708733244737576, nan, 0.02531371700562527, 0.0, 0.841237008743322, 0.0, nan, 0.0, 0.02248026248333846, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 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, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan]
3.7138 5.0 100 3.9207 0.0334 0.0754 0.3866 [0.39533436673600314, 0.41913782145680584, 0.6296196211653284, 0.2657397735123425, 0.0, 0.18049224398470504, 0.0, 0.00025655426816161535, 0.005437715811159795, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0510938602681722, 0.033338780846543556, nan, 0.00503490101842316, 0.0, 0.12880259388864115, 0.02004239737907111, nan, 0.0, 0.002835672763363108, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan] [0.8946034295498848, 0.4328329140198336, 0.9497457199425443, 0.6595936286373614, nan, 0.2803220870828039, 0.0, 0.00025655426816161535, 0.005750441869599372, 0.0, nan, 0.0, 0.0, nan, 0.11799217731421122, 0.04016340995225673, nan, 0.006346458964373287, 0.0, 0.4325216045074426, 0.02088493205703193, nan, 0.0, 0.0030759766225776685, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 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, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan]
3.8038 6.0 120 3.8465 0.0430 0.0887 0.4111 [0.4311648697791428, 0.5470893990025003, 0.6223746987359206, 0.30599206953086194, 0.0, 0.2683889644282644, 0.0, 0.0, 0.026833528695212484, 0.0, 0.0, 0.0, 0.0, nan, 0.035525950596724955, 0.009893983126110124, nan, 0.009826103820544314, 0.0, 0.13802782708968697, 0.013595468177274242, nan, 0.0, 0.044167283360106856, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 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, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan] [0.796126809145938, 0.5551639591376104, 0.9824527349664195, 0.7997598544117371, nan, 0.4760509322891004, 0.0, 0.0, 0.028660153181461114, 0.0, nan, 0.0, 0.0, nan, 0.20860495436766624, 0.011697921281029023, nan, 0.010962065483917496, 0.0, 0.5771988376077053, 0.01365553249882857, nan, 0.0, 0.06272428996206296, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 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, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan]
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1.8328 49.0 980 2.6763 0.0689 0.1156 0.4889 [0.4376471178140347, 0.850819547112454, 0.8315124950935496, 0.3680024481360312, 0.0, 0.307117903930131, 0.05044730900048589, 0.009257334497429288, 0.07258397995670259, 0.0, 0.0, 0.0, 0.0, nan, 0.020940965764276367, 0.011856616154233461, nan, 0.03958333333333333, 0.0, 0.15822959507576803, 0.6246765541180183, nan, 0.0, 0.1431078454687846, nan, 0.0, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 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, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan] [0.833721312809337, 0.8631953022658937, 0.9868783726076323, 0.9340500178233054, nan, 0.45596587225435026, 0.05067397826617476, 0.009263689250376165, 0.10987824037706206, 0.0, nan, 0.0, 0.0, nan, 0.1981747066492829, 0.011976833850141918, nan, 0.03973748737920092, 0.0, 0.2909787698437877, 0.6625610817323784, nan, 0.0, 0.44732390033835745, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 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, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan]
1.0733 50.0 1000 2.6888 0.0707 0.1197 0.4906 [0.4415036020019309, 0.8523328409339264, 0.8177294034546972, 0.37529152669357374, 0.0, 0.3154792713672716, 0.05970276977493796, 0.01978970408954893, 0.07565132680664692, 0.0, 0.0, 0.0, 0.0, nan, 0.022858017135862913, 0.011225201550764839, nan, 0.10394415357766143, 1.7838667094794678e-05, 0.16320877381423485, 0.6260946260946261, nan, 0.0, 0.14388990770070173, nan, 0.0, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 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, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan] [0.8267252999175692, 0.8635981633801915, 0.9887417989828797, 0.9322714395602334, nan, 0.4900028526231166, 0.0600910121875942, 0.019810149841560404, 0.11533410251374705, 0.0, nan, 0.0, 0.0, nan, 0.24348109517601044, 0.011353382225066037, nan, 0.10738497043127074, 1.7838667094794678e-05, 0.29308528863114347, 0.6652386371243055, nan, 0.0, 0.48672203424587307, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 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, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan]

Framework versions

  • Transformers 4.46.2
  • Pytorch 2.5.1+cu124
  • Datasets 3.1.0
  • Tokenizers 0.20.1
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