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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: 2.3867
  • Mean Iou: 0.0854
  • Mean Accuracy: 0.1569
  • Overall Accuracy: 0.5029
  • Per Category Iou: [0.2771319317345961, 0.5947571607182376, 0.939295828662458, 0.5107730625538844, 0.022752808988764046, 0.39377705160129767, 0.03627070632428105, 0.5970283178156206, 0.009085428262972674, 0.0, 0.19687228940252055, 0.3002657911194497, 0.0, 0.0, 0.0, 0.1685958623072604, nan, 0.0, 0.0, 0.038824310860179345, 0.0, nan, 0.0, 0.012886162290077854, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, 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, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 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, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0]
  • Per Category Accuracy: [0.8898568588469185, 0.6259764769587272, 0.9577347224989943, 0.9247819843070327, 0.06789606035205364, 0.7643305303763789, 1.0, 0.5975183468520664, 0.009635974304068522, 0.0, 0.34045087572241584, 0.3327269577269577, nan, 0.0, 0.0, 0.5489382646603853, nan, 0.0, 0.0, 0.1400167684752665, 0.0, nan, 0.0, 0.019002375296912115, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, 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, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 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, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 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
4.703 1.0 20 4.8562 0.0103 0.0632 0.2675 [0.21165428777704154, 0.32179166978239737, 0.5031269364905134, 0.0006521120800294145, 0.0, 0.05342669416334948, 0.016990612864757983, 0.027912294312196318, 0.02371828937431824, 0.0, 0.0, 0.00024627233242287196, 0.0, 0.0, 0.0, 0.0010805657079294454, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.005723263382336438, 0.0016670060063117174, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.040193309056257016, 0.0, 0.0, 0.0, 0.0, 0.0, 0.01132487378905717, 0.0, 0.0, 0.0013201102292041385, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, 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, 0.0, nan, 0.0, nan, 0.0056419113413932066, nan, 0.0, nan, nan, nan, nan, 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, 0.0, nan, 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, 0.0, 0.0, 0.0005311262088653816, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0] [0.5105606361829026, 0.4283478925616544, 0.89445524377451, 0.0006521392247868407, 0.0, 0.06794184690213538, 0.6289379362384456, 0.03300502124372345, 0.025220080894599095, 0.0, 0.0, 0.0009528759528759529, nan, 0.0, 0.0, 0.002390662354099283, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.010216346153846154, 0.0019207647869563943, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.07199463545476713, 0.0, nan, nan, 0.0, nan, 0.04764638346727899, nan, 0.0, 0.0013201102292041385, 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, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.006364738482854174, nan, 0.0, 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, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.17647058823529413, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0]
4.5481 2.0 40 4.5134 0.0218 0.0587 0.3869 [0.31807012011985564, 0.4034885725313557, 0.7290694120485804, 0.0563904892734368, 0.0, 0.1394507050374461, 7.56807483312395e-05, 0.018919704980871484, 0.0, 0.0, 0.00014696372935159603, 0.005305999397045523, 0.0, 0.0, 0.0, 0.007459121807826566, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0004156707887353216, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0] [0.7179443339960239, 0.8574184377961284, 0.8520470892567763, 0.057242561103364065, 0.0, 0.16594369182212532, 0.003772873042822109, 0.024497875627655465, 0.0, 0.0, 0.0001470566609314569, 0.007623007623007623, nan, 0.0, 0.0, 0.014273660525945718, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.00046919445177560774, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, 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, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 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, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0]
4.209 3.0 60 4.0911 0.0323 0.0737 0.3651 [0.2131257612947356, 0.430094454707051, 0.8035509290787042, 0.1717034475186649, 0.0, 0.09090225769419996, 0.008882520581643424, 0.015518334763308092, 4.379881743192934e-05, 0.0, 0.0, 0.0, 0.0, 0.0018995929443690637, 0.0, 0.07508926317308039, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.000701303255215943, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, 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, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0] [0.8758926441351889, 0.614147269846073, 0.9316747066321255, 0.17359391151719497, 0.0, 0.10141723399226964, 0.5285795132993775, 0.016067979915025107, 4.461099214846538e-05, 0.0, 0.0, 0.0, nan, 0.001924303402168415, 0.0, 0.14639291238925609, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0007078445396429809, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, 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, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 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, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0]
4.1436 4.0 80 3.7854 0.0422 0.0857 0.4296 [0.3251539435304937, 0.4991531629689501, 0.8484109381360809, 0.20315060022058026, 0.0, 0.1797945205479452, 0.0068934562976889135, 0.004992170075452, 0.0051620559222724915, 0.0, 0.0, 0.0, 0.0, 0.0029679397279932162, 0.0, 0.11349021435228332, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.002313329054343175, 0.0027497773820124665, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, 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, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, 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, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0] [0.9334671968190855, 0.8372418955398594, 0.9089723006583622, 0.221075197202739, 0.0, 0.2201324987992773, 0.46066779852857953, 0.005079181151023561, 0.005174875089221985, 0.0, 0.0, 0.0, nan, 0.0030019133073827275, 0.0, 0.3424975390240472, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0025365825049118796, 0.0028461249198144857, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, 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, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 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, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0]
4.0442 5.0 100 3.5572 0.0430 0.0916 0.4161 [0.2693000892903345, 0.5072622910556279, 0.8415237725538792, 0.20845653459491426, 0.0, 0.19705011738287231, 0.012493718654856096, 0.003271727066544419, 0.018662656996285158, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.13326740870205134, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, 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, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, 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, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0] [0.9725566600397614, 0.7771004706200878, 0.8476968600895614, 0.23477012092326263, 0.0, 0.23547887871556974, 0.7176004527447651, 0.0032734646581691774, 0.018825838686652392, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.40746730417662774, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, 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, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 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, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0]
3.2827 6.0 120 3.5066 0.0511 0.1105 0.4184 [0.25310375608698304, 0.5468134672897857, 0.9003626984184326, 0.2962989524829784, 0.0, 0.2664608228406448, 0.01782702798659047, 0.0028186144386420455, 0.02881383063870658, 0.0, 0.0, 0.0, 0.0, 0.00013167279310912384, 0.0, 0.1409057898233849, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, 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, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 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, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0] [0.9560357852882704, 0.6158732749902451, 0.9370965134247997, 0.45860650335435443, 0.0, 0.45593157024037323, 0.9850971514808526, 0.0028196214754731557, 0.029443254817987152, 0.0, 0.0, 0.0, nan, 0.00013195223329154845, 0.0, 0.6411897060891576, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, 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, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 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, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0]
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1.6094 49.0 980 2.3686 0.0896 0.1618 0.5130 [0.28037557124227125, 0.6142512603589863, 0.9359444928585144, 0.5361338598030613, 0.016878030585602388, 0.40150319552667474, 0.03638847320803416, 0.6875101806161069, 0.0053602750298182835, 0.0, 0.20195978119711935, 0.33967391304347827, 0.0, 0.0, 0.0, 0.17283582089552238, nan, 0.0, 0.0, 0.058360352014821676, 0.0, nan, 0.0, 0.015887581225125638, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, 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, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 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, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0] [0.8984493041749503, 0.6510244547257105, 0.9530085011824954, 0.9156242845547069, 0.05057278569432803, 0.7428318759481898, 1.0, 0.69285438393202, 0.005680466333571259, 0.0, 0.3773473919501184, 0.378984753984754, nan, 0.0, 0.0, 0.5292504570383912, nan, 0.0, 0.0, 0.22637441609773626, 0.0, nan, 0.0, 0.021832204334183748, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, 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, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 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, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0]
1.2836 50.0 1000 2.3867 0.0854 0.1569 0.5029 [0.2771319317345961, 0.5947571607182376, 0.939295828662458, 0.5107730625538844, 0.022752808988764046, 0.39377705160129767, 0.03627070632428105, 0.5970283178156206, 0.009085428262972674, 0.0, 0.19687228940252055, 0.3002657911194497, 0.0, 0.0, 0.0, 0.1685958623072604, nan, 0.0, 0.0, 0.038824310860179345, 0.0, nan, 0.0, 0.012886162290077854, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, 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, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 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, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0] [0.8898568588469185, 0.6259764769587272, 0.9577347224989943, 0.9247819843070327, 0.06789606035205364, 0.7643305303763789, 1.0, 0.5975183468520664, 0.009635974304068522, 0.0, 0.34045087572241584, 0.3327269577269577, nan, 0.0, 0.0, 0.5489382646603853, nan, 0.0, 0.0, 0.1400167684752665, 0.0, nan, 0.0, 0.019002375296912115, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, 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, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 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, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0]

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu118
  • Datasets 2.15.0
  • Tokenizers 0.15.0
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