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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: 3.2289
  • Mean Iou: 0.0624
  • Mean Accuracy: 0.1917
  • Overall Accuracy: 0.3217
  • Per Category Iou: [0.2478175629093416, 0.25383335249325295, 0.8595279462283469, 0.3585768829967094, 0.0, 0.09958428678812746, 0.01625582944703531, 0.0, 0.08457054462449773, nan, 0.05180472234492783, 0.03730669006246153, 0.13281580262096, 0.003548456316827952, nan, 0.0, 0.00566525353600937, 0.06168678810630946, nan, 0.2245182436378021, 0.14621728948172283, 0.20058242899202094, 0.0, nan, 0.0, 0.0, 0.02158498001776199, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 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, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 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, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]
  • Per Category Accuracy: [0.5219981938563889, 0.5001658464235151, 0.9977606431263399, 0.9121276782964495, 0.0, 0.6783117875024752, 0.016302376634532788, nan, 0.0941490255376344, nan, 0.8225113122171945, 0.3077670951712218, 0.5481798715203426, 0.00355890566275432, nan, 0.0, 0.00566525353600937, 0.10318989509740954, nan, 0.33737156443714794, 0.479978608195735, 0.9331381403735133, 0.0, nan, 0.0, nan, 0.02162684481643946, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 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, nan, 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
4.2285 1.0 20 4.2035 0.0431 0.1369 0.2843 [0.22050628234305308, 0.2563038672781469, 0.8125239885835986, 0.2703117244673665, 7.155196205701669e-05, 0.05622590511416175, 0.0, 0.0, 0.01720283194634207, nan, 0.07446164326533701, 0.0, 0.0, 0.0, 0.0, 0.0, 0.005959625108214245, 0.0, nan, 0.18143939878069043, 0.0, 0.3020646758068193, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 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, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0] [0.4929002219106095, 0.42711251938245803, 0.9944828463144213, 0.7967024506137533, 0.0025017869907076485, 0.5590223756046505, 0.0, nan, 0.01745211693548387, nan, 0.8902714932126696, 0.0, 0.0, 0.0, nan, 0.0, 0.006047180740684159, 0.0, nan, 0.40182286506835746, 0.0, 0.6137329826476767, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 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, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]
4.1493 2.0 40 3.9645 0.0397 0.1236 0.3160 [0.2494581568011776, 0.3504709042216185, 0.6945768786978617, 0.24269182770487463, 0.0, 0.08821616654296116, 0.0, 0.0, 0.01828378905848758, nan, 0.0407216459831951, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0002672095686474106, 0.0, nan, 0.038871612616614835, 0.0, 0.10474296079482211, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 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, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0] [0.4737405778751946, 0.7294492011056428, 0.999311238816461, 0.8470456245325355, 0.0, 0.7060337755650476, 0.0, nan, 0.01869119623655914, nan, 0.6781674208144797, 0.0, 0.0, 0.0, nan, 0.0, 0.0002673490432723523, 0.0, nan, 0.0743015652863087, 0.0, 0.16811407208906093, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 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, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]
3.7043 3.0 60 3.8422 0.0369 0.1197 0.3047 [0.2021212658805299, 0.37212244496824687, 0.6943778657134937, 0.178581155596037, 0.0, 0.08608014243237187, 0.0, 0.0, 0.0, nan, 0.03591316688835288, 0.0, 0.0019866046089226925, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0025656309119651698, 0.0016608129815676984, 0.04813731600901376, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 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, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0] [0.5066868156054438, 0.6432818715027304, 0.9997386239611186, 0.8798671300981126, 0.0, 0.804192243500891, 0.0, nan, 0.0, nan, 0.6383484162895927, 0.0, 0.0027757950670156237, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0028022304622264994, 0.004077812688013905, 0.0664317734438324, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 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, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]
3.5075 4.0 80 3.9024 0.0425 0.1258 0.3038 [0.24532855441440674, 0.29787745967326146, 0.8339459035112761, 0.18163523652986108, 0.0, 0.08493965781957022, 0.0, 0.0, 0.0, nan, 0.04218993253762325, 0.0, 0.05424256398432096, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0036449340897256708, 0.0, 0.08577250021908685, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 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, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan] [0.4963672915560517, 0.6309957527135441, 0.990565737839833, 0.8885234722161116, 0.0, 0.8294249101864162, 0.0, nan, 0.0, nan, 0.7357466063348417, 0.0, 0.0746292330874772, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.003764612641172974, 0.0, 0.12952210808396605, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 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, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]
3.4706 5.0 100 3.7212 0.0470 0.1324 0.3401 [0.29729258586902946, 0.33147047893754256, 0.6567743612234621, 0.17931655544616598, 0.0, 0.15023420427789919, 0.0, 0.0, 0.0, nan, 0.03693687018375815, 0.0, 0.0005457664119756744, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.008637438756546713, 0.0, 0.36042466127982953, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 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, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan] [0.44887660590218686, 0.8082114204813591, 0.9996962386575161, 0.9395815917990232, 0.0, 0.8537523690984696, 0.0, nan, 0.0, nan, 0.3383484162895928, 0.0, 0.0005551590134031248, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.011576891505562003, 0.0, 0.6323424809356029, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 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, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]
2.9252 6.0 120 3.6661 0.0458 0.1381 0.3267 [0.26655654652977095, 0.3628751321035356, 0.668043495193295, 0.19590840707440443, 0.0, 0.08144395016597901, 0.0, 0.0, 0.0, nan, 0.047927470036745766, 0.00012295333920777065, 0.017286963595688428, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.007809601543370186, 0.003069956636862504, 0.27059077498740736, 0.0, nan, 0.0, 0.0, 0.001726672584045268, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 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, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan] [0.5023711307457376, 0.7000121351041596, 0.9997138992006838, 0.9095208764133926, 0.0, 0.6856948884048542, 0.0, nan, 0.0, nan, 0.789366515837104, 0.0006481581505887436, 0.020223649773970974, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0119165558040137, 0.0053479510662477435, 0.6220369543281558, 0.0, nan, 0.0, nan, 0.0017309817934083656, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 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, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]
2.1149 7.0 140 3.6300 0.0489 0.1432 0.3179 [0.26711071158756416, 0.28632214638442427, 0.774339699086748, 0.2199487941945284, 0.0, 0.09644734362919312, 0.0, 0.0, 0.0, nan, 0.04710744914307255, 0.0, 0.09596901448859561, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.006643629472745514, 0.0, 0.2961657572629406, 0.0, nan, 0.0, 0.0, 0.010740205210911215, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 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, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan] [0.5070180932024559, 0.6137018809411448, 0.9990816517552814, 0.9014474899907607, 0.0, 0.8398347995813414, 0.0, nan, 0.0, nan, 0.7916289592760181, 0.0, 0.10611467999048299, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.008434996744883806, 0.0, 0.6644169850958596, 0.0, nan, 0.0, nan, 0.010740429200063956, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 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, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]
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2.0286 48.0 960 3.2213 0.0609 0.1904 0.3186 [0.24773052931435385, 0.2523722351913743, 0.8588030073725604, 0.3459261824087585, 0.0, 0.09890749160402347, 0.013931625545089008, 0.0, 0.08085451086035077, nan, 0.04958242683697101, 0.03781382865015083, 0.13705386378519974, 0.0028923199230109415, nan, 0.0, 0.0009930107321544513, 0.05309734513274336, nan, 0.2018507474172262, 0.14577812858243597, 0.20181852773200945, 0.0, nan, 0.0, 0.0, 0.009308307264511644, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 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, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 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, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan] [0.5240947726210411, 0.48627789388525583, 0.9981597714019292, 0.9230608473755995, 0.0, 0.6781420610449492, 0.01408800229073208, nan, 0.0901377688172043, nan, 0.7992081447963801, 0.34395592524575996, 0.5311285589658181, 0.0029027652382052197, nan, 0.0, 0.0009930107321544513, 0.08734746307000642, nan, 0.29697981827960035, 0.5185507052610469, 0.9300117446611417, 0.0, nan, 0.0, nan, 0.009308371973388761, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 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, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]
2.775 49.0 980 3.2312 0.0625 0.1886 0.3207 [0.24248139186349288, 0.25271433156185574, 0.8634379013025133, 0.3531656975755721, 0.0, 0.09866450997470035, 0.017130500188040618, 0.0, 0.03661274538023142, nan, 0.05296371087485894, 0.0358082188265784, 0.14039829610569335, 0.004076692115425931, nan, 0.0, 0.006849227870501216, 0.05880163751395608, nan, 0.22099825267796094, 0.13593260040046848, 0.2081117637249634, 0.0, nan, 0.0, nan, 0.021928850903238338, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 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, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 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, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan] [0.5257103181626346, 0.5011393514460999, 0.9974533496752226, 0.913920542038805, 0.0, 0.6729371163474867, 0.017390474372434857, nan, 0.04007056451612903, nan, 0.8070135746606335, 0.3015015663821973, 0.5149496391466413, 0.0040838180023936, nan, 0.0, 0.006849227870501216, 0.1014771997430957, nan, 0.3293611480653288, 0.48104819840898455, 0.9289861545332738, 0.0, nan, 0.0, nan, 0.021974431521943148, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 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, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]
1.1549 50.0 1000 3.2289 0.0624 0.1917 0.3217 [0.2478175629093416, 0.25383335249325295, 0.8595279462283469, 0.3585768829967094, 0.0, 0.09958428678812746, 0.01625582944703531, 0.0, 0.08457054462449773, nan, 0.05180472234492783, 0.03730669006246153, 0.13281580262096, 0.003548456316827952, nan, 0.0, 0.00566525353600937, 0.06168678810630946, nan, 0.2245182436378021, 0.14621728948172283, 0.20058242899202094, 0.0, nan, 0.0, 0.0, 0.02158498001776199, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 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, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 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, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan] [0.5219981938563889, 0.5001658464235151, 0.9977606431263399, 0.9121276782964495, 0.0, 0.6783117875024752, 0.016302376634532788, nan, 0.0941490255376344, nan, 0.8225113122171945, 0.3077670951712218, 0.5481798715203426, 0.00355890566275432, nan, 0.0, 0.00566525353600937, 0.10318989509740954, nan, 0.33737156443714794, 0.479978608195735, 0.9331381403735133, 0.0, nan, 0.0, nan, 0.02162684481643946, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 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, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]

Framework versions

  • Transformers 4.26.1
  • Pytorch 1.13.1+cu116
  • Datasets 2.10.1
  • Tokenizers 0.13.2
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Dataset used to train sertannavdann/segformer-b0-scene-parse-150

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