Loss: 3.1966
Mean Iou: 0.0592
Mean Accuracy: 0.1149
Overall Accuracy: 0.5616
Per Category Iou: [0.2482659499078375, 0.5797069149618939, 0.8776968883527723, 0.28273848421955133, 0.4149252382888377, 0.09651529589590248, 0.24546015344874117, 0.0, 0.061830755057846694, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.03446133362920226, 0.0, 0.0, 0.0, 0.18589422756089422, 0.048920801072710754, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 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, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan]
Per Category Accuracy: [0.7830056019206585, 0.8075731226849805, 0.9184958662992266, 0.901344955168161, 0.44654247044181705, 0.11797132299783115, 0.29920575242034025, nan, 0.0845660426757429, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.038712733074085154, 0.0, 0.0, nan, 0.25228301886792454, 0.059538850284270375, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 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, nan, 0.0, 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, nan, nan, nan, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, 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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Mean Iou	Mean Accuracy	Overall Accuracy	Per Category Iou	Per Category Accuracy
4.9087	1.0	20	4.8819	0.0069	0.0340	0.2131	[0.1702543312021142, 0.06043264300255621, 0.6057438550249282, 0.010851584728379542, 0.01729407379798733, 0.00019686724300265344, 0.00016335108120756184, nan, 0.016497304452135066, 0.0, 0.0, 0.00029025996408032947, 0.0, 0.0, 0.0, 0.012160550548397818, 0.0, 0.0004327355812504327, 0.0, 0.0, 0.009764694674668953, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, 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, 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, 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, 0.004115800488315312, nan, 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, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, 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, 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]	[0.5295587058420029, 0.06206462895825351, 0.6553880344919548, 0.010932968901036632, 0.01804604853764779, 0.00023094224435697645, 0.00017388852335745842, nan, 0.039157612252912685, nan, 0.0, 0.000341975335028961, 0.0, nan, 0.0, 0.015505035397347692, 0.0, 0.036818851251840944, nan, 0.0, 0.010791745630659086, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 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, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.013390830685428961, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan]
4.4934	2.0	40	4.4054	0.0161	0.0687	0.3869	[0.20769955983642488, 0.39252580986474045, 0.7881153499685442, 0.11395642817582621, 0.036175143775452785, 0.008752590917655926, 0.021175352037919943, nan, 0.0, 0.0, 0.0, 2.0126393752767377e-05, 0.0, nan, 0.0, 0.045857150213708224, 0.0, 0.0023872815959945287, 0.0, 0.006001846722068329, 0.014336755461082719, 0.0, 0.0, 0.00015817779183802593, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 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, 0.0, nan, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0]	[0.7908540070881445, 0.471651880016899, 0.8664112365543604, 0.2246091796940102, 0.03687966708151836, 0.009328058478592659, 0.021562176896324843, nan, 0.0, nan, 0.0, 2.1373458439310063e-05, 0.0, nan, 0.0, 0.08879250174493968, 0.0, 0.27245949926362295, nan, 0.006377358490566038, 0.025031585596967783, nan, nan, 0.0011452567283832794, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 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, nan, 0.0, 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, nan, nan, nan, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan]
4.0883	3.0	60	3.9489	0.0344	0.0894	0.4865	[0.22584248437410168, 0.5172610129258783, 0.8232194426733676, 0.24945083091015924, 0.10604197094319318, 0.011806636397962849, 0.11359135429641644, nan, 0.0006913360361838251, nan, 0.0, 0.008041064074789703, 0.0, nan, 0.0, 0.07858137205157228, 0.0, 0.0, 0.0, 0.07708083548936707, 0.014355997703040368, nan, nan, 0.010004967004896047, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan]	[0.7858980221790328, 0.760473958793881, 0.858545648502089, 0.6898436718776041, 0.107303982576229, 0.012872519881114949, 0.11914653632860231, nan, 0.0009654405026835974, nan, 0.0, 0.008805864876995747, 0.0, nan, 0.0, 0.15056336623791006, 0.0, 0.0, nan, 0.09218867924528303, 0.02434723099599916, nan, nan, 0.05382706623401413, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 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, nan, 0.0, 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, nan, nan, nan, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan]
3.5779	4.0	80	3.7257	0.0424	0.0989	0.5123	[0.22708138746369488, 0.5250432204806172, 0.8396193553013978, 0.2585391577487232, 0.2856092749739467, 0.02496460594620104, 0.19142474318892364, nan, 0.023254978505310806, nan, 0.0, 0.00021742997766401137, 0.0, nan, 0.0, 0.06279386402831987, 0.0, 0.0, 0.0, 0.11986189916941406, 0.02337162207024766, nan, nan, 0.0045935327893623455, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan]	[0.8116154109980565, 0.7531268114874092, 0.8742341541470353, 0.7517249425019166, 0.2984501400124456, 0.026558358101052292, 0.2115001409906946, nan, 0.031777719596805865, nan, 0.0, 0.0002351080428324107, 0.0, nan, 0.0, 0.08622494765180976, 0.0, 0.0, nan, 0.15983018867924528, 0.03706043377553169, nan, nan, 0.014506585226188204, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 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, nan, 0.0, 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, nan, nan, nan, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan]
3.8181	5.0	100	3.4234	0.0453	0.0997	0.5261	[0.24528431045819335, 0.5342929509553547, 0.8518968875640627, 0.26043330118932817, 0.2002535449337966, 0.050677609390547815, 0.13341983805003038, 0.0, 0.06462879962873856, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.07052976434235508, 0.0, 0.0, 0.0, 0.10530546623794212, 0.021125101911405018, nan, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan]	[0.7783297130444724, 0.8004205107043554, 0.9105413814561294, 0.8439385353821539, 0.2073448195395146, 0.05778576592497389, 0.1527023216467713, nan, 0.08659510407121351, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.09445109183368232, 0.0, 0.0, nan, 0.12358490566037736, 0.030690671720362182, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 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, nan, 0.0, 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, nan, nan, nan, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan]
3.8662	6.0	120	3.3548	0.0488	0.1029	0.5228	[0.24440109918908598, 0.5585233877224912, 0.8472040411900672, 0.2431921886906784, 0.26001049298281775, 0.08004929143561307, 0.11688678434470141, 0.0, 0.07755954486835648, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.021856639247943597, 0.0, 0.0, 0.0, 0.14995594500971623, 0.03336775526010068, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan]	[0.7463244540985481, 0.7610045096825537, 0.9136367677126855, 0.8829122362587913, 0.2698448195395146, 0.09783918387019037, 0.134223141272676, nan, 0.11120565519046996, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.025501046963804966, 0.0, 0.0, nan, 0.23441509433962265, 0.04082438408085913, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 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, nan, 0.0, 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, nan, nan, nan, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan]
3.8333	7.0	140	3.1873	0.0538	0.1074	0.5516	[0.24660873213052267, 0.5688862105730198, 0.8559621182407808, 0.27943243912935745, 0.3056501468118838, 0.06940647850748309, 0.21391673780548331, 0.0, 0.03934881278367531, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0263415720329548, 0.0, 0.0, 0.0, 0.1588940225238233, 0.03389608975057183, nan, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan]	[0.7796044358065622, 0.8440258987433804, 0.9040661392123744, 0.8927452418252725, 0.31679760423148723, 0.08158285806088843, 0.2532004887677413, nan, 0.05149561460924205, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.02948948050653106, 0.0, 0.0, nan, 0.20764150943396226, 0.040955990734891555, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 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, nan, 0.0, 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, nan, nan, nan, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan]
3.6256	8.0	160	3.2788	0.0553	0.1118	0.5403	[0.24341030359768057, 0.5851589584716382, 0.8681411636555498, 0.24774307715703758, 0.3521220340217164, 0.1420685149646809, 0.1381724722213171, 0.0, 0.05397744627301494, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.03428934510637366, 0.0, 0.0, 0.0, 0.17940412243804107, 0.08617305604276289, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 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, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan]	[0.781770892877558, 0.7794185555260805, 0.9068752778024713, 0.8959701343288557, 0.3761667703795893, 0.1746827054381878, 0.15942757777986652, nan, 0.07229349391281581, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.03901186558978961, 0.0, 0.0, nan, 0.29050943396226414, 0.10862813223836597, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 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, nan, 0.0, 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, nan, nan, nan, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan]
2.8868	9.0	180	3.1532	0.0601	0.1132	0.5647	[0.2715461402839888, 0.5968571873369805, 0.8669868462312885, 0.26692639728890705, 0.3377123191355512, 0.1110059281790248, 0.19162928791482434, 0.0, 0.10924448177703112, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.04195385740564261, 0.0, 0.0, 0.0, 0.16768739988962622, 0.04133449593090849, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan]	[0.736898365153767, 0.8588302335406411, 0.9339781313894568, 0.8992116929435685, 0.3549315494710641, 0.14364607599003937, 0.22567910517905818, nan, 0.1532268621547323, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0471881543523781, 0.0, 0.0, nan, 0.2350566037735849, 0.05240576963571278, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 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, nan, 0.0, 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, nan, nan, nan, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan]
3.2667	10.0	200	3.1966	0.0592	0.1149	0.5616	[0.2482659499078375, 0.5797069149618939, 0.8776968883527723, 0.28273848421955133, 0.4149252382888377, 0.09651529589590248, 0.24546015344874117, 0.0, 0.061830755057846694, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.03446133362920226, 0.0, 0.0, 0.0, 0.18589422756089422, 0.048920801072710754, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 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, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan]	[0.7830056019206585, 0.8075731226849805, 0.9184958662992266, 0.901344955168161, 0.44654247044181705, 0.11797132299783115, 0.29920575242034025, nan, 0.0845660426757429, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.038712733074085154, 0.0, 0.0, nan, 0.25228301886792454, 0.059538850284270375, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 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, nan, 0.0, 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, nan, nan, nan, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan]

Framework versions

Transformers 4.37.2
Pytorch 2.1.0+cu121
Datasets 2.17.1
Tokenizers 0.15.2

tonyscan6003/segformer-b0-scene-parse-150

segformer-b0-scene-parse-150

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

tonyscan6003/
segformer-b0-scene-parse-150