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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: 2.0158
  • Mean Iou: 0.0866
  • Mean Accuracy: 0.1287
  • Overall Accuracy: 0.5649
  • Per Category Iou: [0.5044815482330359, nan, nan, 0.6263191271823676, 0.0, 0.42552218642834877, nan, nan, 0.2569818650770293, nan, 0.4836286215402508, nan, 0.0, nan, 0.45211360942327256, nan, nan, 0.0, 0.051105784451178145, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, 0.013868721536532243, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, 0.2449399479010581, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, 0.24752827792482165, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0053818653529870515, nan, nan, nan, nan, nan, nan, 0.40623454642026413, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.1797867716615959, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, 0.0]
  • Per Category Accuracy: [0.7083710462454917, nan, nan, 0.9227779938829523, 0.0, 0.6033019582751015, nan, nan, 0.5550495827650771, nan, 0.563153238753645, nan, 0.0, nan, 0.5989613173134389, nan, nan, 0.0, 0.06185679877381213, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, 0.021813321568067683, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, 0.42341373023700646, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, 0.4008880858098497, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.012575779445727483, nan, nan, nan, nan, nan, nan, 0.7027883396704689, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.21636257345927817, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 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
4.7699 1.0 20 4.8946 0.0089 0.0525 0.1609 [0.18870815847334255, 0.0, nan, 0.22588805106781887, 0.0, 0.05135027020499351, nan, 0.0, 0.0, 0.0, 0.1427562309682223, 0.0, 0.0, 0.0, 0.011534277192696807, 0.0, 0.0, 0.0, 0.09313133295026138, 0.0, 0.0, 0.0, 0.0, 0.0, 0.010175879396984925, 0.0, 0.0, 0.12540826032873686, 0.0030923709389893404, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.057777392209594866, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.037318938707658976, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.08743364800864563, 0.0, 0.0, 0.0, 0.0, 0.010066594393681277, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, 0.03394269370595634, 0.010337992771177987, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, 0.0, 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, nan, 0.0, nan, 0.0, 0.0, 0.0, 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, 0.0, 0.0, 0.003908081913396905, 0.0, 0.0] [0.2064563090828255, nan, nan, 0.23157449145367595, 0.0, 0.057279125764030374, nan, nan, 0.0, nan, 0.48999049834540154, nan, 0.0, nan, 0.012847515611153474, nan, nan, 0.0, 0.363761769213926, 0.0, nan, nan, 0.0, nan, 0.06464485235434957, nan, nan, 0.24464399257750152, 0.006342810238041937, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, 0.05971487492154577, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, 0.07681365576102418, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.34863751584283903, 0.0, 0.0, nan, nan, 0.026744843902689913, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0606135195840128, 0.08395581273014203, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.02820078962210942, nan, 0.0]
4.405 2.0 40 4.5440 0.0259 0.0893 0.3974 [0.41025728458935135, nan, nan, 0.5334198011240813, 0.0, 0.11799138092561363, nan, nan, 0.00629715776933114, 0.0, 0.20328653861565998, 0.0, 0.00698359276398822, 0.0, 0.18225703088016024, nan, nan, 0.0, 0.08833903401281874, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.09650943697505829, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, 0.16272093136696963, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.05235508632341315, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0013810442819455018, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.15653193622212555, 0.0, 0.0, 0.0, nan, 0.019930598807723108, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.04858341004398077, 0.010969793322734499, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] [0.561719899790647, nan, nan, 0.7998916931713307, 0.0, 0.13254137971678256, nan, nan, 0.006414553523959224, nan, 0.664864628725577, nan, 0.008483671487708897, nan, 0.233270820023494, nan, nan, 0.0, 0.21744033282242173, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, 0.23528801110779493, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, 0.19939826852765075, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, 0.11839221867671369, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0014073325635103927, nan, nan, nan, nan, nan, nan, 0.6555766793409379, 0.0, 0.0, nan, nan, 0.046083423340019546, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.11691947940063382, 0.02177801157285639, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, 0.0]
3.9635 3.0 60 4.0321 0.0440 0.0966 0.4477 [0.4402604787134595, nan, nan, 0.5479993425959873, 0.0, 0.2743365940744573, nan, nan, 0.06608177643700656, nan, 0.2590639089672941, 0.0, 0.0021372958119179686, 0.0, 0.245492677444293, nan, nan, 0.0, 0.06796441476319526, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, 0.09669127150529913, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, 0.1330646493343464, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, 0.030585195250718407, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.00037731780940060373, nan, nan, nan, nan, nan, 0.0, 0.15495660820167134, 0.0, 0.0, 0.0, nan, 0.018610421836228287, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.037478372495395436, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0] [0.6046802564018221, nan, nan, 0.8265298339549535, 0.0, 0.3615989493003755, nan, nan, 0.08000277386098334, nan, 0.7906905627819097, nan, 0.0021464710992998414, nan, 0.3259073016919811, nan, nan, 0.0, 0.1845084300416028, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, 0.17474014767138574, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, 0.16051485898163922, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, 0.05278536003998308, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0003788972286374134, nan, nan, nan, nan, nan, nan, 0.671562103929024, 0.0, 0.0, nan, nan, 0.0270020058632927, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.08264361096581643, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, 0.0]
3.6942 4.0 80 3.7439 0.0512 0.0954 0.4844 [0.45591606119702416, nan, nan, 0.5561968746960456, 0.0, 0.2784381013470173, nan, nan, 0.07475866197710095, nan, 0.21676515118107922, nan, 0.004798856442720032, 0.0, 0.34231074694702407, nan, nan, 0.0, 0.05981299081591907, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, 0.05836055086029833, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, 0.185907119536085, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, 0.026083483673722336, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0007296987386636089, nan, nan, nan, nan, nan, nan, 0.18593037192578207, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.009575923392612859, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, 0.0] [0.6563755070684519, nan, nan, 0.8941110068721445, 0.0, 0.36545909175099767, nan, nan, 0.10391576708813943, nan, 0.644223103218549, nan, 0.004804006746052026, nan, 0.5382849370401666, nan, nan, 0.0, 0.07871688197941756, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, 0.08996535302285143, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, 0.22804028811381094, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, 0.03640767367652147, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0007577944572748268, nan, nan, nan, nan, nan, nan, 0.6340779467680608, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.016368727116088735, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, 0.0]
3.5846 5.0 100 3.5738 0.0570 0.1042 0.4739 [0.4036794061747523, nan, nan, 0.538666137793497, 0.0, 0.3211053134416109, nan, nan, 0.1121588693957115, nan, 0.2496870886990632, nan, 0.0, 0.0, 0.36017552704614314, nan, nan, 0.0, 0.06727786641613956, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, 0.08227258407233874, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, 0.17437563656871574, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, 0.08587790337400372, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.012642450142450143, nan, nan, nan, nan, nan, nan, 0.21545747224708445, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0004094724629768648, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, 0.0] [0.5487830887697402, nan, nan, 0.932216705184236, 0.0, 0.45981579080301066, nan, nan, 0.15960102632856382, nan, 0.8453305374441641, nan, 0.0, nan, 0.6065865671949385, nan, nan, 0.0, 0.09094591635647033, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, 0.15927228371592075, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, 0.20638194008587624, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, 0.15451155280458267, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.014091368360277136, nan, nan, nan, nan, nan, nan, 0.5110424588086185, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0005538291129503708, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, 0.0]
3.4443 6.0 120 3.4223 0.0576 0.1034 0.4770 [0.42308240661534074, nan, nan, 0.5113487052941931, 0.0, 0.32574558618663585, nan, nan, 0.10969625345344405, nan, 0.20352233152074295, nan, 0.0, nan, 0.36931055109826294, nan, nan, 0.0, 0.05612292861354915, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0721477435727684, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, 0.2050052930564046, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, 0.09141549899914213, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0007991430466053424, nan, nan, nan, nan, nan, nan, 0.22556136976290445, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 9.651810921024057e-05, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, 0.0] [0.5478885897793675, nan, nan, 0.9736097445636837, 0.0, 0.4340829109767802, nan, nan, 0.16199348142668918, nan, 0.7275973919596344, nan, 0.0, nan, 0.6539908909177091, nan, nan, 0.0, 0.07189621195533173, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, 0.1357590542802642, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, 0.2739571814260239, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, 0.15362731152204837, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0008480080831408776, nan, nan, nan, nan, nan, nan, 0.518330164765526, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0001230731362111935, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, 0.0]
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1.4615 49.0 980 1.9799 0.0871 0.1287 0.5643 [0.5033978895763482, nan, nan, 0.6317018088071933, 0.0, 0.4264064135517172, nan, nan, 0.250764373269409, nan, 0.5005625623809091, nan, 0.0, nan, 0.44855311829266437, nan, nan, 0.0, 0.05046246996805393, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, 0.020478671932679143, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, 0.24938529919379626, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, 0.2450863644402523, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.004932132560173637, nan, nan, nan, nan, nan, nan, 0.4125046659201195, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.17715046604527296, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, 0.0] [0.7055952344319507, nan, nan, 0.919513534539963, 0.0, 0.5984778325952618, nan, nan, 0.522306465407642, nan, 0.6025031945218047, nan, 0.0, nan, 0.6072749005626198, nan, nan, 0.0, 0.06277643967593606, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, 0.03707356318856001, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, 0.42034529822568917, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, 0.39958094652262505, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.010988019630484989, nan, nan, nan, nan, nan, nan, 0.7003168567807351, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.2046706255192148, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, 0.0]
0.9449 50.0 1000 2.0158 0.0866 0.1287 0.5649 [0.5044815482330359, nan, nan, 0.6263191271823676, 0.0, 0.42552218642834877, nan, nan, 0.2569818650770293, nan, 0.4836286215402508, nan, 0.0, nan, 0.45211360942327256, nan, nan, 0.0, 0.051105784451178145, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, 0.013868721536532243, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, 0.2449399479010581, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, 0.24752827792482165, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0053818653529870515, nan, nan, nan, nan, nan, nan, 0.40623454642026413, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.1797867716615959, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, 0.0] [0.7083710462454917, nan, nan, 0.9227779938829523, 0.0, 0.6033019582751015, nan, nan, 0.5550495827650771, nan, 0.563153238753645, nan, 0.0, nan, 0.5989613173134389, nan, nan, 0.0, 0.06185679877381213, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, 0.021813321568067683, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, 0.42341373023700646, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, 0.4008880858098497, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.012575779445727483, nan, nan, nan, nan, nan, nan, 0.7027883396704689, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.21636257345927817, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, 0.0]

Framework versions

  • Transformers 4.32.0.dev0
  • Pytorch 2.0.1+cpu
  • Datasets 2.13.1
  • Tokenizers 0.13.3
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Dataset used to train Kosuna/segformer-b0-scene-parse-150

Evaluation results

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