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segformer-b0-scene-parse-150-FINETUNE

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segformer-b0-scene-parse-150-FINETUNE

This model is a fine-tuned version of kxwoo/segformer-b0-scene-parse-150 on the scene_parse_150 dataset. It achieves the following results on the evaluation set:

  • Loss: 1.6911
  • Mean Iou: 0.1305
  • Mean Accuracy: 0.2183
  • Overall Accuracy: 0.6443
  • Per Category Iou: [0.4941171449830129, 0.6755914823518744, 0.9277173608506933, 0.6595893946814566, 0.2628451285738408, 0.48086506053451367, 0.47962367163888076, 0.3297800465430523, 0.06813804173354736, 0.27008782173307955, 0.0, 0.047366168689698104, 0.4032724535477992, 0.009869851446600665, 0.0, 0.0013409769016728688, 0.0, 0.12749696022233803, nan, 0.0, 0.6324666384240627, nan, nan, nan, 0.0015743142863478125, 0.0, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 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, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0]
  • Per Category Accuracy: [0.7816896653956457, 0.9451074805625882, 0.9619947928888293, 0.8581466237277627, 0.32036540351063547, 0.5302474940349395, 0.7679752308019201, 0.8681818181818182, 0.420054424012534, 0.6170601564213142, 0.0, 0.06267534941185555, 0.5886877566364005, 0.009915575377675732, 0.0, 0.0013427549975662566, nan, 0.5187279151943462, nan, 0.0, 0.6984707155179976, nan, nan, nan, 0.0016577165538174178, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 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, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 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
3.3033 1.0 20 1.7785 0.1226 0.1901 0.6440 [0.4800136753560712, 0.6896904881483451, 0.9323150741440327, 0.5226362361852047, 0.3375309405940594, 0.4285230562594175, 0.48130442894674474, 0.4380214087082397, 0.0, 0.40783070343607136, 0.0, 0.011482228698099579, 0.2423747859589041, 0.0, 0.0, 0.02628975688719686, nan, 0.14115832532355768, 0.0, 0.000457235072619688, 0.0, nan, nan, nan, 0.1337959466263847, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 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, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0] [0.8119065021677806, 0.9254375069372136, 0.9596616495144872, 0.988676873267088, 0.434540722840375, 0.485731831353509, 0.8277820900311783, 0.7574769433465086, 0.0, 0.6064249689350194, 0.0, 0.0118658464389591, 0.3492761166695583, 0.0, 0.0, 0.029439903321640176, nan, 0.4057179569547061, nan, 0.00047625717887659334, 0.0, nan, nan, nan, 0.198529068409993, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 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, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0]
2.4735 2.0 40 1.7652 0.1236 0.1903 0.6373 [0.4954767956843636, 0.6052252369314935, 0.9197324341485844, 0.694701011484156, 0.33534409964112305, 0.42262032863167076, 0.45726831825927383, 0.23762436610128151, 0.005565681551881266, 0.3440879011112498, 0.0, 0.01639553103940278, 0.30572370297594526, 0.0, 0.0, 0.35830456821220885, nan, 0.12873614967109376, nan, 0.0, 0.0, nan, nan, nan, 0.11283469001177494, 0.0, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 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, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0] [0.7861778666220488, 0.960120932150087, 0.938734873118568, 0.926128437839048, 0.4218405608519, 0.46478855220147514, 0.7563668373740834, 0.7701581027667984, 0.01410076688381298, 0.503581609531467, 0.0, 0.01656328022444725, 0.37192759238910417, 0.0, 0.0, 0.3867805770489602, nan, 0.33067780276260844, nan, 0.0, 0.0, nan, nan, nan, 0.15437777258930657, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 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, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0]
2.6365 3.0 60 1.7426 0.1212 0.1853 0.6457 [0.4861758166128435, 0.6435349482411329, 0.9296230604438971, 0.6955325649560335, 0.42840654870856215, 0.3294138304764557, 0.4669125757350338, 0.23438131726381856, 0.00508635831381733, 0.36841332027424095, 0.00409373235460192, 0.03122789162084673, 0.1717725668179526, 0.0, 0.0, 0.10945761697316352, nan, 0.23136639190544725, nan, 0.0, 0.0005848124214158309, nan, nan, nan, 0.07591575091575091, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 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, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0] [0.8626152504909429, 0.9464790667928138, 0.9581330383381941, 0.9644290216474073, 0.5593847093501872, 0.3480204954998177, 0.7893187169624776, 0.8019762845849803, 0.011462026882163768, 0.5498867041882903, 0.01274351838289146, 0.03238011891585802, 0.21012858327068032, 0.0, 0.0, 0.11049195186223333, nan, 0.3408287825248956, nan, 0.0, 0.0005848124214158309, nan, nan, nan, 0.09677795937427038, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 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, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0]
1.6107 4.0 80 1.7359 0.1211 0.1965 0.6412 [0.5161767236658896, 0.6310518492611699, 0.9195442836113837, 0.6879123379085463, 0.2608181666747269, 0.5792574189095928, 0.48821671849745824, 0.2124466127999611, 0.019415655713558824, 0.2905896607431341, 0.0, 0.045875141991669824, 0.15931561601570718, 0.0, 0.0, 0.1729563174030097, nan, 0.130392198015923, 0.0, 0.0, 0.04128775695195766, nan, nan, nan, 0.051519987390901745, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 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, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0] [0.7747885790102474, 0.9536805551885073, 0.9381359435933536, 0.937348235658808, 0.32223756539288845, 0.671144460010107, 0.7937721424575798, 0.8634387351778656, 0.05978395316236497, 0.6310942182588992, 0.0, 0.049895755579006974, 0.17519711603338925, 0.0, 0.0, 0.18654223803689218, nan, 0.598715065852875, nan, 0.0, 0.04128775695195766, nan, nan, nan, 0.06105533504552883, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 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, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0]
2.6167 5.0 100 1.7056 0.1315 0.1958 0.6560 [0.4928916007969971, 0.6421745217501978, 0.9279672364579319, 0.686182471975191, 0.3804885887346953, 0.4403389102877518, 0.5112859767459486, 0.3625702348364789, 0.013510539981516525, 0.34078307808798025, 0.0, 0.02510867215831312, 0.38129277786620747, 0.0, 0.0, 0.031470820255459137, 0.0, 0.20737563224278122, nan, 0.0, 0.06213631977543203, nan, nan, nan, 0.017904761904761906, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 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, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0] [0.837963900654884, 0.9200568719377157, 0.952492373705206, 0.979316995884065, 0.565910720450381, 0.4724135945805907, 0.8483623796122441, 0.8289196310935442, 0.05063082378164426, 0.5099042467655873, 0.0, 0.02691050423412525, 0.5079713916681126, 0.0, 0.0, 0.031470820255459137, nan, 0.41619017025377447, nan, 0.0, 0.06213631977543203, nan, nan, nan, 0.018655148260565024, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 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, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0]
1.4622 6.0 120 1.7536 0.1306 0.1996 0.6440 [0.5017467007293978, 0.6069786995993703, 0.9212855533806467, 0.689136458745688, 0.2918129034512713, 0.5459976977286127, 0.4901317342650739, 0.3706203516615795, 0.0322785015757497, 0.29829107051001164, 0.0, 0.0017645253682487725, 0.3002764543262161, 0.0, 0.0, 0.14320457556901092, 0.0, 0.12799454821856052, nan, 0.0, 0.1140276519248195, nan, nan, nan, 0.048042594465195945, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 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, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0] [0.7719500632575124, 0.9405223127216605, 0.9414010034304359, 0.9443746017531472, 0.38804870276442627, 0.621991082794399, 0.8102415777354743, 0.8518774703557312, 0.1638492619774058, 0.572216943205906, 0.0, 0.0017760160613626418, 0.3936537312281919, 0.0, 0.0, 0.14330552711525874, nan, 0.47060713138451654, nan, 0.0, 0.11406766279715781, nan, nan, nan, 0.05435442446883026, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 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, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0]
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0.6548 48.0 960 1.6967 0.1306 0.2184 0.6433 [0.49110343227004305, 0.6660683787569551, 0.9257447294577085, 0.671389649406796, 0.26025681691404073, 0.45756657537439543, 0.48218765130853675, 0.3580425831617727, 0.06920128316659417, 0.26182810971183285, 0.0, 0.04728447973020446, 0.40490148715873037, 0.012355665203939253, 0.0, 0.0020397585728377725, 0.0, 0.13613359515941056, nan, 0.0, 0.6297183623489325, nan, nan, nan, 0.0015791814946619217, 0.0, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 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, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0] [0.7826407296188992, 0.9512941537127967, 0.9599410009721431, 0.8678509308212926, 0.3159372759380726, 0.5022996667242383, 0.7643630560819396, 0.8707180500658761, 0.4198070421373794, 0.6063518748629486, 0.0, 0.06062907003680729, 0.5978254583309236, 0.0124147880240981, 0.0, 0.0020477013712885414, nan, 0.5478316736267266, nan, 0.0, 0.6917161320506447, nan, nan, nan, 0.0016577165538174178, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 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, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0]
0.8233 49.0 980 1.6847 0.1278 0.2181 0.6434 [0.4874437380086247, 0.6861187531097718, 0.9303208396189263, 0.657786316998772, 0.2660056626726523, 0.4543340479621364, 0.47990164983219746, 0.33751732535395534, 0.06515475907276716, 0.2775920270053046, 0.0, 0.05150827742651672, 0.4010929976521774, 0.009305995286311083, 0.0, 0.005365649811951525, 0.0, 0.12328682648577816, nan, 0.0, 0.6455219981189257, nan, nan, nan, 0.0015838315338627643, 0.0, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, 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, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0] [0.7890163823747839, 0.9365687616611257, 0.9661269596504755, 0.8578624692165946, 0.32807977268502536, 0.4961586929960915, 0.7676586776751991, 0.8582345191040843, 0.4065308815040818, 0.6311307652949346, 0.0, 0.06867262103935548, 0.5829236789852139, 0.009346648921579584, 0.0, 0.005387804427734604, nan, 0.5137809187279152, nan, 0.0, 0.7224772654171174, nan, nan, nan, 0.0016577165538174178, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 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, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0]
1.0235 50.0 1000 1.6911 0.1305 0.2183 0.6443 [0.4941171449830129, 0.6755914823518744, 0.9277173608506933, 0.6595893946814566, 0.2628451285738408, 0.48086506053451367, 0.47962367163888076, 0.3297800465430523, 0.06813804173354736, 0.27008782173307955, 0.0, 0.047366168689698104, 0.4032724535477992, 0.009869851446600665, 0.0, 0.0013409769016728688, 0.0, 0.12749696022233803, nan, 0.0, 0.6324666384240627, nan, nan, nan, 0.0015743142863478125, 0.0, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 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, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0] [0.7816896653956457, 0.9451074805625882, 0.9619947928888293, 0.8581466237277627, 0.32036540351063547, 0.5302474940349395, 0.7679752308019201, 0.8681818181818182, 0.420054424012534, 0.6170601564213142, 0.0, 0.06267534941185555, 0.5886877566364005, 0.009915575377675732, 0.0, 0.0013427549975662566, nan, 0.5187279151943462, nan, 0.0, 0.6984707155179976, nan, nan, nan, 0.0016577165538174178, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 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, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0]

Framework versions

  • Transformers 4.42.4
  • Pytorch 2.3.1+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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Safetensors
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Dataset used to train kxwoo/segformer-b0-scene-parse-150-FINETUNE

Evaluation results

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