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segformer-b0-scene-parse-150_epoch_500_230609

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PyTorch
segformer
generated_from_trainer
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segformer-b0-scene-parse-150_epoch_500_230609

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: 2.8363
  • Mean Iou: 0.0891
  • Mean Accuracy: 0.1916
  • Overall Accuracy: 0.5016
  • Per Category Iou: [0.41868138102795893, 0.41164379787292665, 0.8678939714436806, 0.49194778723391036, 0.029843826630701325, 0.835960288057647, 0.0, 0.34373422146269467, 0.013432504440497336, 0.1204883859440143, 0.0, 0.17471152509384125, 0.04084956814333784, 0.21202216853772915, 0.056338467294381744, 0.056798931456867346, 0.47129763627592863, 0.28277576385292597, 0.0, 0.07881762508014414, 0.0, 0.0, 0.01960102064486198, 0.0, 0.0, 0.0, nan, 0.017165794195445887, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.27608723215417774, 0.0, 0.0, 0.023283028004196595, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.004678027590815791, nan, nan, 0.0, nan, 0.0, nan, 0.022047401914115347, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.34324942791762014, nan, nan, 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, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan]
  • Per Category Accuracy: [0.6994942191263431, 0.5978423542028475, 0.9986688978474176, 0.7972636815920398, 0.3682394099848714, 0.9211447857428524, 0.0, 0.3737798214540252, 0.02567911714770798, 0.5617883921133019, 0.0, 0.846832884097035, 0.2152456239412761, 0.2470880485785261, 0.3816261879619852, 0.1420366598778004, 0.47624704212020824, 0.7307815845824411, 0.0, 0.11847789963443005, 0.0, 0.0, 0.01960329428140587, 0.0, 0.0, nan, nan, 0.023911979180087094, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.424919504341887, nan, nan, 0.031995120328268824, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.008119976800066285, nan, nan, nan, nan, 0.0, nan, 0.032657908409411414, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.34443168771526983, 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, 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, 0.0, 0.0, nan, 0.0, 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: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 500

Training results

Training Loss Epoch Step Validation Loss Mean Iou Mean Accuracy Overall Accuracy Per Category Iou Per Category Accuracy
3.1536 10.0 100 3.7299 0.0636 0.1309 0.3950 [0.4118507412764684, 0.6359830625223599, 0.653558934458942, 0.3313574174036149, 0.009771904954942479, 0.610306483003609, 0.0, 0.19612487218547192, 0.0, 0.00023209933851688522, 0.0, 0.08304655121373594, 0.04586194110953422, 0.06462424718512699, 0.0, 0.01314730346122887, 0.0, 0.250886590321389, 0.0, 3.385393156991965e-05, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 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, 0.0, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan] [0.6823375291352629, 0.9532136597546238, 0.9875963011659368, 0.9511350131931436, 0.18348146747352495, 0.6301247597959363, 0.0, 0.19847005844186696, 0.0, 0.0005554012774229381, 0.0, 0.6049191374663073, 0.40508187464709206, 0.06812034225779741, 0.0, 0.02395112016293279, 0.0, 0.7271413276231263, 0.0, 4.9850448654037884e-05, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 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, 0.0, nan, 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, 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, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan]
2.3717 20.0 200 3.2813 0.0746 0.1329 0.4690 [0.4353412422920181, 0.6160292678776534, 0.6667624454879082, 0.38961931993750354, 0.0175498356091348, 0.7737603033734496, 0.0, 0.3407311442973571, 0.026281775096940973, 0.0, 0.0, 0.005606700353014467, 0.012182422120477602, 0.1556179775280899, 0.0, 0.0004365079365079365, 0.24729798292026758, 0.19051530134533567, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 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, 0.0, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan] [0.6830958358752002, 0.9271474417971844, 0.9959849612622108, 0.9016053336556086, 0.22409228441754916, 0.8598183715871514, 0.0, 0.3818360354557885, 0.22007640067911716, 0.0, 0.0, 0.01091644204851752, 0.15324675324675324, 0.25995031741650565, 0.0, 0.0004480651731160896, 0.27450544249881687, 0.6208779443254818, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 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, 0.0, nan, 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, 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, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan]
2.1377 30.0 300 3.0484 0.0828 0.1570 0.4457 [0.41408741165785873, 0.5651525264025755, 0.6942762191706158, 0.4724181711859317, 0.028112952365367306, 0.8062353890394521, 0.0, 0.42361356031345965, 0.047244094488188976, 0.04630346266446815, 0.0, 0.08896756509821836, 0.021292082519115005, 0.21415716856628675, 0.0, 0.0, 0.01793870391209373, 0.3824538625614393, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 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, 0.0, 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, 0.0, 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, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan] [0.6549193934518268, 0.9216412833830862, 0.9965608666833281, 0.9031059278506254, 0.5522881996974282, 0.9503545753387244, 0.0, 0.5199636784060733, 0.13879456706281834, 0.3821160788669814, 0.0, 0.26246630727762804, 0.36668548842461884, 0.36458735854264424, 0.0, 0.0, 0.01859678182678656, 0.6623126338329764, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 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, 0.0, nan, 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, 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, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan]
1.392 40.0 400 2.8204 0.0876 0.1590 0.5052 [0.39708613876954113, 0.6178270179264523, 0.7243542260957274, 0.3721274683109001, 0.016621138086260628, 0.8039642615811998, 0.0, 0.5479698590506946, 0.04542003175260578, 0.04085742501403869, 0.0, 0.02442296847959243, 0.030204182985879884, 0.3227314466983888, 0.0, 0.0, 0.3772798664270655, 0.2985112521638777, 0.0, 0.023060520389093873, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, 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, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 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, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan] [0.7549648432468167, 0.8751910749013614, 0.9988373230177444, 0.6211906056760731, 0.1838124054462935, 0.8878332374142826, 0.0, 0.6879774468242362, 0.27928692699490665, 0.5859483476811996, 0.0, 0.08463611859838274, 0.30220214568040654, 0.42682859508694454, 0.0, 0.0, 0.3785636535731188, 0.6923447537473233, 0.0, 0.03198737121967431, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 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, 0.0, nan, 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, 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, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan]
1.3334 50.0 500 2.8298 0.0819 0.1542 0.4808 [0.40480086059537657, 0.5803259388109014, 0.6756930420414907, 0.4699824571952951, 0.01321047230167915, 0.796913459007008, 0.0, 0.449844649547656, 0.0, 0.04189729397293973, 0.0, 0.0932436627004656, 0.03510132957773375, 0.37397181661671874, 0.010650703568374408, 0.00026010508245331116, 0.18837952965886698, 0.2687367405978785, 0.0, 0.021754987650845246, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, 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, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan] [0.6987407733270465, 0.8757673007819065, 0.9998207086896522, 0.905215823715431, 0.2002174735249622, 0.9300847664289825, 0.0, 0.5197630649512457, 0.0, 0.15134684809775062, 0.0, 0.3036388140161725, 0.332128740824393, 0.6475296715429202, 0.028933474128827876, 0.0004073319755600815, 0.18888547089446284, 0.7459314775160599, 0.0, 0.02824858757062147, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 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, 0.0, nan, 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, 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, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan]
0.9039 60.0 600 2.6701 0.0886 0.1678 0.4992 [0.4041052977036986, 0.4767061770636036, 0.8194395492123262, 0.48368437849050583, 0.010394407160364025, 0.814759515142948, 0.0, 0.4848792735187468, 0.04776689754000478, 0.07346528010734653, 0.0, 0.21862264755712257, 0.04752327049908789, 0.3002597505601491, 0.04104660099210508, 0.007043286867204695, 0.3801844890772957, 0.29784075840639657, 0.0004245383145828911, 0.0348453566512833, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.019663917184656474, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, 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, 0.0, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan] [0.6913181169688146, 0.7493097294139303, 0.9978919688359105, 0.7937287247970672, 0.14395801815431164, 0.8995678765473043, 0.0, 0.5668755510270881, 0.1273344651952462, 0.3040821993890586, 0.0, 0.6434636118598382, 0.3442123094297007, 0.4179685343637869, 0.2481520591341077, 0.025417515274949082, 0.3822077614765736, 0.8056209850107067, 0.0008650519031141869, 0.05721169823861748, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.021438326161457393, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 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, 0.0, nan, 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, 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, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan]
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0.0943 480.0 4800 2.8448 0.0882 0.1911 0.5008 [0.41911690322353634, 0.40501890608512137, 0.8647450945340102, 0.4931016041127609, 0.030502923437085556, 0.8356140800056504, 0.0, 0.3432461292044848, 0.008052230685527748, 0.11677318084987107, 0.0, 0.1733837756341351, 0.04271008403361345, 0.21119568589085877, 0.05501559875209983, 0.056384824380503455, 0.46929777420545726, 0.2883860345337105, 0.0, 0.0762278420143822, 0.0, 0.0, 0.02120571279585156, 0.0, 0.0, 0.0, nan, 0.014898478571826643, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.273700688791484, 0.0, 0.0, 0.020450717780094635, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.004908501715592832, nan, nan, 0.0, nan, 0.0, nan, 0.02159318637274549, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.3104238258877434, nan, nan, 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, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan] [0.6947985504675009, 0.5897831950124449, 0.9986960631974704, 0.8032157028622072, 0.3751418305597579, 0.9232371216481169, 0.0, 0.3733469187357129, 0.015704584040747028, 0.57845043043599, 0.0, 0.8369272237196765, 0.22958780350084698, 0.24430030361578803, 0.38732840549102426, 0.14032586558044807, 0.4752744912446758, 0.7313704496788008, 0.0, 0.11590229312063809, 0.0, 0.0, 0.021227235819510498, 0.0, 0.0, nan, nan, 0.020665309593135613, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.42648063225680555, nan, nan, 0.028279915714761007, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.008534261330681912, nan, nan, nan, nan, 0.0, nan, 0.03198990573740073, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.3111366245694604, 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, 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, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan]
0.1182 490.0 4900 2.8413 0.0874 0.1918 0.5010 [0.42108588345669934, 0.40911054736398983, 0.8661098313005545, 0.49214842891161836, 0.02954288427171425, 0.8358979141409432, 0.0, 0.34096083067248395, 0.03647956517194523, 0.12091988130563798, 0.0, 0.17095466578424884, 0.03946138021320367, 0.19972277612956568, 0.0567538674380581, 0.05491907906141166, 0.4722305896528353, 0.2811591192355629, 0.0, 0.08498282524688708, 0.0, 0.0, 0.020493941677778422, 0.0, 0.0, 0.0, nan, 0.0180073126142596, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.2724654017158244, 0.0, 0.0, 0.015181493037059585, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.004800537660217944, nan, nan, 0.0, nan, 0.0, nan, 0.02163304321577703, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.3306636155606407, nan, nan, nan, 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, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan] [0.7014215820903503, 0.5911117157925907, 0.9988699214378076, 0.8002950832880134, 0.361857034795764, 0.9180428611839988, 0.0, 0.3692501808160744, 0.07406621392190153, 0.5884476534296029, 0.0, 0.8355121293800539, 0.21445511010728402, 0.22669058791057134, 0.3812038014783527, 0.1419551934826884, 0.47483199242782775, 0.7245717344753747, 0.0, 0.13155533399800598, 0.0, 0.0, 0.020502261918570932, 0.0, 0.0, nan, nan, 0.025380710659898477, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.4245292223631574, nan, nan, 0.022124875235665965, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.008285690612312536, nan, nan, nan, nan, 0.0, nan, 0.03191568321828843, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.33180252583237657, 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, 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, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan]
0.1381 500.0 5000 2.8363 0.0891 0.1916 0.5016 [0.41868138102795893, 0.41164379787292665, 0.8678939714436806, 0.49194778723391036, 0.029843826630701325, 0.835960288057647, 0.0, 0.34373422146269467, 0.013432504440497336, 0.1204883859440143, 0.0, 0.17471152509384125, 0.04084956814333784, 0.21202216853772915, 0.056338467294381744, 0.056798931456867346, 0.47129763627592863, 0.28277576385292597, 0.0, 0.07881762508014414, 0.0, 0.0, 0.01960102064486198, 0.0, 0.0, 0.0, nan, 0.017165794195445887, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.27608723215417774, 0.0, 0.0, 0.023283028004196595, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.004678027590815791, nan, nan, 0.0, nan, 0.0, nan, 0.022047401914115347, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.34324942791762014, nan, nan, 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, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan] [0.6994942191263431, 0.5978423542028475, 0.9986688978474176, 0.7972636815920398, 0.3682394099848714, 0.9211447857428524, 0.0, 0.3737798214540252, 0.02567911714770798, 0.5617883921133019, 0.0, 0.846832884097035, 0.2152456239412761, 0.2470880485785261, 0.3816261879619852, 0.1420366598778004, 0.47624704212020824, 0.7307815845824411, 0.0, 0.11847789963443005, 0.0, 0.0, 0.01960329428140587, 0.0, 0.0, nan, nan, 0.023911979180087094, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.424919504341887, nan, nan, 0.031995120328268824, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.008119976800066285, nan, nan, nan, nan, 0.0, nan, 0.032657908409411414, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.34443168771526983, 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, 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, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan]

Framework versions

  • Transformers 4.29.2
  • Pytorch 2.0.1
  • Datasets 2.12.0
  • Tokenizers 0.13.3
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Dataset used to train manadopeee/segformer-b0-scene-parse-150_epoch_500_230609

Evaluation results

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