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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: 2.8109
  • Mean Iou: 0.0916
  • Mean Accuracy: 0.1656
  • Overall Accuracy: 0.4554
  • Per Category Iou: [0.4368866056989907, 0.7837220066222808, 0.6812373730748039, 0.3025766255890313, 0.37453613756798737, 0.4311155703267072, 0.3870147278695286, 0.0, 0.27452882957957103, 0.0, 0.048119083488858405, 0.0, 0.7042929292929293, 0.0, 0.008028367431882944, 0.0, 0.0, 0.0, nan, 0.12938554820432208, 0.4710568242166755, nan, 0.0, nan, 0.006463054187192118, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 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, 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, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan]
  • Per Category Accuracy: [0.9271225217318416, 0.9791121786317943, 0.9719005789578758, 0.6925102583049035, 0.9562733521212972, 0.8051859833224023, 0.9988911066755378, 0.0, 0.3584587867044269, nan, 0.1376028806584362, 0.0, 0.8593228034897674, nan, 0.00894218339054072, 0.0, 0.0, 0.0, nan, 0.25676185252476774, 0.4804116266474093, nan, 0.0, nan, 0.011968182149894183, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 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, 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, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 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: 50

Training results

Training Loss Epoch Step Validation Loss Mean Iou Mean Accuracy Overall Accuracy Per Category Iou Per Category Accuracy
4.8479 1.0 20 4.9013 0.0150 0.0619 0.1426 [0.2076503199387906, 0.11027203515562833, 0.33989902623878737, 0.0, 0.5290951069845542, 0.06365353609339178, 0.26081863379418374, 0.0, 0.05395916993291173, 0.0, 0.0, 0.0, 0.10797994113158181, 0.0, 0.0006769171260032879, 0.0, 0.0, 0.0, 0.0, 0.026470687161548552, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.03490191358767601, 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, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.00011275228323373548, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 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, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 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, nan, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] [0.23953099653375276, 0.19108620229516948, 0.3536571670992214, 0.0, 0.5464619543733024, 0.6575002342359224, 0.8493235750720781, 0.0, 0.10034282307348338, nan, 0.0, 0.0, 0.14456102228132195, nan, 0.0011233450719921544, 0.0, 0.0, 0.0, nan, 0.026978848856741285, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.04438662279023494, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, 0.00017424638438752395, nan, 0.0, nan, nan, nan, nan, nan, nan, 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, 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, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan]
4.451 2.0 40 4.5502 0.0293 0.1051 0.3009 [0.370222814439943, 0.313884697372518, 0.6613302112099501, 0.13471489807876152, 0.4652476354745162, 0.08288349825607051, 0.22781184076732786, 0.0, 0.09632573089115885, nan, 0.0, 0.0, 0.15124789942117384, 0.0, 0.0005959300905618351, 0.0, 0.0, 0.0, 0.0, 0.016842388924445045, 0.0010546933855657677, 0.0, 0.0, nan, 0.0, 0.001984086676824107, 0.0, 0.0, 0.0, 0.0, 0.0514569496798899, nan, 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, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan] [0.61031097612086, 0.5829107730628947, 0.9726242763026552, 0.1716949392362476, 0.9390326323977607, 0.6423451700552797, 0.8877504250757744, 0.0, 0.26087345356983155, nan, 0.0, 0.0, 0.19703726526773263, nan, 0.001087683323674943, 0.0, 0.0, 0.0, nan, 0.017140310582427754, 0.00758259613648673, nan, 0.0, nan, 0.0, 0.0019844091811095084, 0.0, 0.0, 0.0, nan, 0.06581464758552077, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 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, 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, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan]
4.1448 3.0 60 4.1898 0.0458 0.1155 0.3473 [0.4441256490543131, 0.2984021271837181, 0.8737655187910791, 0.24011826344050957, 0.18650396558298804, 0.09946665516596943, 0.3082211256237159, 0.0, 0.12781097958089108, nan, 0.0, 0.0, 0.1783879559797272, 0.0, 0.007779555989691216, 0.0, 0.0, 0.0, nan, 0.03458303859152716, 0.0681618551267787, nan, 0.0, nan, 0.00039768283468324565, 0.001225092051115443, 0.0, 0.0, 0.0, nan, 0.015458937198067632, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 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, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 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, 0.0, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan] [0.752163322863919, 0.7477626545680989, 0.97037208025554, 0.43411888628610057, 0.9292900955125671, 0.32413566944626626, 0.9936719154284025, 0.0, 0.1989119093754658, nan, 0.0, 0.0, 0.25142704245451303, nan, 0.01590513974947622, 0.0, 0.0, 0.0, nan, 0.04525041993760927, 0.21014623578263225, nan, 0.0, nan, 0.0010946508063927607, 0.0012258636920847133, 0.0, 0.0, 0.0, nan, 0.015917961276498048, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 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, 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, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan]
4.0777 4.0 80 3.9487 0.0460 0.1110 0.3635 [0.3774617542366128, 0.29316716611021465, 0.7633307050474857, 0.256738551199018, 0.21756699154397363, 0.02867328701004521, 0.2728916619491156, 0.0, 0.0236669180221911, nan, 0.0026376811594202897, 0.0, 0.3360886752397452, 0.0, 0.00012589049008427256, 0.0, 0.0, 0.0, nan, 0.04661089783991291, 0.18454218106995884, nan, 0.0, nan, 0.00034316019341756356, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, 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, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan] [0.9225789273863115, 0.7014678409394182, 0.8093244659612697, 0.40446806169132327, 0.963299710529336, 0.07027077672631875, 0.9906852960745176, 0.0, 0.03274705619317335, nan, 0.0029256687242798355, 0.0, 0.4467048292413972, nan, 0.00015156243034814782, 0.0, 0.0, 0.0, nan, 0.05577457063521991, 0.25907203466329665, nan, 0.0, nan, 0.00040137196234401223, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 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, 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, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan]
3.7269 5.0 100 3.7389 0.0551 0.1160 0.3735 [0.4255796439020644, 0.43681870142371915, 0.8852097993952233, 0.23808850521442917, 0.17365552486595867, 0.09256198347107437, 0.42408886544595986, 0.0, 0.14573030003297066, nan, 5.246452086776318e-05, 0.0, 0.12130999147530035, nan, 0.010975599767382811, 0.0, 0.0, 0.0, nan, 0.006541209620609842, 0.06541319522630039, nan, 0.0, nan, 0.00015364818407052452, 0.0032846616459879722, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 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, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 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, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan] [0.8470191752994137, 0.7104705987011831, 0.9880465162707127, 0.7147876806011917, 0.8995524043917928, 0.19544645366813454, 0.9985510460560361, 0.0, 0.210821284841258, nan, 6.430041152263375e-05, 0.0, 0.22384296046443744, nan, 0.011946685686265768, 0.0, 0.0, 0.0, nan, 0.006684721127146824, 0.10489257988806644, nan, 0.0, nan, 0.00029190688170473617, 0.0032847728765805855, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 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, 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, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan]
3.7755 6.0 120 3.5602 0.0617 0.1297 0.4116 [0.4135174410609956, 0.5181620367373563, 0.9205332399871649, 0.26453974292466426, 0.18848335044816786, 0.26292162096578503, 0.4134307819332742, 0.0, 0.03229816195948975, 0.0, 0.004489005967421107, 0.0, 0.38779175307014996, nan, 0.00021934100214466757, 0.0, 0.0, 0.0, nan, 0.03485741596303967, 0.012106106462524479, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 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, 0.0, 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, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 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, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan] [0.9267182083988699, 0.9257450404768259, 0.9843781193851068, 0.6493860738597953, 0.9315599535826776, 0.6091070926637309, 0.999452945959932, 0.0, 0.04724996273662245, nan, 0.0053690843621399175, 0.0, 0.48672688353387605, nan, 0.00024071680114117595, 0.0, 0.0, 0.0, nan, 0.03750299955435193, 0.012276584220978517, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 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, 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, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan]
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1.3779 49.0 980 2.8165 0.0918 0.1654 0.4543 [0.43316242067506666, 0.7853887853023965, 0.7185705581506988, 0.29972862311940585, 0.3790482718301767, 0.38939868908520947, 0.37772323999172613, 0.0, 0.25863274150705995, 0.0, 0.054101408089570736, 0.0, 0.7060419086496177, 0.0, 0.00877592250996175, 0.0, 0.0, 0.0, nan, 0.13200138584132118, 0.49743589743589745, nan, 0.0, nan, 0.007428040854224698, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 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, 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, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan] [0.9288901599009926, 0.9705186371319278, 0.9712143142343781, 0.6928246891065448, 0.9590787946798608, 0.8001499109903495, 0.9989798181414948, 0.0, 0.3308987926665673, nan, 0.16280864197530864, 0.0, 0.8526578665715305, nan, 0.009798065350153791, 0.0, 0.0, 0.0, nan, 0.23509649994857906, 0.5078534031413613, nan, 0.0, nan, 0.014011530321827337, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 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, 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, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan]
1.7715 50.0 1000 2.8109 0.0916 0.1656 0.4554 [0.4368866056989907, 0.7837220066222808, 0.6812373730748039, 0.3025766255890313, 0.37453613756798737, 0.4311155703267072, 0.3870147278695286, 0.0, 0.27452882957957103, 0.0, 0.048119083488858405, 0.0, 0.7042929292929293, 0.0, 0.008028367431882944, 0.0, 0.0, 0.0, nan, 0.12938554820432208, 0.4710568242166755, nan, 0.0, nan, 0.006463054187192118, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 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, 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, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan] [0.9271225217318416, 0.9791121786317943, 0.9719005789578758, 0.6925102583049035, 0.9562733521212972, 0.8051859833224023, 0.9988911066755378, 0.0, 0.3584587867044269, nan, 0.1376028806584362, 0.0, 0.8593228034897674, nan, 0.00894218339054072, 0.0, 0.0, 0.0, nan, 0.25676185252476774, 0.4804116266474093, nan, 0.0, nan, 0.011968182149894183, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 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, 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, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan]

Framework versions

  • Transformers 4.40.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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Safetensors
Model size
3.75M params
Tensor type
F32
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Finetuned from

Dataset used to train Sa3ed99/segformer-b0-scene-parse-150

Evaluation results

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