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segformer-b0-scene-parse-150

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metadata
license: other
base_model: nvidia/mit-b0
tags:
  - generated_from_trainer
datasets:
  - scene_parse_150
model-index:
  - name: segformer-b0-scene-parse-150
    results: []

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: 3.3175
  • Mean Iou: 0.0536
  • Mean Accuracy: 0.1241
  • Overall Accuracy: 0.3983
  • Per Category Iou: [0.28886228584264156, 0.24371287587146617, 0.8069558270192259, 0.4761964588791857, 0.5448661292194517, 0.1137512299406072, 0.0, 0.0, 0.0009700472124042208, 0.0, 0.004326142142338239, 0.009256580850448365, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0036519462973908638, nan, 0.07551971444624385, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.006026594421253421, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, 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, 0.0, 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, 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, 0.0, nan, 0.0]
  • Per Category Accuracy: [0.36078075062366005, 0.7357816119498363, 0.9711514230439687, 0.7818717815042213, 0.9586573048709611, 0.34005504955641397, 0.0, nan, 0.0009738207962538979, nan, 0.05175275851967581, 0.11026878015161957, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0074408602150537635, nan, 0.6405943369778525, 0.0, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, nan, 0.006209764712584743, nan, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, 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, 0.0, 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, 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, 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: 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: 50

Training results

Training Loss Epoch Step Validation Loss Mean Iou Mean Accuracy Overall Accuracy Per Category Iou Per Category Accuracy
4.697 2.0 20 4.9388 0.0146 0.0740 0.2066 [0.085571230710775, 0.2964774873114647, 0.556787522438757, 0.07943290508800724, 0.5710624205368254, 7.988314237458347e-05, 0.0, 0.0, 0.003537290193845518, 0.0, 0.012328710639526093, 0.0, 0.0, 0.0, 0.0, 0.0, 0.13723623262995369, 0.0, 0.0018603707211473414, 0.0, 0.02562518292088062, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.007467363199275381, 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, nan, 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, 0.034510631609672854, nan, 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, nan, 1.1162458419842386e-05, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, 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, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, 0.0025575447570332483, nan, 0.0, 0.0, 0.0] [0.08902916258199237, 0.3715352663950795, 0.8032861246912958, 0.09475176560161727, 0.8866060349025336, 8.269246671628214e-05, 0.0, nan, 0.003636288292394874, nan, 0.04379455131334831, 0.0, nan, 0.0, 0.0, nan, 0.3532489898655362, 0.0, 0.0023655913978494624, nan, 0.2209139332772638, 0.0, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, 0.007638110833405154, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.04975559224369557, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 2.2303506111160674e-05, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 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, 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, 0.03361344537815126, nan, 0.0, nan, 0.0]
4.0945 4.0 40 4.6344 0.0196 0.0893 0.3038 [0.20635825082660963, 0.1497617706207396, 0.6430633164341487, 0.20803427211231343, 0.48320529531461826, 0.05435056746532156, 0.0, 0.0, 0.00018992279894875164, 0.0, 0.02522212668386357, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0167847439120388, 0.0, 0.005801286258039113, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.002079884773308683, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0019606068832383194, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.006265614985153501, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0] [0.24881046314229013, 0.8015616263279814, 0.9432100584260253, 0.25698833183933867, 0.9685636345548696, 0.0712809063094352, 0.0, nan, 0.00019165622053933097, nan, 0.11600429645542427, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.028430107526881722, nan, 0.12391365292963274, 0.0, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, 0.0020845901921916748, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.002104172736395714, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.010683379427245962, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 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, 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, 0.0, nan, 0.0]
3.9633 6.0 60 4.2067 0.0266 0.1027 0.3562 [0.2871756509311777, 0.17553996035436806, 0.6508065400502357, 0.28472075103957967, 0.5344282513158123, 0.0396569507272742, 0.0, 0.0, 0.01198079221182846, 0.0, 0.02074043347505963, 0.0036676362716580244, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.03343392818953021, nan, 0.015774441212692922, 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, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, 0.0, nan, 0.0013235016071090943, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.014526084050792153, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0] [0.40999131259514304, 0.7462656761722182, 0.9663556039746756, 0.35285027923322443, 0.9665425757504359, 0.057683902139372245, 0.0, nan, 0.014177380422058078, nan, 0.03905868567522703, 0.13990351481736732, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.060516129032258066, nan, 0.3375385477992711, 0.0, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0013596193065941536, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.01648229101614774, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 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, 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, 0.0, nan, 0.0]
3.9982 8.0 80 3.9414 0.0306 0.0944 0.3554 [0.3041052532757534, 0.16874660879001627, 0.6654845578699627, 0.2502437796860747, 0.47240134425999425, 0.035202401300704546, 0.0, 0.0, 0.00223447952118296, 0.0, 0.0022180941026423047, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.017687682044536315, nan, 0.007851227828877618, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, 0.0, 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, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0] [0.4337326351529063, 0.8073727933541017, 0.9668906266355992, 0.2983801097429704, 0.9516516658027425, 0.04987537063944903, 0.0, nan, 0.0024656313777492306, nan, 0.0039058685675227027, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.03238709677419355, nan, 0.2304457527333894, 0.0, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, 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, 0.0, 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, 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, 0.0, nan, 0.0]
3.9845 10.0 100 3.8601 0.0342 0.0922 0.3594 [0.2922888303737397, 0.18416615155261434, 0.7138469538187262, 0.2908211060948081, 0.4744411224037019, 0.03968080659350258, 0.0, 0.0, 0.001517351802204349, 0.0, 0.0022640195053988156, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.018242732924066078, nan, 0.0017321694198700385, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 2.8339851499178144e-05, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, 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, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0] [0.41156142154635805, 0.8091600766834411, 0.968681789456952, 0.3865645499450535, 0.9405306064747184, 0.07513201261650777, 0.0, nan, 0.0016886466998870782, nan, 0.004442925495557075, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.04051612903225806, nan, 0.0496215306980656, 0.0, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, nan, 2.8485159232040106e-05, nan, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, 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, 0.0, 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, 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, 0.0, nan, 0.0]
3.9115 12.0 120 3.7662 0.0350 0.0957 0.3679 [0.3265435969524282, 0.16934551763002906, 0.6636468421680203, 0.2897614314115308, 0.47149638549909734, 0.04380312895641165, 0.0, 0.0, 0.0005679270662083396, 0.0, 0.006130608618391826, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.015278462296697881, nan, 0.010168610506481272, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0005282032748603041, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, 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, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, 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, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0] [0.4532274904558098, 0.7651170221263679, 0.971015728890836, 0.35641711330230325, 0.9667886632214421, 0.09155237386445524, 0.0, nan, 0.0005905083551752359, nan, 0.02021286983692999, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.02666666666666667, nan, 0.17549761704513597, 0.0, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, nan, 0.000541218025408762, nan, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, 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, 0.0, 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, 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, 0.0, nan, 0.0]
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1.7264 46.0 460 3.3351 0.0549 0.1237 0.3989 [0.2948823282162118, 0.24265564314301968, 0.8097134839089304, 0.4768203409948526, 0.544499023495295, 0.11367812320564351, 0.0, 0.0, 0.0009235373026519451, 0.0, 0.004245009273275516, 0.006109259820256488, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.004259190340321714, nan, 0.07332351927835375, 0.0, nan, nan, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.011091085539997228, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, 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, 0.0, 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, 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, 0.0, nan, 0.0] [0.37015677179223555, 0.736740154964454, 0.9709730821569943, 0.7653915828716953, 0.9634481567001241, 0.32742672856788463, 0.0, nan, 0.0009272017155821687, nan, 0.05106923152035934, 0.0833907649896623, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.008860215053763441, nan, 0.6562938043173535, 0.0, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, nan, 0.011394063692816044, nan, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, 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, 0.0, 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, 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, 0.0, nan, 0.0]
1.9152 48.0 480 3.3416 0.0535 0.1244 0.3956 [0.28584432792206127, 0.2464477707388237, 0.8098088290455681, 0.4647101057424465, 0.5453601518927258, 0.11637491362574447, 0.0, 0.0, 0.000902136258660508, 0.0, 0.005328897173914753, 0.006776967657506076, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.003578076525336091, nan, 0.07035055736529093, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.013375989409525911, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, 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, 0.0, 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, 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, 0.0, nan, 0.0] [0.3548844734555946, 0.7387970285166546, 0.9709304354231525, 0.7671168653867071, 0.9625161658524837, 0.3342429504672124, 0.0, nan, 0.0009064821241725114, nan, 0.06615564886241578, 0.09993108201240523, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0074408602150537635, nan, 0.6599383235211662, 0.0, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, nan, 0.013815302227539452, nan, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, 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, 0.0, 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, 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, 0.0, nan, 0.0]
2.3061 50.0 500 3.3175 0.0536 0.1241 0.3983 [0.28886228584264156, 0.24371287587146617, 0.8069558270192259, 0.4761964588791857, 0.5448661292194517, 0.1137512299406072, 0.0, 0.0, 0.0009700472124042208, 0.0, 0.004326142142338239, 0.009256580850448365, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0036519462973908638, nan, 0.07551971444624385, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.006026594421253421, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, 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, 0.0, 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, 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, 0.0, nan, 0.0] [0.36078075062366005, 0.7357816119498363, 0.9711514230439687, 0.7818717815042213, 0.9586573048709611, 0.34005504955641397, 0.0, nan, 0.0009738207962538979, nan, 0.05175275851967581, 0.11026878015161957, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0074408602150537635, nan, 0.6405943369778525, 0.0, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, nan, 0.006209764712584743, nan, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, 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, 0.0, 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, 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, 0.0, nan, 0.0]

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.1+cu121
  • Datasets 2.15.0
  • Tokenizers 0.15.0