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: 2.2863
  • Mean Iou: 0.1322
  • Mean Accuracy: 0.2193
  • Overall Accuracy: 0.5236
  • Per Category Iou: [0.17584122398758895, 0.46366573409354317, 0.6899099859557716, 0.8850136717893229, 0.2200496783644354, 0.21159926360234527, 0.28788921058002676, 0.8057838286364055, 0.3129988790098432, 0.01191510487774606, 0.13235068324888685, 0.0, 0.2795662866085401, 0.0396786413020855, 0.0, 0.0, 0.0023832843617368595, 0.021505376344086023, 0.030850694907567956, nan, 0.0, 0.8503331373701744, 0.0, 0.0, nan, 0.0, nan, 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, 0.0, nan, nan, 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, 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, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0]
  • Per Category Accuracy: [0.21451742313435987, 0.8538336753640183, 0.984218271094859, 0.9792485738046007, 0.3231085757037314, 0.6344898969443319, 0.36251832390960836, 0.9197207801318928, 0.9971040015654046, 0.0165147084121796, 0.13401741293532338, nan, 0.5442280491785443, 0.03995674007998055, nan, nan, 0.002386205769387922, 0.10079726651480637, 0.03569003826688063, nan, 0.0, 0.9717276900683014, 0.0, 0.0, nan, 0.0, nan, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 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, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • 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
4.2263 1.0 20 3.5893 0.0845 0.1572 0.4326 [0.09895809215096087, 0.3766523287544517, 0.4026077186261011, 0.7401129262459497, 0.07194570618215938, 0.16042202572347267, 0.2403559937369879, 0.7332509445672412, 0.16759665790517025, 0.0, 0.0, nan, 0.23127111732494465, 0.010414577064526915, nan, 0.0, 0.0030889924000980632, 0.0, 0.0, nan, 0.0, 0.22757075729428478, 0.0, 0.0, 0.0, 0.0, nan, 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, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 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, 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, 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, 0.0, nan, nan, nan, nan, 0.0, 0.0] [0.1476695574059358, 0.47749047200234535, 0.9076271868244234, 0.9933600613514799, 0.42068019576670096, 0.598727930036152, 0.531888362175643, 0.944892661708994, 0.22333431171118287, 0.0, 0.0, nan, 0.323958219997824, 0.010446096965937004, nan, nan, 0.0030889924000980632, 0.0, 0.0, nan, 0.0, 0.2331765759713358, 0.0, 0.0, nan, 0.0, nan, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 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, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0]
3.8869 2.0 40 3.4918 0.0916 0.1573 0.4367 [0.09252577101279869, 0.31475782946456565, 0.4295326761989256, 0.8197392257882057, 0.05785553150563142, 0.1740403836219482, 0.2149033864646486, 0.7299493926028674, 0.33963437276016617, 0.0, 0.0, nan, 0.09344845099035043, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.21577064937968035, 0.0, 0.0, nan, 0.0, nan, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 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, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0] [0.12580474265510372, 0.6357314570507183, 0.8192354905935082, 0.9941916716013189, 0.43411577667633033, 0.5811919655581057, 0.5840710491747102, 0.9451241756699874, 0.38479600821837395, 0.0, 0.0, nan, 0.1000979218801001, 0.0, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.21615720524017468, 0.0, 0.0, nan, 0.0, nan, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 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, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0]
3.0216 3.0 60 3.2395 0.0969 0.1700 0.4619 [0.1664985131690739, 0.20999590917060057, 0.4289943594009393, 0.815095824349939, 0.09465792603500028, 0.15100404742383425, 0.23608409199104305, 0.7688087904309501, 0.44141398105519397, 0.0, 0.0, nan, 0.09315274642588413, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.2777312098351495, 0.0, 0.0, nan, 0.0, nan, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 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, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0] [0.2287043115395394, 0.2528290823805336, 0.9409164873779907, 0.9921207355705914, 0.41681473861404655, 0.5221637190045453, 0.7647305195423306, 0.9753472709414901, 0.8161040994031895, 0.0, 0.0, nan, 0.10102273963660102, 0.0, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.27824431754562756, 0.0, 0.0, nan, 0.0, nan, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 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, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0]
3.8877 4.0 80 3.2859 0.1132 0.1880 0.5045 [0.13958900136723335, 0.44969956518889154, 0.4770084513190282, 0.8353439211241448, 0.1095341605825186, 0.17624136214635808, 0.33751825907089317, 0.7435181556072182, 0.4413269579617956, 0.0, 0.022456249032058232, nan, 0.1530906233630173, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.41781281449178126, 0.0, 0.0, nan, 0.0, nan, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 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, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0] [0.19401160134670828, 0.8045108961203948, 0.9188750100566024, 0.9897035649222267, 0.3502914679385268, 0.5895624259334263, 0.6026519694633237, 0.9715237827978112, 0.9021230799334703, 0.0, 0.02254353233830846, nan, 0.19078446306169078, 0.0, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.418374202216997, 0.0, 0.0, nan, 0.0, nan, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 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, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0]
3.2562 5.0 100 3.1562 0.1131 0.1913 0.5028 [0.13037894205033448, 0.4834356789963185, 0.4751899573128162, 0.7748325322635583, 0.1412642564547108, 0.17349191238521242, 0.3597649327494358, 0.7669447541424782, 0.38942214990147345, 0.0, 0.0, nan, 0.2171898871420827, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.38578765211566374, 0.0, 0.0, nan, 0.0, nan, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 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, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0] [0.17634469282536172, 0.7714883220951823, 0.9415289669079386, 0.9937289468319532, 0.5181582967050095, 0.6260444324437844, 0.6357682715555809, 0.9796758804546092, 0.8101359945210841, 0.0, 0.0, nan, 0.23974540311173975, 0.0, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.3869107602732057, 0.0, 0.0, nan, 0.0, nan, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 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, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0]
2.3162 6.0 120 3.0800 0.1224 0.1966 0.5413 [0.2575755334243388, 0.43287422594667885, 0.5950764259725814, 0.8216711856315689, 0.15240326899990767, 0.1724841670068072, 0.39731244651247144, 0.7701781913142707, 0.37261120352567567, 0.0, 0.0, nan, 0.13170231467916788, 0.0, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.5472581978506476, 0.0, 0.0, nan, 0.0, nan, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 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, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0] [0.3676171939482585, 0.7812176292387374, 0.9329776107588778, 0.9913926721222888, 0.41157766763303094, 0.5895324242833356, 0.6673044339101796, 0.9848814367896731, 0.8437432736522845, 0.0, 0.0, nan, 0.1467196170166467, 0.0, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.5559287873698354, 0.0, 0.0, nan, 0.0, nan, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 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, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0]
2.7766 7.0 140 2.8844 0.1088 0.1827 0.5185 [0.19119784006848564, 0.3880060032373116, 0.5818301479410719, 0.8527143738433066, 0.10056249675981128, 0.17833744039158628, 0.16069364920943427, 0.7868340841345615, 0.41851637958452603, 0.0, 0.0, nan, 0.046007078012001844, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.5400733081678428, 0.0, 0.0, nan, 0.0, nan, 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, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 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, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0] [0.2507917861543954, 0.8751607544219682, 0.9728043517189653, 0.98400201916263, 0.24187162941488202, 0.6361699893494143, 0.23295638433567498, 0.9852041532201488, 0.9784463359749536, 0.0, 0.0, nan, 0.048797736916548796, 0.0, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.5526816705856007, 0.0, 0.0, nan, 0.0, nan, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 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, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0]
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1.8843 49.0 980 2.2918 0.1320 0.2172 0.5234 [0.1767027937577472, 0.46560560158548614, 0.6625505590001549, 0.8845600368113623, 0.2269413833026028, 0.20745588500993717, 0.2993936587412992, 0.8051597903949266, 0.3106521858373101, 0.008812729498164015, 0.1330620393120393, 0.0, 0.27645742622157715, 0.05612690283585936, 0.0, 0.0, 0.003634230211372044, 0.010895367946923125, 0.028342906221482635, nan, 0.0, 0.8566964285714286, 0.0, 0.0, nan, 0.0, nan, 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, 0.0, nan, nan, 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, 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, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0] [0.21343099655645004, 0.8338512655135346, 0.987550574978135, 0.9766113662029712, 0.32996664484553756, 0.6200741040757242, 0.3938736268966436, 0.928125438473411, 0.9973877311417669, 0.012386031309134697, 0.13471703980099503, nan, 0.4973887498639974, 0.056598395358780675, nan, nan, 0.003644684154613059, 0.05096810933940774, 0.032588569312430565, nan, 0.0, 0.9669129996640914, 0.0, 0.0, nan, 0.0, nan, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 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, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0]
1.5944 50.0 1000 2.2863 0.1322 0.2193 0.5236 [0.17584122398758895, 0.46366573409354317, 0.6899099859557716, 0.8850136717893229, 0.2200496783644354, 0.21159926360234527, 0.28788921058002676, 0.8057838286364055, 0.3129988790098432, 0.01191510487774606, 0.13235068324888685, 0.0, 0.2795662866085401, 0.0396786413020855, 0.0, 0.0, 0.0023832843617368595, 0.021505376344086023, 0.030850694907567956, nan, 0.0, 0.8503331373701744, 0.0, 0.0, nan, 0.0, nan, 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, 0.0, nan, nan, 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, 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, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0] [0.21451742313435987, 0.8538336753640183, 0.984218271094859, 0.9792485738046007, 0.3231085757037314, 0.6344898969443319, 0.36251832390960836, 0.9197207801318928, 0.9971040015654046, 0.0165147084121796, 0.13401741293532338, nan, 0.5442280491785443, 0.03995674007998055, nan, nan, 0.002386205769387922, 0.10079726651480637, 0.03569003826688063, nan, 0.0, 0.9717276900683014, 0.0, 0.0, nan, 0.0, nan, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 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, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0]

Framework versions

  • Transformers 4.46.2
  • Pytorch 2.5.1+cu121
  • Datasets 3.1.0
  • Tokenizers 0.20.3
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