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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: 2.3440
  • Mean Iou: 0.0924
  • Mean Accuracy: 0.1531
  • Overall Accuracy: 0.5487
  • Per Category Iou: [0.36135412286702273, 0.6332733881308499, 0.8284794627754917, 0.34081559402523537, 0.6382171001361363, 0.36977016524917494, 0.4290942294174342, 0.006225915717008818, 0.0, 0.20017482517482518, 0.010114590855535708, 0.0, 0.415883250213659, nan, nan, 0.0, 0.0, 0.0, 0.00044973465655263396, 0.38541750868967745, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]
  • Per Category Accuracy: [0.8313462628275238, 0.9058792557788168, 0.9352794988571527, 0.7990161175480613, 0.7657342386032978, 0.5584336703705027, 0.9005216492023178, 0.006827478344562079, 0.0, 0.481486760984997, 0.013402665424396755, 0.0, 0.8510172005401456, nan, nan, 0.0, 0.0, 0.0, 0.00045044368703172624, 0.4537581606045033, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, nan, 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: 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
4.9035 1.0 20 4.8923 0.0080 0.0319 0.1655 [0.13751218952561234, 0.3485383865239691, 0.20578130389789584, 0.0, 0.0, 0.06100683743789252, 0.0, 0.0, 0.05244144039156275, 0.010265047988304837, 3.766762091306313e-05, 0.0, 0.009841574651944312, 0.0, nan, 0.0, 0.0, 0.012531668004629001, 0.042205470297900276, 0.025510392439177465, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.012802926383173296, 0.0, 0.0014566270140423956, nan, nan, 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, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, 0.0, 0.002386341038437136, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0, 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, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, nan] [0.17306102706819568, 0.7251091665569755, 0.21252401119477426, 0.0, 0.0, 0.12129765264925506, 0.0, 0.0, 0.1124906257811849, 0.023021275079291543, 3.777172031300166e-05, 0.0, 0.009983839904367653, nan, nan, 0.0, 0.0, 0.06939352827411022, 0.05405324244380715, 0.026304269209539582, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.017169487368162865, nan, 0.012714699977693509, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.003923033812815244, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]
4.6054 2.0 40 4.5293 0.0247 0.0814 0.3469 [0.2560094212513826, 0.35678088574656114, 0.6651459898084865, 0.04138256313506752, 0.03139873415274454, 0.22060956170523868, 0.00266955165582454, 0.0, 0.16933429150062063, 0.06540174419240828, 0.0035479787744819888, 0.0, 0.2511488636127342, 0.0, 0.0, 0.0, 0.0, 0.05029949998730932, 0.0031414703868028466, 0.0995822513266343, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.004630757981964416, nan, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, 0.0, 0.0008233724198631498, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, 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, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan] [0.4519764222624088, 0.9706466437364436, 0.7849366446457173, 0.05224933652663603, 0.03150727449078564, 0.6576512201221909, 0.00288960199534622, 0.0, 0.215982001499875, 0.2130002494565411, 0.003582018143016324, 0.0, 0.26737210280477275, nan, nan, 0.0, 0.0, 0.2288196749704125, 0.003168120598789808, 0.100725175583852, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.004660289428501349, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0009029204807273181, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]
4.4153 3.0 60 4.2056 0.0433 0.1158 0.3844 [0.2730002273839136, 0.4911020106193084, 0.7384136998009628, 0.07962881640234114, 0.0811012591976848, 0.15890294676421843, 0.09561344736530958, 0.0, 0.2954495493515058, 0.11147300967577661, 0.006524039394679339, 0.0, 0.4310325725681365, 0.0, nan, 7.635482085250158e-05, 0.0, 0.09816100452132089, 0.00618242507800595, 0.297599914282653, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan] [0.5720489025090149, 0.8053830701699164, 0.8913268999481301, 0.14319373422227977, 0.08176139670223084, 0.7022580299403337, 0.11068696485331468, 0.0, 0.44796266977751853, 0.37443426820141834, 0.006559688761024621, 0.0, 0.5167467292409182, nan, nan, 0.00016886187098953058, 0.0, 0.6975146494241261, 0.006396300355850513, 0.3171929423856564, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]
4.2477 4.0 80 3.7011 0.0524 0.1063 0.4594 [0.2900867500684869, 0.45081740714033824, 0.7498938831647716, 0.1786014920789754, 0.5550358869032337, 0.18409195210480203, 0.0607389016047898, 0.0, 0.0, 0.05741808591480041, 0.003999033466231727, 0.0, 0.3491988597267276, 0.0, nan, 0.007904288852803516, 0.0, 0.1057950501990767, 0.0, 0.09882470710366306, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan] [0.5733339108651788, 0.9803671887966211, 0.9012648270908977, 0.6399896433426112, 0.5787468477206595, 0.6306048804887634, 0.07143400301126945, 0.0, 0.0, 0.09155055058622287, 0.004167479807867849, 0.0, 0.3931994775640316, nan, nan, 0.013973319824383655, 0.0, 0.23086915105504718, 0.0, 0.101467481299606, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]
4.0027 5.0 100 3.5096 0.0631 0.1231 0.4887 [0.3169070910716059, 0.5972709494005479, 0.821972321458468, 0.19012153789694106, 0.5650177561779, 0.2030719145996385, 0.0, 0.0, 0.0, 0.07025779885600757, 0.0022350361603411307, 0.0, 0.40979028738395534, nan, nan, 0.0003805278464841945, 0.0, 0.1050679456434852, 0.0010192926995006943, 0.31192510660545364, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan] [0.7371472092578355, 0.9246106917411135, 0.9095041581404363, 0.7980969642048029, 0.5962948593598448, 0.7666583300582371, 0.0, 0.0, 0.0, 0.15626670467909198, 0.0023229607992496016, 0.0, 0.4905363823522901, nan, nan, 0.000591016548463357, 0.0, 0.284559651300407, 0.0010360204801729703, 0.3633871980814252, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]
3.532 6.0 120 3.2473 0.0755 0.1284 0.5075 [0.33283893433198647, 0.56720945029832, 0.8436870605865754, 0.2112269856955629, 0.6145018893551814, 0.23210655825398524, 0.0007121592434767381, 0.0, 0.006095671040396735, 0.07563008880511456, 0.00661958879562388, 0.0, 0.45964543758941023, nan, nan, 0.005447809980387884, 0.0, 0.1600128852142167, 0.0015837678734180998, 0.4076342334440198, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan] [0.7314404727098155, 0.9744324197489884, 0.9049441686284122, 0.7803352967829633, 0.6845586808923375, 0.7751259423344885, 0.0009277143248216811, 0.0, 0.009832513957170236, 0.1386978368554221, 0.007069606985250144, 0.0, 0.5619064485422708, nan, nan, 0.009498480243161094, 0.0, 0.2150795254452559, 0.001591567694178766, 0.49534631416661906, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]
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1.3103 49.0 980 2.3541 0.0926 0.1531 0.5458 [0.36013622188629557, 0.6246660685705837, 0.8224188110826692, 0.3480022126242506, 0.6340751429781826, 0.370121035009051, 0.4286424162987822, 0.024130873874717424, 0.0, 0.1926029803388294, 0.010475682952824368, 0.0, 0.4174862431489241, nan, nan, 0.0, 0.0, 0.0, 0.0018138482063889431, 0.3949920297555792, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan] [0.8332773849358037, 0.8945963269674303, 0.9358067476444805, 0.8063046151854489, 0.743286129970902, 0.558844546071671, 0.9052058461210896, 0.027129451395572667, 0.0, 0.48455151277573855, 0.014107737536906119, 0.0, 0.8447966705775574, nan, nan, 0.0, 0.0, 0.0, 0.0018167895376946291, 0.4527684196501646, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]
1.0991 50.0 1000 2.3440 0.0924 0.1531 0.5487 [0.36135412286702273, 0.6332733881308499, 0.8284794627754917, 0.34081559402523537, 0.6382171001361363, 0.36977016524917494, 0.4290942294174342, 0.006225915717008818, 0.0, 0.20017482517482518, 0.010114590855535708, 0.0, 0.415883250213659, nan, nan, 0.0, 0.0, 0.0, 0.00044973465655263396, 0.38541750868967745, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan] [0.8313462628275238, 0.9058792557788168, 0.9352794988571527, 0.7990161175480613, 0.7657342386032978, 0.5584336703705027, 0.9005216492023178, 0.006827478344562079, 0.0, 0.481486760984997, 0.013402665424396755, 0.0, 0.8510172005401456, nan, nan, 0.0, 0.0, 0.0, 0.00045044368703172624, 0.4537581606045033, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.14.7
  • Tokenizers 0.15.0
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