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segformer-b0-scene-parse-150

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license: other
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: 2.0485
  • Mean Iou: 0.1143
  • Mean Accuracy: 0.1916
  • Overall Accuracy: 0.5885
  • Per Category Iou: [0.5389197200177074, 0.717547165311136, 0.8775832004926136, 0.4666962362569759, 0.5127754280916853, 0.4086772583394205, 0.43686948440659384, 0.3713747236760066, 0.23987614869378396, nan, 0.02093962295037241, 0.008571053917770334, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.07904494450320337, 0.14534279304747488, 0.31956492502185463, nan, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 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, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan]
  • Per Category Accuracy: [0.8006767641143445, 0.966601443897173, 0.9654087453073266, 0.8562518463193449, 0.8260647663766045, 0.7196837732815222, 0.9784940116595793, 0.7095618428771265, 0.3872881232419512, nan, 0.025398348693681023, 0.008602536491983729, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.0971216036566239, 0.16867036362866697, 0.7297681203931204, nan, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 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, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 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
3.9614 1.0 20 4.0702 0.0691 0.1473 0.5001 [0.40379043253221286, 0.5581611702198642, 0.8959154347598167, 0.44210588723543015, 0.5549362402303579, 0.1750434771883518, 0.42016314672030397, 0.013876497658687554, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.00035554406322219886, nan, 0.005088325652841782, 0.15721170265244944, 0.0, 0.23458438867142528, nan, 0.0, 0.0, 0.003818749126810413, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.006755831469393345, nan, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] [0.6763923706760969, 0.9406986868696605, 0.9196690280389215, 0.8728394580042472, 0.6885191517595121, 0.760659252311403, 0.7643041247591248, 0.02484544921258066, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.00038228956697018143, nan, 0.005490378887939295, 0.24753909809252095, 0.0, 0.3911240786240786, nan, 0.0, 0.0, 0.006223436551305404, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.035491606714628296, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 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, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan]
3.8577 2.0 40 3.6033 0.0718 0.1404 0.5171 [0.44943875694163005, 0.5758821036990603, 0.8946545516274, 0.31382104512836045, 0.5766883898551326, 0.1972386899170344, 0.4136864850415451, 0.0019439640262884814, 0.002352872828676001, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.00015070959099091556, nan, 7.24287783679382e-05, 0.08483871689835024, 0.0010365763364430624, 0.14749010292953285, nan, 0.0004922016796382318, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0017607405171546433, nan, nan, nan, nan, nan, 0.001781388057574462, nan, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] [0.7462839930989124, 0.956336086826607, 0.9509049816724593, 0.9472161684623573, 0.709061678617909, 0.6695966769395686, 0.7549780874712373, 0.0025359866432020216, 0.0023610686021599404, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0001563911864878015, nan, 7.76940408670655e-05, 0.11322389352771596, 0.0010371248359649493, 0.17878531941031942, nan, 0.0004922016796382318, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.001929863255403617, nan, nan, nan, nan, nan, 0.002997601918465228, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 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, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan]
3.5201 3.0 60 3.6193 0.0723 0.1384 0.5216 [0.4758095252100789, 0.6116582374094812, 0.9220882746103187, 0.2744727914423049, 0.5808009148472079, 0.1405845711547676, 0.44719448679421536, 0.002192869872608195, 0.03344919358357208, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0008888049898927928, nan, 0.0, 0.14981422783853565, 0.0015652762501057618, 0.0938425405902175, nan, 0.00394640234948605, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.02047530197387803, nan, nan, nan, nan, nan, 0.00186710072769054, 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, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 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, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] [0.7401740522919427, 0.9574413396692595, 0.9519938718274995, 0.9952455535056379, 0.6998749585321663, 0.3931394881414981, 0.825187618404898, 0.002698434186182934, 0.03352134435165348, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0009817891151734206, nan, 0.0, 0.21321343749533214, 0.0015662701604368624, 0.10584305896805897, nan, 0.003968376042083244, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.022992942214380238, nan, nan, nan, nan, nan, 0.0023381294964028776, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 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, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan]
3.8325 4.0 80 3.0598 0.0703 0.1291 0.5303 [0.49650156001206236, 0.5922758347907352, 0.9196581248225065, 0.28986056306151164, 0.37242664182580343, 0.13962191464186455, 0.44777031972436937, 0.010011396257988199, 0.02876453488372093, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.06673494752347633, 0.0032136665398114087, 0.06902320168739545, nan, 0.003568242640499554, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.006893692012647074, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 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, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] [0.8066589776095929, 0.9814613113310907, 0.9635569989680867, 0.9851068217667813, 0.5101181514277694, 0.2719549778909286, 0.8157721422241013, 0.012526510536528136, 0.028842930639966187, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.08662075970543863, 0.0032172035727892306, 0.07286547911547911, nan, 0.0035684621773771803, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.007333480370533745, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 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, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan]
3.4347 5.0 100 3.0505 0.0783 0.1363 0.5439 [0.4962000928454516, 0.7129415785863313, 0.9071521170966718, 0.2986780568155731, 0.48462510905756456, 0.10866613172026418, 0.41739471919234705, 0.015329389179506577, 0.015745748213017066, nan, 0.007342991980462691, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.07925797305316834, 0.003484175168471344, 0.20060581457077725, nan, 0.006603396910224516, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.004777315456927107, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 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, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] [0.8680500614806836, 0.9650495917954254, 0.9679442133718243, 0.9934898083172158, 0.6945670758159593, 0.18871767385769797, 0.7691338249762174, 0.019385406795722215, 0.01582790433299812, nan, 0.007363039197842381, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.10772700793164743, 0.0035346907674723787, 0.24662162162162163, nan, 0.00661396007013874, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0051279223643581825, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 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, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan]
3.1703 6.0 120 2.8807 0.0807 0.1372 0.5418 [0.5227936279061995, 0.7150097640588297, 0.8485212658682469, 0.2903245162095936, 0.45022208483152465, 0.12095896035273747, 0.4099720249623413, 0.04653035346330639, 0.05287725078759502, nan, 0.004035246644157128, 0.0, 0.0, nan, 0.0, 0.0005315923683270622, nan, 0.007720020586721565, 0.06069358364923682, 0.004777919041955461, 0.1673501903047827, nan, 3.069367710251688e-05, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.011388721653622315, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 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, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] [0.8349648749892766, 0.9740586876407671, 0.9721984818845396, 0.9978540892141508, 0.7061525505907571, 0.1815891732547233, 0.7745164201676573, 0.06623347321871757, 0.05332808651421742, nan, 0.004053808097688502, 0.0, 0.0, nan, 0.0, 0.0005560575519566275, nan, 0.00776940408670655, 0.09039986855273574, 0.004931634424078229, 0.21775184275184276, nan, 3.076260497738949e-05, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.012516541685046317, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 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, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan]
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2.0758 49.0 980 2.0553 0.1149 0.1916 0.5900 [0.5368149758251105, 0.7183445953198158, 0.88245854833759, 0.4815842442634627, 0.5126223353284006, 0.4105781173844001, 0.44517012847569326, 0.36466245442398715, 0.23511730416494608, nan, 0.020494166094715167, 0.01164935327645498, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.09590073705369963, 0.13460368943847556, 0.32060876145631884, nan, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 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, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] [0.8036735899953293, 0.9676456507979347, 0.9646490545014845, 0.8668253340096204, 0.8327251384387679, 0.6998258073160927, 0.9776158843473807, 0.7266098100266234, 0.3568274233745792, nan, 0.02470341016264871, 0.011713328547499402, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.11972157079480783, 0.1545950979977141, 0.7319179975429976, nan, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 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, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan]
1.4412 50.0 1000 2.0485 0.1143 0.1916 0.5885 [0.5389197200177074, 0.717547165311136, 0.8775832004926136, 0.4666962362569759, 0.5127754280916853, 0.4086772583394205, 0.43686948440659384, 0.3713747236760066, 0.23987614869378396, nan, 0.02093962295037241, 0.008571053917770334, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.07904494450320337, 0.14534279304747488, 0.31956492502185463, nan, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 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, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] [0.8006767641143445, 0.966601443897173, 0.9654087453073266, 0.8562518463193449, 0.8260647663766045, 0.7196837732815222, 0.9784940116595793, 0.7095618428771265, 0.3872881232419512, nan, 0.025398348693681023, 0.008602536491983729, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.0971216036566239, 0.16867036362866697, 0.7297681203931204, nan, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 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, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan]

Framework versions

  • Transformers 4.26.1
  • Pytorch 1.11.0
  • Datasets 2.9.0
  • Tokenizers 0.12.1