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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: 2.8793
  • Mean Iou: 0.0853
  • Mean Accuracy: 0.1641
  • Overall Accuracy: 0.4819
  • Per Category Iou: [0.4317989411680538, 0.6127684780127228, 0.8395740912649352, 0.2848933793985543, 0.44958329517355067, 0.09829267138361059, 0.46117888090450854, 0.0, 0.014580237741456167, 0.3008435962194392, 0.0, 0.0, 0.019724431432322713, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.1541033434650456, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 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, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 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, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]
  • Per Category Accuracy: [0.9158289392157607, 0.6849953787366707, 0.8479535448414122, 0.5054130130620156, 0.9837511063609492, 0.629475279408979, 0.7025265725736191, nan, 0.014580237741456167, 0.8992295320120369, 0.0, 0.0, 0.020591108170274444, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.36142001710863986, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 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, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 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, nan, 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
4.9494 1.0 20 4.9402 0.0105 0.0409 0.1070 [0.019316150089396068, 0.22597135209859112, 0.3251175481165965, 0.020768590455049946, 0.2322911051212938, 0.017061670182404766, 0.20379071599342188, 0.0, 0.0, 0.09314392277314612, 0.0, 0.0, 0.0002551631884573452, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.00026726057906458796, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.03840301474349428, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0058213952916841595, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, 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, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0, nan] [0.02035519643918415, 0.264957029148446, 0.4000276518801118, 0.024757960751107245, 0.2878375444631853, 0.03125591968175791, 0.22840216065516641, nan, 0.0, 0.1101354155857632, 0.0, 0.0, 0.00025994895547783343, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.000427715996578272, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.03988031199569661, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.22858866103739445, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 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, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 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, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]
4.4612 2.0 40 4.6969 0.0266 0.1218 0.3294 [0.34216766546921495, 0.42585209858826995, 0.6403746189940177, 0.1024496819576244, 0.2974973307469995, 0.16287507919138397, 0.27474553518326567, 0.0, 0.0, 0.24339640047267408, 0.0, 0.0, 0.11371477345268578, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0008258396035969903, nan, 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, 0.007088276694148401, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, 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, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan] [0.5191033471163208, 0.6181525982535763, 0.8750523873509931, 0.1278053233750211, 0.8887460129256358, 0.5357075203637053, 0.37564035546262414, nan, 0.0, 0.7186754176610979, 0.0, 0.0, 0.12488578000441125, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0012831479897348161, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0850422195416164, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 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, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 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, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]
4.3912 3.0 60 4.3825 0.0422 0.1351 0.4265 [0.40149317998722117, 0.5048064005731857, 0.8592410472929486, 0.21444215960889565, 0.2567525011506504, 0.16000235557387668, 0.364405007148567, 0.0, 0.0, 0.24131094005131795, 0.0, 0.0, 0.16137940079272559, 0.0, nan, 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, 0.0, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0035188077451404703, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan] [0.913758329855974, 0.6997903187981956, 0.8652143668799606, 0.3390699474410159, 0.8850052604331925, 0.5146808107596136, 0.4924783644072719, nan, 0.0, 0.48306008093805125, 0.0, 0.0, 0.17447301257207676, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.037595496582227585, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 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, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 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, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]
3.7297 4.0 80 4.2364 0.0494 0.1441 0.4187 [0.4178153253297762, 0.3992706203914134, 0.875503295623462, 0.21609721156678022, 0.24611598608609758, 0.12711537027875108, 0.24177242477171726, 0.0, 0.0, 0.3477315189202755, 0.0, 0.0, 0.09290263328264503, 0.0, nan, 0.0, nan, 0.0, 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, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, 0.0015500713848664084, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, 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, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan] [0.810948623597992, 0.723427735856865, 0.9084809180424197, 0.3931703089700887, 0.965347940081161, 0.7105891267285471, 0.33873884339122184, nan, 0.0, 0.808731970530248, 0.0, 0.0, 0.09721303210763463, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.007639726578206675, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 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, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 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, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]
4.2485 5.0 100 4.0703 0.0582 0.1432 0.4201 [0.40563896949448436, 0.5564846499937436, 0.8781875640514384, 0.22651747451650744, 0.2522927138367742, 0.12171385877823929, 0.15290364109596707, 0.0, 0.0, 0.35980873654474, 0.0, 0.0, 0.016112608565438755, 0.0, nan, 0.0, nan, 0.0, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 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, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 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, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan] [0.9284422695143077, 0.7055220648080451, 0.8848731253969557, 0.4400632427801685, 0.9840684023312903, 0.7282818715665845, 0.2115505992139552, nan, 0.0, 0.8276823700321677, 0.0, 0.0, 0.016951822793584776, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 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, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 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, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]
3.5922 6.0 120 3.8704 0.0609 0.1449 0.4258 [0.3978909784800342, 0.4996328220380213, 0.8284300695403136, 0.2404360919027437, 0.26860529846047143, 0.11806087443441099, 0.18067079783554835, 0.0, 0.0, 0.37611450281096276, 0.0, 0.0, 0.01149608450191222, 0.0, nan, 0.0, nan, 0.0, 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, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 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, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan] [0.9307468103132153, 0.7508449324743761, 0.8348621078509737, 0.4563535509564147, 0.9830664150565288, 0.6949422239060428, 0.24577258910766492, nan, 0.0, 0.8885934419425132, 0.0, 0.0, 0.011934020228755081, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 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, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 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, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]
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1.2278 48.0 960 2.8481 0.0854 0.1626 0.4926 [0.44501170615707086, 0.6019321901971109, 0.888336992901149, 0.2912264711930154, 0.45576681697736043, 0.1096861917200415, 0.4475901739781579, 0.0, 0.02349554234769688, 0.30162976108146194, 0.0, 0.0, 0.022346028092585114, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0864600326264274, nan, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 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, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 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, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan] [0.9181366412503319, 0.7254141893476431, 0.9002199188590143, 0.5199965600161415, 0.9823483241762829, 0.580678158742186, 0.7128651913806122, nan, 0.02349554234769688, 0.8995019196845492, 0.0, 0.0, 0.023096070832151747, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.21913316224693472, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 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, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 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, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]
1.2502 49.0 980 2.8952 0.0855 0.1610 0.4832 [0.4127476233376052, 0.6135788067622047, 0.8156754998630512, 0.2931328400543053, 0.45637344854552353, 0.09138291754860338, 0.5121103857532373, 0.0, 0.005850668647845468, 0.3008252904918938, 0.0, 0.0, 0.024220305242203054, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.1506468110709988, nan, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 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, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 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, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan] [0.9254801916973306, 0.700197265867487, 0.8234816309424539, 0.5363464063745547, 0.9843188991499808, 0.5659405190376965, 0.684354610752938, nan, 0.005850668647845468, 0.9039898308602262, 0.0, 0.0, 0.02530169833317579, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.2855717137154263, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 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, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 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, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]
1.0421 50.0 1000 2.8793 0.0853 0.1641 0.4819 [0.4317989411680538, 0.6127684780127228, 0.8395740912649352, 0.2848933793985543, 0.44958329517355067, 0.09829267138361059, 0.46117888090450854, 0.0, 0.014580237741456167, 0.3008435962194392, 0.0, 0.0, 0.019724431432322713, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.1541033434650456, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 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, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 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, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan] [0.9158289392157607, 0.6849953787366707, 0.8479535448414122, 0.5054130130620156, 0.9837511063609492, 0.629475279408979, 0.7025265725736191, nan, 0.014580237741456167, 0.8992295320120369, 0.0, 0.0, 0.020591108170274444, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.36142001710863986, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 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, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 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, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]

Framework versions

  • Transformers 4.31.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.1
  • Tokenizers 0.13.3