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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: 2.4844
  • Mean Iou: 0.0977
  • Mean Accuracy: 0.1574
  • Overall Accuracy: 0.4990
  • Per Category Iou: [0.013201109658493033, 0.5037632108956074, 0.6119445994249033, 0.6806858295511851, 0.3765853085706027, 0.45575549730308584, 0.6364137027692811, 0.1574933003504432, 0.4121863049244307, 0.3146005409953228, 0.20593809222994314, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.46804568654035905, 0.0002093002093002093, 0.3404269878198987, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, 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, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 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, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0]
  • Per Category Accuracy: [0.027324528274213302, 0.8933653157848469, 0.9547663384521198, 0.9233189684656953, 0.8688615984202327, 0.5284644508604469, 0.7424679181065171, 0.4441860465116279, 0.787299525355983, 0.603669756622574, 0.3621739323645736, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.5460410265753493, 0.00021437026404824263, 0.34414775871610404, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, 0.0, 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, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 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, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 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: 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
4.1947 1.0 20 4.1571 0.0475 0.0912 0.3658 [0.016031748582078762, 0.44894856624040225, 0.496627586040411, 0.5642433877727996, 0.32883137889203395, 0.014150448709305288, 0.28518174130002144, 2.4000384006144097e-05, 0.36857579990687156, 0.10543007674542776, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.018592562974810076, nan, 0.017048724818894512, 0.08022913397674268, 0.0, 0.010765302601614795, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 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, 0.0, 0.0, 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, nan, nan, nan, nan, nan, 0.0] [0.03658670734300863, 0.7476710161126251, 0.9839644660986684, 0.7121326128098137, 0.8262203858758799, 0.014390297785463437, 0.29425043846701515, 0.0005813953488372093, 0.5536647514364227, 0.2845016144151651, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.01954294720252167, nan, 0.04441112604694447, 0.12364286838204239, 0.0, 0.01079136690647482, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, 0.0, 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, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 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, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0]
3.6022 2.0 40 3.8145 0.0629 0.1095 0.4057 [0.032837181044957475, 0.48207852713983856, 0.6315494007966522, 0.582020987524583, 0.33552038837009635, 0.3353030452073467, 0.3401478108785151, 0.0, 0.39186191144700566, 0.19844384265019677, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.030304513854890826, 0.034203420342034205, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, 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, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 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, 0.0, 0.0, nan, 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, nan, nan, nan, nan, nan, 0.0] [0.08720235257881652, 0.8389390533361799, 0.9398308759757156, 0.8839865927902045, 0.8246364503170476, 0.36353594527268435, 0.3554534877663362, 0.0, 0.5383162628028978, 0.6118633475679617, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.09600868576155516, 0.04437230333496203, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, 0.0, 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, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 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, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0]
3.8734 3.0 60 3.4631 0.0599 0.1028 0.4060 [0.06399190629590278, 0.49081291597640014, 0.4376804585399634, 0.6297402857524369, 0.40035502929841643, 0.03470009305998139, 0.46282257809785526, 0.001023682820814884, 0.43893988257669725, 0.17272938804002172, 0.004941718743074946, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0034395973154362418, 0.03242621846074564, 0.0, 0.0035971223021582736, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, 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, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 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, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0] [0.11086014329610372, 0.8483253167895312, 0.9753998520483649, 0.8602731604988941, 0.8589984733778989, 0.03749552445741188, 0.5088822129994617, 0.07325581395348837, 0.5304121908568573, 0.38659167447835296, 0.004954894902901835, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.00423947885430669, 0.0406456261231791, 0.0, 0.0035971223021582736, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, 0.0, 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, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 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, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0]
3.4047 4.0 80 3.3117 0.0692 0.1208 0.4390 [0.07479336397530231, 0.4232768463957199, 0.6344493427229061, 0.644169745192763, 0.3483714092287478, 0.5174867391097907, 0.2851821388462694, 0.0004698202319428303, 0.33923699527100765, 0.24902234272753343, 0.10133147054465401, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.022242947764232156, 0.0, 0.02838789888106092, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, 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, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 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, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0] [0.11121948357668249, 0.915272457834654, 0.9632193510535176, 0.9303645940214789, 0.9062299728542623, 0.5811806290898841, 0.31308281382951014, 0.022093023255813953, 0.5963927054708968, 0.6632468840051383, 0.10636359596498245, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.02488592226979487, 0.0, 0.028431101272827893, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, 0.0, 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, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 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, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0]
3.0309 5.0 100 3.2265 0.0816 0.1315 0.4761 [0.08181274761937861, 0.5319411154070397, 0.6453149044879072, 0.7124546299381038, 0.30875810153929245, 0.6322967418283058, 0.6132020405552358, 0.0, 0.32853596247570793, 0.2647553364302203, 0.07213979558193208, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.04768314508730505, 0.0, 0.0023519645821804096, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, 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, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 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, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0] [0.21579483870021487, 0.8456051339369812, 0.9480192337125657, 0.9264655585197346, 0.9531384328416533, 0.7335699974860782, 0.6658577456717661, 0.0, 0.6453060204846365, 0.6450716939207721, 0.07292361018530863, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.052513022666478955, 0.0, 0.0023519645821804096, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, 0.0, 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, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 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, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0]
3.4515 6.0 120 3.1185 0.0760 0.1278 0.4653 [0.056320025915310455, 0.48714167715326323, 0.6265857752363827, 0.69506323534398, 0.32534859563273016, 0.5995281862339057, 0.4769354205914684, 0.00037910379862006216, 0.2765722921018712, 0.30957976437119267, 0.06031184341479597, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.03705568119491799, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, 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, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 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, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0] [0.11729893444606596, 0.8828663644241275, 0.9510771134125809, 0.9348336639533028, 0.9252788820749556, 0.6892183226809071, 0.5857919322069217, 0.014534883720930232, 0.6217936547589308, 0.6951706419470194, 0.060591921077189706, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.04084438224114086, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, 0.0, 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, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 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, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0]
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1.1171 49.0 980 2.4953 0.0950 0.1605 0.5005 [0.01272703871109395, 0.5006422951346143, 0.6190401059582852, 0.6749110789092346, 0.37272357931146255, 0.4636030426043432, 0.6291207285298213, 0.11258597803789067, 0.4068444012570294, 0.3059591192327718, 0.20120135406856882, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.474866179874313, 0.00043247529034408816, 0.3567567567567568, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, 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, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 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, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0] [0.0246551433327711, 0.8927449232044407, 0.9508156471608591, 0.9345372460496614, 0.8747440433081328, 0.537659310271275, 0.7473778804244013, 0.5424418604651163, 0.7865400949288034, 0.6324514807485332, 0.35128649513398214, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.5488070492169838, 0.0004473814206224194, 0.36068068622025456, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, 0.0, 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, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 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, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0]
1.3742 50.0 1000 2.4844 0.0977 0.1574 0.4990 [0.013201109658493033, 0.5037632108956074, 0.6119445994249033, 0.6806858295511851, 0.3765853085706027, 0.45575549730308584, 0.6364137027692811, 0.1574933003504432, 0.4121863049244307, 0.3146005409953228, 0.20593809222994314, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.46804568654035905, 0.0002093002093002093, 0.3404269878198987, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, 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, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 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, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0] [0.027324528274213302, 0.8933653157848469, 0.9547663384521198, 0.9233189684656953, 0.8688615984202327, 0.5284644508604469, 0.7424679181065171, 0.4441860465116279, 0.787299525355983, 0.603669756622574, 0.3621739323645736, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.5460410265753493, 0.00021437026404824263, 0.34414775871610404, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, 0.0, 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, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 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, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0]

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.0+cu116
  • Datasets 2.7.1
  • Tokenizers 0.13.2