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metadata
license: other
base_model: nvidia/mit-b0
tags:
  - vision
  - image-segmentation
  - generated_from_trainer
model-index:
  - name: segformer-b0-finetuned-segments-sidewalk-oct-22
    results: []

segformer-b0-finetuned-segments-sidewalk-oct-22

This model is a fine-tuned version of nvidia/mit-b0 on the segments/sidewalk-semantic dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8205
  • Mean Iou: 0.1912
  • Mean Accuracy: 0.2374
  • Overall Accuracy: 0.7870
  • Accuracy Unlabeled: nan
  • Accuracy Flat-road: 0.8060
  • Accuracy Flat-sidewalk: 0.9462
  • Accuracy Flat-crosswalk: 0.0
  • Accuracy Flat-cyclinglane: 0.5762
  • Accuracy Flat-parkingdriveway: 0.2892
  • Accuracy Flat-railtrack: nan
  • Accuracy Flat-curb: 0.1372
  • Accuracy Human-person: 0.0
  • Accuracy Human-rider: 0.0
  • Accuracy Vehicle-car: 0.9165
  • Accuracy Vehicle-truck: 0.0
  • Accuracy Vehicle-bus: 0.0
  • Accuracy Vehicle-tramtrain: 0.0
  • Accuracy Vehicle-motorcycle: 0.0
  • Accuracy Vehicle-bicycle: 0.0
  • Accuracy Vehicle-caravan: 0.0
  • Accuracy Vehicle-cartrailer: 0.0
  • Accuracy Construction-building: 0.8735
  • Accuracy Construction-door: 0.0
  • Accuracy Construction-wall: 0.2350
  • Accuracy Construction-fenceguardrail: 0.0103
  • Accuracy Construction-bridge: 0.0
  • Accuracy Construction-tunnel: nan
  • Accuracy Construction-stairs: 0.0
  • Accuracy Object-pole: 0.0207
  • Accuracy Object-trafficsign: 0.0
  • Accuracy Object-trafficlight: 0.0
  • Accuracy Nature-vegetation: 0.9298
  • Accuracy Nature-terrain: 0.8976
  • Accuracy Sky: 0.9572
  • Accuracy Void-ground: 0.0
  • Accuracy Void-dynamic: 0.0
  • Accuracy Void-static: 0.0007
  • Accuracy Void-unclear: 0.0
  • Iou Unlabeled: nan
  • Iou Flat-road: 0.5959
  • Iou Flat-sidewalk: 0.8090
  • Iou Flat-crosswalk: 0.0
  • Iou Flat-cyclinglane: 0.5222
  • Iou Flat-parkingdriveway: 0.2225
  • Iou Flat-railtrack: nan
  • Iou Flat-curb: 0.1299
  • Iou Human-person: 0.0
  • Iou Human-rider: 0.0
  • Iou Vehicle-car: 0.6616
  • Iou Vehicle-truck: 0.0
  • Iou Vehicle-bus: 0.0
  • Iou Vehicle-tramtrain: 0.0
  • Iou Vehicle-motorcycle: 0.0
  • Iou Vehicle-bicycle: 0.0
  • Iou Vehicle-caravan: 0.0
  • Iou Vehicle-cartrailer: 0.0
  • Iou Construction-building: 0.5911
  • Iou Construction-door: 0.0
  • Iou Construction-wall: 0.2088
  • Iou Construction-fenceguardrail: 0.0103
  • Iou Construction-bridge: 0.0
  • Iou Construction-tunnel: nan
  • Iou Construction-stairs: 0.0
  • Iou Object-pole: 0.0206
  • Iou Object-trafficsign: 0.0
  • Iou Object-trafficlight: 0.0
  • Iou Nature-vegetation: 0.7950
  • Iou Nature-terrain: 0.6650
  • Iou Sky: 0.8853
  • Iou Void-ground: 0.0
  • Iou Void-dynamic: 0.0
  • Iou Void-static: 0.0006
  • Iou Void-unclear: 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: 3

Training results

Training Loss Epoch Step Validation Loss Mean Iou Mean Accuracy Overall Accuracy Accuracy Unlabeled Accuracy Flat-road Accuracy Flat-sidewalk Accuracy Flat-crosswalk Accuracy Flat-cyclinglane Accuracy Flat-parkingdriveway Accuracy Flat-railtrack Accuracy Flat-curb Accuracy Human-person Accuracy Human-rider Accuracy Vehicle-car Accuracy Vehicle-truck Accuracy Vehicle-bus Accuracy Vehicle-tramtrain Accuracy Vehicle-motorcycle Accuracy Vehicle-bicycle Accuracy Vehicle-caravan Accuracy Vehicle-cartrailer Accuracy Construction-building Accuracy Construction-door Accuracy Construction-wall Accuracy Construction-fenceguardrail Accuracy Construction-bridge Accuracy Construction-tunnel Accuracy Construction-stairs Accuracy Object-pole Accuracy Object-trafficsign Accuracy Object-trafficlight Accuracy Nature-vegetation Accuracy Nature-terrain Accuracy Sky Accuracy Void-ground Accuracy Void-dynamic Accuracy Void-static Accuracy Void-unclear Iou Unlabeled Iou Flat-road Iou Flat-sidewalk Iou Flat-crosswalk Iou Flat-cyclinglane Iou Flat-parkingdriveway Iou Flat-railtrack Iou Flat-curb Iou Human-person Iou Human-rider Iou Vehicle-car Iou Vehicle-truck Iou Vehicle-bus Iou Vehicle-tramtrain Iou Vehicle-motorcycle Iou Vehicle-bicycle Iou Vehicle-caravan Iou Vehicle-cartrailer Iou Construction-building Iou Construction-door Iou Construction-wall Iou Construction-fenceguardrail Iou Construction-bridge Iou Construction-tunnel Iou Construction-stairs Iou Object-pole Iou Object-trafficsign Iou Object-trafficlight Iou Nature-vegetation Iou Nature-terrain Iou Sky Iou Void-ground Iou Void-dynamic Iou Void-static Iou Void-unclear
3.0344 0.05 20 3.2785 0.0660 0.1145 0.5080 nan 0.0286 0.8074 0.0003 0.0514 0.0021 nan 0.0 0.0151 0.0 0.7902 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.3593 0.0 0.0058 0.0013 0.0 nan 0.0 0.0059 0.0 0.0 0.9358 0.1013 0.3657 0.0009 0.0023 0.1913 0.0 0.0 0.0266 0.5726 0.0003 0.0380 0.0021 0.0 0.0 0.0062 0.0 0.4125 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2842 0.0 0.0054 0.0012 0.0 0.0 0.0 0.0022 0.0 0.0 0.5146 0.0706 0.3331 0.0009 0.0008 0.0389 0.0
2.613 0.1 40 2.4625 0.0703 0.1172 0.5601 nan 0.2214 0.8690 0.0001 0.0012 0.0007 nan 0.0 0.0 0.0 0.8179 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5076 0.0 0.0000 0.0007 0.0 nan 0.0 0.0163 0.0 0.0 0.9858 0.0895 0.2402 0.0 0.0 0.0012 0.0 nan 0.1743 0.6050 0.0001 0.0012 0.0007 nan 0.0 0.0 0.0 0.3520 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.3723 0.0 0.0000 0.0007 0.0 0.0 0.0 0.0086 0.0 0.0 0.5042 0.0595 0.2388 0.0 0.0 0.0011 0.0
2.0538 0.15 60 2.1700 0.1015 0.1462 0.6281 nan 0.4778 0.8740 0.0 0.0004 0.0001 nan 0.0 0.0 0.0 0.8473 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7761 0.0 0.0 0.0 0.0 nan 0.0 0.0019 0.0 0.0 0.9629 0.1345 0.6048 0.0 0.0 0.0 0.0 nan 0.3109 0.6422 0.0 0.0004 0.0001 nan 0.0 0.0 0.0 0.5365 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4576 0.0 0.0 0.0 0.0 nan 0.0 0.0017 0.0 0.0 0.6049 0.0972 0.5971 0.0 0.0 0.0 0.0
2.2012 0.2 80 1.8887 0.1185 0.1661 0.6687 nan 0.6100 0.8959 0.0 0.0002 0.0005 nan 0.0 0.0 0.0 0.9058 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7497 0.0 0.0000 0.0 0.0 nan 0.0 0.0003 0.0 0.0 0.9552 0.3603 0.8387 0.0 0.0 0.0000 0.0 nan 0.3640 0.6910 0.0 0.0002 0.0005 nan 0.0 0.0 0.0 0.4923 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4872 0.0 0.0000 0.0 0.0 nan 0.0 0.0003 0.0 0.0 0.6719 0.2920 0.7928 0.0 0.0 0.0000 0.0
1.8908 0.25 100 1.7540 0.1288 0.1744 0.6843 nan 0.6032 0.9146 0.0 0.0004 0.0 nan 0.0 0.0 0.0 0.8872 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8525 0.0 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.9141 0.5837 0.8237 0.0 0.0 0.0 0.0 nan 0.3655 0.6936 0.0 0.0004 0.0 nan 0.0 0.0 0.0 0.5745 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4759 0.0 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7370 0.4760 0.7981 0.0 0.0 0.0 0.0
1.6295 0.3 120 1.6573 0.1321 0.1797 0.6886 nan 0.6838 0.8819 0.0 0.0002 0.0002 nan 0.0 0.0 0.0 0.8767 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8359 0.0 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.9300 0.6555 0.8848 0.0 0.0 0.0 0.0 nan 0.3759 0.7034 0.0 0.0002 0.0002 nan 0.0 0.0 0.0 0.5728 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4867 0.0 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7394 0.5249 0.8232 0.0 0.0 0.0 0.0
1.4891 0.35 140 1.5579 0.1310 0.1783 0.6944 nan 0.7201 0.8884 0.0 0.0030 0.0001 nan 0.0 0.0 0.0 0.8757 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8378 0.0 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.9563 0.5210 0.9034 0.0 0.0 0.0 0.0 nan 0.4092 0.7265 0.0 0.0030 0.0001 nan 0.0 0.0 0.0 0.5723 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4981 0.0 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.6989 0.4428 0.8409 0.0 0.0 0.0 0.0
1.5695 0.4 160 1.4544 0.1396 0.1878 0.7096 nan 0.6025 0.9527 0.0 0.0975 0.0000 nan 0.0 0.0 0.0 0.9111 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8360 0.0 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8770 0.8080 0.9245 0.0 0.0 0.0 0.0 nan 0.4255 0.7027 0.0 0.0970 0.0000 nan 0.0 0.0 0.0 0.5630 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5198 0.0 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7464 0.5716 0.8424 0.0 0.0 0.0 0.0
1.6222 0.45 180 1.3876 0.1429 0.1881 0.7135 nan 0.7565 0.8988 0.0 0.1457 0.0000 nan 0.0 0.0 0.0 0.8611 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8042 0.0 0.0 0.0 0.0 nan 0.0 0.0000 0.0 0.0 0.9584 0.6861 0.9093 0.0 0.0 0.0 0.0 nan 0.4343 0.7345 0.0 0.1445 0.0000 nan 0.0 0.0 0.0 0.6140 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5214 0.0 0.0 0.0 0.0 nan 0.0 0.0000 0.0 0.0 0.7063 0.5765 0.8421 0.0 0.0 0.0 0.0
1.5213 0.5 200 1.3347 0.1437 0.1912 0.7175 nan 0.7966 0.8948 0.0 0.1280 0.0001 nan 0.0 0.0 0.0 0.8899 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7904 0.0 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.9511 0.7569 0.9111 0.0 0.0 0.0 0.0 nan 0.4368 0.7480 0.0 0.1273 0.0001 nan 0.0 0.0 0.0 0.5884 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5327 0.0 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7227 0.5942 0.8483 0.0 0.0 0.0 0.0
1.5815 0.55 220 1.2830 0.1478 0.1933 0.7305 nan 0.6904 0.9574 0.0 0.1857 0.0002 nan 0.0 0.0 0.0 0.9084 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8306 0.0 0.0 0.0 0.0 nan 0.0 0.0000 0.0 0.0 0.9229 0.7662 0.9246 0.0 0.0 0.0 0.0 nan 0.4913 0.7311 0.0 0.1835 0.0002 nan 0.0 0.0 0.0 0.5616 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5288 0.0 0.0 0.0 0.0 nan 0.0 0.0000 0.0 0.0 0.7565 0.6257 0.8514 0.0 0.0 0.0 0.0
1.3495 0.6 240 1.2556 0.1542 0.2016 0.7401 nan 0.7581 0.9240 0.0 0.3392 0.0003 nan 0.0 0.0 0.0 0.8641 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8703 0.0 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.9260 0.8520 0.9166 0.0 0.0 0.0 0.0 nan 0.5103 0.7582 0.0 0.3288 0.0003 nan 0.0 0.0 0.0 0.5999 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5142 0.0 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7489 0.6277 0.8476 0.0 0.0 0.0 0.0
1.4165 0.65 260 1.2116 0.1564 0.2051 0.7459 nan 0.7789 0.9279 0.0 0.3985 0.0033 nan 0.0 0.0 0.0 0.9057 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8510 0.0 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.9161 0.8591 0.9229 0.0 0.0 0.0 0.0 nan 0.5211 0.7700 0.0 0.3795 0.0033 nan 0.0 0.0 0.0 0.5803 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5283 0.0 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7511 0.6205 0.8517 0.0 0.0 0.0 0.0
1.6014 0.7 280 1.1417 0.1568 0.2001 0.7461 nan 0.7075 0.9589 0.0 0.4195 0.0036 nan 0.0 0.0 0.0 0.8856 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8297 0.0 0.0000 0.0 0.0 nan 0.0 0.0000 0.0 0.0 0.9453 0.7286 0.9236 0.0 0.0 0.0 0.0 nan 0.5315 0.7537 0.0 0.3857 0.0035 nan 0.0 0.0 0.0 0.5986 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5321 0.0 0.0000 0.0 0.0 nan 0.0 0.0000 0.0 0.0 0.7376 0.6149 0.8599 0.0 0.0 0.0 0.0
1.0657 0.75 300 1.1932 0.1491 0.1996 0.7295 nan 0.8205 0.9079 0.0 0.1982 0.0001 nan 0.0 0.0 0.0 0.8932 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8422 0.0 0.0000 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8842 0.8971 0.9425 0.0 0.0 0.0 0.0 nan 0.4513 0.7701 0.0 0.1964 0.0001 nan 0.0 0.0 0.0 0.6328 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5365 0.0 0.0000 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7527 0.5770 0.8536 0.0 0.0 0.0 0.0
1.0489 0.8 320 1.1246 0.1579 0.2052 0.7487 nan 0.7758 0.9321 0.0 0.4135 0.0034 nan 0.0 0.0 0.0 0.9132 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8774 0.0 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.9190 0.7974 0.9346 0.0 0.0 0.0 0.0 nan 0.5130 0.7765 0.0 0.3864 0.0034 nan 0.0 0.0 0.0 0.5971 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5242 0.0 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7665 0.6439 0.8423 0.0 0.0 0.0 0.0
1.5638 0.85 340 1.1140 0.1593 0.2055 0.7523 nan 0.7516 0.9477 0.0 0.4362 0.0104 nan 0.0000 0.0 0.0 0.8985 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8186 0.0 0.0006 0.0 0.0 nan 0.0 0.0000 0.0 0.0 0.9420 0.8408 0.9295 0.0 0.0 0.0000 0.0 nan 0.5424 0.7660 0.0 0.4047 0.0102 nan 0.0000 0.0 0.0 0.6019 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5592 0.0 0.0006 0.0 0.0 nan 0.0 0.0000 0.0 0.0 0.7376 0.6128 0.8628 0.0 0.0 0.0000 0.0
1.1776 0.9 360 1.0707 0.1620 0.2080 0.7556 nan 0.7588 0.9374 0.0 0.5169 0.0077 nan 0.0000 0.0 0.0 0.8884 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8878 0.0 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.9295 0.7984 0.9324 0.0 0.0 0.0 0.0 nan 0.5349 0.7831 0.0 0.4307 0.0076 nan 0.0000 0.0 0.0 0.6297 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5240 0.0 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7673 0.6460 0.8607 0.0 0.0 0.0 0.0
1.2379 0.95 380 1.0703 0.1594 0.2063 0.7513 nan 0.8500 0.9162 0.0 0.3756 0.0084 nan 0.0000 0.0 0.0 0.8808 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8357 0.0 0.0011 0.0 0.0 nan 0.0 0.0000 0.0 0.0 0.9440 0.8566 0.9337 0.0 0.0 0.0 0.0 nan 0.5019 0.7946 0.0 0.3577 0.0082 nan 0.0000 0.0 0.0 0.6323 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5476 0.0 0.0011 0.0 0.0 nan 0.0 0.0000 0.0 0.0 0.7520 0.6421 0.8617 0.0 0.0 0.0 0.0
1.2458 1.0 400 1.0662 0.1615 0.2087 0.7558 nan 0.7929 0.9473 0.0 0.4294 0.0103 nan 0.0 0.0 0.0 0.9013 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8872 0.0 0.0043 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8873 0.8934 0.9253 0.0 0.0 0.0 0.0 nan 0.5344 0.7801 0.0 0.4025 0.0101 nan 0.0 0.0 0.0 0.6306 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5374 0.0 0.0043 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7776 0.6274 0.8639 0.0 0.0 0.0 0.0
1.1771 1.05 420 1.0356 0.1603 0.2083 0.7534 nan 0.7536 0.9561 0.0 0.4531 0.0177 nan 0.0 0.0 0.0 0.8970 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8564 0.0 0.0080 0.0 0.0 nan 0.0 0.0002 0.0 0.0 0.8820 0.8957 0.9467 0.0 0.0 0.0 0.0 nan 0.5444 0.7694 0.0 0.4170 0.0173 nan 0.0 0.0 0.0 0.6175 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5506 0.0 0.0080 0.0 0.0 nan 0.0 0.0002 0.0 0.0 0.7505 0.5961 0.8599 0.0 0.0 0.0 0.0
1.6228 1.1 440 1.0142 0.1621 0.2080 0.7567 nan 0.7339 0.9441 0.0 0.5419 0.0236 nan 0.0000 0.0 0.0 0.8966 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8471 0.0 0.0008 0.0 0.0 nan 0.0 0.0002 0.0 0.0 0.9528 0.7766 0.9374 0.0 0.0 0.0 0.0 nan 0.5463 0.7793 0.0 0.4414 0.0228 nan 0.0000 0.0 0.0 0.5976 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5471 0.0 0.0008 0.0 0.0 nan 0.0 0.0002 0.0 0.0 0.7484 0.6349 0.8673 0.0 0.0 0.0 0.0
1.0048 1.15 460 1.0068 0.1639 0.2111 0.7569 nan 0.8128 0.9349 0.0 0.4943 0.0336 nan 0.0 0.0 0.0 0.8689 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8799 0.0 0.0182 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8916 0.8868 0.9328 0.0 0.0 0.0 0.0 nan 0.5359 0.7881 0.0 0.4307 0.0320 nan 0.0 0.0 0.0 0.6679 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5443 0.0 0.0182 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7584 0.6021 0.8680 0.0 0.0 0.0 0.0
1.2324 1.2 480 0.9910 0.1654 0.2122 0.7616 nan 0.7681 0.9474 0.0 0.5180 0.0362 nan 0.0 0.0 0.0 0.9269 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8841 0.0 0.0166 0.0 0.0 nan 0.0 0.0002 0.0 0.0 0.9114 0.8465 0.9359 0.0 0.0 0.0 0.0 nan 0.5440 0.7851 0.0 0.4523 0.0342 nan 0.0 0.0 0.0 0.6220 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5470 0.0 0.0166 0.0 0.0 nan 0.0 0.0002 0.0 0.0 0.7809 0.6369 0.8732 0.0 0.0 0.0 0.0
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0.5214 2.9 1160 0.8243 0.1915 0.2361 0.7869 nan 0.8016 0.9534 0.0 0.5681 0.2683 nan 0.1163 0.0 0.0 0.8982 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8968 0.0 0.2615 0.0054 0.0 nan 0.0 0.0179 0.0 0.0 0.9167 0.8951 0.9558 0.0 0.0 0.0004 0.0 nan 0.5963 0.8027 0.0 0.5200 0.2119 nan 0.1114 0.0 0.0 0.6924 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5836 0.0 0.2227 0.0054 0.0 nan 0.0 0.0179 0.0 0.0 0.8057 0.6715 0.8857 0.0 0.0 0.0004 0.0
0.5897 2.95 1180 0.8193 0.1911 0.2378 0.7867 nan 0.8184 0.9417 0.0 0.5589 0.3065 nan 0.1409 0.0 0.0 0.9231 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8825 0.0 0.2340 0.0084 0.0 nan 0.0 0.0179 0.0 0.0 0.9257 0.8956 0.9565 0.0 0.0 0.0003 0.0 nan 0.5919 0.8119 0.0 0.5141 0.2286 nan 0.1330 0.0 0.0 0.6552 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5886 0.0 0.2069 0.0084 0.0 nan 0.0 0.0179 0.0 0.0 0.8010 0.6718 0.8861 0.0 0.0 0.0003 0.0
1.1597 3.0 1200 0.8205 0.1912 0.2374 0.7870 nan 0.8060 0.9462 0.0 0.5762 0.2892 nan 0.1372 0.0 0.0 0.9165 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8735 0.0 0.2350 0.0103 0.0 nan 0.0 0.0207 0.0 0.0 0.9298 0.8976 0.9572 0.0 0.0 0.0007 0.0 nan 0.5959 0.8090 0.0 0.5222 0.2225 nan 0.1299 0.0 0.0 0.6616 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5911 0.0 0.2088 0.0103 0.0 nan 0.0 0.0206 0.0 0.0 0.7950 0.6650 0.8853 0.0 0.0 0.0006 0.0

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.1+cpu
  • Datasets 2.19.2
  • Tokenizers 0.19.1