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segformer-b0-finetuned-segments-sidewalk-2

Image Segmentation
Transformers
PyTorch
segformer
vision
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segformer-b0-finetuned-segments-sidewalk-2

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: 0.9530
  • Mean Iou: 0.1712
  • Mean Accuracy: 0.2121
  • Overall Accuracy: 0.7831
  • Accuracy Unlabeled: nan
  • Accuracy Flat-road: 0.8549
  • Accuracy Flat-sidewalk: 0.9623
  • Accuracy Flat-crosswalk: 0.0
  • Accuracy Flat-cyclinglane: 0.5957
  • Accuracy Flat-parkingdriveway: 0.0956
  • Accuracy Flat-railtrack: nan
  • Accuracy Flat-curb: 0.0075
  • Accuracy Human-person: 0.0
  • Accuracy Human-rider: 0.0
  • Accuracy Vehicle-car: 0.9053
  • 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: 0.9017
  • Accuracy Construction-door: 0.0
  • Accuracy Construction-wall: 0.0
  • Accuracy Construction-fenceguardrail: 0.0
  • Accuracy Construction-bridge: 0.0
  • Accuracy Construction-tunnel: 0.0
  • Accuracy Construction-stairs: 0.0
  • Accuracy Object-pole: 0.0
  • Accuracy Object-trafficsign: 0.0
  • Accuracy Object-trafficlight: 0.0
  • Accuracy Nature-vegetation: 0.9152
  • Accuracy Nature-terrain: 0.8300
  • Accuracy Sky: 0.9299
  • Accuracy Void-ground: 0.0
  • Accuracy Void-dynamic: 0.0
  • Accuracy Void-static: 0.0
  • Accuracy Void-unclear: 0.0
  • Iou Unlabeled: nan
  • Iou Flat-road: 0.6261
  • Iou Flat-sidewalk: 0.8045
  • Iou Flat-crosswalk: 0.0
  • Iou Flat-cyclinglane: 0.5253
  • Iou Flat-parkingdriveway: 0.0861
  • Iou Flat-railtrack: nan
  • Iou Flat-curb: 0.0075
  • Iou Human-person: 0.0
  • Iou Human-rider: 0.0
  • Iou Vehicle-car: 0.6945
  • 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: 0.5817
  • Iou Construction-door: 0.0
  • Iou Construction-wall: 0.0
  • Iou Construction-fenceguardrail: 0.0
  • Iou Construction-bridge: 0.0
  • Iou Construction-tunnel: 0.0
  • Iou Construction-stairs: 0.0
  • Iou Object-pole: 0.0
  • Iou Object-trafficsign: 0.0
  • Iou Object-trafficlight: 0.0
  • Iou Nature-vegetation: 0.7847
  • Iou Nature-terrain: 0.6656
  • Iou Sky: 0.8751
  • Iou Void-ground: 0.0
  • Iou Void-dynamic: 0.0
  • Iou Void-static: 0.0
  • 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: 4
  • eval_batch_size: 4
  • 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
2.7688 0.1 20 3.0043 0.0900 0.1326 0.6099 nan 0.2649 0.9602 0.0002 0.0001 0.0040 nan 0.0 0.0055 0.0 0.8361 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7673 0.0054 0.0021 0.0007 0.0 0.0 0.0 0.0 0.0 0.0 0.7635 0.0259 0.7359 0.0 0.0036 0.0 0.0 nan 0.2274 0.6135 0.0002 0.0001 0.0039 0.0 0.0 0.0055 0.0 0.5402 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.3692 0.0018 0.0021 0.0007 0.0 0.0 0.0 0.0 0.0 0.0 0.6087 0.0247 0.6591 0.0 0.0020 0.0 0.0
2.2362 0.2 40 2.2122 0.1016 0.1476 0.6596 nan 0.5986 0.9497 0.0000 0.0002 0.0010 nan 0.0 0.0 0.0 0.8828 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7864 0.0 0.0004 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8463 0.0423 0.7626 0.0 0.0 0.0 0.0 nan 0.4075 0.6846 0.0000 0.0002 0.0010 0.0 0.0 0.0 0.0 0.5190 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4231 0.0 0.0004 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.6493 0.0415 0.7290 0.0 0.0 0.0 0.0
1.9229 0.3 60 1.9323 0.1109 0.1552 0.6790 nan 0.7454 0.9277 0.0002 0.0006 0.0012 nan 0.0 0.0 0.0 0.8370 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8759 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8641 0.0240 0.8450 0.0 0.0 0.0 0.0 nan 0.4388 0.7425 0.0002 0.0006 0.0012 nan 0.0 0.0 0.0 0.5825 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4447 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.6474 0.0237 0.7787 0.0 0.0 0.0 0.0
1.8943 0.4 80 1.6697 0.1102 0.1565 0.6866 nan 0.6675 0.9567 0.0 0.0005 0.0029 nan 0.0 0.0 0.0 0.8692 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8957 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8753 0.0270 0.8696 0.0 0.0 0.0 0.0 nan 0.4490 0.7236 0.0 0.0005 0.0029 0.0 0.0 0.0 0.0 0.6018 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4761 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.6626 0.0268 0.8032 0.0 0.0 0.0 0.0
1.9991 0.5 100 1.6000 0.1166 0.1629 0.7001 nan 0.8482 0.9229 0.0 0.0024 0.0013 nan 0.0 0.0000 0.0 0.9172 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8210 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9390 0.0378 0.8872 0.0 0.0 0.0 0.0 nan 0.4629 0.7702 0.0 0.0024 0.0013 nan 0.0 0.0000 0.0 0.5626 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5357 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.6573 0.0375 0.8165 0.0 0.0 0.0 0.0
1.5725 0.6 120 1.5214 0.1250 0.1686 0.7146 nan 0.8401 0.9399 0.0 0.0415 0.0017 nan 0.0000 0.0 0.0 0.8705 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8933 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9241 0.1360 0.9159 0.0 0.0 0.0 0.0 nan 0.4995 0.7742 0.0 0.0413 0.0017 nan 0.0000 0.0 0.0 0.6375 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5282 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.6744 0.1315 0.8355 0.0 0.0 0.0 0.0
1.4764 0.7 140 1.4602 0.1327 0.1750 0.7245 nan 0.8603 0.9330 0.0 0.0371 0.0026 nan 0.0000 0.0 0.0 0.8552 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9104 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9283 0.3764 0.8728 0.0 0.0 0.0 0.0 nan 0.4935 0.7879 0.0 0.0369 0.0026 nan 0.0000 0.0 0.0 0.6449 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5233 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7071 0.3529 0.8309 0.0 0.0 0.0 0.0
1.9994 0.8 160 1.3414 0.1439 0.1867 0.7418 nan 0.8373 0.9468 0.0 0.0849 0.0051 nan 0.0 0.0 0.0 0.8907 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8805 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9226 0.6707 0.9236 0.0 0.0 0.0 0.0 nan 0.5211 0.7762 0.0 0.0842 0.0051 nan 0.0 0.0 0.0 0.6352 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5546 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7427 0.5786 0.8500 0.0 0.0 0.0 0.0
1.2919 0.9 180 1.3036 0.1401 0.1822 0.7365 nan 0.8860 0.9322 0.0 0.0832 0.0067 nan 0.0000 0.0 0.0 0.8551 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8824 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9462 0.5071 0.9144 0.0 0.0 0.0 0.0 nan 0.4969 0.8018 0.0 0.0814 0.0067 nan 0.0000 0.0 0.0 0.6676 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5458 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7185 0.4640 0.8420 0.0 0.0 0.0 0.0
1.2882 1.0 200 1.2697 0.1466 0.1914 0.7471 nan 0.8344 0.9563 0.0 0.1067 0.0068 nan 0.0 0.0 0.0 0.9191 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9000 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8746 0.8138 0.9034 0.0 0.0 0.0 0.0 nan 0.5319 0.7814 0.0 0.1053 0.0068 nan 0.0 0.0 0.0 0.6284 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5583 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7614 0.6179 0.8480 0.0 0.0 0.0 0.0
1.1952 1.1 220 1.2088 0.1497 0.1917 0.7499 nan 0.8263 0.9565 0.0 0.1384 0.0093 nan 0.0 0.0 0.0 0.8891 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8945 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9050 0.7813 0.9251 0.0 0.0 0.0 0.0 nan 0.5518 0.7648 0.0 0.1374 0.0092 nan 0.0 0.0 0.0 0.6640 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5651 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7604 0.6254 0.8607 0.0 0.0 0.0 0.0
1.1901 1.2 240 1.1659 0.1508 0.1941 0.7546 nan 0.8903 0.9465 0.0 0.1520 0.0136 nan 0.0000 0.0 0.0 0.9018 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8951 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9068 0.7657 0.9340 0.0 0.0 0.0 0.0 nan 0.5301 0.8032 0.0 0.1479 0.0135 nan 0.0000 0.0 0.0 0.6624 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5553 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7704 0.6415 0.8526 0.0 0.0 0.0 0.0
1.5003 1.3 260 1.1250 0.1582 0.1977 0.7625 nan 0.8352 0.9605 0.0 0.3475 0.0185 nan 0.0000 0.0006 0.0 0.8674 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8876 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9278 0.7537 0.9255 0.0 0.0 0.0 0.0 nan 0.5715 0.7817 0.0 0.3299 0.0182 nan 0.0000 0.0006 0.0 0.6920 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5613 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7639 0.6390 0.8616 0.0 0.0 0.0 0.0
1.0678 1.4 280 1.1183 0.1595 0.2042 0.7680 nan 0.8673 0.9506 0.0 0.4007 0.0276 nan 0.0000 0.0001 0.0 0.9294 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8812 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9051 0.8502 0.9251 0.0 0.0 0.0 0.0 nan 0.5684 0.8048 0.0 0.3824 0.0270 nan 0.0000 0.0001 0.0 0.6348 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5821 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7698 0.6311 0.8630 0.0 0.0 0.0 0.0
1.0902 1.5 300 1.0917 0.1642 0.2070 0.7718 nan 0.8710 0.9473 0.0 0.5234 0.0382 nan 0.0001 0.0 0.0 0.8855 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9072 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8980 0.8378 0.9211 0.0 0.0 0.0 0.0 nan 0.5662 0.8125 0.0 0.4669 0.0370 nan 0.0001 0.0 0.0 0.6874 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5623 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7753 0.6467 0.8642 0.0 0.0 0.0 0.0
1.0474 1.6 320 1.0803 0.1645 0.2080 0.7736 nan 0.8752 0.9445 0.0 0.5435 0.0427 nan 0.0001 0.0001 0.0 0.9137 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8937 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9148 0.7931 0.9432 0.0 0.0 0.0 0.0 nan 0.5693 0.8150 0.0 0.4817 0.0411 nan 0.0001 0.0001 0.0 0.6565 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5710 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7761 0.6556 0.8619 0.0 0.0 0.0 0.0
1.814 1.7 340 1.0579 0.1655 0.2100 0.7740 nan 0.8714 0.9443 0.0 0.5910 0.0501 nan 0.0002 0.0 0.0 0.9037 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8918 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8947 0.8552 0.9273 0.0 0.0 0.0 0.0 nan 0.5724 0.8148 0.0 0.4928 0.0478 nan 0.0002 0.0 0.0 0.6809 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5749 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7711 0.6423 0.8650 0.0 0.0 0.0 0.0
1.3638 1.8 360 1.0449 0.1641 0.2055 0.7708 nan 0.7817 0.9653 0.0 0.5410 0.0607 nan 0.0010 0.0000 0.0 0.9017 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9009 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9180 0.7825 0.9291 0.0 0.0 0.0 0.0 nan 0.5960 0.7909 0.0 0.4226 0.0572 nan 0.0010 0.0000 0.0 0.6764 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5664 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7769 0.6636 0.8631 0.0 0.0 0.0 0.0
1.2779 1.9 380 1.0227 0.1667 0.2074 0.7745 nan 0.8069 0.9631 0.0 0.5564 0.0757 nan 0.0019 0.0000 0.0 0.8764 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8981 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9214 0.8241 0.9197 0.0 0.0 0.0 0.0 nan 0.6092 0.7941 0.0 0.4529 0.0701 nan 0.0019 0.0000 0.0 0.6993 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5686 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7724 0.6635 0.8689 0.0 0.0 0.0 0.0
1.0811 2.0 400 0.9893 0.1672 0.2089 0.7794 nan 0.8730 0.9570 0.0 0.5573 0.0561 nan 0.0013 0.0 0.0 0.9041 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8843 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9289 0.7991 0.9315 0.0 0.0 0.0 0.0 nan 0.6005 0.8145 0.0 0.4776 0.0532 nan 0.0013 0.0 0.0 0.6819 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5802 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7736 0.6686 0.8671 0.0 0.0 0.0 0.0
1.005 2.1 420 0.9977 0.1680 0.2082 0.7783 nan 0.8414 0.9628 0.0 0.5530 0.0624 nan 0.0015 0.0 0.0 0.8958 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8909 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9283 0.8101 0.9248 0.0 0.0 0.0 0.0 nan 0.6081 0.8005 0.0 0.4885 0.0582 nan 0.0014 0.0 0.0 0.6984 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5775 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7744 0.6669 0.8710 0.0 0.0 0.0 0.0
1.1406 2.2 440 0.9950 0.1688 0.2118 0.7810 nan 0.8863 0.9485 0.0 0.5892 0.0719 nan 0.0020 0.0 0.0 0.9067 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8789 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9261 0.8432 0.9362 0.0 0.0 0.0 0.0 nan 0.5949 0.8221 0.0 0.5206 0.0665 nan 0.0020 0.0 0.0 0.6859 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5834 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7685 0.6580 0.8695 0.0 0.0 0.0 0.0
1.0543 2.3 460 0.9919 0.1675 0.2111 0.7794 nan 0.8561 0.9568 0.0 0.5935 0.0637 nan 0.0044 0.0 0.0 0.9143 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8675 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9190 0.8489 0.9415 0.0 0.0 0.0 0.0 nan 0.6062 0.8089 0.0 0.5003 0.0600 nan 0.0044 0.0 0.0 0.6668 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5922 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7687 0.6544 0.8671 0.0 0.0 0.0 0.0
1.0831 2.4 480 0.9767 0.1686 0.2107 0.7797 nan 0.8387 0.9593 0.0 0.6142 0.0727 nan 0.0043 0.0 0.0 0.9063 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8895 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9216 0.8086 0.9375 0.0 0.0 0.0 0.0 nan 0.6101 0.8042 0.0 0.4901 0.0678 nan 0.0042 0.0 0.0 0.6846 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5854 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7796 0.6671 0.8714 0.0 0.0 0.0 0.0
1.0854 2.5 500 0.9623 0.1708 0.2138 0.7830 nan 0.8582 0.9533 0.0 0.6350 0.1068 nan 0.0074 0.0 0.0 0.9125 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8950 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9187 0.8375 0.9325 0.0 0.0 0.0 0.0 nan 0.6113 0.8175 0.0 0.5387 0.0943 nan 0.0073 0.0 0.0 0.6782 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5824 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7791 0.6587 0.8701 0.0 0.0 0.0 0.0
0.9507 2.6 520 0.9477 0.1706 0.2132 0.7834 nan 0.8834 0.9526 0.0 0.5999 0.0910 nan 0.0063 0.0 0.0 0.9084 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8915 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9170 0.8497 0.9341 0.0 0.0 0.0 0.0 nan 0.6044 0.8194 0.0 0.5368 0.0825 nan 0.0062 0.0 0.0 0.6840 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5855 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7806 0.6592 0.8710 0.0 0.0 0.0 0.0
1.2475 2.7 540 0.9406 0.1710 0.2129 0.7839 nan 0.8619 0.9584 0.0 0.6319 0.0836 nan 0.0067 0.0000 0.0 0.9037 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8810 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9258 0.8315 0.9419 0.0 0.0 0.0 0.0 nan 0.6158 0.8110 0.0 0.5375 0.0770 nan 0.0066 0.0000 0.0 0.6905 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5898 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7781 0.6668 0.8708 0.0 0.0 0.0 0.0
1.1332 2.8 560 0.9532 0.1721 0.2141 0.7852 nan 0.8774 0.9543 0.0 0.6470 0.0940 nan 0.0065 0.0 0.0 0.9043 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8968 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9194 0.8224 0.9417 0.0 0.0 0.0 0.0 nan 0.6092 0.8193 0.0 0.5542 0.0848 nan 0.0064 0.0 0.0 0.6936 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5837 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7845 0.6707 0.8731 0.0 0.0 0.0 0.0
0.9905 2.9 580 0.9639 0.1719 0.2137 0.7845 nan 0.8574 0.9590 0.0 0.6292 0.1033 nan 0.0097 0.0 0.0 0.9041 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8990 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9170 0.8356 0.9374 0.0 0.0 0.0 0.0 nan 0.6231 0.8120 0.0 0.5398 0.0920 nan 0.0096 0.0 0.0 0.6950 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5820 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7835 0.6635 0.8737 0.0 0.0 0.0 0.0
1.1681 3.0 600 0.9530 0.1712 0.2121 0.7831 nan 0.8549 0.9623 0.0 0.5957 0.0956 nan 0.0075 0.0 0.0 0.9053 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9017 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9152 0.8300 0.9299 0.0 0.0 0.0 0.0 nan 0.6261 0.8045 0.0 0.5253 0.0861 nan 0.0075 0.0 0.0 0.6945 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5817 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7847 0.6656 0.8751 0.0 0.0 0.0 0.0

Framework versions

  • Transformers 4.33.1
  • Pytorch 2.0.0+cu117
  • Datasets 2.14.4
  • Tokenizers 0.13.3
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