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segformer-b0-finetuned-segments-sidewalk-2

Image Segmentation
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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: 2.1850
  • Mean Iou: 0.0074
  • Mean Accuracy: 0.0858
  • Overall Accuracy: 0.0532
  • Accuracy Unlabeled: 0.0
  • Accuracy Flat-road: 0.0521
  • Accuracy Flat-sidewalk: 0.2880
  • Accuracy Flat-crosswalk: 0.0002
  • Accuracy Flat-cyclinglane: 0.0414
  • Accuracy Flat-parkingdriveway: nan
  • Accuracy Flat-railtrack: 0.0
  • Accuracy Flat-curb: 0.0
  • Accuracy Human-person: 0.0
  • Accuracy Human-rider: 0.0
  • Accuracy Vehicle-car: 0.7261
  • Accuracy Vehicle-truck: 0.0
  • Accuracy Vehicle-bus: 0.0
  • Accuracy Vehicle-tramtrain: 0.0
  • Accuracy Vehicle-motorcycle: 0.0
  • Accuracy Vehicle-bicycle: nan
  • Accuracy Vehicle-caravan: 0.0
  • Accuracy Vehicle-cartrailer: 0.0
  • Accuracy Construction-building: 0.8347
  • Accuracy Construction-door: 0.0
  • Accuracy Construction-wall: 0.0011
  • Accuracy Construction-fenceguardrail: 0.0
  • Accuracy Construction-bridge: nan
  • 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: 0.7158
  • Accuracy Nature-terrain: 0.0
  • Accuracy Sky: 0.0001
  • Accuracy Void-ground: 0.0
  • Accuracy Void-dynamic: 0.0
  • Accuracy Void-static: 0.0
  • Accuracy Void-unclear: nan
  • Iou Unlabeled: 0.0
  • Iou Flat-road: 0.0373
  • Iou Flat-sidewalk: 0.0114
  • Iou Flat-crosswalk: 0.0002
  • Iou Flat-cyclinglane: 0.0279
  • Iou Flat-parkingdriveway: 0.0
  • Iou Flat-railtrack: 0.0
  • Iou Flat-curb: 0.0
  • Iou Human-person: 0.0
  • Iou Human-rider: 0.0
  • Iou Vehicle-car: 0.0081
  • Iou Vehicle-truck: 0.0
  • Iou Vehicle-bus: 0.0
  • Iou Vehicle-tramtrain: 0.0
  • Iou Vehicle-motorcycle: 0.0
  • Iou Vehicle-bicycle: nan
  • Iou Vehicle-caravan: 0.0
  • Iou Vehicle-cartrailer: 0.0
  • Iou Construction-building: 0.0229
  • Iou Construction-door: 0.0
  • Iou Construction-wall: 0.0011
  • 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: 0.1347
  • Iou Nature-terrain: 0.0
  • Iou Sky: 0.0000
  • Iou Void-ground: 0.0
  • Iou Void-dynamic: 0.0
  • Iou Void-static: 0.0
  • Iou Void-unclear: 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: 1e-06
  • train_batch_size: 6
  • eval_batch_size: 6
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 40

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
3.583 0.43 50 3.5690 0.0035 0.0283 0.0143 0.0179 0.0003 0.0008 0.0087 0.2546 nan 0.0010 0.0022 0.0015 0.0234 0.2546 0.0 0.0330 0.0 0.0004 nan 0.0 0.0105 0.0 0.0027 0.0120 0.0 nan 0.0 0.0000 0.0061 0.0439 0.0009 0.0312 0.0055 0.0143 0.0679 0.0008 0.0841 nan 0.0156 0.0003 0.0008 0.0069 0.0354 0.0 0.0007 0.0004 0.0001 0.0096 0.0010 0.0 0.0001 0.0 0.0001 0.0 0.0 0.0097 0.0 0.0023 0.0081 0.0 0.0 0.0 0.0000 0.0033 0.0005 0.0009 0.0144 0.0041 0.0056 0.0014 0.0007 0.0001 0.0
3.541 0.85 100 3.5349 0.0040 0.0309 0.0152 0.0195 0.0003 0.0033 0.0139 0.2434 nan 0.0007 0.0027 0.0032 0.0195 0.3347 0.0 0.0174 0.0 0.0005 nan 0.0 0.0105 0.0003 0.0033 0.0132 0.0 nan 0.0 0.0 0.0086 0.0445 0.0007 0.0547 0.0053 0.0147 0.0689 0.0011 0.0731 nan 0.0166 0.0003 0.0029 0.0102 0.0339 0.0 0.0005 0.0004 0.0002 0.0079 0.0013 0.0 0.0000 0.0 0.0001 0.0 0.0 0.0098 0.0002 0.0028 0.0089 0.0 0.0 0.0 0.0 0.0046 0.0005 0.0007 0.0263 0.0039 0.0056 0.0014 0.0009 0.0001 0.0
3.4975 1.28 150 3.5016 0.0044 0.0336 0.0165 0.0157 0.0004 0.0078 0.0120 0.2803 nan 0.0004 0.0011 0.0018 0.0176 0.4099 0.0 0.0113 0.0 0.0004 nan 0.0 0.0090 0.0008 0.0025 0.0113 0.0 nan 0.0 0.0 0.0141 0.0421 0.0004 0.0806 0.0057 0.0142 0.0624 0.0011 0.0390 nan 0.0136 0.0004 0.0044 0.0095 0.0338 0.0 0.0003 0.0002 0.0001 0.0071 0.0016 0.0 0.0000 0.0 0.0001 0.0 0.0 0.0085 0.0005 0.0022 0.0085 0.0 0.0 0.0 0.0 0.0073 0.0004 0.0004 0.0415 0.0042 0.0057 0.0015 0.0009 0.0000 0.0
3.5169 1.71 200 3.4636 0.0052 0.0399 0.0195 0.0159 0.0003 0.0224 0.0081 0.3090 nan 0.0002 0.0010 0.0022 0.0136 0.4941 0.0 0.0071 0.0 0.0003 nan 0.0 0.0112 0.0032 0.0018 0.0168 0.0 nan 0.0 0.0 0.0127 0.0408 0.0002 0.1364 0.0040 0.0128 0.0652 0.0014 0.0562 nan 0.0138 0.0003 0.0047 0.0068 0.0366 0.0 0.0001 0.0002 0.0002 0.0062 0.0021 0.0 0.0000 0.0 0.0000 0.0 0.0 0.0106 0.0016 0.0017 0.0111 0.0 0.0 0.0 0.0 0.0071 0.0006 0.0002 0.0657 0.0031 0.0052 0.0017 0.0012 0.0000 0.0
3.3938 2.14 250 3.4255 0.0057 0.0433 0.0208 0.0139 0.0005 0.0461 0.0090 0.2873 nan 0.0002 0.0015 0.0016 0.0119 0.5499 0.0 0.0067 0.0 0.0003 nan 0.0 0.0101 0.0044 0.0021 0.0197 0.0 nan 0.0 0.0 0.0134 0.0390 0.0001 0.1878 0.0037 0.0157 0.0644 0.0011 0.0534 nan 0.0121 0.0005 0.0054 0.0075 0.0382 0.0 0.0001 0.0003 0.0002 0.0052 0.0025 0.0 0.0000 0.0 0.0000 0.0 0.0 0.0096 0.0021 0.0019 0.0132 0.0 0.0 0.0 0.0 0.0071 0.0006 0.0001 0.0801 0.0029 0.0062 0.0018 0.0010 0.0000 0.0
3.4231 2.56 300 3.3861 0.0062 0.0466 0.0232 0.0130 0.0005 0.0759 0.0072 0.2834 nan 0.0001 0.0006 0.0022 0.0097 0.5913 0.0 0.0017 0.0 0.0003 nan 0.0 0.0109 0.0069 0.0018 0.0223 0.0 nan 0.0 0.0 0.0136 0.0389 0.0000 0.2467 0.0033 0.0148 0.0719 0.0010 0.0262 nan 0.0113 0.0005 0.0060 0.0062 0.0426 0.0 0.0001 0.0002 0.0003 0.0045 0.0031 0.0 0.0000 0.0 0.0001 0.0 0.0 0.0105 0.0031 0.0016 0.0150 0.0 0.0 0.0 0.0 0.0072 0.0008 0.0000 0.0909 0.0027 0.0059 0.0019 0.0010 0.0000 0.0
3.3664 2.99 350 3.3542 0.0065 0.0503 0.0246 0.0112 0.0006 0.1034 0.0054 0.2629 nan 0.0002 0.0002 0.0015 0.0066 0.6758 0.0 0.0009 0.0 0.0002 nan 0.0 0.0073 0.0123 0.0020 0.0218 0.0 nan 0.0 0.0 0.0118 0.0363 0.0 0.3115 0.0032 0.0066 0.0634 0.0008 0.0131 nan 0.0099 0.0006 0.0065 0.0048 0.0455 0.0 0.0001 0.0001 0.0002 0.0035 0.0031 0.0 0.0000 0.0 0.0000 0.0 0.0 0.0071 0.0042 0.0019 0.0151 0.0 0.0 0.0 0.0 0.0072 0.0008 0.0 0.1091 0.0027 0.0030 0.0021 0.0007 0.0000 0.0
3.3089 3.42 400 3.3039 0.0069 0.0551 0.0281 0.0107 0.0006 0.1407 0.0043 0.2687 nan 0.0002 0.0002 0.0011 0.0051 0.6984 0.0 0.0002 0.0 0.0002 nan 0.0 0.0081 0.0164 0.0018 0.0267 0.0 nan 0.0 0.0 0.0104 0.0366 0.0 0.3861 0.0041 0.0079 0.0729 0.0007 0.0069 nan 0.0094 0.0006 0.0075 0.0039 0.0495 0.0 0.0002 0.0001 0.0002 0.0025 0.0037 0.0 0.0000 0.0 0.0000 0.0 0.0 0.0079 0.0054 0.0018 0.0179 0.0 0.0 0.0 0.0 0.0066 0.0010 0.0 0.1123 0.0033 0.0032 0.0025 0.0007 0.0000 0.0
3.2464 3.85 450 3.2705 0.0070 0.0575 0.0288 0.0092 0.0006 0.1587 0.0043 0.2538 nan 0.0001 0.0 0.0001 0.0027 0.7500 0.0 0.0001 0.0 0.0001 nan 0.0 0.0068 0.0248 0.0020 0.0284 0.0 nan 0.0 0.0 0.0089 0.0347 0.0 0.4160 0.0040 0.0057 0.0694 0.0005 0.0007 nan 0.0083 0.0006 0.0080 0.0040 0.0504 0.0 0.0001 0.0 0.0000 0.0016 0.0036 0.0 0.0000 0.0 0.0000 0.0 0.0 0.0067 0.0065 0.0019 0.0191 0.0 0.0 0.0 0.0 0.0060 0.0012 0.0 0.1181 0.0032 0.0025 0.0026 0.0005 0.0000 0.0
3.2788 4.27 500 3.2230 0.0074 0.0616 0.0320 0.0100 0.0009 0.1784 0.0041 0.2465 nan 0.0001 0.0 0.0 0.0020 0.7658 0.0 0.0 0.0 0.0001 nan 0.0 0.0060 0.0325 0.0018 0.0373 0.0 nan 0.0 0.0 0.0075 0.0318 0.0 0.4977 0.0046 0.0049 0.0783 0.0004 0.0 nan 0.0089 0.0009 0.0084 0.0038 0.0523 0.0 0.0001 0.0 0.0 0.0012 0.0040 0.0 0.0 0.0 0.0000 0.0 0.0 0.0058 0.0071 0.0018 0.0231 0.0 0.0 0.0 0.0 0.0048 0.0013 0.0 0.1257 0.0037 0.0023 0.0029 0.0004 0.0 0.0
3.2179 4.7 550 3.1821 0.0074 0.0641 0.0337 0.0090 0.0011 0.2000 0.0030 0.2313 nan 0.0001 0.0 0.0 0.0016 0.7777 0.0 0.0 0.0 0.0000 nan 0.0 0.0054 0.0473 0.0018 0.0371 0.0 nan 0.0 0.0 0.0042 0.0317 0.0 0.5484 0.0049 0.0047 0.0782 0.0004 0.0 nan 0.0081 0.0011 0.0090 0.0028 0.0523 0.0 0.0001 0.0 0.0 0.0010 0.0042 0.0 0.0 0.0 0.0000 0.0 0.0 0.0053 0.0088 0.0018 0.0229 0.0 0.0 0.0 0.0 0.0027 0.0016 0.0 0.1282 0.0039 0.0022 0.0034 0.0003 0.0 0.0
3.1906 5.13 600 3.1424 0.0074 0.0651 0.0338 0.0104 0.0015 0.2149 0.0034 0.2067 nan 0.0001 0.0 0.0 0.0011 0.8076 0.0 0.0 0.0 0.0 nan 0.0 0.0044 0.0642 0.0017 0.0322 0.0 nan 0.0 0.0 0.0024 0.0266 0.0 0.5584 0.0044 0.0047 0.0734 0.0002 0.0 nan 0.0093 0.0015 0.0094 0.0032 0.0515 0.0 0.0001 0.0 0.0 0.0008 0.0041 0.0 0.0 0.0 0.0 0.0 0.0 0.0044 0.0099 0.0017 0.0211 0.0 0.0 0.0 0.0 0.0016 0.0016 0.0 0.1304 0.0035 0.0021 0.0034 0.0002 0.0 0.0
3.2075 5.56 650 3.1091 0.0075 0.0678 0.0367 0.0088 0.0019 0.2249 0.0032 0.2201 nan 0.0000 0.0 0.0 0.0009 0.8058 0.0 0.0 0.0 0.0 nan 0.0 0.0035 0.0846 0.0014 0.0332 0.0 nan 0.0 0.0 0.0009 0.0145 0.0 0.6252 0.0050 0.0049 0.0639 0.0002 0.0 nan 0.0080 0.0018 0.0096 0.0030 0.0525 0.0 0.0000 0.0 0.0 0.0006 0.0042 0.0 0.0 0.0 0.0 0.0 0.0 0.0034 0.0114 0.0014 0.0220 0.0 0.0 0.0 0.0 0.0007 0.0013 0.0 0.1327 0.0041 0.0022 0.0035 0.0002 0.0 0.0
3.0888 5.98 700 3.0596 0.0075 0.0690 0.0364 0.0080 0.0025 0.2672 0.0028 0.1936 nan 0.0001 0.0 0.0 0.0008 0.8043 0.0 0.0 0.0 0.0 nan 0.0 0.0033 0.1121 0.0018 0.0380 0.0 nan 0.0 0.0000 0.0007 0.0109 0.0 0.6151 0.0053 0.0040 0.0672 0.0001 0.0 nan 0.0073 0.0024 0.0108 0.0027 0.0502 0.0 0.0001 0.0 0.0 0.0006 0.0044 0.0 0.0 0.0 0.0 0.0 0.0 0.0033 0.0125 0.0018 0.0244 0.0 0.0 0.0 0.0000 0.0005 0.0012 0.0 0.1313 0.0043 0.0017 0.0041 0.0001 0.0 0.0
3.1177 6.41 750 3.0297 0.0075 0.0700 0.0387 0.0082 0.0029 0.2403 0.0022 0.2030 nan 0.0000 0.0 0.0 0.0004 0.8050 0.0 0.0 0.0 0.0 nan 0.0 0.0028 0.1223 0.0012 0.0318 0.0 nan 0.0 0.0000 0.0 0.0030 0.0 0.6823 0.0056 0.0042 0.0556 0.0001 0.0 nan 0.0077 0.0028 0.0099 0.0022 0.0513 0.0 0.0000 0.0 0.0 0.0003 0.0042 0.0 0.0 0.0 0.0 0.0 0.0 0.0028 0.0131 0.0012 0.0210 0.0 0.0 0.0 0.0000 0.0 0.0005 0.0 0.1343 0.0045 0.0018 0.0039 0.0001 0.0 0.0
3.0981 6.84 800 2.9921 0.0075 0.0716 0.0382 0.0071 0.0029 0.3004 0.0017 0.1831 nan 0.0000 0.0 0.0 0.0004 0.8008 0.0 0.0 0.0 0.0 nan 0.0 0.0026 0.1617 0.0013 0.0377 0.0 nan 0.0 0.0000 0.0 0.0003 0.0 0.6584 0.0052 0.0035 0.0532 0.0001 0.0 nan 0.0066 0.0028 0.0117 0.0016 0.0489 0.0 0.0000 0.0 0.0 0.0003 0.0045 0.0 0.0 0.0 0.0 0.0 0.0 0.0026 0.0139 0.0013 0.0245 0.0 0.0 0.0 0.0000 0.0 0.0001 0.0 0.1324 0.0042 0.0013 0.0044 0.0001 0.0 0.0
2.9986 7.26 850 2.9500 0.0073 0.0718 0.0379 0.0051 0.0029 0.3269 0.0015 0.1622 nan 0.0000 0.0 0.0 0.0002 0.7995 0.0 0.0 0.0 0.0 nan 0.0 0.0019 0.1661 0.0011 0.0342 0.0 nan 0.0 0.0000 0.0 0.0 0.0 0.6631 0.0057 0.0034 0.0505 0.0000 0.0 nan 0.0049 0.0028 0.0124 0.0015 0.0477 0.0 0.0000 0.0 0.0 0.0002 0.0043 0.0 0.0 0.0 0.0 0.0 0.0 0.0019 0.0139 0.0011 0.0226 0.0 0.0 0.0 0.0000 0.0 0.0 0.0 0.1328 0.0044 0.0012 0.0047 0.0000 0.0 0.0
3.01 7.69 900 2.9155 0.0075 0.0726 0.0397 0.0057 0.0048 0.2827 0.0016 0.1780 nan 0.0 0.0 0.0 0.0001 0.7988 0.0 0.0 0.0 0.0 nan 0.0 0.0018 0.1896 0.0014 0.0313 0.0 nan 0.0 0.0 0.0 0.0 0.0 0.7004 0.0053 0.0027 0.0462 0.0 0.0 nan 0.0054 0.0044 0.0112 0.0016 0.0495 0.0 0.0 0.0 0.0 0.0001 0.0043 0.0 0.0 0.0 0.0 0.0 0.0 0.0018 0.0146 0.0014 0.0215 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1358 0.0041 0.0010 0.0043 0.0 0.0 0.0
2.7829 8.12 950 2.9108 0.0075 0.0737 0.0396 0.0046 0.0056 0.3126 0.0016 0.1523 nan 0.0 0.0 0.0 0.0001 0.7949 0.0 0.0 0.0 0.0 nan 0.0 0.0012 0.2263 0.0013 0.0359 0.0 nan 0.0 0.0000 0.0 0.0 0.0 0.6970 0.0047 0.0030 0.0449 0.0 0.0 nan 0.0045 0.0051 0.0120 0.0016 0.0474 0.0 0.0 0.0 0.0 0.0001 0.0045 0.0 0.0 0.0 0.0 0.0 0.0 0.0012 0.0158 0.0013 0.0238 0.0 0.0 0.0 0.0000 0.0 0.0 0.0 0.1359 0.0036 0.0010 0.0057 0.0 0.0 0.0
2.8855 8.55 1000 2.8632 0.0075 0.0762 0.0407 0.0035 0.0060 0.3065 0.0012 0.1668 nan 0.0 0.0 0.0 0.0000 0.7886 0.0 0.0 0.0 0.0 nan 0.0 0.0011 0.2899 0.0015 0.0307 0.0 nan 0.0 0.0000 0.0 0.0 0.0 0.7177 0.0046 0.0028 0.0425 0.0 0.0 nan 0.0034 0.0053 0.0118 0.0012 0.0482 0.0 0.0 0.0 0.0 0.0000 0.0047 0.0 0.0 0.0 0.0 0.0 0.0 0.0011 0.0177 0.0015 0.0216 0.0 0.0 0.0 0.0000 0.0 0.0 0.0 0.1363 0.0035 0.0008 0.0067 0.0 0.0 0.0
2.9367 8.97 1050 2.8275 0.0073 0.0747 0.0400 0.0028 0.0064 0.3273 0.0011 0.1432 nan 0.0 0.0 0.0 0.0000 0.7941 0.0 0.0 0.0 0.0 nan 0.0 0.0007 0.2668 0.0013 0.0213 0.0 nan 0.0 0.0 0.0 0.0 0.0 0.7122 0.0036 0.0029 0.0306 0.0 0.0 nan 0.0027 0.0057 0.0123 0.0011 0.0455 0.0 0.0 0.0 0.0 0.0000 0.0044 0.0 0.0 0.0 0.0 0.0 0.0 0.0007 0.0169 0.0013 0.0157 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1387 0.0028 0.0007 0.0061 0.0 0.0 0.0
2.7874 9.4 1100 2.7847 0.0072 0.0772 0.0396 0.0020 0.0044 0.3967 0.0012 0.1218 nan 0.0 0.0 0.0 0.0000 0.7892 0.0 0.0 0.0 0.0 nan 0.0 0.0007 0.3182 0.0009 0.0262 0.0 nan 0.0 0.0 0.0 0.0 0.0 0.7052 0.0033 0.0022 0.0224 0.0 0.0 nan 0.0020 0.0040 0.0142 0.0012 0.0427 0.0 0.0 0.0 0.0 0.0000 0.0045 0.0 0.0 0.0 0.0 0.0 0.0 0.0007 0.0183 0.0009 0.0183 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1382 0.0025 0.0005 0.0057 0.0 0.0 0.0
2.7519 9.83 1150 2.7757 0.0074 0.0773 0.0408 0.0016 0.0078 0.3511 0.0007 0.1389 nan 0.0 0.0 0.0 0.0000 0.7855 0.0 0.0 0.0 0.0 nan 0.0 0.0005 0.3444 0.0012 0.0257 0.0 nan 0.0 0.0 0.0 0.0 0.0 0.7131 0.0030 0.0018 0.0220 0.0 0.0 nan 0.0016 0.0068 0.0130 0.0007 0.0451 0.0 0.0 0.0 0.0 0.0000 0.0048 0.0 0.0 0.0 0.0 0.0 0.0 0.0005 0.0190 0.0012 0.0186 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1375 0.0023 0.0004 0.0067 0.0 0.0 0.0
2.8513 10.26 1200 2.7939 0.0076 0.0773 0.0420 0.0021 0.0113 0.3051 0.0007 0.1357 nan 0.0 0.0 0.0 0.0 0.7816 0.0 0.0 0.0 0.0 nan 0.0 0.0003 0.3811 0.0013 0.0213 0.0 nan 0.0 0.0 0.0 0.0 0.0 0.7334 0.0018 0.0024 0.0175 0.0 0.0 nan 0.0021 0.0096 0.0117 0.0007 0.0452 0.0 0.0 0.0 0.0 0.0 0.0047 0.0 0.0 0.0 0.0 nan 0.0 0.0003 0.0194 0.0013 0.0157 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1406 0.0014 0.0005 0.0058 0.0 0.0 0.0
2.9147 10.68 1250 2.7415 0.0073 0.0800 0.0437 0.0016 0.0124 0.3254 0.0004 0.1348 nan 0.0 0.0 0.0 0.0000 0.7681 0.0 0.0 0.0 0.0 nan 0.0 0.0003 0.4424 0.0013 0.0158 0.0 nan 0.0 0.0 0.0 0.0 0.0 0.7583 0.0027 0.0016 0.0161 0.0 0.0 nan 0.0016 0.0105 0.0123 0.0004 0.0444 0.0 0.0 0.0 0.0 0.0000 0.0055 0.0 0.0 0.0 0.0 0.0 0.0 0.0003 0.0210 0.0013 0.0118 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1361 0.0020 0.0004 0.0062 0.0 0.0 0.0
2.9311 11.11 1300 2.7368 0.0071 0.0793 0.0437 0.0013 0.0122 0.3176 0.0005 0.1358 nan 0.0 0.0 0.0 0.0 0.7735 0.0 0.0 0.0 0.0 nan 0.0 0.0001 0.4230 0.0011 0.0100 0.0 nan 0.0 0.0 0.0 0.0 0.0 0.7709 0.0014 0.0014 0.0102 0.0 0.0 nan 0.0012 0.0103 0.0121 0.0005 0.0446 0.0 0.0 0.0 0.0 0.0 0.0051 0.0 0.0 0.0 0.0 0.0 0.0 0.0001 0.0205 0.0011 0.0079 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1390 0.0011 0.0003 0.0044 0.0 0.0 0.0
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2.4924 38.89 4550 2.2621 0.0076 0.0866 0.0536 0.0 0.0498 0.2829 0.0002 0.0517 nan 0.0 0.0 0.0 0.0 0.7265 0.0 0.0 0.0 0.0 nan 0.0 0.0 0.8296 0.0 0.0011 0.0 nan 0.0 0.0 0.0 0.0 0.0 0.7427 0.0 0.0001 0.0 0.0 0.0 nan 0.0 0.0359 0.0112 0.0002 0.0325 0.0 0.0 0.0 0.0 0.0 0.0079 0.0 0.0 0.0 0.0 nan 0.0 0.0 0.0230 0.0 0.0010 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1380 0.0 0.0000 0.0 0.0 0.0 nan
2.1744 39.32 4600 2.1896 0.0072 0.0852 0.0514 0.0 0.0507 0.2949 0.0002 0.0365 nan 0.0 0.0 0.0 0.0 0.7249 0.0 0.0 0.0 0.0 nan 0.0 0.0 0.8512 0.0000 0.0009 0.0 nan 0.0 0.0 0.0 0.0 0.0 0.6806 0.0 0.0002 0.0 0.0 0.0 nan 0.0 0.0364 0.0116 0.0002 0.0253 0.0 0.0 0.0 0.0 0.0 0.0081 0.0 0.0 0.0 0.0 nan 0.0 0.0 0.0224 0.0000 0.0008 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1315 0.0 0.0000 0.0 0.0 0.0 nan
2.4663 39.74 4650 2.1850 0.0074 0.0858 0.0532 0.0 0.0521 0.2880 0.0002 0.0414 nan 0.0 0.0 0.0 0.0 0.7261 0.0 0.0 0.0 0.0 nan 0.0 0.0 0.8347 0.0 0.0011 0.0 nan 0.0 0.0 0.0 0.0 0.0 0.7158 0.0 0.0001 0.0 0.0 0.0 nan 0.0 0.0373 0.0114 0.0002 0.0279 0.0 0.0 0.0 0.0 0.0 0.0081 0.0 0.0 0.0 0.0 nan 0.0 0.0 0.0229 0.0 0.0011 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1347 0.0 0.0000 0.0 0.0 0.0 nan

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.0
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Safetensors
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