Hugging Face's logo

PushkarA07
/
segformer-b0-finetuned-segments-sidewalk-oct-22

Image Segmentation
Transformers
TensorBoard
Safetensors
segformer
vision
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
Edit model card

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: 0.9415
  • Mean Iou: 0.1739
  • Mean Accuracy: 0.2202
  • Overall Accuracy: 0.7714
  • Accuracy Unlabeled: nan
  • Accuracy Flat-road: 0.8361
  • Accuracy Flat-sidewalk: 0.9327
  • Accuracy Flat-crosswalk: 0.0
  • Accuracy Flat-cyclinglane: 0.4491
  • Accuracy Flat-parkingdriveway: 0.0618
  • Accuracy Flat-railtrack: nan
  • Accuracy Flat-curb: 0.0106
  • Accuracy Human-person: 0.0
  • Accuracy Human-rider: 0.0
  • Accuracy Vehicle-car: 0.8757
  • Accuracy Vehicle-truck: 0.0
  • Accuracy Vehicle-bus: 0.0
  • Accuracy Vehicle-tramtrain: nan
  • Accuracy Vehicle-motorcycle: 0.0
  • Accuracy Vehicle-bicycle: 0.0
  • Accuracy Vehicle-caravan: 0.0
  • Accuracy Vehicle-cartrailer: 0.0
  • Accuracy Construction-building: 0.8775
  • Accuracy Construction-door: 0.0
  • Accuracy Construction-wall: 0.0398
  • Accuracy Construction-fenceguardrail: 0.0000
  • Accuracy Construction-bridge: 0.0
  • Accuracy Construction-tunnel: nan
  • Accuracy Construction-stairs: 0.0
  • Accuracy Object-pole: 0.0
  • Accuracy Object-trafficsign: 0.0
  • Accuracy Object-trafficlight: 0.0
  • Accuracy Nature-vegetation: 0.9075
  • Accuracy Nature-terrain: 0.9080
  • Accuracy Sky: 0.9280
  • 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: 0.5895
  • Iou Flat-sidewalk: 0.7842
  • Iou Flat-crosswalk: 0.0
  • Iou Flat-cyclinglane: 0.4140
  • Iou Flat-parkingdriveway: 0.0569
  • Iou Flat-railtrack: nan
  • Iou Flat-curb: 0.0105
  • Iou Human-person: 0.0
  • Iou Human-rider: 0.0
  • Iou Vehicle-car: 0.6473
  • Iou Vehicle-truck: 0.0
  • Iou Vehicle-bus: 0.0
  • Iou Vehicle-tramtrain: nan
  • Iou Vehicle-motorcycle: 0.0
  • Iou Vehicle-bicycle: 0.0
  • Iou Vehicle-caravan: 0.0
  • Iou Vehicle-cartrailer: 0.0
  • Iou Construction-building: 0.5914
  • Iou Construction-door: 0.0
  • Iou Construction-wall: 0.0393
  • Iou Construction-fenceguardrail: 0.0000
  • Iou Construction-bridge: 0.0
  • Iou Construction-tunnel: nan
  • Iou Construction-stairs: 0.0
  • Iou Object-pole: 0.0
  • Iou Object-trafficsign: 0.0
  • Iou Object-trafficlight: 0.0
  • Iou Nature-vegetation: 0.7895
  • Iou Nature-terrain: 0.6699
  • Iou Sky: 0.7975
  • 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: 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: 2

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
2.9835 0.05 20 3.2065 0.0687 0.1233 0.5589 nan 0.2838 0.8965 0.0069 0.0036 0.0007 nan 0.0008 0.0172 0.0 0.8081 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8197 0.0 0.0110 0.0014 0.0 nan 0.0030 0.0084 0.0 0.0 0.6134 0.1250 0.2229 0.0 0.0 0.0012 0.0 0.0 0.2033 0.6129 0.0067 0.0035 0.0007 0.0 0.0008 0.0123 0.0 0.3235 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.3814 0.0 0.0099 0.0011 0.0 0.0 0.0014 0.0036 0.0 0.0 0.5201 0.1173 0.2045 0.0 0.0 0.0011 0.0
2.5539 0.1 40 2.4846 0.0922 0.1406 0.6363 nan 0.6139 0.8851 0.0 0.0001 0.0 nan 0.0 0.0 0.0 0.7404 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7823 0.0 0.0095 0.0001 0.0 nan 0.0 0.0 0.0 0.0 0.9250 0.0450 0.3566 0.0 0.0 0.0002 0.0 nan 0.3914 0.6639 0.0 0.0001 0.0 nan 0.0 0.0 0.0 0.4531 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4448 0.0 0.0093 0.0001 0.0 nan 0.0 0.0 0.0 0.0 0.6167 0.0431 0.3282 0.0 0.0 0.0002 0.0
2.1941 0.15 60 2.0471 0.1050 0.1507 0.6598 nan 0.6534 0.9013 0.0 0.0000 0.0 nan 0.0 0.0 0.0 0.8191 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8068 0.0 0.0027 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.9374 0.0319 0.5185 0.0 0.0 0.0000 0.0 nan 0.4189 0.6905 0.0 0.0000 0.0 nan 0.0 0.0 0.0 0.5057 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.4936 0.0 0.0027 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.6186 0.0311 0.4939 0.0 0.0 0.0000 0.0
2.0689 0.2 80 1.8596 0.1144 0.1599 0.6742 nan 0.6956 0.8961 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.8106 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8269 0.0 0.0010 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.9406 0.1659 0.6189 0.0 0.0 0.0 0.0 nan 0.4425 0.6991 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.5351 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.5100 0.0 0.0010 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.6370 0.1547 0.5682 0.0 0.0 0.0 0.0
2.1181 0.25 100 1.6938 0.1148 0.1605 0.6782 nan 0.6755 0.9120 0.0 0.0000 0.0 nan 0.0 0.0 0.0 0.8326 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8362 0.0 0.0004 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.9375 0.0969 0.6848 0.0 0.0 0.0 0.0 nan 0.4698 0.6984 0.0 0.0000 0.0 nan 0.0 0.0 0.0 0.5419 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.5172 0.0 0.0004 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.6223 0.0891 0.6195 0.0 0.0 0.0 0.0
1.7511 0.3 120 1.7105 0.1289 0.1785 0.6857 nan 0.7919 0.8523 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.9031 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7983 0.0 0.0001 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8947 0.4820 0.8097 0.0 0.0 0.0 0.0 nan 0.4352 0.7026 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.4821 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.5383 0.0 0.0001 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7010 0.4272 0.7081 0.0 0.0 0.0 0.0
1.6833 0.35 140 1.5535 0.1359 0.1810 0.7089 nan 0.7051 0.9316 0.0 0.0001 0.0001 nan 0.0 0.0 0.0 0.8416 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8372 0.0 0.0000 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.9141 0.5586 0.8235 0.0 0.0 0.0 0.0 nan 0.4813 0.7152 0.0 0.0001 0.0001 nan 0.0 0.0 0.0 0.5654 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.5267 0.0 0.0000 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7200 0.4968 0.7074 0.0 0.0 0.0 0.0
1.3625 0.4 160 1.5401 0.1379 0.1875 0.6960 nan 0.8227 0.8315 0.0 0.0088 0.0 nan 0.0 0.0 0.0 0.8202 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7865 0.0 0.0003 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.9384 0.7172 0.8861 0.0 0.0 0.0 0.0 nan 0.4355 0.6978 0.0 0.0087 0.0 nan 0.0 0.0 0.0 0.5993 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.5463 0.0 0.0003 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7186 0.5697 0.6994 0.0 0.0 0.0 0.0
1.5652 0.45 180 1.4347 0.1410 0.1858 0.7167 nan 0.7172 0.9289 0.0 0.0297 0.0001 nan 0.0 0.0 0.0 0.8140 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8634 0.0 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.9192 0.6085 0.8794 0.0 0.0 0.0 0.0 nan 0.4974 0.7238 0.0 0.0297 0.0001 nan 0.0 0.0 0.0 0.5906 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.5262 0.0 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7211 0.5269 0.7543 0.0 0.0 0.0 0.0
2.251 0.5 200 1.3852 0.1438 0.1954 0.7167 nan 0.8140 0.8843 0.0 0.0396 0.0000 nan 0.0 0.0 0.0 0.8636 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8323 0.0 0.0002 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8637 0.8718 0.8885 0.0 0.0 0.0 0.0 nan 0.4719 0.7384 0.0 0.0396 0.0000 nan 0.0 0.0 0.0 0.5543 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.5495 0.0 0.0002 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7409 0.6157 0.7470 0.0 0.0 0.0 0.0
1.5334 0.55 220 1.3557 0.1485 0.1958 0.7332 nan 0.8039 0.9151 0.0 0.0808 0.0010 nan 0.0 0.0 0.0 0.8567 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8422 0.0 0.0001 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.9310 0.7820 0.8578 0.0 0.0 0.0 0.0 nan 0.5151 0.7568 0.0 0.0805 0.0010 nan 0.0 0.0 0.0 0.5778 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.5628 0.0 0.0001 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7331 0.6244 0.7510 0.0 0.0 0.0 0.0
1.1032 0.6 240 1.3035 0.1484 0.1983 0.7294 nan 0.8280 0.8915 0.0 0.0295 0.0006 nan 0.0 0.0 0.0 0.8420 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8958 0.0 0.0000 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8890 0.8915 0.8781 0.0 0.0 0.0 0.0 nan 0.5051 0.7588 0.0 0.0295 0.0006 nan 0.0 0.0 0.0 0.5893 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.5361 0.0 0.0000 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7585 0.6389 0.7831 0.0 0.0 0.0 0.0
1.5162 0.65 260 1.2855 0.1499 0.1982 0.7346 nan 0.7899 0.9274 0.0 0.0696 0.0004 nan 0.0 0.0 0.0 0.8823 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7802 0.0 0.0001 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.9275 0.8540 0.9115 0.0 0.0 0.0 0.0 nan 0.5089 0.7497 0.0 0.0693 0.0004 nan 0.0 0.0 0.0 0.5665 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.5720 0.0 0.0001 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7467 0.6577 0.7756 0.0 0.0 0.0 0.0
1.423 0.7 280 1.1915 0.1506 0.1993 0.7353 nan 0.7402 0.9425 0.0 0.0845 0.0010 nan 0.0 0.0 0.0 0.8551 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8733 0.0 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8687 0.9102 0.9032 0.0 0.0 0.0 0.0 nan 0.5234 0.7414 0.0 0.0841 0.0010 nan 0.0 0.0 0.0 0.6108 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.5614 0.0 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7488 0.6217 0.7766 0.0 0.0 0.0 0.0
1.5383 0.75 300 1.2519 0.1443 0.1948 0.7075 nan 0.8838 0.8184 0.0 0.0051 0.0001 nan 0.0 0.0 0.0 0.8848 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7914 0.0 0.0005 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.9453 0.7949 0.9133 0.0 0.0 0.0 0.0 nan 0.4399 0.7253 0.0 0.0051 0.0001 nan 0.0 0.0 0.0 0.5790 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.5762 0.0 0.0005 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7339 0.6488 0.7635 0.0 0.0 0.0 0.0
1.1151 0.8 320 1.1587 0.1554 0.2030 0.7440 nan 0.7824 0.9307 0.0 0.1656 0.0020 nan 0.0 0.0 0.0 0.8517 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8978 0.0 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8867 0.9163 0.8613 0.0 0.0 0.0 0.0 nan 0.5322 0.7605 0.0 0.1648 0.0020 nan 0.0 0.0 0.0 0.6094 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.5644 0.0 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7635 0.6291 0.7922 0.0 0.0 0.0 0.0
1.8368 0.85 340 1.1384 0.1576 0.2078 0.7473 nan 0.7884 0.9303 0.0 0.2963 0.0030 nan 0.0 0.0 0.0 0.8826 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8052 0.0 0.0001 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.9000 0.9177 0.9172 0.0 0.0 0.0 0.0 nan 0.5405 0.7619 0.0 0.2939 0.0030 nan 0.0 0.0 0.0 0.5768 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.5739 0.0 0.0001 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7456 0.6228 0.7663 0.0 0.0 0.0 0.0
1.0473 0.9 360 1.1197 0.1620 0.2067 0.7529 nan 0.8541 0.9158 0.0 0.2833 0.0019 nan 0.0 0.0 0.0 0.8277 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8720 0.0 0.0010 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.9178 0.8401 0.8938 0.0 0.0 0.0 0.0 nan 0.5348 0.7771 0.0 0.2824 0.0019 nan 0.0 0.0 0.0 0.6333 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.5658 0.0 0.0010 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7679 0.6838 0.7734 0.0 0.0 0.0 0.0
1.2099 0.95 380 1.1402 0.1596 0.2125 0.7489 nan 0.8279 0.9097 0.0 0.3973 0.0049 nan 0.0 0.0 0.0 0.8926 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8234 0.0 0.0045 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8687 0.9479 0.9095 0.0 0.0 0.0 0.0 nan 0.5527 0.7692 0.0 0.3760 0.0048 nan 0.0 0.0 0.0 0.5899 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.5926 0.0 0.0045 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7353 0.5382 0.7842 0.0 0.0 0.0 0.0
1.4778 1.0 400 1.0639 0.1629 0.2062 0.7559 nan 0.7707 0.9485 0.0 0.3733 0.0050 nan 0.0 0.0 0.0 0.8102 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8614 0.0 0.0006 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.9319 0.7720 0.9201 0.0 0.0 0.0 0.0 nan 0.5704 0.7620 0.0 0.3430 0.0050 nan 0.0 0.0 0.0 0.6244 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.5635 0.0 0.0006 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7570 0.6502 0.7751 0.0 0.0 0.0 0.0
1.3524 1.05 420 1.0537 0.1646 0.2128 0.7594 nan 0.8552 0.9147 0.0 0.3862 0.0047 nan 0.0000 0.0 0.0 0.8886 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8363 0.0 0.0012 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.9223 0.8621 0.9254 0.0 0.0 0.0 0.0 nan 0.5567 0.7816 0.0 0.3792 0.0047 nan 0.0000 0.0 0.0 0.5949 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.5790 0.0 0.0011 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7683 0.6633 0.7752 0.0 0.0 0.0 0.0
1.13 1.1 440 1.0641 0.1623 0.2100 0.7552 nan 0.8688 0.9058 0.0 0.3920 0.0061 nan 0.0001 0.0 0.0 0.8676 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7887 0.0 0.0043 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.9566 0.8035 0.9177 0.0 0.0 0.0 0.0 nan 0.5569 0.7839 0.0 0.3826 0.0060 nan 0.0001 0.0 0.0 0.6087 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.5866 0.0 0.0042 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7200 0.6085 0.7728 0.0 0.0 0.0 0.0
0.9163 1.15 460 1.0375 0.1669 0.2122 0.7625 nan 0.7922 0.9441 0.0 0.4037 0.0117 nan 0.0 0.0 0.0 0.8629 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8731 0.0 0.0161 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.9124 0.8587 0.9033 0.0 0.0 0.0 0.0 nan 0.5745 0.7713 0.0 0.3669 0.0115 nan 0.0 0.0 0.0 0.6337 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.5842 0.0 0.0160 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7742 0.6522 0.7883 0.0 0.0 0.0 0.0
0.9166 1.2 480 1.0155 0.1683 0.2160 0.7657 nan 0.8269 0.9353 0.0 0.4213 0.0204 nan 0.0001 0.0 0.0 0.8988 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8703 0.0 0.0283 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8959 0.8917 0.9064 0.0 0.0 0.0 0.0 nan 0.5802 0.7839 0.0 0.3953 0.0197 nan 0.0001 0.0 0.0 0.6081 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.5865 0.0 0.0278 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7779 0.6530 0.7844 0.0 0.0 0.0 0.0
1.1753 1.25 500 1.0090 0.1691 0.2150 0.7662 nan 0.7755 0.9463 0.0 0.4466 0.0306 nan 0.0012 0.0 0.0 0.8801 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8743 0.0 0.0047 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.9204 0.8869 0.8998 0.0 0.0 0.0 0.0 nan 0.5951 0.7715 0.0 0.4037 0.0296 nan 0.0012 0.0 0.0 0.6267 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.5790 0.0 0.0047 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7733 0.6728 0.7853 0.0 0.0 0.0 0.0
1.0271 1.3 520 1.0026 0.1693 0.2156 0.7668 nan 0.8177 0.9396 0.0 0.4255 0.0255 nan 0.0004 0.0 0.0 0.8799 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8736 0.0 0.0105 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.9017 0.8936 0.9169 0.0 0.0 0.0 0.0 nan 0.5912 0.7772 0.0 0.4068 0.0247 nan 0.0004 0.0 0.0 0.6212 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.5754 0.0 0.0104 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7784 0.6832 0.7782 0.0 0.0 0.0 0.0
1.1564 1.35 540 0.9947 0.1696 0.2148 0.7660 nan 0.7851 0.9423 0.0 0.4547 0.0382 nan 0.0004 0.0 0.0 0.8674 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8639 0.0 0.0128 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.9343 0.8540 0.9054 0.0 0.0 0.0 0.0 nan 0.5956 0.7720 0.0 0.4192 0.0359 nan 0.0004 0.0 0.0 0.6274 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.5781 0.0 0.0127 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7658 0.6675 0.7816 0.0 0.0 0.0 0.0
0.8783 1.4 560 0.9893 0.1700 0.2180 0.7636 nan 0.8414 0.9153 0.0 0.4471 0.0536 nan 0.0001 0.0 0.0 0.8736 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8714 0.0 0.0164 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.9007 0.9204 0.9170 0.0 0.0 0.0 0.0 nan 0.5617 0.7824 0.0 0.4156 0.0496 nan 0.0001 0.0 0.0 0.6400 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.5854 0.0 0.0163 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7741 0.6553 0.7882 0.0 0.0 0.0 0.0
1.282 1.45 580 0.9758 0.1717 0.2182 0.7692 nan 0.8157 0.9327 0.0 0.4624 0.0695 nan 0.0011 0.0 0.0 0.8994 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8471 0.0 0.0319 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.9419 0.8405 0.9216 0.0 0.0 0.0 0.0 nan 0.5872 0.7850 0.0 0.4214 0.0620 nan 0.0011 0.0 0.0 0.6214 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.6052 0.0 0.0316 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7636 0.6415 0.8024 0.0 0.0 0.0 0.0
2.0178 1.5 600 0.9683 0.1726 0.2195 0.7706 nan 0.8139 0.9362 0.0 0.4811 0.0607 nan 0.0021 0.0 0.0 0.8846 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8490 0.0 0.0508 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.9324 0.8641 0.9310 0.0 0.0 0.0 0.0 nan 0.5911 0.7843 0.0 0.4197 0.0553 nan 0.0021 0.0 0.0 0.6375 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.6044 0.0 0.0505 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7732 0.6395 0.7940 0.0 0.0 0.0 0.0
0.9306 1.55 620 0.9687 0.1727 0.2200 0.7706 nan 0.8171 0.9378 0.0 0.4601 0.0567 nan 0.0022 0.0 0.0 0.9099 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8513 0.0 0.0563 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.9183 0.8808 0.9294 0.0 0.0 0.0 0.0 nan 0.5877 0.7853 0.0 0.4123 0.0518 nan 0.0022 0.0 0.0 0.6194 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.5984 0.0 0.0555 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7828 0.6705 0.7895 0.0 0.0 0.0 0.0
1.1456 1.6 640 0.9496 0.1728 0.2190 0.7704 nan 0.8418 0.9310 0.0 0.4376 0.0602 nan 0.0044 0.0 0.0 0.8726 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8843 0.0 0.0329 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.9063 0.8883 0.9307 0.0 0.0 0.0 0.0 nan 0.5862 0.7886 0.0 0.4105 0.0552 nan 0.0044 0.0 0.0 0.6434 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.5812 0.0 0.0324 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7896 0.6753 0.7900 0.0 0.0 0.0 0.0
1.2237 1.65 660 0.9564 0.1712 0.2206 0.7665 nan 0.8216 0.9244 0.0 0.4856 0.0672 nan 0.0074 0.0 0.0 0.8700 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8779 0.0 0.0291 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8889 0.9380 0.9269 0.0 0.0 0.0 0.0 nan 0.5866 0.7847 0.0 0.4095 0.0602 nan 0.0074 0.0 0.0 0.6498 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.5852 0.0 0.0287 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7783 0.6227 0.7932 0.0 0.0 0.0 0.0
1.14 1.7 680 0.9590 0.1717 0.2212 0.7676 nan 0.8358 0.9203 0.0 0.4628 0.0661 nan 0.0141 0.0 0.0 0.8984 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8603 0.0 0.0397 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.9056 0.9322 0.9227 0.0 0.0 0.0 0.0 nan 0.5852 0.7859 0.0 0.4126 0.0597 nan 0.0139 0.0 0.0 0.6233 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.5932 0.0 0.0390 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7793 0.6376 0.7923 0.0 0.0 0.0 0.0
0.8264 1.75 700 0.9440 0.1736 0.2211 0.7704 nan 0.8423 0.9270 0.0 0.4383 0.0661 nan 0.0119 0.0 0.0 0.8952 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8535 0.0 0.0634 0.0000 0.0 nan 0.0 0.0 0.0 0.0 0.9183 0.9149 0.9229 0.0 0.0 0.0 0.0 nan 0.5849 0.7866 0.0 0.4085 0.0596 nan 0.0118 0.0 0.0 0.6285 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.6006 0.0 0.0625 0.0000 0.0 nan 0.0 0.0 0.0 0.0 0.7804 0.6604 0.7970 0.0 0.0 0.0 0.0
1.533 1.8 720 0.9434 0.1735 0.2211 0.7691 nan 0.8450 0.9235 0.0 0.4450 0.0624 nan 0.0092 0.0 0.0 0.8964 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8572 0.0 0.0659 0.0000 0.0 nan 0.0 0.0000 0.0 0.0 0.9106 0.9100 0.9305 0.0 0.0 0.0 0.0 nan 0.5785 0.7831 0.0 0.4092 0.0567 nan 0.0091 0.0 0.0 0.6284 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.5997 0.0 0.0649 0.0000 0.0 nan 0.0 0.0000 0.0 0.0 0.7861 0.6699 0.7942 0.0 0.0 0.0 0.0
1.4749 1.85 740 0.9403 0.1742 0.2195 0.7712 nan 0.8383 0.9330 0.0 0.4287 0.0651 nan 0.0085 0.0 0.0 0.8793 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8680 0.0 0.0522 0.0000 0.0 nan 0.0 0.0 0.0 0.0 0.9213 0.8967 0.9120 0.0 0.0 0.0 0.0 nan 0.5856 0.7830 0.0 0.4053 0.0589 nan 0.0084 0.0 0.0 0.6463 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.5982 0.0 0.0515 0.0000 0.0 nan 0.0 0.0 0.0 0.0 0.7840 0.6829 0.7962 0.0 0.0 0.0 0.0
0.7973 1.9 760 0.9333 0.1739 0.2203 0.7708 nan 0.8428 0.9280 0.0 0.4393 0.0688 nan 0.0111 0.0 0.0 0.8836 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8722 0.0 0.0422 0.0000 0.0 nan 0.0 0.0 0.0 0.0 0.9143 0.9051 0.9208 0.0 0.0 0.0 0.0 nan 0.5849 0.7849 0.0 0.4095 0.0621 nan 0.0109 0.0 0.0 0.6428 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.5950 0.0 0.0416 0.0000 0.0 nan 0.0 0.0 0.0 0.0 0.7877 0.6738 0.7970 0.0 0.0 0.0 0.0
0.8955 1.95 780 0.9455 0.1741 0.2208 0.7719 nan 0.8240 0.9347 0.0 0.4616 0.0726 nan 0.0138 0.0 0.0 0.8819 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8736 0.0 0.0362 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.9138 0.9057 0.9261 0.0 0.0 0.0 0.0 nan 0.5964 0.7838 0.0 0.4196 0.0651 nan 0.0137 0.0 0.0 0.6425 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.5920 0.0 0.0357 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.7871 0.6654 0.7968 0.0 0.0 0.0 0.0
1.0652 2.0 800 0.9415 0.1739 0.2202 0.7714 nan 0.8361 0.9327 0.0 0.4491 0.0618 nan 0.0106 0.0 0.0 0.8757 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.8775 0.0 0.0398 0.0000 0.0 nan 0.0 0.0 0.0 0.0 0.9075 0.9080 0.9280 0.0 0.0 0.0 0.0 nan 0.5895 0.7842 0.0 0.4140 0.0569 nan 0.0105 0.0 0.0 0.6473 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.5914 0.0 0.0393 0.0000 0.0 nan 0.0 0.0 0.0 0.0 0.7895 0.6699 0.7975 0.0 0.0 0.0 0.0

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.1
  • Tokenizers 0.19.1
Downloads last month
5
Safetensors
Model size
3.72M params
Tensor type
F32
·
Inference Examples
Image Segmentation
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for PushkarA07/segformer-b0-finetuned-segments-sidewalk-oct-22

Base model

nvidia/mit-b0
Finetuned
(314)
this model

Evaluation results

Metadata error: specify a dataset to view leaderboard