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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:

  • eval_loss: 1.2015
  • eval_mean_iou: 0.1448
  • eval_mean_accuracy: 0.1852
  • eval_overall_accuracy: 0.7367
  • eval_accuracy_unlabeled: nan
  • eval_accuracy_flat-road: 0.7598
  • eval_accuracy_flat-sidewalk: 0.9596
  • eval_accuracy_flat-crosswalk: 0.0001
  • eval_accuracy_flat-cyclinglane: 0.3703
  • eval_accuracy_flat-parkingdriveway: 0.0018
  • eval_accuracy_flat-railtrack: 0.0
  • eval_accuracy_flat-curb: 0.0
  • eval_accuracy_human-person: 0.0
  • eval_accuracy_human-rider: 0.0
  • eval_accuracy_vehicle-car: 0.8814
  • eval_accuracy_vehicle-truck: 0.0
  • eval_accuracy_vehicle-bus: 0.0
  • eval_accuracy_vehicle-tramtrain: 0.0
  • eval_accuracy_vehicle-motorcycle: 0.0
  • eval_accuracy_vehicle-bicycle: 0.0
  • eval_accuracy_vehicle-caravan: 0.0
  • eval_accuracy_vehicle-cartrailer: 0.0
  • eval_accuracy_construction-building: 0.8832
  • eval_accuracy_construction-door: 0.0
  • eval_accuracy_construction-wall: 0.0
  • eval_accuracy_construction-fenceguardrail: 0.0
  • eval_accuracy_construction-bridge: 0.0
  • eval_accuracy_construction-tunnel: 0.0
  • eval_accuracy_construction-stairs: 0.0
  • eval_accuracy_object-pole: 0.0
  • eval_accuracy_object-trafficsign: 0.0
  • eval_accuracy_object-trafficlight: 0.0
  • eval_accuracy_nature-vegetation: 0.9387
  • eval_accuracy_nature-terrain: 0.6141
  • eval_accuracy_sky: 0.8885
  • eval_accuracy_void-ground: 0.0
  • eval_accuracy_void-dynamic: 0.0
  • eval_accuracy_void-static: 0.0
  • eval_accuracy_void-unclear: 0.0
  • eval_iou_unlabeled: nan
  • eval_iou_flat-road: 0.5640
  • eval_iou_flat-sidewalk: 0.7376
  • eval_iou_flat-crosswalk: 0.0001
  • eval_iou_flat-cyclinglane: 0.3544
  • eval_iou_flat-parkingdriveway: 0.0018
  • eval_iou_flat-railtrack: 0.0
  • eval_iou_flat-curb: 0.0
  • eval_iou_human-person: 0.0
  • eval_iou_human-rider: 0.0
  • eval_iou_vehicle-car: 0.5854
  • eval_iou_vehicle-truck: 0.0
  • eval_iou_vehicle-bus: 0.0
  • eval_iou_vehicle-tramtrain: 0.0
  • eval_iou_vehicle-motorcycle: 0.0
  • eval_iou_vehicle-bicycle: 0.0
  • eval_iou_vehicle-caravan: 0.0
  • eval_iou_vehicle-cartrailer: 0.0
  • eval_iou_construction-building: 0.5548
  • eval_iou_construction-door: 0.0
  • eval_iou_construction-wall: 0.0
  • eval_iou_construction-fenceguardrail: 0.0
  • eval_iou_construction-bridge: 0.0
  • eval_iou_construction-tunnel: 0.0
  • eval_iou_construction-stairs: 0.0
  • eval_iou_object-pole: 0.0
  • eval_iou_object-trafficsign: 0.0
  • eval_iou_object-trafficlight: 0.0
  • eval_iou_nature-vegetation: 0.7404
  • eval_iou_nature-terrain: 0.5555
  • eval_iou_sky: 0.8277
  • eval_iou_void-ground: 0.0
  • eval_iou_void-dynamic: 0.0
  • eval_iou_void-static: 0.0
  • eval_iou_void-unclear: 0.0
  • eval_runtime: 35.456
  • eval_samples_per_second: 5.641
  • eval_steps_per_second: 0.282
  • epoch: 0.5
  • step: 20

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: 20
  • eval_batch_size: 20
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 50

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2
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