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metadata
license: apache-2.0
tags:
  - image-segmentation
  - vision
  - generated_from_trainer
model-index:
  - name: segformer-finetuned-sidewalk-50-epochs
    results: []

segformer-finetuned-sidewalk-50-epochs

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: 1.0025
  • Mean Iou: 0.1696
  • Mean Accuracy: 0.2225
  • Overall Accuracy: 0.7429
  • Accuracy Unlabeled: nan
  • Accuracy Flat-road: 0.6270
  • Accuracy Flat-sidewalk: 0.9313
  • Accuracy Flat-crosswalk: 0.0019
  • Accuracy Flat-cyclinglane: 0.7908
  • Accuracy Flat-parkingdriveway: 0.1035
  • Accuracy Flat-railtrack: nan
  • Accuracy Flat-curb: 0.1277
  • Accuracy Human-person: 0.0
  • Accuracy Human-rider: 0.0
  • Accuracy Vehicle-car: 0.8867
  • 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: 0.8696
  • Accuracy Construction-door: 0.0
  • Accuracy Construction-wall: 0.0037
  • Accuracy Construction-fenceguardrail: 0.0
  • Accuracy Construction-bridge: 0.0
  • Accuracy Construction-tunnel: nan
  • Accuracy Construction-stairs: 0.0
  • Accuracy Object-pole: 0.0048
  • Accuracy Object-trafficsign: 0.0
  • Accuracy Object-trafficlight: 0.0
  • Accuracy Nature-vegetation: 0.9035
  • Accuracy Nature-terrain: 0.7721
  • Accuracy Sky: 0.8740
  • 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: 0.4815
  • Iou Flat-sidewalk: 0.7837
  • Iou Flat-crosswalk: 0.0019
  • Iou Flat-cyclinglane: 0.5434
  • Iou Flat-parkingdriveway: 0.0847
  • Iou Flat-railtrack: nan
  • Iou Flat-curb: 0.0991
  • Iou Human-person: 0.0
  • Iou Human-rider: 0.0
  • Iou Vehicle-car: 0.5682
  • 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: 0.5254
  • Iou Construction-door: 0.0
  • Iou Construction-wall: 0.0036
  • Iou Construction-fenceguardrail: 0.0
  • Iou Construction-bridge: 0.0
  • Iou Construction-tunnel: nan
  • Iou Construction-stairs: 0.0
  • Iou Object-pole: 0.0048
  • Iou Object-trafficsign: 0.0
  • Iou Object-trafficlight: 0.0
  • Iou Nature-vegetation: 0.7442
  • Iou Nature-terrain: 0.5920
  • Iou Sky: 0.8243
  • 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: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: polynomial
  • training_steps: 1000

Training results

Framework versions

  • Transformers 4.19.0.dev0
  • Pytorch 1.11.0+cu113
  • Datasets 2.0.0
  • Tokenizers 0.11.6