readme: ---
  license: apache-2.0
  tags:
  - image-segmentation
  - vision
  - generated_from_trainer
  model-index:
  - name: segformer-trainer-test-bis
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # segformer-trainer-test-bis
  
  This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the segments/sidewalk-semantic dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.3784
  - Mean Iou: 0.1424
  - Mean Accuracy: 0.1896
  - Overall Accuracy: 0.7288
  - Accuracy Unlabeled: nan
  - Accuracy Flat-road: 0.6651
  - Accuracy Flat-sidewalk: 0.9129
  - Accuracy Flat-crosswalk: 0.0
  - Accuracy Flat-cyclinglane: 0.5829
  - Accuracy Flat-parkingdriveway: 0.0184
  - Accuracy Flat-railtrack: 0.0
  - Accuracy Flat-curb: 0.0
  - Accuracy Human-person: 0.0
  - Accuracy Human-rider: 0.0
  - Accuracy Vehicle-car: 0.8322
  - 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: 0.8930
  - Accuracy Construction-door: 0.0
  - Accuracy Construction-wall: 0.0025
  - Accuracy Construction-fenceguardrail: 0.0
  - Accuracy Construction-bridge: 0.0
  - Accuracy Construction-tunnel: 0.0
  - Accuracy Construction-stairs: 0.0
  - Accuracy Object-pole: 0.0008
  - Accuracy Object-trafficsign: 0.0
  - Accuracy Object-trafficlight: 0.0
  - Accuracy Nature-vegetation: 0.8552
  - Accuracy Nature-terrain: 0.8507
  - Accuracy Sky: 0.8336
  - 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: 0.4712
  - Iou Flat-sidewalk: 0.7651
  - Iou Flat-crosswalk: 0.0
  - Iou Flat-cyclinglane: 0.5216
  - Iou Flat-parkingdriveway: 0.0178
  - Iou Flat-railtrack: 0.0
  - Iou Flat-curb: 0.0
  - Iou Human-person: 0.0
  - Iou Human-rider: 0.0
  - Iou Vehicle-car: 0.5696
  - 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: 0.4716
  - Iou Construction-door: 0.0
  - Iou Construction-wall: 0.0024
  - Iou Construction-fenceguardrail: 0.0
  - Iou Construction-bridge: 0.0
  - Iou Construction-tunnel: 0.0
  - Iou Construction-stairs: 0.0
  - Iou Object-pole: 0.0008
  - Iou Object-trafficsign: 0.0
  - Iou Object-trafficlight: 0.0
  - Iou Nature-vegetation: 0.6813
  - Iou Nature-terrain: 0.5513
  - Iou Sky: 0.7873
  - 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: 5e-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: linear
  - num_epochs: 10.0
  
  ### Training results
  
  
  
  ### Framework versions
  
  - Transformers 4.19.0.dev0
  - Pytorch 1.11.0+cu113
  - Datasets 2.0.0
  - Tokenizers 0.11.6
  