segformer-trainer-test-bis

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: 1.3784
• 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