iammartian0/RoadSense_High_Definition_Street_Segmentation

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segformer-b0-finetuned-segments-sidewalk

This model is a fine-tuned version of nvidia/mit-b0 on the None dataset. It achieves the following results on the evaluation set:

• —Loss: 0.5449
• —Mean Iou: 0.3292
• —Mean Accuracy: 0.3907
• —Overall Accuracy: 0.8555
• —Accuracy Unlabeled: nan
• —Accuracy Flat-road: 0.8585
• —Accuracy Flat-sidewalk: 0.9611
• —Accuracy Flat-crosswalk: 0.7673
• —Accuracy Flat-cyclinglane: 0.8223
• —Accuracy Flat-parkingdriveway: 0.5127
• —Accuracy Flat-railtrack: nan
• —Accuracy Flat-curb: 0.4937
• —Accuracy Human-person: 0.7164
• —Accuracy Human-rider: 0.0
• —Accuracy Vehicle-car: 0.9332
• —Accuracy Vehicle-truck: 0.0
• —Accuracy Vehicle-bus: nan
• —Accuracy Vehicle-tramtrain: nan
• —Accuracy Vehicle-motorcycle: 0.0
• —Accuracy Vehicle-bicycle: 0.3858
• —Accuracy Vehicle-caravan: 0.0
• —Accuracy Vehicle-cartrailer: 0.0
• —Accuracy Construction-building: 0.9040
• —Accuracy Construction-door: 0.0
• —Accuracy Construction-wall: 0.5848
• —Accuracy Construction-fenceguardrail: 0.4417
• —Accuracy Construction-bridge: 0.0
• —Accuracy Construction-tunnel: nan
• —Accuracy Construction-stairs: 0.0
• —Accuracy Object-pole: 0.3156
• —Accuracy Object-trafficsign: 0.0
• —Accuracy Object-trafficlight: 0.0
• —Accuracy Nature-vegetation: 0.9413
• —Accuracy Nature-terrain: 0.8456
• —Accuracy Sky: 0.9600
• —Accuracy Void-ground: 0.0
• —Accuracy Void-dynamic: 0.0
• —Accuracy Void-static: 0.2780
• —Accuracy Void-unclear: 0.0
• —Iou Unlabeled: nan
• —Iou Flat-road: 0.7447
• —Iou Flat-sidewalk: 0.8755
• —Iou Flat-crosswalk: 0.6244
• —Iou Flat-cyclinglane: 0.7325
• —Iou Flat-parkingdriveway: 0.3997
• —Iou Flat-railtrack: nan
• —Iou Flat-curb: 0.3974
• —Iou Human-person: 0.4985
• —Iou Human-rider: 0.0
• —Iou Vehicle-car: 0.7798
• —Iou Vehicle-truck: 0.0
• —Iou Vehicle-bus: nan
• —Iou Vehicle-tramtrain: nan
• —Iou Vehicle-motorcycle: 0.0
• —Iou Vehicle-bicycle: 0.2904
• —Iou Vehicle-caravan: 0.0
• —Iou Vehicle-cartrailer: 0.0
• —Iou Construction-building: 0.7233
• —Iou Construction-door: 0.0
• —Iou Construction-wall: 0.4555
• —Iou Construction-fenceguardrail: 0.3734
• —Iou Construction-bridge: 0.0
• —Iou Construction-tunnel: nan
• —Iou Construction-stairs: 0.0
• —Iou Object-pole: 0.2484
• —Iou Object-trafficsign: 0.0
• —Iou Object-trafficlight: 0.0
• —Iou Nature-vegetation: 0.8451
• —Iou Nature-terrain: 0.7346
• —Iou Sky: 0.9161
• —Iou Void-ground: 0.0
• —Iou Void-dynamic: 0.0
• —Iou Void-static: 0.2359
• —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
• —trainbatchsize: 8
• —evalbatchsize: 8
• —seed: 42
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —num_epochs: 20

Training results

Framework versions

• —Transformers 4.30.2
• —Pytorch 2.0.1+cu118
• —Datasets 2.13.1
• —Tokenizers 0.13.3