pimupsorn/my-fine-tuned-model

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my-fine-tuned-model

This model is a fine-tuned version of nvidia/segformer-b1-finetuned-ade-512-512 on the segments/sidewalk-semantic dataset. It achieves the following results on the evaluation set:

• —Loss: 1.6885
• —Mean Iou: 0.1644
• —Mean Accuracy: 0.2067
• —Overall Accuracy: 0.7604
• —Accuracy Unlabeled: nan
• —Accuracy Flat-road: 0.9243
• —Accuracy Flat-sidewalk: 0.9308
• —Accuracy Flat-crosswalk: 0.0
• —Accuracy Flat-cyclinglane: 0.3658
• —Accuracy Flat-parkingdriveway: 0.0
• —Accuracy Flat-railtrack: nan
• —Accuracy Flat-curb: 0.0
• —Accuracy Human-person: 0.0
• —Accuracy Human-rider: 0.0
• —Accuracy Vehicle-car: 0.8785
• —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: 0.8929
• —Accuracy Construction-door: 0.0
• —Accuracy Construction-wall: 0.0
• —Accuracy Construction-fenceguardrail: 0.0
• —Accuracy Construction-bridge: 0.0
• —Accuracy Construction-tunnel: nan
• —Accuracy Construction-stairs: 0.0
• —Accuracy Object-pole: 0.0
• —Accuracy Object-trafficsign: 0.0
• —Accuracy Object-trafficlight: 0.0
• —Accuracy Nature-vegetation: 0.9517
• —Accuracy Nature-terrain: 0.5597
• —Accuracy Sky: 0.9033
• —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: 0.5694
• —Iou Flat-sidewalk: 0.7974
• —Iou Flat-crosswalk: 0.0
• —Iou Flat-cyclinglane: 0.3462
• —Iou Flat-parkingdriveway: 0.0
• —Iou Flat-railtrack: nan
• —Iou Flat-curb: 0.0
• —Iou Human-person: 0.0
• —Iou Human-rider: 0.0
• —Iou Vehicle-car: 0.6909
• —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: 0.5876
• —Iou Construction-door: 0.0
• —Iou Construction-wall: 0.0
• —Iou Construction-fenceguardrail: 0.0
• —Iou Construction-bridge: 0.0
• —Iou Construction-tunnel: nan
• —Iou Construction-stairs: 0.0
• —Iou Object-pole: 0.0
• —Iou Object-trafficsign: 0.0
• —Iou Object-trafficlight: 0.0
• —Iou Nature-vegetation: 0.7378
• —Iou Nature-terrain: 0.5221
• —Iou Sky: 0.8453
• —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
• —trainbatchsize: 8
• —evalbatchsize: 8
• —seed: 42
• —optimizer: Use adamwtorch with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
• —lrschedulertype: linear
• —num_epochs: 2

Training results

Framework versions

• —Transformers 4.48.0
• —Pytorch 2.1.1+cu118
• —Datasets 3.2.0
• —Tokenizers 0.21.0