mit-b0-finetuned-sidewalk-imagery-clone

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Lit4pCol4b/mit-b0-finetuned-sidewalk-imagery-clone

This model is a fine-tuned version of nvidia/mit-b0 on an unknown dataset. It achieves the following results on the evaluation set:

• Train Loss: 0.2018
• Validation Loss: 0.4701
• Validation Mean Iou: 0.3452
• Validation Mean Accuracy: 0.4169
• Validation Overall Accuracy: 0.8735
• Validation Accuracy Unlabeled: nan
• Validation Accuracy Flat-road: 0.7035
• Validation Accuracy Flat-sidewalk: 0.9218
• Validation Accuracy Flat-crosswalk: 0.0
• Validation Accuracy Flat-cyclinglane: 0.9869
• Validation Accuracy Flat-parkingdriveway: 0.0
• Validation Accuracy Flat-railtrack: nan
• Validation Accuracy Flat-curb: 0.0056
• Validation Accuracy Human-person: nan
• Validation Accuracy Human-rider: nan
• Validation Accuracy Vehicle-car: 0.9448
• Validation Accuracy Vehicle-truck: nan
• Validation Accuracy Vehicle-bus: nan
• Validation Accuracy Vehicle-tramtrain: nan
• Validation Accuracy Vehicle-motorcycle: nan
• Validation Accuracy Vehicle-bicycle: nan
• Validation Accuracy Vehicle-caravan: nan
• Validation Accuracy Vehicle-cartrailer: nan
• Validation Accuracy Construction-building: 0.9299
• Validation Accuracy Construction-door: 0.0
• Validation Accuracy Construction-wall: 0.0
• Validation Accuracy Construction-fenceguardrail: nan
• Validation Accuracy Construction-bridge: 0.0
• Validation Accuracy Construction-tunnel: nan
• Validation Accuracy Construction-stairs: nan
• Validation Accuracy Object-pole: 0.0361
• Validation Accuracy Object-trafficsign: 0.0
• Validation Accuracy Object-trafficlight: nan
• Validation Accuracy Nature-vegetation: 0.9439
• Validation Accuracy Nature-terrain: 0.6436
• Validation Accuracy Sky: 0.9719
• Validation Accuracy Void-ground: nan
• Validation Accuracy Void-dynamic: nan
• Validation Accuracy Void-static: 0.0
• Validation Accuracy Void-unclear: nan
• Validation Iou Unlabeled: nan
• Validation Iou Flat-road: 0.6208
• Validation Iou Flat-sidewalk: 0.6677
• Validation Iou Flat-crosswalk: 0.0
• Validation Iou Flat-cyclinglane: 0.9719
• Validation Iou Flat-parkingdriveway: 0.0
• Validation Iou Flat-railtrack: nan
• Validation Iou Flat-curb: 0.0049
• Validation Iou Human-person: nan
• Validation Iou Human-rider: nan
• Validation Iou Vehicle-car: 0.8013
• Validation Iou Vehicle-truck: nan
• Validation Iou Vehicle-bus: nan
• Validation Iou Vehicle-tramtrain: nan
• Validation Iou Vehicle-motorcycle: nan
• Validation Iou Vehicle-bicycle: nan
• Validation Iou Vehicle-caravan: nan
• Validation Iou Vehicle-cartrailer: nan
• Validation Iou Construction-building: 0.8179
• Validation Iou Construction-door: 0.0
• Validation Iou Construction-wall: 0.0
• Validation Iou Construction-fenceguardrail: 0.0
• Validation Iou Construction-bridge: 0.0
• Validation Iou Construction-tunnel: nan
• Validation Iou Construction-stairs: nan
• Validation Iou Object-pole: 0.0354
• Validation Iou Object-trafficsign: 0.0
• Validation Iou Object-trafficlight: nan
• Validation Iou Nature-vegetation: 0.8747
• Validation Iou Nature-terrain: 0.4693
• Validation Iou Sky: 0.9491
• Validation Iou Void-ground: nan
• Validation Iou Void-dynamic: nan
• Validation Iou Void-static: 0.0
• Validation Iou Void-unclear: nan
• Epoch: 49

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:

• optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': 6e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
• training_precision: float32

Training results

The model card is truncated. Read the rest on Hugging Face.