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:
eval_loss: 0.5603
eval_mean_iou: 0.3194
eval_mean_accuracy: 0.3797
eval_overall_accuracy: 0.8649
eval_accuracy_unlabeled: nan
eval_accuracy_flat-road: 0.8652
eval_accuracy_flat-sidewalk: 0.9642
eval_accuracy_flat-crosswalk: 0.6083
eval_accuracy_flat-cyclinglane: 0.7173
eval_accuracy_flat-parkingdriveway: 0.5189
eval_accuracy_flat-railtrack: 0.0
eval_accuracy_flat-curb: 0.6089
eval_accuracy_human-person: 0.8421
eval_accuracy_human-rider: 0.0
eval_accuracy_vehicle-car: 0.9347
eval_accuracy_vehicle-truck: 0.0
eval_accuracy_vehicle-bus: 0.0
eval_accuracy_vehicle-tramtrain: 0.0
eval_accuracy_vehicle-motorcycle: 0.0
eval_accuracy_vehicle-bicycle: 0.7877
eval_accuracy_vehicle-caravan: 0.0
eval_accuracy_vehicle-cartrailer: 0.0
eval_accuracy_construction-building: 0.9288
eval_accuracy_construction-door: 0.0851
eval_accuracy_construction-wall: 0.4696
eval_accuracy_construction-fenceguardrail: 0.4756
eval_accuracy_construction-bridge: 0.0
eval_accuracy_construction-tunnel: nan
eval_accuracy_construction-stairs: 0.0047
eval_accuracy_object-pole: 0.3599
eval_accuracy_object-trafficsign: 0.0028
eval_accuracy_object-trafficlight: 0.0
eval_accuracy_nature-vegetation: 0.9419
eval_accuracy_nature-terrain: 0.8921
eval_accuracy_sky: 0.9773
eval_accuracy_void-ground: 0.0003
eval_accuracy_void-dynamic: 0.1852
eval_accuracy_void-static: 0.3603
eval_accuracy_void-unclear: 0.0
eval_iou_unlabeled: nan
eval_iou_flat-road: 0.7774
eval_iou_flat-sidewalk: 0.8659
eval_iou_flat-crosswalk: 0.4889
eval_iou_flat-cyclinglane: 0.6488
eval_iou_flat-parkingdriveway: 0.4072
eval_iou_flat-railtrack: 0.0
eval_iou_flat-curb: 0.4944
eval_iou_human-person: 0.6064
eval_iou_human-rider: 0.0
eval_iou_vehicle-car: 0.8283
eval_iou_vehicle-truck: 0.0
eval_iou_vehicle-bus: 0.0
eval_iou_vehicle-tramtrain: 0.0
eval_iou_vehicle-motorcycle: 0.0
eval_iou_vehicle-bicycle: 0.5105
eval_iou_vehicle-caravan: 0.0
eval_iou_vehicle-cartrailer: 0.0
eval_iou_construction-building: 0.7458
eval_iou_construction-door: 0.0760
eval_iou_construction-wall: 0.4006
eval_iou_construction-fenceguardrail: 0.3288
eval_iou_construction-bridge: 0.0
eval_iou_construction-tunnel: nan
eval_iou_construction-stairs: 0.0047
eval_iou_object-pole: 0.2789
eval_iou_object-trafficsign: 0.0027
eval_iou_object-trafficlight: 0.0
eval_iou_nature-vegetation: 0.8781
eval_iou_nature-terrain: 0.8170
eval_iou_sky: 0.9417
eval_iou_void-ground: 0.0002
eval_iou_void-dynamic: 0.1706
eval_iou_void-static: 0.2686
eval_iou_void-unclear: 0.0
eval_runtime: 246.8492
eval_samples_per_second: 0.81
eval_steps_per_second: 0.405
epoch: 15.45
step: 6180
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
train_batch_size: 2
eval_batch_size: 2
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
