segformer-b0-finetuned-segments-sidewalk-123
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
- lr_scheduler_type: linear
- num_epochs: 50
Framework versions
- Transformers 4.35.0
- Pytorch 2.2.0+cpu
- Datasets 2.14.6
- Tokenizers 0.14.1
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