metadata

license: other
base_model: nvidia/mit-b0
tags:
  - vision
  - image-segmentation
  - generated_from_trainer
model-index:
  - name: segformer-b0-finetuned-segments-sidewalk-oct-22
    results: []

segformer-b0-finetuned-segments-sidewalk-oct-22

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: 0.5925
eval_mean_iou: 0.2753
eval_mean_accuracy: 0.3327
eval_overall_accuracy: 0.8401
eval_accuracy_unlabeled: nan
eval_accuracy_flat-road: 0.8405
eval_accuracy_flat-sidewalk: 0.9533
eval_accuracy_flat-crosswalk: 0.6601
eval_accuracy_flat-cyclinglane: 0.7992
eval_accuracy_flat-parkingdriveway: 0.5578
eval_accuracy_flat-railtrack: nan
eval_accuracy_flat-curb: 0.4836
eval_accuracy_human-person: 0.6161
eval_accuracy_human-rider: 0.0
eval_accuracy_vehicle-car: 0.9299
eval_accuracy_vehicle-truck: 0.0
eval_accuracy_vehicle-bus: 0.0
eval_accuracy_vehicle-tramtrain: nan
eval_accuracy_vehicle-motorcycle: 0.0
eval_accuracy_vehicle-bicycle: 0.0003
eval_accuracy_vehicle-caravan: 0.0
eval_accuracy_vehicle-cartrailer: 0.0
eval_accuracy_construction-building: 0.8840
eval_accuracy_construction-door: 0.0
eval_accuracy_construction-wall: 0.3660
eval_accuracy_construction-fenceguardrail: 0.3076
eval_accuracy_construction-bridge: 0.0
eval_accuracy_construction-tunnel: 0.0
eval_accuracy_construction-stairs: 0.0
eval_accuracy_object-pole: 0.2707
eval_accuracy_object-trafficsign: 0.0
eval_accuracy_object-trafficlight: 0.0
eval_accuracy_nature-vegetation: 0.9456
eval_accuracy_nature-terrain: 0.8426
eval_accuracy_sky: 0.9610
eval_accuracy_void-ground: 0.0
eval_accuracy_void-dynamic: 0.0
eval_accuracy_void-static: 0.2296
eval_accuracy_void-unclear: 0.0
eval_iou_unlabeled: nan
eval_iou_flat-road: 0.7077
eval_iou_flat-sidewalk: 0.8656
eval_iou_flat-crosswalk: 0.5379
eval_iou_flat-cyclinglane: 0.7062
eval_iou_flat-parkingdriveway: 0.4285
eval_iou_flat-railtrack: nan
eval_iou_flat-curb: 0.3675
eval_iou_human-person: 0.3194
eval_iou_human-rider: 0.0
eval_iou_vehicle-car: 0.7878
eval_iou_vehicle-truck: 0.0
eval_iou_vehicle-bus: 0.0
eval_iou_vehicle-tramtrain: nan
eval_iou_vehicle-motorcycle: 0.0
eval_iou_vehicle-bicycle: 0.0003
eval_iou_vehicle-caravan: 0.0
eval_iou_vehicle-cartrailer: 0.0
eval_iou_construction-building: 0.6784
eval_iou_construction-door: 0.0
eval_iou_construction-wall: 0.2711
eval_iou_construction-fenceguardrail: 0.2716
eval_iou_construction-bridge: 0.0
eval_iou_construction-tunnel: 0.0
eval_iou_construction-stairs: 0.0
eval_iou_object-pole: 0.2059
eval_iou_object-trafficsign: 0.0
eval_iou_object-trafficlight: 0.0
eval_iou_nature-vegetation: 0.8358
eval_iou_nature-terrain: 0.7375
eval_iou_sky: 0.9064
eval_iou_void-ground: 0.0
eval_iou_void-dynamic: 0.0
eval_iou_void-static: 0.1826
eval_iou_void-unclear: 0.0
eval_runtime: 11.1228
eval_samples_per_second: 17.981
eval_steps_per_second: 2.248
epoch: 17.4
step: 1740

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 20

Framework versions

Transformers 4.36.2
Pytorch 2.1.2+cu121
Datasets 2.16.1
Tokenizers 0.15.0