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segformer-b0-finetuned-segments-sidewalk-oct-22
samitizerxu/segformer-b0-finetuned-segments-sidewalk-oct-22
segformer-b0-finetuned-segments-sidewalk-oct-22 is a image segmentation model from samitizerxu. Use it for the image segmentation task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as other.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Image Segmentation
- Library
- transformers
- License
- other
- Model type
- segformer
- Access
- Public
- Created
- Jan 15, 2024
- Updated
- Jan 16, 2024
- SHA
- 2dd465f0
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
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
- Task
- Image Segmentation
- Library
- transformers
- Type
- segformer
- License
- other
- Created
- Jan 15, 2024
- Updated
- Jan 16, 2024