--- library_name: transformers license: other base_model: nvidia/mit-b0 tags: - vision - image-segmentation - generated_from_trainer model-index: - name: segformer-b0-finetuned-segments-sidewalk-2 results: [] --- # segformer-b0-finetuned-segments-sidewalk-2 This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the zhaoqiao0120/sidewalk-imagery3 dataset. It achieves the following results on the evaluation set: - Loss: 2.3484 - Mean Iou: 0.1125 - Mean Accuracy: 0.4713 - Overall Accuracy: 0.7748 - Accuracy Unlabeled: nan - Accuracy Flat-road: 0.7626 - Accuracy Flat-sidewalk: 0.0 - Accuracy Flat-crosswalk: nan - Accuracy Flat-cyclinglane: 0.9544 - Accuracy Flat-parkingdriveway: nan - Accuracy Flat-railtrack: 0.1682 - Accuracy Flat-curb: nan - Accuracy Human-person: nan - Accuracy Human-rider: nan - Accuracy Vehicle-car: nan - Accuracy Vehicle-truck: nan - Accuracy Vehicle-bus: nan - Accuracy Vehicle-tramtrain: nan - Accuracy Vehicle-motorcycle: nan - Accuracy Vehicle-bicycle: nan - Accuracy Vehicle-caravan: nan - Accuracy Vehicle-cartrailer: nan - Accuracy Construction-building: nan - Accuracy Construction-door: nan - Accuracy Construction-wall: nan - Accuracy Construction-fenceguardrail: nan - Accuracy Construction-bridge: nan - Accuracy Construction-tunnel: nan - Accuracy Construction-stairs: nan - Accuracy Object-pole: nan - Accuracy Object-trafficsign: nan - Accuracy Object-trafficlight: nan - Accuracy Nature-vegetation: nan - Accuracy Nature-terrain: nan - Accuracy Sky: nan - Accuracy Void-ground: nan - Accuracy Void-dynamic: nan - Accuracy Void-static: nan - Accuracy Void-unclear: nan - Iou Unlabeled: 0.0 - Iou Flat-road: 0.7426 - Iou Flat-sidewalk: 0.0 - Iou Flat-crosswalk: nan - Iou Flat-cyclinglane: 0.4695 - Iou Flat-parkingdriveway: nan - Iou Flat-railtrack: 0.1375 - Iou Flat-curb: 0.0 - Iou Human-person: nan - Iou Human-rider: nan - Iou Vehicle-car: nan - Iou Vehicle-truck: nan - Iou Vehicle-bus: 0.0 - Iou Vehicle-tramtrain: nan - Iou Vehicle-motorcycle: nan - Iou Vehicle-bicycle: nan - Iou Vehicle-caravan: 0.0 - Iou Vehicle-cartrailer: nan - Iou Construction-building: 0.0 - Iou Construction-door: nan - Iou Construction-wall: nan - Iou Construction-fenceguardrail: nan - Iou Construction-bridge: nan - Iou Construction-tunnel: nan - Iou Construction-stairs: nan - Iou Object-pole: nan - Iou Object-trafficsign: nan - Iou Object-trafficlight: 0.0 - Iou Nature-vegetation: 0.0 - Iou Nature-terrain: nan - Iou Sky: nan - Iou Void-ground: 0.0 - Iou Void-dynamic: nan - Iou Void-static: nan - Iou Void-unclear: nan ## 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 ### Training results | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Unlabeled | Accuracy Flat-road | Accuracy Flat-sidewalk | Accuracy Flat-crosswalk | Accuracy Flat-cyclinglane | Accuracy Flat-parkingdriveway | Accuracy Flat-railtrack | Accuracy Flat-curb | Accuracy Human-person | Accuracy Human-rider | Accuracy Vehicle-car | Accuracy Vehicle-truck | Accuracy Vehicle-bus | Accuracy Vehicle-tramtrain | Accuracy Vehicle-motorcycle | Accuracy Vehicle-bicycle | Accuracy Vehicle-caravan | Accuracy Vehicle-cartrailer | Accuracy Construction-building | Accuracy Construction-door | Accuracy Construction-wall | Accuracy Construction-fenceguardrail | Accuracy Construction-bridge | Accuracy Construction-tunnel | Accuracy Construction-stairs | Accuracy Object-pole | Accuracy Object-trafficsign | Accuracy Object-trafficlight | Accuracy Nature-vegetation | Accuracy Nature-terrain | Accuracy Sky | Accuracy Void-ground | Accuracy Void-dynamic | Accuracy Void-static | Accuracy Void-unclear | Iou Unlabeled | Iou Flat-road | Iou Flat-sidewalk | Iou Flat-crosswalk | Iou Flat-cyclinglane | Iou Flat-parkingdriveway | Iou Flat-railtrack | Iou Flat-curb | Iou Human-person | Iou Human-rider | Iou Vehicle-car | Iou Vehicle-truck | Iou Vehicle-bus | Iou Vehicle-tramtrain | Iou Vehicle-motorcycle | Iou Vehicle-bicycle | Iou Vehicle-caravan | Iou Vehicle-cartrailer | Iou Construction-building | Iou Construction-door | Iou Construction-wall | Iou Construction-fenceguardrail | Iou Construction-bridge | Iou Construction-tunnel | Iou Construction-stairs | Iou Object-pole | Iou Object-trafficsign | Iou Object-trafficlight | Iou Nature-vegetation | Iou Nature-terrain | Iou Sky | Iou Void-ground | Iou Void-dynamic | Iou Void-static | Iou Void-unclear | 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| 2.7207 | 10.0 | 20 | 3.2303 | 0.0523 | 0.4061 | 0.6929 | nan | 0.6686 | 0.0 | nan | 0.9330 | nan | 0.0227 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 0.0 | 0.6598 | 0.0 | 0.0 | 0.4724 | 0.0 | 0.0189 | 0.0 | 0.0 | nan | 0.0 | nan | 0.0 | 0.0 | nan | nan | 0.0 | nan | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | nan | 0.0 | 0.0 | nan | 0.0 | nan | nan | 0.0 | nan | nan | 0.0 | | 2.4135 | 20.0 | 40 | 2.7217 | 0.0745 | 0.4526 | 0.7774 | nan | 0.7740 | 0.0 | nan | 0.9332 | nan | 0.1031 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 0.0 | 0.7497 | 0.0 | 0.0 | 0.5036 | nan | 0.0871 | 0.0 | 0.0 | nan | 0.0 | nan | 0.0 | 0.0 | nan | nan | 0.0 | nan | 0.0 | nan | nan | nan | nan | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | nan | nan | nan | | 2.1972 | 30.0 | 60 | 2.4738 | 0.0930 | 0.4666 | 0.8011 | nan | 0.8060 | 0.0 | nan | 0.9207 | nan | 0.1396 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 0.0 | 0.7786 | 0.0 | 0.0 | 0.5117 | nan | 0.1051 | 0.0 | 0.0 | nan | nan | nan | 0.0 | nan | nan | nan | 0.0 | 0.0 | 0.0 | nan | nan | nan | nan | nan | nan | nan | nan | 0.0 | 0.0 | nan | nan | 0.0 | nan | nan | nan | | 2.0612 | 40.0 | 80 | 2.3500 | 0.1074 | 0.4754 | 0.7908 | nan | 0.7841 | 0.0 | nan | 0.9514 | nan | 0.1660 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 0.0 | 0.7615 | 0.0 | nan | 0.4904 | nan | 0.1442 | 0.0 | nan | nan | nan | nan | 0.0 | nan | nan | nan | 0.0 | 0.0 | 0.0 | nan | nan | nan | nan | nan | nan | nan | nan | 0.0 | 0.0 | nan | nan | 0.0 | nan | nan | nan | | 1.9932 | 50.0 | 100 | 2.3484 | 0.1125 | 0.4713 | 0.7748 | nan | 0.7626 | 0.0 | nan | 0.9544 | nan | 0.1682 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 0.0 | 0.7426 | 0.0 | nan | 0.4695 | nan | 0.1375 | 0.0 | nan | nan | nan | nan | 0.0 | nan | nan | nan | 0.0 | nan | 0.0 | nan | nan | nan | nan | nan | nan | nan | nan | 0.0 | 0.0 | nan | nan | 0.0 | nan | nan | nan | ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.1+cpu - Datasets 2.21.0 - Tokenizers 0.19.1