--- library_name: transformers base_model: segformer-b0-finetuned-ade-512-512 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 [segformer-b0-finetuned-ade-512-512](https://huggingface.co/segformer-b0-finetuned-ade-512-512) on the segments/sidewalk-semantic dataset. It achieves the following results on the evaluation set: - Loss: 1.5824 - Mean Iou: 0.0054 - Mean Accuracy: 0.0686 - Overall Accuracy: 0.0400 - Accuracy Unlabeled: nan - Accuracy Flat-road: 0.7137 - Accuracy Flat-sidewalk: 0.0 - Accuracy Flat-crosswalk: 0.0005 - Accuracy Flat-cyclinglane: nan - Accuracy Flat-parkingdriveway: 0.0 - Accuracy Flat-railtrack: 0.0 - Accuracy Flat-curb: 0.0 - Accuracy Human-person: 0.0 - Accuracy Human-rider: 0.0947 - Accuracy Vehicle-car: 0.0 - Accuracy Vehicle-truck: nan - Accuracy Vehicle-bus: 0.0 - Accuracy Vehicle-tramtrain: 0.0 - Accuracy Vehicle-motorcycle: 0.0 - Accuracy Vehicle-bicycle: 0.0 - Accuracy Vehicle-caravan: 0.0 - Accuracy Vehicle-cartrailer: 0.9616 - Accuracy Construction-building: 0.0 - Accuracy Construction-door: 0.0 - Accuracy Construction-wall: 0.0 - Accuracy Construction-fenceguardrail: nan - Accuracy Construction-bridge: 0.0 - Accuracy Construction-tunnel: 0.0 - Accuracy Construction-stairs: 0.0 - Accuracy Object-pole: 0.0 - Accuracy Object-trafficsign: 0.0 - Accuracy Object-trafficlight: 0.2176 - Accuracy Nature-vegetation: 0.0000 - Accuracy Nature-terrain: 0.0 - Accuracy Sky: 0.0 - Accuracy Void-ground: 0.0 - Accuracy Void-dynamic: 0.0 - Accuracy Void-static: nan - Accuracy Void-unclear: nan - Iou Unlabeled: 0.0 - Iou Flat-road: 0.1014 - Iou Flat-sidewalk: 0.0 - Iou Flat-crosswalk: 0.0004 - Iou Flat-cyclinglane: 0.0 - Iou Flat-parkingdriveway: 0.0 - Iou Flat-railtrack: 0.0 - Iou Flat-curb: 0.0 - Iou Human-person: 0.0 - Iou Human-rider: 0.0039 - Iou Vehicle-car: 0.0 - Iou Vehicle-truck: nan - Iou Vehicle-bus: 0.0 - Iou Vehicle-tramtrain: 0.0 - Iou Vehicle-motorcycle: 0.0 - Iou Vehicle-bicycle: 0.0 - Iou Vehicle-caravan: 0.0 - Iou Vehicle-cartrailer: 0.0228 - Iou Construction-building: 0.0 - Iou Construction-door: 0.0 - Iou Construction-wall: 0.0 - Iou Construction-fenceguardrail: nan - Iou Construction-bridge: 0.0 - Iou Construction-tunnel: 0.0 - Iou Construction-stairs: 0.0 - Iou Object-pole: 0.0 - Iou Object-trafficsign: 0.0 - Iou Object-trafficlight: 0.0394 - Iou Nature-vegetation: 0.0000 - Iou Nature-terrain: 0.0 - Iou Sky: 0.0 - Iou Void-ground: 0.0 - Iou Void-dynamic: 0.0 - 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: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - num_epochs: 2 ### 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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| 2.3223 | 0.2 | 20 | 2.3183 | 0.0081 | 0.0599 | 0.0598 | nan | 0.7724 | 0.0000 | 0.0019 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0005 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.3997 | 0.0077 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5064 | 0.0125 | 0.0350 | 0.0004 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0945 | 0.0000 | 0.0018 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0001 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0456 | 0.0073 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0955 | 0.0036 | 0.0020 | 0.0001 | 0.0 | 0.0 | nan | nan | | 2.3053 | 0.4 | 40 | 2.1137 | 0.0070 | 0.0753 | 0.0608 | nan | 0.7392 | 0.0000 | 0.0018 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0659 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.8513 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5173 | 0.0012 | 0.0063 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0932 | 0.0000 | 0.0017 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0032 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0273 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0898 | 0.0006 | 0.0006 | 0.0 | 0.0 | 0.0 | nan | nan | | 2.0433 | 0.6 | 60 | 1.9808 | 0.0076 | 0.0829 | 0.0702 | nan | 0.7626 | 0.0 | 0.0002 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0679 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9286 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6419 | 0.0001 | 0.0015 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0947 | 0.0 | 0.0002 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0034 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0248 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1130 | 0.0000 | 0.0002 | 0.0 | 0.0 | 0.0 | nan | nan | | 1.9249 | 0.8 | 80 | 1.8427 | 0.0070 | 0.0791 | 0.0632 | nan | 0.7638 | 0.0 | 0.0002 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0417 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9489 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5388 | 0.0000 | 0.0003 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0968 | 0.0 | 0.0002 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0023 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0235 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0936 | 0.0000 | 0.0000 | 0.0 | 0.0 | 0.0 | nan | nan | | 1.7157 | 1.0 | 100 | 1.7687 | 0.0065 | 0.0790 | 0.0588 | nan | 0.7749 | 0.0 | 0.0005 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0989 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9497 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4683 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0903 | 0.0 | 0.0005 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0043 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0242 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0819 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | | 1.6624 | 1.2 | 120 | 1.6653 | 0.0054 | 0.0709 | 0.0441 | nan | 0.7509 | 0.0 | 0.0003 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0849 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9559 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2636 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0931 | 0.0 | 0.0002 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0038 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0235 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0472 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | | 1.6718 | 1.4 | 140 | 1.6575 | 0.0050 | 0.0639 | 0.0370 | nan | 0.5706 | 0.0 | 0.0008 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0856 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9640 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2325 | 0.0000 | 0.0000 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0864 | 0.0 | 0.0005 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0037 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0223 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0423 | 0.0000 | 0.0000 | 0.0 | 0.0 | 0.0 | nan | nan | | 1.731 | 1.6 | 160 | 1.5986 | 0.0056 | 0.0693 | 0.0438 | nan | 0.6585 | 0.0 | 0.0004 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0946 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9597 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2964 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0949 | 0.0 | 0.0003 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0041 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0238 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0515 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | | 1.7125 | 1.8 | 180 | 1.5779 | 0.0055 | 0.0693 | 0.0416 | nan | 0.7108 | 0.0 | 0.0006 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0942 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9633 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2420 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.1009 | 0.0 | 0.0004 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0039 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0230 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0433 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | | 1.6421 | 2.0 | 200 | 1.5824 | 0.0054 | 0.0686 | 0.0400 | nan | 0.7137 | 0.0 | 0.0005 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0947 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9616 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2176 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.1014 | 0.0 | 0.0004 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0039 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0228 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0394 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | ### Framework versions - Transformers 4.48.0 - Pytorch 2.1.1+cu118 - Datasets 3.2.0 - Tokenizers 0.21.0