--- base_model: nvidia/mit-b0 license: other 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 segments/sidewalk-semantic dataset. It achieves the following results on the evaluation set: - Loss: 1.2030 - Mean Iou: 0.1619 - Mean Accuracy: 0.2092 - Overall Accuracy: 0.7485 - Accuracy Unlabeled: nan - Accuracy Flat-road: 0.8436 - Accuracy Flat-sidewalk: 0.9312 - Accuracy Flat-crosswalk: 0.0 - Accuracy Flat-cyclinglane: 0.4507 - Accuracy Flat-parkingdriveway: 0.0198 - Accuracy Flat-railtrack: nan - Accuracy Flat-curb: 0.0 - Accuracy Human-person: 0.0 - Accuracy Human-rider: 0.0 - Accuracy Vehicle-car: 0.9019 - Accuracy Vehicle-truck: 0.0 - 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: 0.0 - Accuracy Construction-building: 0.8988 - Accuracy Construction-door: 0.0 - Accuracy Construction-wall: 0.0004 - Accuracy Construction-fenceguardrail: 0.0 - Accuracy Construction-bridge: 0.0 - Accuracy Construction-tunnel: nan - Accuracy Construction-stairs: 0.0 - Accuracy Object-pole: 0.0 - Accuracy Object-trafficsign: 0.0 - Accuracy Object-trafficlight: 0.0 - Accuracy Nature-vegetation: 0.9346 - Accuracy Nature-terrain: 0.7865 - Accuracy Sky: 0.9277 - Accuracy Void-ground: 0.0 - Accuracy Void-dynamic: 0.0 - Accuracy Void-static: 0.0 - Accuracy Void-unclear: 0.0 - Iou Unlabeled: nan - Iou Flat-road: 0.5666 - Iou Flat-sidewalk: 0.7709 - Iou Flat-crosswalk: 0.0 - Iou Flat-cyclinglane: 0.4018 - Iou Flat-parkingdriveway: 0.0192 - Iou Flat-railtrack: nan - Iou Flat-curb: 0.0 - Iou Human-person: 0.0 - Iou Human-rider: 0.0 - Iou Vehicle-car: 0.6148 - Iou Vehicle-truck: 0.0 - 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: 0.0 - Iou Construction-building: 0.5632 - Iou Construction-door: 0.0 - Iou Construction-wall: 0.0004 - Iou Construction-fenceguardrail: 0.0 - Iou Construction-bridge: 0.0 - Iou Construction-tunnel: nan - Iou Construction-stairs: 0.0 - Iou Object-pole: 0.0 - Iou Object-trafficsign: 0.0 - Iou Object-trafficlight: 0.0 - Iou Nature-vegetation: 0.7501 - Iou Nature-terrain: 0.6356 - Iou Sky: 0.8596 - Iou Void-ground: 0.0 - Iou Void-dynamic: 0.0 - Iou Void-static: 0.0 - Iou Void-unclear: 0.0 ## 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: 4 - eval_batch_size: 4 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - 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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| 2.3674 | 0.5 | 100 | 1.6720 | 0.1214 | 0.1717 | 0.6859 | nan | 0.8443 | 0.9140 | 0.0 | 0.0013 | 0.0016 | nan | 0.0000 | 0.0 | 0.0 | 0.9316 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.8364 | 0.0 | 0.0003 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9363 | 0.1751 | 0.8520 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.4679 | 0.7424 | 0.0 | 0.0013 | 0.0016 | nan | 0.0000 | 0.0 | 0.0 | 0.4884 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5352 | 0.0 | 0.0003 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.6734 | 0.1662 | 0.8072 | 0.0 | 0.0 | 0.0 | 0.0 | | 1.6248 | 1.0 | 200 | 1.3491 | 0.1433 | 0.1884 | 0.7207 | nan | 0.8164 | 0.9497 | 0.0 | 0.1026 | 0.0029 | nan | 0.0 | 0.0 | 0.0 | 0.8847 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.8799 | 0.0 | 0.0003 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9487 | 0.5417 | 0.9021 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.5258 | 0.7439 | 0.0 | 0.1022 | 0.0029 | nan | 0.0 | 0.0 | 0.0 | 0.6004 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5538 | 0.0 | 0.0003 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7135 | 0.4965 | 0.8474 | 0.0 | 0.0 | 0.0 | 0.0 | | 1.3902 | 1.5 | 300 | 1.2406 | 0.1583 | 0.2052 | 0.7431 | nan | 0.8351 | 0.9301 | 0.0 | 0.4278 | 0.0119 | nan | 0.0 | 0.0 | 0.0 | 0.8945 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.8936 | 0.0 | 0.0002 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9464 | 0.6912 | 0.9360 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.5562 | 0.7694 | 0.0 | 0.3883 | 0.0117 | nan | 0.0 | 0.0 | 0.0 | 0.5991 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5557 | 0.0 | 0.0002 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7361 | 0.5997 | 0.8479 | 0.0 | 0.0 | 0.0 | 0.0 | | 1.2893 | 2.0 | 400 | 1.2030 | 0.1619 | 0.2092 | 0.7485 | nan | 0.8436 | 0.9312 | 0.0 | 0.4507 | 0.0198 | nan | 0.0 | 0.0 | 0.0 | 0.9019 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.8988 | 0.0 | 0.0004 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9346 | 0.7865 | 0.9277 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.5666 | 0.7709 | 0.0 | 0.4018 | 0.0192 | nan | 0.0 | 0.0 | 0.0 | 0.6148 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5632 | 0.0 | 0.0004 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7501 | 0.6356 | 0.8596 | 0.0 | 0.0 | 0.0 | 0.0 | ### Framework versions - Transformers 4.42.3 - Pytorch 2.1.0+rocm5.6 - Datasets 2.20.0 - Tokenizers 0.19.1