segformer-b0-finetuned-segments-sidewalk-2
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:
- Loss: 2.7084
- Mean Iou: 0.0871
- Mean Accuracy: 0.1451
- Overall Accuracy: 0.6167
- Accuracy Unlabeled: nan
- Accuracy Flat-road: 0.5180
- Accuracy Flat-sidewalk: 0.9088
- Accuracy Flat-crosswalk: 0.0001
- Accuracy Flat-cyclinglane: 0.0259
- Accuracy Flat-parkingdriveway: 0.0
- Accuracy Flat-railtrack: nan
- Accuracy Flat-curb: 0.0012
- Accuracy Human-person: 0.0017
- Accuracy Human-rider: 0.0
- Accuracy Vehicle-car: 0.9553
- Accuracy Vehicle-truck: 0.0
- Accuracy Vehicle-bus: 0.0
- Accuracy Vehicle-tramtrain: nan
- Accuracy Vehicle-motorcycle: 0.0
- Accuracy Vehicle-bicycle: 0.0000
- Accuracy Vehicle-caravan: 0.0
- Accuracy Vehicle-cartrailer: 0.0
- Accuracy Construction-building: 0.4663
- Accuracy Construction-door: 0.0
- Accuracy Construction-wall: 0.0670
- Accuracy Construction-fenceguardrail: 0.0
- Accuracy Construction-bridge: 0.0
- Accuracy Construction-tunnel: nan
- Accuracy Construction-stairs: 0.0
- Accuracy Object-pole: 0.0064
- Accuracy Object-trafficsign: 0.0
- Accuracy Object-trafficlight: 0.0
- Accuracy Nature-vegetation: 0.9708
- Accuracy Nature-terrain: 0.0024
- Accuracy Sky: 0.5740
- 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: 0.3925
- Iou Flat-sidewalk: 0.6649
- Iou Flat-crosswalk: 0.0001
- Iou Flat-cyclinglane: 0.0249
- Iou Flat-parkingdriveway: 0.0
- Iou Flat-railtrack: 0.0
- Iou Flat-curb: 0.0012
- Iou Human-person: 0.0017
- Iou Human-rider: 0.0
- Iou Vehicle-car: 0.2851
- Iou Vehicle-truck: 0.0
- Iou Vehicle-bus: 0.0
- Iou Vehicle-tramtrain: 0.0
- Iou Vehicle-motorcycle: 0.0
- Iou Vehicle-bicycle: 0.0000
- Iou Vehicle-caravan: 0.0
- Iou Vehicle-cartrailer: 0.0
- Iou Construction-building: 0.3825
- Iou Construction-door: 0.0
- Iou Construction-wall: 0.0540
- Iou Construction-fenceguardrail: 0.0
- Iou Construction-bridge: 0.0
- Iou Construction-tunnel: 0.0
- Iou Construction-stairs: 0.0
- Iou Object-pole: 0.0048
- Iou Object-trafficsign: 0.0
- Iou Object-trafficlight: 0.0
- Iou Nature-vegetation: 0.6011
- Iou Nature-terrain: 0.0024
- Iou Sky: 0.5451
- 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2.9796 | 0.4 | 20 | 3.2289 | 0.0664 | 0.1236 | 0.5591 | nan | 0.2423 | 0.9160 | 0.0000 | 0.0110 | 0.0000 | nan | 0.0006 | 0.0021 | 0.0 | 0.9292 | 0.0 | 0.0 | nan | 0.0 | 0.0000 | 0.0 | 0.0 | 0.2970 | 0.0 | 0.1131 | 0.0 | 0.0 | nan | 0.0 | 0.0502 | 0.0 | 0.0 | 0.9793 | 0.0015 | 0.2752 | 0.0 | 0.0148 | 0.0000 | 0.0 | 0.0 | 0.2077 | 0.6059 | 0.0000 | 0.0107 | 0.0000 | 0.0 | 0.0006 | 0.0020 | 0.0 | 0.2985 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0000 | 0.0 | 0.0 | 0.2620 | 0.0 | 0.0654 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0249 | 0.0 | 0.0 | 0.5724 | 0.0015 | 0.2711 | 0.0 | 0.0027 | 0.0000 | 0.0 |
2.6315 | 0.8 | 40 | 2.7084 | 0.0871 | 0.1451 | 0.6167 | nan | 0.5180 | 0.9088 | 0.0001 | 0.0259 | 0.0 | nan | 0.0012 | 0.0017 | 0.0 | 0.9553 | 0.0 | 0.0 | nan | 0.0 | 0.0000 | 0.0 | 0.0 | 0.4663 | 0.0 | 0.0670 | 0.0 | 0.0 | nan | 0.0 | 0.0064 | 0.0 | 0.0 | 0.9708 | 0.0024 | 0.5740 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.3925 | 0.6649 | 0.0001 | 0.0249 | 0.0 | 0.0 | 0.0012 | 0.0017 | 0.0 | 0.2851 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0000 | 0.0 | 0.0 | 0.3825 | 0.0 | 0.0540 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0048 | 0.0 | 0.0 | 0.6011 | 0.0024 | 0.5451 | 0.0 | 0.0 | 0.0 | 0.0 |
Framework versions
- Transformers 4.41.1
- Pytorch 1.13.1
- Datasets 2.19.1
- Tokenizers 0.19.1
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Base model
nvidia/mit-b0