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: 1.7930
- Mean Iou: 0.1305
- Mean Accuracy: 0.1772
- Overall Accuracy: 0.7058
- Accuracy Unlabeled: nan
- Accuracy Flat-road: 0.7362
- Accuracy Flat-sidewalk: 0.9065
- Accuracy Flat-crosswalk: 0.0
- Accuracy Flat-cyclinglane: 0.1582
- Accuracy Flat-parkingdriveway: 0.0099
- Accuracy Flat-railtrack: nan
- Accuracy Flat-curb: 0.0
- Accuracy Human-person: 0.0
- Accuracy Human-rider: 0.0
- Accuracy Vehicle-car: 0.8899
- 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: 0.8183
- Accuracy Construction-door: 0.0
- Accuracy Construction-wall: 0.0008
- Accuracy Construction-fenceguardrail: 0.0
- Accuracy Construction-bridge: 0.0
- Accuracy Construction-tunnel: nan
- Accuracy Construction-stairs: 0.0
- Accuracy Object-pole: 0.0013
- Accuracy Object-trafficsign: 0.0
- Accuracy Object-trafficlight: 0.0
- Accuracy Nature-vegetation: 0.9377
- Accuracy Nature-terrain: 0.3048
- Accuracy Sky: 0.9061
- Accuracy Void-ground: 0.0
- Accuracy Void-dynamic: 0.0
- Accuracy Void-static: 0.0001
- Accuracy Void-unclear: 0.0
- Iou Unlabeled: nan
- Iou Flat-road: 0.4830
- Iou Flat-sidewalk: 0.7385
- Iou Flat-crosswalk: 0.0
- Iou Flat-cyclinglane: 0.1519
- Iou Flat-parkingdriveway: 0.0096
- Iou Flat-railtrack: nan
- Iou Flat-curb: 0.0
- Iou Human-person: 0.0
- Iou Human-rider: 0.0
- Iou Vehicle-car: 0.5115
- 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: 0.5531
- Iou Construction-door: 0.0
- Iou Construction-wall: 0.0008
- Iou Construction-fenceguardrail: 0.0
- Iou Construction-bridge: 0.0
- Iou Construction-tunnel: nan
- Iou Construction-stairs: 0.0
- Iou Object-pole: 0.0013
- Iou Object-trafficsign: 0.0
- Iou Object-trafficlight: 0.0
- Iou Nature-vegetation: 0.6622
- Iou Nature-terrain: 0.2852
- Iou Sky: 0.7791
- Iou Void-ground: 0.0
- Iou Void-dynamic: 0.0
- Iou Void-static: 0.0001
- 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2.6535 | 1.5385 | 20 | 2.9345 | 0.0958 | 0.1467 | 0.6325 | nan | 0.5565 | 0.9030 | 0.0014 | 0.0181 | 0.0096 | nan | 0.0 | 0.0002 | 0.0 | 0.9614 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5618 | 0.0 | 0.0001 | 0.0 | 0.0 | nan | 0.0 | 0.0038 | 0.0 | 0.0 | 0.9189 | 0.0006 | 0.7575 | 0.0 | 0.0 | 0.0001 | 0.0 | 0.0 | 0.4194 | 0.6782 | 0.0014 | 0.0176 | 0.0086 | nan | 0.0 | 0.0002 | 0.0 | 0.3003 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4572 | 0.0 | 0.0001 | 0.0 | 0.0 | nan | 0.0 | 0.0036 | 0.0 | 0.0 | 0.5947 | 0.0006 | 0.6789 | 0.0 | 0.0 | 0.0001 | 0.0 |
2.211 | 3.0769 | 40 | 2.0975 | 0.1100 | 0.1594 | 0.6675 | nan | 0.6787 | 0.8889 | 0.0001 | 0.0340 | 0.0100 | nan | 0.0 | 0.0 | 0.0 | 0.9126 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.7377 | 0.0 | 0.0002 | 0.0 | 0.0 | nan | 0.0 | 0.0011 | 0.0 | 0.0 | 0.9412 | 0.0234 | 0.8741 | 0.0 | 0.0 | 0.0001 | 0.0 | nan | 0.4407 | 0.7112 | 0.0001 | 0.0330 | 0.0093 | nan | 0.0 | 0.0 | 0.0 | 0.4148 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5271 | 0.0 | 0.0002 | 0.0 | 0.0 | nan | 0.0 | 0.0010 | 0.0 | 0.0 | 0.6111 | 0.0232 | 0.7478 | 0.0 | 0.0 | 0.0001 | 0.0 |
2.002 | 4.6154 | 60 | 1.9114 | 0.1192 | 0.1665 | 0.6871 | nan | 0.6881 | 0.9098 | 0.0001 | 0.0851 | 0.0084 | nan | 0.0 | 0.0 | 0.0 | 0.8903 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.7976 | 0.0 | 0.0011 | 0.0 | 0.0 | nan | 0.0 | 0.0014 | 0.0 | 0.0 | 0.9390 | 0.1220 | 0.8862 | 0.0 | 0.0000 | 0.0001 | 0.0 | nan | 0.4604 | 0.7221 | 0.0001 | 0.0825 | 0.0081 | nan | 0.0 | 0.0 | 0.0 | 0.4745 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5425 | 0.0 | 0.0011 | 0.0 | 0.0 | nan | 0.0 | 0.0014 | 0.0 | 0.0 | 0.6357 | 0.1188 | 0.7661 | 0.0 | 0.0000 | 0.0001 | 0.0 |
1.8864 | 6.1538 | 80 | 1.8135 | 0.1265 | 0.1739 | 0.6998 | nan | 0.7364 | 0.9042 | 0.0 | 0.1141 | 0.0086 | nan | 0.0 | 0.0 | 0.0 | 0.8965 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.8031 | 0.0 | 0.0008 | 0.0 | 0.0 | nan | 0.0 | 0.0014 | 0.0 | 0.0 | 0.9379 | 0.2537 | 0.9076 | 0.0 | 0.0000 | 0.0001 | 0.0 | nan | 0.4741 | 0.7366 | 0.0 | 0.1100 | 0.0083 | nan | 0.0 | 0.0 | 0.0 | 0.4981 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5526 | 0.0 | 0.0008 | 0.0 | 0.0 | nan | 0.0 | 0.0014 | 0.0 | 0.0 | 0.6544 | 0.2405 | 0.7726 | 0.0 | 0.0000 | 0.0001 | 0.0 |
1.8777 | 7.6923 | 100 | 1.7930 | 0.1305 | 0.1772 | 0.7058 | nan | 0.7362 | 0.9065 | 0.0 | 0.1582 | 0.0099 | nan | 0.0 | 0.0 | 0.0 | 0.8899 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.8183 | 0.0 | 0.0008 | 0.0 | 0.0 | nan | 0.0 | 0.0013 | 0.0 | 0.0 | 0.9377 | 0.3048 | 0.9061 | 0.0 | 0.0 | 0.0001 | 0.0 | nan | 0.4830 | 0.7385 | 0.0 | 0.1519 | 0.0096 | nan | 0.0 | 0.0 | 0.0 | 0.5115 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5531 | 0.0 | 0.0008 | 0.0 | 0.0 | nan | 0.0 | 0.0013 | 0.0 | 0.0 | 0.6622 | 0.2852 | 0.7791 | 0.0 | 0.0 | 0.0001 | 0.0 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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