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--- |
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license: other |
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base_model: nvidia/mit-b0 |
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tags: |
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- image-segmentation |
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- vision |
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- generated_from_trainer |
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model-index: |
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- name: Segments |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Segments |
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This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the segments/sidewalk-semantic dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9830 |
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- Mean Iou: 0.1931 |
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- Mean Accuracy: 0.2401 |
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- Overall Accuracy: 0.7586 |
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- Accuracy Unlabeled: nan |
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- Accuracy Flat-road: 0.7259 |
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- Accuracy Flat-sidewalk: 0.9518 |
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- Accuracy Flat-crosswalk: 0.5588 |
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- Accuracy Flat-cyclinglane: 0.5550 |
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- Accuracy Flat-parkingdriveway: 0.1159 |
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- Accuracy Flat-railtrack: nan |
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- Accuracy Flat-curb: 0.1277 |
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- Accuracy Human-person: 0.0990 |
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- Accuracy Human-rider: 0.0 |
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- Accuracy Vehicle-car: 0.9049 |
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- Accuracy Vehicle-truck: 0.0 |
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- Accuracy Vehicle-bus: 0.0 |
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- Accuracy Vehicle-tramtrain: nan |
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- Accuracy Vehicle-motorcycle: 0.0 |
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- Accuracy Vehicle-bicycle: 0.0 |
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- Accuracy Vehicle-caravan: 0.0 |
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- Accuracy Vehicle-cartrailer: 0.0 |
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- Accuracy Construction-building: 0.8590 |
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- Accuracy Construction-door: 0.0 |
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- Accuracy Construction-wall: 0.0013 |
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- Accuracy Construction-fenceguardrail: 0.0 |
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- Accuracy Construction-bridge: 0.0 |
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- Accuracy Construction-tunnel: nan |
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- Accuracy Construction-stairs: 0.0 |
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- Accuracy Object-pole: 0.0088 |
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- Accuracy Object-trafficsign: 0.0 |
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- Accuracy Object-trafficlight: 0.0 |
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- Accuracy Nature-vegetation: 0.9206 |
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- Accuracy Nature-terrain: 0.7756 |
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- Accuracy Sky: 0.8391 |
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- Accuracy Void-ground: 0.0 |
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- Accuracy Void-dynamic: 0.0 |
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- Accuracy Void-static: 0.0 |
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- Accuracy Void-unclear: 0.0 |
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- Iou Unlabeled: nan |
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- Iou Flat-road: 0.5951 |
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- Iou Flat-sidewalk: 0.7822 |
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- Iou Flat-crosswalk: 0.5498 |
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- Iou Flat-cyclinglane: 0.4666 |
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- Iou Flat-parkingdriveway: 0.1001 |
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- Iou Flat-railtrack: nan |
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- Iou Flat-curb: 0.1078 |
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- Iou Human-person: 0.0979 |
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- Iou Human-rider: 0.0 |
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- Iou Vehicle-car: 0.6265 |
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- Iou Vehicle-truck: 0.0 |
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- Iou Vehicle-bus: 0.0 |
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- Iou Vehicle-tramtrain: nan |
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- Iou Vehicle-motorcycle: 0.0 |
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- Iou Vehicle-bicycle: 0.0 |
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- Iou Vehicle-caravan: 0.0 |
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- Iou Vehicle-cartrailer: 0.0 |
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- Iou Construction-building: 0.4997 |
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- Iou Construction-door: 0.0 |
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- Iou Construction-wall: 0.0013 |
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- Iou Construction-fenceguardrail: 0.0 |
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- Iou Construction-bridge: 0.0 |
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- Iou Construction-tunnel: nan |
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- Iou Construction-stairs: 0.0 |
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- Iou Object-pole: 0.0088 |
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- Iou Object-trafficsign: 0.0 |
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- Iou Object-trafficlight: 0.0 |
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- Iou Nature-vegetation: 0.7405 |
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- Iou Nature-terrain: 0.6034 |
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- Iou Sky: 0.8052 |
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- Iou Void-ground: 0.0 |
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- Iou Void-dynamic: 0.0 |
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- Iou Void-static: 0.0 |
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- Iou Void-unclear: 0.0 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 20 |
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### Training results |
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### Framework versions |
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- Transformers 4.33.0.dev0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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