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mit-b0-finetuned-sidewalk-semantic

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  1. README.md +141 -0
  2. config.json +144 -0
  3. model.safetensors +3 -0
  4. preprocessor_config.json +23 -0
  5. runs/Apr12_16-30-02_4ece0295354f/events.out.tfevents.1712939413.4ece0295354f.2236.0 +3 -0
  6. training_args.bin +3 -0
README.md ADDED
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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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+ - generated_from_trainer
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+ model-index:
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+ - name: mit-b0-finetuned-sidewalk-semantic
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+ results: []
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+ ---
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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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+
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+ # mit-b0-finetuned-sidewalk-semantic
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+
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+ This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7584
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+ - Mean Iou: 0.1932
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+ - Mean Accuracy: 0.2342
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+ - Overall Accuracy: 0.8034
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+ - Accuracy Unlabeled: nan
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+ - Accuracy Flat-road: 0.7939
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+ - Accuracy Flat-sidewalk: 0.9534
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+ - Accuracy Flat-crosswalk: 0.0000
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+ - Accuracy Flat-cyclinglane: 0.7630
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+ - Accuracy Flat-parkingdriveway: 0.3561
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+ - Accuracy Flat-railtrack: 0.0
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+ - Accuracy Flat-curb: 0.2446
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+ - Accuracy Human-person: 0.0018
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+ - Accuracy Human-rider: 0.0
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+ - Accuracy Vehicle-car: 0.9007
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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: 0.0
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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: 0.9194
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+ - Accuracy Construction-door: 0.0
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+ - Accuracy Construction-wall: 0.0706
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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: 0.0018
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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: 0.9304
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+ - Accuracy Nature-terrain: 0.8467
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+ - Accuracy Sky: 0.9472
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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: 0.0004
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+ - Accuracy Void-unclear: 0.0
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+ - Iou Unlabeled: nan
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+ - Iou Flat-road: 0.6083
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+ - Iou Flat-sidewalk: 0.8277
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+ - Iou Flat-crosswalk: 0.0000
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+ - Iou Flat-cyclinglane: 0.6702
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+ - Iou Flat-parkingdriveway: 0.2581
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+ - Iou Flat-railtrack: 0.0
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+ - Iou Flat-curb: 0.2113
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+ - Iou Human-person: 0.0018
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+ - Iou Human-rider: 0.0
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+ - Iou Vehicle-car: 0.7545
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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: 0.0
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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: 0.6531
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+ - Iou Construction-door: 0.0
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+ - Iou Construction-wall: 0.0652
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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: 0.0018
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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: 0.8060
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+ - Iou Nature-terrain: 0.6540
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+ - Iou Sky: 0.8649
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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: 0.0003
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+ - Iou Void-unclear: 0.0
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 2
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+ - eval_batch_size: 2
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 8
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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: 10
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+
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+ ### Training results
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+
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+ | 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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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:------------------:|:----------------------:|:-----------------------:|:-------------------------:|:-----------------------------:|:-----------------------:|:------------------:|:---------------------:|:--------------------:|:--------------------:|:----------------------:|:--------------------:|:--------------------------:|:---------------------------:|:------------------------:|:------------------------:|:---------------------------:|:------------------------------:|:--------------------------:|:--------------------------:|:------------------------------------:|:----------------------------:|:----------------------------:|:----------------------------:|:--------------------:|:---------------------------:|:----------------------------:|:--------------------------:|:-----------------------:|:------------:|:--------------------:|:---------------------:|:--------------------:|:---------------------:|:-------------:|:-------------:|:-----------------:|:------------------:|:--------------------:|:------------------------:|:------------------:|:-------------:|:----------------:|:---------------:|:---------------:|:-----------------:|:---------------:|:---------------------:|:----------------------:|:-------------------:|:-------------------:|:----------------------:|:-------------------------:|:---------------------:|:---------------------:|:-------------------------------:|:-----------------------:|:-----------------------:|:-----------------------:|:---------------:|:----------------------:|:-----------------------:|:---------------------:|:------------------:|:-------:|:---------------:|:----------------:|:---------------:|:----------------:|
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+ | 2.1654 | 1.0 | 100 | 1.6435 | 0.1291 | 0.1770 | 0.6919 | nan | 0.6823 | 0.9206 | 0.0 | 0.0022 | 0.0053 | 0.0 | 0.0 | 0.0 | 0.0 | 0.8850 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.8425 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9138 | 0.7723 | 0.8186 | 0.0 | 0.0 | 0.0000 | 0.0 | nan | 0.4039 | 0.7194 | 0.0 | 0.0022 | 0.0053 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5851 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5722 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7101 | 0.4854 | 0.7772 | 0.0 | 0.0 | 0.0000 | 0.0 |
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+ | 1.5984 | 2.0 | 200 | 1.2905 | 0.1517 | 0.1973 | 0.7396 | nan | 0.7415 | 0.9557 | 0.0 | 0.3711 | 0.0160 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9108 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.8769 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8585 | 0.8699 | 0.9088 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.4974 | 0.7465 | 0.0 | 0.3665 | 0.0159 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6673 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5889 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7531 | 0.5509 | 0.8181 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 1.2146 | 3.0 | 300 | 1.0847 | 0.1626 | 0.2071 | 0.7634 | nan | 0.7918 | 0.9561 | 0.0 | 0.5225 | 0.0828 | 0.0 | 0.0000 | 0.0 | 0.0 | 0.9191 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.8607 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8959 | 0.8726 | 0.9324 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.5364 | 0.7830 | 0.0 | 0.5010 | 0.0768 | 0.0 | 0.0000 | 0.0 | 0.0 | 0.6566 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6147 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7682 | 0.5979 | 0.8319 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 1.0528 | 4.0 | 400 | 0.9593 | 0.1726 | 0.2148 | 0.7818 | nan | 0.8491 | 0.9467 | 0.0 | 0.6248 | 0.1582 | 0.0 | 0.0028 | 0.0 | 0.0 | 0.9208 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.8971 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9124 | 0.8446 | 0.9320 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.5559 | 0.8209 | 0.0 | 0.5799 | 0.1382 | 0.0 | 0.0028 | 0.0 | 0.0 | 0.6851 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6297 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7887 | 0.6506 | 0.8429 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 1.151 | 5.0 | 500 | 0.8917 | 0.1781 | 0.2211 | 0.7856 | nan | 0.7689 | 0.9449 | 0.0 | 0.7350 | 0.2627 | 0.0 | 0.0394 | 0.0 | 0.0 | 0.8992 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9103 | 0.0 | 0.0001 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9213 | 0.8734 | 0.9404 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.5697 | 0.8051 | 0.0 | 0.6312 | 0.2044 | 0.0 | 0.0386 | 0.0 | 0.0 | 0.7368 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6341 | 0.0 | 0.0001 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7860 | 0.6232 | 0.8482 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 0.8834 | 6.0 | 600 | 0.8488 | 0.1833 | 0.2253 | 0.7930 | nan | 0.8031 | 0.9523 | 0.0 | 0.6739 | 0.3297 | 0.0 | 0.1109 | 0.0 | 0.0 | 0.9189 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9135 | 0.0 | 0.0097 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9249 | 0.8625 | 0.9365 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.5945 | 0.8182 | 0.0 | 0.6215 | 0.2340 | 0.0 | 0.1044 | 0.0 | 0.0 | 0.7278 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6417 | 0.0 | 0.0096 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7977 | 0.6393 | 0.8609 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 0.7373 | 7.0 | 700 | 0.7922 | 0.1870 | 0.2305 | 0.7991 | nan | 0.8274 | 0.9366 | 0.0 | 0.7533 | 0.3386 | 0.0 | 0.1780 | 0.0001 | 0.0 | 0.9212 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9144 | 0.0 | 0.0184 | 0.0 | 0.0 | nan | 0.0 | 0.0009 | 0.0 | 0.0 | 0.9324 | 0.8420 | 0.9422 | 0.0 | 0.0 | 0.0000 | 0.0 | nan | 0.5946 | 0.8448 | 0.0 | 0.6344 | 0.2432 | 0.0 | 0.1632 | 0.0001 | 0.0 | 0.7258 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6472 | 0.0 | 0.0181 | 0.0 | 0.0 | nan | 0.0 | 0.0009 | 0.0 | 0.0 | 0.8002 | 0.6380 | 0.8615 | 0.0 | 0.0 | 0.0000 | 0.0 |
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+ | 0.8252 | 8.0 | 800 | 0.7820 | 0.1888 | 0.2303 | 0.7987 | nan | 0.8024 | 0.9520 | 0.0 | 0.7312 | 0.3178 | 0.0 | 0.1998 | 0.0003 | 0.0 | 0.9060 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9255 | 0.0 | 0.0366 | 0.0 | 0.0 | nan | 0.0 | 0.0005 | 0.0 | 0.0 | 0.9177 | 0.8774 | 0.9322 | 0.0 | 0.0 | 0.0002 | 0.0 | nan | 0.5972 | 0.8253 | 0.0 | 0.6590 | 0.2429 | 0.0 | 0.1763 | 0.0003 | 0.0 | 0.7464 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6439 | 0.0 | 0.0351 | 0.0 | 0.0 | nan | 0.0 | 0.0005 | 0.0 | 0.0 | 0.8022 | 0.6324 | 0.8689 | 0.0 | 0.0 | 0.0002 | 0.0 |
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+ | 0.6442 | 9.0 | 900 | 0.7593 | 0.1923 | 0.2328 | 0.8030 | nan | 0.8301 | 0.9488 | 0.0 | 0.7388 | 0.3596 | 0.0 | 0.2196 | 0.0013 | 0.0 | 0.9120 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9158 | 0.0 | 0.0559 | 0.0 | 0.0 | nan | 0.0 | 0.0009 | 0.0 | 0.0 | 0.9261 | 0.8226 | 0.9516 | 0.0 | 0.0 | 0.0001 | 0.0 | nan | 0.5992 | 0.8342 | 0.0 | 0.6607 | 0.2569 | 0.0 | 0.1954 | 0.0013 | 0.0 | 0.7445 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6532 | 0.0 | 0.0523 | 0.0 | 0.0 | nan | 0.0 | 0.0009 | 0.0 | 0.0 | 0.8115 | 0.6722 | 0.8643 | 0.0 | 0.0 | 0.0001 | 0.0 |
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+ | 0.8239 | 10.0 | 1000 | 0.7584 | 0.1932 | 0.2342 | 0.8034 | nan | 0.7939 | 0.9534 | 0.0000 | 0.7630 | 0.3561 | 0.0 | 0.2446 | 0.0018 | 0.0 | 0.9007 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9194 | 0.0 | 0.0706 | 0.0 | 0.0 | nan | 0.0 | 0.0018 | 0.0 | 0.0 | 0.9304 | 0.8467 | 0.9472 | 0.0 | 0.0 | 0.0004 | 0.0 | nan | 0.6083 | 0.8277 | 0.0000 | 0.6702 | 0.2581 | 0.0 | 0.2113 | 0.0018 | 0.0 | 0.7545 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6531 | 0.0 | 0.0652 | 0.0 | 0.0 | nan | 0.0 | 0.0018 | 0.0 | 0.0 | 0.8060 | 0.6540 | 0.8649 | 0.0 | 0.0 | 0.0003 | 0.0 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.38.2
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
config.json ADDED
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+ {
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+ "_name_or_path": "nvidia/mit-b0",
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+ "architectures": [
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+ "SegformerForSemanticSegmentation"
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+ ],
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+ "attention_probs_dropout_prob": 0.0,
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+ "classifier_dropout_prob": 0.1,
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+ "decoder_hidden_size": 256,
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+ "depths": [
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+ 2,
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+ 2,
12
+ 2,
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+ 2
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+ ],
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+ "downsampling_rates": [
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+ 1,
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+ 4,
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+ 8,
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+ 16
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+ ],
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+ "drop_path_rate": 0.1,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.0,
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+ "hidden_sizes": [
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+ 32,
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+ 64,
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+ 160,
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+ 256
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+ ],
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+ "id2label": {
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+ "0": "unlabeled",
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+ "1": "flat-road",
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+ "2": "flat-sidewalk",
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+ "3": "flat-crosswalk",
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+ "4": "flat-cyclinglane",
36
+ "5": "flat-parkingdriveway",
37
+ "6": "flat-railtrack",
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+ "7": "flat-curb",
39
+ "8": "human-person",
40
+ "9": "human-rider",
41
+ "10": "vehicle-car",
42
+ "11": "vehicle-truck",
43
+ "12": "vehicle-bus",
44
+ "13": "vehicle-tramtrain",
45
+ "14": "vehicle-motorcycle",
46
+ "15": "vehicle-bicycle",
47
+ "16": "vehicle-caravan",
48
+ "17": "vehicle-cartrailer",
49
+ "18": "construction-building",
50
+ "19": "construction-door",
51
+ "20": "construction-wall",
52
+ "21": "construction-fenceguardrail",
53
+ "22": "construction-bridge",
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+ "23": "construction-tunnel",
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+ "24": "construction-stairs",
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+ "25": "object-pole",
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+ "26": "object-trafficsign",
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+ "27": "object-trafficlight",
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+ "28": "nature-vegetation",
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+ "29": "nature-terrain",
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+ "30": "sky",
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+ "31": "void-ground",
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+ "32": "void-dynamic",
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+ "33": "void-static",
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+ "34": "void-unclear"
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+ },
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+ "image_size": 224,
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+ "initializer_range": 0.02,
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+ "label2id": {
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+ "construction-bridge": 22,
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+ "construction-building": 18,
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+ "construction-door": 19,
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+ "construction-fenceguardrail": 21,
74
+ "construction-stairs": 24,
75
+ "construction-tunnel": 23,
76
+ "construction-wall": 20,
77
+ "flat-crosswalk": 3,
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+ "flat-curb": 7,
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+ "flat-cyclinglane": 4,
80
+ "flat-parkingdriveway": 5,
81
+ "flat-railtrack": 6,
82
+ "flat-road": 1,
83
+ "flat-sidewalk": 2,
84
+ "human-person": 8,
85
+ "human-rider": 9,
86
+ "nature-terrain": 29,
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+ "nature-vegetation": 28,
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+ "object-pole": 25,
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+ "object-trafficlight": 27,
90
+ "object-trafficsign": 26,
91
+ "sky": 30,
92
+ "unlabeled": 0,
93
+ "vehicle-bicycle": 15,
94
+ "vehicle-bus": 12,
95
+ "vehicle-car": 10,
96
+ "vehicle-caravan": 16,
97
+ "vehicle-cartrailer": 17,
98
+ "vehicle-motorcycle": 14,
99
+ "vehicle-tramtrain": 13,
100
+ "vehicle-truck": 11,
101
+ "void-dynamic": 32,
102
+ "void-ground": 31,
103
+ "void-static": 33,
104
+ "void-unclear": 34
105
+ },
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+ "layer_norm_eps": 1e-06,
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+ "mlp_ratios": [
108
+ 4,
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+ 4,
110
+ 4,
111
+ 4
112
+ ],
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+ "model_type": "segformer",
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+ "num_attention_heads": [
115
+ 1,
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+ 2,
117
+ 5,
118
+ 8
119
+ ],
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+ "num_channels": 3,
121
+ "num_encoder_blocks": 4,
122
+ "patch_sizes": [
123
+ 7,
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+ 3,
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+ 3,
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