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twdent
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segformer-b5-finetuned-HikingHD

Image Segmentation
Transformers
PyTorch
segformer
vision
Generated from Trainer
Inference Endpoints
Model card Files Community
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  1. README.md +104 -0
  2. config.json +80 -0
  3. pytorch_model.bin +3 -0
  4. 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-b5
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+ tags:
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+ - vision
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+ - image-segmentation
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+ - generated_from_trainer
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+ model-index:
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+ - name: segformer-b5-finetuned-HikingHD
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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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+ # segformer-b5-finetuned-HikingHD
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+
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+ This model is a fine-tuned version of [nvidia/mit-b5](https://huggingface.co/nvidia/mit-b5) on the twdent/HikingHD dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1077
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+ - Mean Iou: 0.6364
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+ - Mean Accuracy: 0.9770
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+ - Overall Accuracy: 0.9771
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+ - Accuracy Unlabeled: nan
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+ - Accuracy Traversable: 0.9758
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+ - Accuracy Non-traversable: 0.9781
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+ - Iou Unlabeled: 0.0
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+ - Iou Traversable: 0.9493
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+ - Iou Non-traversable: 0.9600
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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: 6e-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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+ - 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: 50
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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 Traversable | Accuracy Non-traversable | Iou Unlabeled | Iou Traversable | Iou Non-traversable |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:--------------------:|:------------------------:|:-------------:|:---------------:|:-------------------:|
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+ | 0.1595 | 1.33 | 20 | 0.1789 | 0.9314 | 0.9657 | 0.9649 | nan | 0.9727 | 0.9588 | nan | 0.9240 | 0.9388 |
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+ | 0.3593 | 2.67 | 40 | 0.1137 | 0.9429 | 0.9731 | 0.9709 | nan | 0.9911 | 0.9551 | nan | 0.9372 | 0.9485 |
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+ | 0.1002 | 4.0 | 60 | 0.0979 | 0.9363 | 0.9661 | 0.9677 | nan | 0.9531 | 0.9791 | nan | 0.9282 | 0.9444 |
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+ | 0.0348 | 5.33 | 80 | 0.0933 | 0.9442 | 0.9713 | 0.9717 | nan | 0.9675 | 0.9750 | nan | 0.9375 | 0.9509 |
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+ | 0.0374 | 6.67 | 100 | 0.0884 | 0.9459 | 0.9714 | 0.9727 | nan | 0.9611 | 0.9817 | nan | 0.9391 | 0.9528 |
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+ | 0.0447 | 8.0 | 120 | 0.0886 | 0.9491 | 0.9737 | 0.9743 | nan | 0.9684 | 0.9789 | nan | 0.9430 | 0.9553 |
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+ | 0.0464 | 9.33 | 140 | 0.0790 | 0.9564 | 0.9783 | 0.9780 | nan | 0.9804 | 0.9762 | nan | 0.9514 | 0.9614 |
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+ | 0.0421 | 10.67 | 160 | 0.0868 | 0.9540 | 0.9764 | 0.9768 | nan | 0.9733 | 0.9796 | nan | 0.9485 | 0.9596 |
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+ | 0.0253 | 12.0 | 180 | 0.0887 | 0.9530 | 0.9756 | 0.9763 | nan | 0.9700 | 0.9812 | nan | 0.9472 | 0.9587 |
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+ | 0.0364 | 13.33 | 200 | 0.0960 | 0.9494 | 0.9733 | 0.9745 | nan | 0.9638 | 0.9829 | nan | 0.9431 | 0.9558 |
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+ | 0.0276 | 14.67 | 220 | 0.0980 | 0.9470 | 0.9717 | 0.9732 | nan | 0.9595 | 0.9840 | nan | 0.9402 | 0.9538 |
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+ | 0.0279 | 16.0 | 240 | 0.0914 | 0.9534 | 0.9761 | 0.9765 | nan | 0.9725 | 0.9796 | nan | 0.9478 | 0.9590 |
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+ | 0.026 | 17.33 | 260 | 0.0886 | 0.9557 | 0.9778 | 0.9777 | nan | 0.9792 | 0.9764 | nan | 0.9506 | 0.9609 |
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+ | 0.0228 | 18.67 | 280 | 0.0888 | 0.9547 | 0.9775 | 0.9771 | nan | 0.9804 | 0.9745 | nan | 0.9495 | 0.9599 |
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+ | 0.0259 | 20.0 | 300 | 0.0984 | 0.9505 | 0.9742 | 0.9750 | nan | 0.9679 | 0.9806 | nan | 0.9444 | 0.9565 |
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+ | 0.0306 | 21.33 | 320 | 0.0890 | 0.9542 | 0.9763 | 0.9769 | nan | 0.9716 | 0.9811 | nan | 0.9487 | 0.9598 |
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+ | 0.0305 | 22.67 | 340 | 0.0967 | 0.6352 | 0.9752 | 0.9762 | nan | 0.9669 | 0.9834 | 0.0 | 0.9468 | 0.9586 |
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+ | 0.0219 | 24.0 | 360 | 0.0983 | 0.9538 | 0.9764 | 0.9767 | nan | 0.9735 | 0.9792 | nan | 0.9483 | 0.9593 |
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+ | 0.023 | 25.33 | 380 | 0.0940 | 0.6368 | 0.9771 | 0.9774 | nan | 0.9743 | 0.9799 | 0.0 | 0.9499 | 0.9606 |
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+ | 0.0217 | 26.67 | 400 | 0.0973 | 0.6360 | 0.9767 | 0.9768 | nan | 0.9758 | 0.9776 | 0.0 | 0.9486 | 0.9595 |
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+ | 0.0267 | 28.0 | 420 | 0.1023 | 0.6360 | 0.9770 | 0.9768 | nan | 0.9792 | 0.9749 | 0.0 | 0.9487 | 0.9593 |
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+ | 0.0202 | 29.33 | 440 | 0.0955 | 0.6376 | 0.9783 | 0.9780 | nan | 0.9802 | 0.9764 | 0.0 | 0.9514 | 0.9615 |
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+ | 0.0225 | 30.67 | 460 | 0.1016 | 0.6360 | 0.9763 | 0.9768 | nan | 0.9727 | 0.9800 | 0.0 | 0.9484 | 0.9595 |
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+ | 0.0288 | 32.0 | 480 | 0.1026 | 0.6354 | 0.9756 | 0.9763 | nan | 0.9697 | 0.9815 | 0.0 | 0.9473 | 0.9588 |
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+ | 0.0209 | 33.33 | 500 | 0.0977 | 0.6370 | 0.9771 | 0.9776 | nan | 0.9735 | 0.9808 | 0.0 | 0.9502 | 0.9609 |
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+ | 0.0202 | 34.67 | 520 | 0.1005 | 0.6367 | 0.9772 | 0.9773 | nan | 0.9762 | 0.9782 | 0.0 | 0.9497 | 0.9604 |
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+ | 0.0194 | 36.0 | 540 | 0.1032 | 0.6365 | 0.9771 | 0.9772 | nan | 0.9766 | 0.9776 | 0.0 | 0.9495 | 0.9601 |
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+ | 0.0165 | 37.33 | 560 | 0.1013 | 0.6373 | 0.9777 | 0.9778 | nan | 0.9769 | 0.9785 | 0.0 | 0.9508 | 0.9612 |
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+ | 0.0226 | 38.67 | 580 | 0.1005 | 0.6367 | 0.9771 | 0.9773 | nan | 0.9752 | 0.9790 | 0.0 | 0.9497 | 0.9604 |
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+ | 0.0206 | 40.0 | 600 | 0.1032 | 0.6369 | 0.9773 | 0.9775 | nan | 0.9757 | 0.9789 | 0.0 | 0.9501 | 0.9607 |
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+ | 0.016 | 41.33 | 620 | 0.1007 | 0.6373 | 0.9776 | 0.9777 | nan | 0.9761 | 0.9790 | 0.0 | 0.9506 | 0.9611 |
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+ | 0.012 | 42.67 | 640 | 0.1048 | 0.6364 | 0.9768 | 0.9771 | nan | 0.9748 | 0.9789 | 0.0 | 0.9493 | 0.9601 |
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+ | 0.0261 | 44.0 | 660 | 0.1073 | 0.6364 | 0.9770 | 0.9771 | nan | 0.9760 | 0.9780 | 0.0 | 0.9493 | 0.9600 |
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+ | 0.0125 | 45.33 | 680 | 0.1088 | 0.6357 | 0.9761 | 0.9765 | nan | 0.9727 | 0.9795 | 0.0 | 0.9479 | 0.9591 |
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+ | 0.0259 | 46.67 | 700 | 0.1073 | 0.6365 | 0.9770 | 0.9772 | nan | 0.9760 | 0.9780 | 0.0 | 0.9494 | 0.9601 |
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+ | 0.0173 | 48.0 | 720 | 0.1052 | 0.6366 | 0.9770 | 0.9772 | nan | 0.9755 | 0.9785 | 0.0 | 0.9495 | 0.9602 |
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+ | 0.0162 | 49.33 | 740 | 0.1077 | 0.6364 | 0.9770 | 0.9771 | nan | 0.9758 | 0.9781 | 0.0 | 0.9493 | 0.9600 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.0.dev0
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.14.5
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+ - Tokenizers 0.14.0
config.json ADDED
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+ {
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+ "_name_or_path": "nvidia/mit-b5",
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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": 768,
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+ "depths": [
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+ 3,
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+ 6,
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+ 40,
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+ 3
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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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+ 64,
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+ 128,
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+ 320,
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+ 512
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+ ],
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+ "id2label": {
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+ "0": "unlabeled",
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+ "1": "traversable",
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+ "2": "non-traversable"
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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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+ "non-traversable": 2,
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+ "traversable": 1,
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+ "unlabeled": 0
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+ },
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+ "layer_norm_eps": 1e-06,
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+ "mlp_ratios": [
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+ 4,
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+ 4,
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+ 4,
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+ 4
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+ ],
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+ "model_type": "segformer",
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+ "num_attention_heads": [
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+ 1,
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+ 2,
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+ 5,
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+ 8
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+ ],
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+ "num_channels": 3,
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+ "num_encoder_blocks": 4,
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+ "patch_sizes": [
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+ 7,
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+ 3,
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+ 3,
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+ 3
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+ ],
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+ "reshape_last_stage": true,
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+ "semantic_loss_ignore_index": 255,
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+ "sr_ratios": [
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+ 8,
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+ 4,
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+ 2,
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+ 1
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+ ],
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+ "strides": [
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+ 4,
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+ 2,
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+ 2,
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+ 2
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+ ],
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.35.0.dev0"
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+ }
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