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twdent
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segformer-b5-finetuned-Hiking

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-Hiking
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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-Hiking
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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/Hiking dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1401
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+ - Mean Iou: 0.6237
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+ - Mean Accuracy: 0.9673
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+ - Overall Accuracy: 0.9683
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+ - Accuracy Unlabeled: nan
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+ - Accuracy Traversable: 0.9641
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+ - Accuracy Non-traversable: 0.9705
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+ - Iou Unlabeled: 0.0
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+ - Iou Traversable: 0.9178
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+ - Iou Non-traversable: 0.9532
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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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+ | 0.2675 | 1.33 | 20 | 0.2742 | 0.6058 | 0.9616 | 0.9550 | nan | 0.9826 | 0.9406 | 0.0 | 0.8853 | 0.9321 |
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+ | 0.1418 | 2.67 | 40 | 0.1827 | 0.6073 | 0.9562 | 0.9566 | nan | 0.9548 | 0.9575 | 0.0 | 0.8858 | 0.9360 |
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+ | 0.0949 | 4.0 | 60 | 0.1561 | 0.6002 | 0.9382 | 0.9523 | nan | 0.8931 | 0.9832 | 0.0 | 0.8692 | 0.9314 |
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+ | 0.0684 | 5.33 | 80 | 0.1364 | 0.6135 | 0.9556 | 0.9614 | nan | 0.9369 | 0.9742 | 0.0 | 0.8967 | 0.9437 |
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+ | 0.0627 | 6.67 | 100 | 0.1289 | 0.6122 | 0.9506 | 0.9610 | nan | 0.9177 | 0.9836 | 0.0 | 0.8928 | 0.9438 |
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+ | 0.0625 | 8.0 | 120 | 0.1097 | 0.6208 | 0.9610 | 0.9658 | nan | 0.9458 | 0.9762 | 0.0 | 0.9113 | 0.9510 |
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+ | 0.0371 | 9.33 | 140 | 0.1361 | 0.6130 | 0.9551 | 0.9610 | nan | 0.9361 | 0.9741 | 0.0 | 0.8959 | 0.9431 |
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+ | 0.0409 | 10.67 | 160 | 0.1239 | 0.6194 | 0.9615 | 0.9653 | nan | 0.9494 | 0.9737 | 0.0 | 0.9086 | 0.9494 |
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+ | 0.0457 | 12.0 | 180 | 0.0993 | 0.6281 | 0.9715 | 0.9713 | nan | 0.9723 | 0.9707 | 0.0 | 0.9264 | 0.9579 |
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+ | 0.0368 | 13.33 | 200 | 0.1354 | 0.6146 | 0.9563 | 0.9617 | nan | 0.9389 | 0.9737 | 0.0 | 0.8993 | 0.9446 |
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+ | 0.0667 | 14.67 | 220 | 0.1208 | 0.6171 | 0.9565 | 0.9644 | nan | 0.9316 | 0.9815 | 0.0 | 0.9032 | 0.9482 |
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+ | 0.029 | 16.0 | 240 | 0.0946 | 0.6291 | 0.9695 | 0.9724 | nan | 0.9606 | 0.9785 | 0.0 | 0.9276 | 0.9596 |
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+ | 0.0467 | 17.33 | 260 | 0.1188 | 0.6224 | 0.9655 | 0.9676 | nan | 0.9589 | 0.9721 | 0.0 | 0.9151 | 0.9522 |
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+ | 0.0449 | 18.67 | 280 | 0.1201 | 0.6212 | 0.9638 | 0.9667 | nan | 0.9545 | 0.9731 | 0.0 | 0.9125 | 0.9511 |
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+ | 0.0353 | 20.0 | 300 | 0.1285 | 0.6234 | 0.9687 | 0.9681 | nan | 0.9706 | 0.9668 | 0.0 | 0.9174 | 0.9527 |
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+ | 0.025 | 21.33 | 320 | 0.1292 | 0.6204 | 0.9641 | 0.9659 | nan | 0.9582 | 0.9699 | 0.0 | 0.9114 | 0.9500 |
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+ | 0.0244 | 22.67 | 340 | 0.1352 | 0.6208 | 0.9665 | 0.9664 | nan | 0.9667 | 0.9662 | 0.0 | 0.9124 | 0.9501 |
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+ | 0.035 | 24.0 | 360 | 0.1260 | 0.6252 | 0.9699 | 0.9693 | nan | 0.9718 | 0.9681 | 0.0 | 0.9211 | 0.9544 |
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+ | 0.0295 | 25.33 | 380 | 0.1190 | 0.6244 | 0.9669 | 0.9688 | nan | 0.9607 | 0.9730 | 0.0 | 0.9190 | 0.9543 |
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+ | 0.032 | 26.67 | 400 | 0.1258 | 0.6253 | 0.9694 | 0.9695 | nan | 0.9693 | 0.9695 | 0.0 | 0.9211 | 0.9547 |
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+ | 0.0241 | 28.0 | 420 | 0.1255 | 0.6230 | 0.9658 | 0.9678 | nan | 0.9593 | 0.9723 | 0.0 | 0.9164 | 0.9527 |
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+ | 0.0246 | 29.33 | 440 | 0.1273 | 0.6238 | 0.9675 | 0.9683 | nan | 0.9651 | 0.9699 | 0.0 | 0.9179 | 0.9534 |
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+ | 0.0214 | 30.67 | 460 | 0.1321 | 0.6233 | 0.9670 | 0.9675 | nan | 0.9652 | 0.9687 | 0.0 | 0.9171 | 0.9527 |
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+ | 0.0236 | 32.0 | 480 | 0.1289 | 0.6241 | 0.9687 | 0.9685 | nan | 0.9695 | 0.9679 | 0.0 | 0.9189 | 0.9534 |
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+ | 0.0238 | 33.33 | 500 | 0.1309 | 0.6234 | 0.9664 | 0.9680 | nan | 0.9612 | 0.9716 | 0.0 | 0.9172 | 0.9529 |
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+ | 0.0204 | 34.67 | 520 | 0.1271 | 0.6249 | 0.9681 | 0.9693 | nan | 0.9643 | 0.9719 | 0.0 | 0.9201 | 0.9547 |
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+ | 0.0243 | 36.0 | 540 | 0.1264 | 0.6248 | 0.9679 | 0.9693 | nan | 0.9636 | 0.9723 | 0.0 | 0.9196 | 0.9547 |
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+ | 0.0259 | 37.33 | 560 | 0.1305 | 0.6226 | 0.9656 | 0.9679 | nan | 0.9582 | 0.9730 | 0.0 | 0.9154 | 0.9525 |
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+ | 0.0341 | 38.67 | 580 | 0.1277 | 0.6245 | 0.9674 | 0.9690 | nan | 0.9623 | 0.9725 | 0.0 | 0.9192 | 0.9543 |
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+ | 0.0275 | 40.0 | 600 | 0.1369 | 0.6221 | 0.9653 | 0.9672 | nan | 0.9590 | 0.9715 | 0.0 | 0.9147 | 0.9516 |
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+ | 0.0303 | 41.33 | 620 | 0.1380 | 0.6235 | 0.9674 | 0.9681 | nan | 0.9650 | 0.9698 | 0.0 | 0.9175 | 0.9530 |
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+ | 0.0207 | 42.67 | 640 | 0.1389 | 0.6237 | 0.9677 | 0.9682 | nan | 0.9662 | 0.9692 | 0.0 | 0.9180 | 0.9531 |
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+ | 0.0231 | 44.0 | 660 | 0.1369 | 0.6243 | 0.9679 | 0.9688 | nan | 0.9652 | 0.9707 | 0.0 | 0.9190 | 0.9538 |
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+ | 0.0249 | 45.33 | 680 | 0.1379 | 0.6237 | 0.9672 | 0.9683 | nan | 0.9640 | 0.9705 | 0.0 | 0.9179 | 0.9532 |
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+ | 0.0382 | 46.67 | 700 | 0.1384 | 0.6239 | 0.9677 | 0.9685 | nan | 0.9650 | 0.9704 | 0.0 | 0.9182 | 0.9534 |
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+ | 0.0238 | 48.0 | 720 | 0.1420 | 0.6230 | 0.9668 | 0.9677 | nan | 0.9640 | 0.9697 | 0.0 | 0.9166 | 0.9524 |
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+ | 0.0212 | 49.33 | 740 | 0.1401 | 0.6237 | 0.9673 | 0.9683 | nan | 0.9641 | 0.9705 | 0.0 | 0.9178 | 0.9532 |
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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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+ ],
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+ "model_type": "segformer",
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+ "num_attention_heads": [
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+ 1,
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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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+ ],
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+ "strides": [
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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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