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  1. README.md +160 -0
  2. config.json +78 -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-b3-finetuned-100by100PNG-50epochs-attempt2-100epochs-backgroundclass
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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-b3-finetuned-100by100PNG-50epochs-attempt2-100epochs-backgroundclass
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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 JCAI2000/100By100BranchPNG dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1497
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+ - Mean Iou: 0.8933
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+ - Mean Accuracy: 0.9531
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+ - Overall Accuracy: 0.9662
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+ - Accuracy Background: 0.9732
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+ - Accuracy Branch: 0.9330
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+ - Iou Background: 0.9597
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+ - Iou Branch: 0.8270
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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: 100
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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 Background | Accuracy Branch | Iou Background | Iou Branch |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:---------------:|:--------------:|:----------:|
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+ | 0.2055 | 1.05 | 20 | 0.2925 | 0.8151 | 0.9469 | 0.9320 | 0.9242 | 0.9695 | 0.9183 | 0.7118 |
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+ | 0.1549 | 2.11 | 40 | 0.1328 | 0.8802 | 0.9311 | 0.9628 | 0.9796 | 0.8825 | 0.9561 | 0.8043 |
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+ | 0.0735 | 3.16 | 60 | 0.1178 | 0.8804 | 0.9512 | 0.9613 | 0.9666 | 0.9357 | 0.9538 | 0.8070 |
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+ | 0.0636 | 4.21 | 80 | 0.0844 | 0.8966 | 0.9368 | 0.9686 | 0.9854 | 0.8881 | 0.9629 | 0.8303 |
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+ | 0.0546 | 5.26 | 100 | 0.1099 | 0.8969 | 0.9526 | 0.9676 | 0.9756 | 0.9297 | 0.9614 | 0.8325 |
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+ | 0.0567 | 6.32 | 120 | 0.1012 | 0.8996 | 0.9500 | 0.9688 | 0.9788 | 0.9213 | 0.9629 | 0.8364 |
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+ | 0.0515 | 7.37 | 140 | 0.1137 | 0.8935 | 0.9462 | 0.9668 | 0.9777 | 0.9147 | 0.9605 | 0.8265 |
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+ | 0.052 | 8.42 | 160 | 0.0987 | 0.8914 | 0.9317 | 0.9670 | 0.9858 | 0.8776 | 0.9611 | 0.8217 |
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+ | 0.0358 | 9.47 | 180 | 0.1167 | 0.8978 | 0.9581 | 0.9676 | 0.9726 | 0.9435 | 0.9613 | 0.8344 |
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+ | 0.0254 | 10.53 | 200 | 0.0767 | 0.9111 | 0.9519 | 0.9729 | 0.9840 | 0.9197 | 0.9678 | 0.8545 |
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+ | 0.0483 | 11.58 | 220 | 0.0953 | 0.9037 | 0.9524 | 0.9701 | 0.9795 | 0.9253 | 0.9645 | 0.8429 |
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+ | 0.0285 | 12.63 | 240 | 0.0904 | 0.9026 | 0.9490 | 0.9700 | 0.9811 | 0.9169 | 0.9643 | 0.8409 |
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+ | 0.0389 | 13.68 | 260 | 0.0902 | 0.9025 | 0.9472 | 0.9701 | 0.9821 | 0.9123 | 0.9644 | 0.8406 |
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+ | 0.0473 | 14.74 | 280 | 0.0852 | 0.9084 | 0.9522 | 0.9719 | 0.9823 | 0.9220 | 0.9665 | 0.8502 |
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+ | 0.0266 | 15.79 | 300 | 0.0983 | 0.8985 | 0.9409 | 0.9690 | 0.9839 | 0.8979 | 0.9633 | 0.8337 |
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+ | 0.0233 | 16.84 | 320 | 0.0965 | 0.9052 | 0.9601 | 0.9702 | 0.9756 | 0.9447 | 0.9644 | 0.8460 |
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+ | 0.0257 | 17.89 | 340 | 0.0941 | 0.9039 | 0.9550 | 0.9701 | 0.9781 | 0.9319 | 0.9643 | 0.8434 |
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+ | 0.0352 | 18.95 | 360 | 0.0855 | 0.9043 | 0.9483 | 0.9706 | 0.9824 | 0.9142 | 0.9651 | 0.8435 |
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+ | 0.1941 | 20.0 | 380 | 0.0946 | 0.9045 | 0.9509 | 0.9706 | 0.9809 | 0.9210 | 0.9650 | 0.8441 |
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+ | 0.0325 | 21.05 | 400 | 0.0972 | 0.8973 | 0.9449 | 0.9683 | 0.9807 | 0.9092 | 0.9624 | 0.8323 |
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+ | 0.0159 | 22.11 | 420 | 0.0828 | 0.9081 | 0.9528 | 0.9717 | 0.9817 | 0.9239 | 0.9664 | 0.8498 |
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+ | 0.0175 | 23.16 | 440 | 0.1061 | 0.8995 | 0.9491 | 0.9688 | 0.9793 | 0.9188 | 0.9629 | 0.8360 |
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+ | 0.0281 | 24.21 | 460 | 0.1090 | 0.8969 | 0.9516 | 0.9677 | 0.9761 | 0.9271 | 0.9615 | 0.8323 |
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+ | 0.0177 | 25.26 | 480 | 0.1122 | 0.8983 | 0.9547 | 0.9680 | 0.9750 | 0.9343 | 0.9618 | 0.8347 |
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+ | 0.0228 | 26.32 | 500 | 0.1088 | 0.8957 | 0.9546 | 0.9670 | 0.9736 | 0.9357 | 0.9606 | 0.8307 |
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+ | 0.0348 | 27.37 | 520 | 0.0933 | 0.9059 | 0.9524 | 0.9710 | 0.9808 | 0.9241 | 0.9654 | 0.8464 |
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+ | 0.0177 | 28.42 | 540 | 0.1053 | 0.9025 | 0.9527 | 0.9697 | 0.9787 | 0.9268 | 0.9639 | 0.8411 |
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+ | 0.0182 | 29.47 | 560 | 0.1039 | 0.8992 | 0.9473 | 0.9688 | 0.9802 | 0.9143 | 0.9630 | 0.8355 |
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+ | 0.0171 | 30.53 | 580 | 0.1117 | 0.8991 | 0.9555 | 0.9682 | 0.9750 | 0.9360 | 0.9621 | 0.8361 |
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+ | 0.0275 | 31.58 | 600 | 0.1142 | 0.8935 | 0.9497 | 0.9665 | 0.9754 | 0.9241 | 0.9601 | 0.8268 |
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+ | 0.0186 | 32.63 | 620 | 0.1065 | 0.9024 | 0.9524 | 0.9697 | 0.9788 | 0.9261 | 0.9639 | 0.8408 |
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+ | 0.0173 | 33.68 | 640 | 0.1081 | 0.8986 | 0.9529 | 0.9682 | 0.9764 | 0.9294 | 0.9621 | 0.8351 |
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+ | 0.015 | 34.74 | 660 | 0.1243 | 0.8935 | 0.9530 | 0.9663 | 0.9733 | 0.9327 | 0.9598 | 0.8272 |
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+ | 0.0183 | 35.79 | 680 | 0.1120 | 0.9005 | 0.9500 | 0.9691 | 0.9792 | 0.9209 | 0.9633 | 0.8377 |
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+ | 0.0248 | 36.84 | 700 | 0.1185 | 0.8962 | 0.9517 | 0.9674 | 0.9757 | 0.9277 | 0.9611 | 0.8312 |
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+ | 0.0104 | 37.89 | 720 | 0.1136 | 0.8975 | 0.9506 | 0.9680 | 0.9771 | 0.9241 | 0.9619 | 0.8332 |
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+ | 0.0481 | 38.95 | 740 | 0.1127 | 0.9010 | 0.9528 | 0.9691 | 0.9778 | 0.9277 | 0.9632 | 0.8388 |
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+ | 0.0153 | 40.0 | 760 | 0.1101 | 0.9019 | 0.9537 | 0.9694 | 0.9777 | 0.9297 | 0.9635 | 0.8402 |
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+ | 0.0143 | 41.05 | 780 | 0.1105 | 0.9032 | 0.9558 | 0.9698 | 0.9771 | 0.9345 | 0.9639 | 0.8425 |
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+ | 0.0104 | 42.11 | 800 | 0.1122 | 0.8986 | 0.9428 | 0.9689 | 0.9827 | 0.9028 | 0.9631 | 0.8340 |
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+ | 0.0172 | 43.16 | 820 | 0.1097 | 0.9041 | 0.9540 | 0.9702 | 0.9788 | 0.9291 | 0.9645 | 0.8437 |
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+ | 0.0371 | 44.21 | 840 | 0.1064 | 0.9011 | 0.9503 | 0.9693 | 0.9794 | 0.9212 | 0.9635 | 0.8387 |
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+ | 0.0221 | 45.26 | 860 | 0.1150 | 0.9004 | 0.9515 | 0.9690 | 0.9783 | 0.9247 | 0.9631 | 0.8377 |
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+ | 0.0186 | 46.32 | 880 | 0.1228 | 0.8958 | 0.9518 | 0.9672 | 0.9754 | 0.9282 | 0.9610 | 0.8306 |
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+ | 0.0119 | 47.37 | 900 | 0.1205 | 0.8980 | 0.9525 | 0.9680 | 0.9762 | 0.9288 | 0.9619 | 0.8340 |
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+ | 0.0113 | 48.42 | 920 | 0.1133 | 0.8998 | 0.9502 | 0.9688 | 0.9787 | 0.9216 | 0.9629 | 0.8366 |
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+ | 0.0121 | 49.47 | 940 | 0.1145 | 0.8993 | 0.9490 | 0.9688 | 0.9792 | 0.9188 | 0.9629 | 0.8358 |
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+ | 0.0263 | 50.53 | 960 | 0.1168 | 0.8977 | 0.9542 | 0.9678 | 0.9750 | 0.9334 | 0.9616 | 0.8338 |
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+ | 0.0093 | 51.58 | 980 | 0.1213 | 0.8940 | 0.9534 | 0.9664 | 0.9733 | 0.9334 | 0.9600 | 0.8280 |
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+ | 0.0193 | 52.63 | 1000 | 0.1241 | 0.8971 | 0.9507 | 0.9678 | 0.9769 | 0.9246 | 0.9617 | 0.8326 |
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+ | 0.0139 | 53.68 | 1020 | 0.1263 | 0.8962 | 0.9546 | 0.9672 | 0.9739 | 0.9353 | 0.9609 | 0.8316 |
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+ | 0.012 | 54.74 | 1040 | 0.1252 | 0.8952 | 0.9504 | 0.9671 | 0.9760 | 0.9247 | 0.9609 | 0.8296 |
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+ | 0.008 | 55.79 | 1060 | 0.1219 | 0.8986 | 0.9516 | 0.9683 | 0.9772 | 0.9260 | 0.9623 | 0.8349 |
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+ | 0.0092 | 56.84 | 1080 | 0.1290 | 0.8995 | 0.9552 | 0.9684 | 0.9754 | 0.9349 | 0.9623 | 0.8366 |
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+ | 0.015 | 57.89 | 1100 | 0.1243 | 0.8989 | 0.9545 | 0.9682 | 0.9755 | 0.9335 | 0.9621 | 0.8358 |
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+ | 0.0126 | 58.95 | 1120 | 0.1214 | 0.8977 | 0.9541 | 0.9678 | 0.9751 | 0.9331 | 0.9616 | 0.8337 |
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+ | 0.0212 | 60.0 | 1140 | 0.1298 | 0.8953 | 0.9542 | 0.9669 | 0.9736 | 0.9347 | 0.9605 | 0.8301 |
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+ | 0.0192 | 61.05 | 1160 | 0.1341 | 0.8930 | 0.9518 | 0.9661 | 0.9737 | 0.9299 | 0.9597 | 0.8262 |
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+ | 0.0136 | 62.11 | 1180 | 0.1327 | 0.8970 | 0.9528 | 0.9676 | 0.9754 | 0.9302 | 0.9614 | 0.8325 |
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+ | 0.0131 | 63.16 | 1200 | 0.1233 | 0.8997 | 0.9549 | 0.9685 | 0.9757 | 0.9340 | 0.9624 | 0.8369 |
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+ | 0.0135 | 64.21 | 1220 | 0.1301 | 0.8957 | 0.9542 | 0.9670 | 0.9738 | 0.9345 | 0.9607 | 0.8307 |
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+ | 0.0228 | 65.26 | 1240 | 0.1274 | 0.8979 | 0.9524 | 0.9680 | 0.9762 | 0.9285 | 0.9618 | 0.8339 |
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+ | 0.0138 | 66.32 | 1260 | 0.1336 | 0.8965 | 0.9520 | 0.9675 | 0.9757 | 0.9283 | 0.9613 | 0.8318 |
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+ | 0.0127 | 67.37 | 1280 | 0.1278 | 0.8980 | 0.9519 | 0.9681 | 0.9767 | 0.9271 | 0.9620 | 0.8341 |
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+ | 0.0107 | 68.42 | 1300 | 0.1293 | 0.8970 | 0.9530 | 0.9676 | 0.9753 | 0.9308 | 0.9614 | 0.8327 |
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+ | 0.0278 | 69.47 | 1320 | 0.1413 | 0.8926 | 0.9534 | 0.9659 | 0.9725 | 0.9343 | 0.9593 | 0.8258 |
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+ | 0.0159 | 70.53 | 1340 | 0.1360 | 0.8953 | 0.9522 | 0.9670 | 0.9748 | 0.9296 | 0.9607 | 0.8298 |
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+ | 0.0105 | 71.58 | 1360 | 0.1319 | 0.8972 | 0.9537 | 0.9676 | 0.9750 | 0.9324 | 0.9614 | 0.8330 |
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+ | 0.0168 | 72.63 | 1380 | 0.1343 | 0.8942 | 0.9533 | 0.9665 | 0.9735 | 0.9331 | 0.9601 | 0.8283 |
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+ | 0.0156 | 73.68 | 1400 | 0.1357 | 0.8950 | 0.9516 | 0.9669 | 0.9751 | 0.9281 | 0.9606 | 0.8294 |
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+ | 0.0109 | 74.74 | 1420 | 0.1446 | 0.8905 | 0.9524 | 0.9652 | 0.9719 | 0.9328 | 0.9585 | 0.8226 |
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+ | 0.0168 | 75.79 | 1440 | 0.1339 | 0.8958 | 0.9533 | 0.9671 | 0.9745 | 0.9320 | 0.9608 | 0.8308 |
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+ | 0.0252 | 76.84 | 1460 | 0.1355 | 0.8935 | 0.9532 | 0.9662 | 0.9731 | 0.9333 | 0.9597 | 0.8272 |
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+ | 0.0109 | 77.89 | 1480 | 0.1388 | 0.8932 | 0.9533 | 0.9661 | 0.9729 | 0.9338 | 0.9596 | 0.8267 |
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+ | 0.0109 | 78.95 | 1500 | 0.1404 | 0.8924 | 0.9519 | 0.9659 | 0.9734 | 0.9305 | 0.9594 | 0.8255 |
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+ | 0.0112 | 80.0 | 1520 | 0.1424 | 0.8921 | 0.9535 | 0.9657 | 0.9722 | 0.9349 | 0.9591 | 0.8251 |
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+ | 0.0094 | 81.05 | 1540 | 0.1451 | 0.8924 | 0.9524 | 0.9659 | 0.9730 | 0.9317 | 0.9593 | 0.8254 |
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+ | 0.007 | 82.11 | 1560 | 0.1457 | 0.8931 | 0.9527 | 0.9661 | 0.9732 | 0.9322 | 0.9596 | 0.8266 |
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+ | 0.0119 | 83.16 | 1580 | 0.1424 | 0.8927 | 0.9520 | 0.9661 | 0.9735 | 0.9306 | 0.9595 | 0.8259 |
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+ | 0.0153 | 84.21 | 1600 | 0.1535 | 0.8909 | 0.9530 | 0.9653 | 0.9718 | 0.9342 | 0.9586 | 0.8233 |
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+ | 0.0104 | 85.26 | 1620 | 0.1452 | 0.8921 | 0.9529 | 0.9658 | 0.9725 | 0.9333 | 0.9592 | 0.8251 |
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+ | 0.0101 | 86.32 | 1640 | 0.1503 | 0.8910 | 0.9536 | 0.9653 | 0.9714 | 0.9358 | 0.9586 | 0.8235 |
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+ | 0.009 | 87.37 | 1660 | 0.1508 | 0.8925 | 0.9532 | 0.9659 | 0.9725 | 0.9339 | 0.9593 | 0.8257 |
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+ | 0.0073 | 88.42 | 1680 | 0.1419 | 0.8949 | 0.9528 | 0.9668 | 0.9742 | 0.9315 | 0.9604 | 0.8293 |
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+ | 0.0137 | 89.47 | 1700 | 0.1437 | 0.8942 | 0.9526 | 0.9666 | 0.9739 | 0.9313 | 0.9601 | 0.8282 |
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+ | 0.0061 | 90.53 | 1720 | 0.1474 | 0.8928 | 0.9523 | 0.9660 | 0.9733 | 0.9313 | 0.9595 | 0.8260 |
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+ | 0.0132 | 91.58 | 1740 | 0.1408 | 0.8935 | 0.9522 | 0.9663 | 0.9738 | 0.9306 | 0.9598 | 0.8271 |
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+ | 0.0089 | 92.63 | 1760 | 0.1468 | 0.8933 | 0.9527 | 0.9662 | 0.9734 | 0.9320 | 0.9597 | 0.8268 |
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+ | 0.0141 | 93.68 | 1780 | 0.1458 | 0.8930 | 0.9529 | 0.9661 | 0.9731 | 0.9328 | 0.9596 | 0.8265 |
147
+ | 0.0132 | 94.74 | 1800 | 0.1442 | 0.8934 | 0.9528 | 0.9662 | 0.9733 | 0.9324 | 0.9597 | 0.8270 |
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+ | 0.0109 | 95.79 | 1820 | 0.1445 | 0.8928 | 0.9529 | 0.9660 | 0.9730 | 0.9327 | 0.9595 | 0.8262 |
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+ | 0.0248 | 96.84 | 1840 | 0.1391 | 0.8938 | 0.9529 | 0.9664 | 0.9736 | 0.9322 | 0.9599 | 0.8276 |
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+ | 0.0074 | 97.89 | 1860 | 0.1424 | 0.8938 | 0.9531 | 0.9664 | 0.9735 | 0.9327 | 0.9599 | 0.8277 |
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+ | 0.0072 | 98.95 | 1880 | 0.1465 | 0.8931 | 0.9534 | 0.9661 | 0.9728 | 0.9339 | 0.9596 | 0.8266 |
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+ | 0.0183 | 100.0 | 1900 | 0.1497 | 0.8933 | 0.9531 | 0.9662 | 0.9732 | 0.9330 | 0.9597 | 0.8270 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.33.0
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+ - Pytorch 2.0.1+cu117
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+ - Datasets 2.14.4
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+ - Tokenizers 0.13.3
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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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+ "classifier_dropout_prob": 0.1,
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+ 3
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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": "background",
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+ "branch": 1
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+ },
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+ "layer_norm_eps": 1e-06,
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+ "mlp_ratios": [
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+ "model_type": "segformer",
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+ "num_attention_heads": [
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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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+ "reshape_last_stage": true,
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+ "semantic_loss_ignore_index": 255,
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+ "sr_ratios": [
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.33.0"
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+ }
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