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segformer-b0_DsB

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segformer
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segformer-b0-finetuned-metallography_DsB

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  1. README.md +121 -0
  2. config.json +86 -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-b0
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: segformer-b0-finetuned-metallography_DsB
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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-b0-finetuned-metallography_DsB
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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: 0.0162
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+ - Mean Iou: 0.7889
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+ - Mean Accuracy: 0.9743
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+ - Overall Accuracy: 0.9937
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+ - Accuracy Background: nan
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+ - Accuracy Haz: 0.9934
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+ - Accuracy Matrix: 0.9859
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+ - Accuracy Porosity: 0.9183
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+ - Accuracy Carbides: 0.9759
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+ - Accuracy Substrate: 0.9981
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+ - Iou Background: 0.0
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+ - Iou Haz: 0.9909
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+ - Iou Matrix: 0.9758
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+ - Iou Porosity: 0.8239
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+ - Iou Carbides: 0.9504
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+ - Iou Substrate: 0.9926
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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 Background | Accuracy Haz | Accuracy Matrix | Accuracy Porosity | Accuracy Carbides | Accuracy Substrate | Iou Background | Iou Haz | Iou Matrix | Iou Porosity | Iou Carbides | Iou Substrate |
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+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:------------:|:---------------:|:-----------------:|:-----------------:|:------------------:|:--------------:|:-------:|:----------:|:------------:|:------------:|:-------------:|
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+ | 1.1925 | 1.0 | 350 | 0.2093 | 0.5751 | 0.7355 | 0.9228 | nan | 0.8617 | 0.9887 | 0.0 | 0.8605 | 0.9668 | 0.0 | 0.8289 | 0.9133 | 0.0 | 0.8400 | 0.8683 |
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+ | 0.3065 | 2.0 | 700 | 0.1070 | 0.6106 | 0.7607 | 0.9570 | nan | 0.9158 | 0.9711 | 0.0 | 0.9221 | 0.9945 | 0.0 | 0.9053 | 0.9400 | 0.0 | 0.8907 | 0.9276 |
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+ | 0.1839 | 3.0 | 1050 | 0.0717 | 0.6284 | 0.7777 | 0.9747 | nan | 0.9737 | 0.9668 | 0.0 | 0.9676 | 0.9802 | 0.0 | 0.9488 | 0.9513 | 0.0 | 0.9116 | 0.9590 |
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+ | 1.0057 | 4.0 | 1400 | 0.0470 | 0.6322 | 0.7765 | 0.9783 | nan | 0.9889 | 0.9718 | 0.0 | 0.9460 | 0.9761 | 0.0 | 0.9580 | 0.9493 | 0.0 | 0.9193 | 0.9669 |
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+ | 1.3313 | 5.0 | 1750 | 0.0360 | 0.6338 | 0.7751 | 0.9839 | nan | 0.9825 | 0.9861 | 0.0 | 0.9128 | 0.9940 | 0.0 | 0.9737 | 0.9478 | 0.0 | 0.9015 | 0.9799 |
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+ | 0.1398 | 6.0 | 2100 | 0.0333 | 0.6407 | 0.7849 | 0.9853 | nan | 0.9943 | 0.9782 | 0.0 | 0.9689 | 0.9830 | 0.0 | 0.9743 | 0.9623 | 0.0 | 0.9290 | 0.9787 |
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+ | 0.4763 | 7.0 | 2450 | 0.0941 | 0.6520 | 0.8054 | 0.9710 | nan | 0.9435 | 0.9745 | 0.1384 | 0.9757 | 0.9950 | 0.0 | 0.9367 | 0.9622 | 0.1384 | 0.9258 | 0.9486 |
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+ | 0.074 | 8.0 | 2800 | 0.0373 | 0.7154 | 0.8725 | 0.9848 | nan | 0.9877 | 0.9841 | 0.4466 | 0.9577 | 0.9864 | 0.0 | 0.9711 | 0.9646 | 0.4466 | 0.9339 | 0.9760 |
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+ | 0.0637 | 9.0 | 3150 | 0.0239 | 0.7358 | 0.8946 | 0.9885 | nan | 0.9867 | 0.9907 | 0.5610 | 0.9388 | 0.9956 | 0.0 | 0.9815 | 0.9631 | 0.5591 | 0.9258 | 0.9851 |
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+ | 0.0402 | 10.0 | 3500 | 0.0295 | 0.7462 | 0.9085 | 0.9865 | nan | 0.9774 | 0.9872 | 0.6256 | 0.9541 | 0.9982 | 0.0 | 0.9752 | 0.9662 | 0.6232 | 0.9333 | 0.9796 |
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+ | 1.069 | 11.0 | 3850 | 0.0244 | 0.7494 | 0.9115 | 0.9889 | nan | 0.9874 | 0.9908 | 0.6455 | 0.9383 | 0.9957 | 0.0 | 0.9822 | 0.9644 | 0.6384 | 0.9263 | 0.9854 |
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+ | 0.5997 | 12.0 | 4200 | 0.0243 | 0.7492 | 0.9106 | 0.9893 | nan | 0.9859 | 0.9884 | 0.6271 | 0.9545 | 0.9970 | 0.0 | 0.9817 | 0.9684 | 0.6246 | 0.9356 | 0.9850 |
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+ | 0.091 | 13.0 | 4550 | 0.0269 | 0.7557 | 0.9197 | 0.9886 | nan | 0.9858 | 0.9900 | 0.6747 | 0.9530 | 0.9950 | 0.0 | 0.9799 | 0.9693 | 0.6659 | 0.9361 | 0.9833 |
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+ | 1.3004 | 14.0 | 4900 | 0.0226 | 0.7740 | 0.9448 | 0.9906 | nan | 0.9887 | 0.9859 | 0.7857 | 0.9674 | 0.9964 | 0.0 | 0.9841 | 0.9719 | 0.7585 | 0.9424 | 0.9870 |
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+ | 0.94 | 15.0 | 5250 | 0.1346 | 0.7572 | 0.9315 | 0.9731 | nan | 0.9938 | 0.9862 | 0.7591 | 0.9657 | 0.9528 | 0.0 | 0.9423 | 0.9709 | 0.7399 | 0.9417 | 0.9481 |
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+ | 0.8906 | 16.0 | 5600 | 0.0221 | 0.7781 | 0.9528 | 0.9911 | nan | 0.9886 | 0.9844 | 0.8206 | 0.9729 | 0.9973 | 0.0 | 0.9851 | 0.9724 | 0.7805 | 0.9429 | 0.9877 |
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+ | 0.9739 | 17.0 | 5950 | 0.0233 | 0.7629 | 0.9264 | 0.9905 | nan | 0.9870 | 0.9914 | 0.7040 | 0.9516 | 0.9980 | 0.0 | 0.9845 | 0.9700 | 0.6986 | 0.9367 | 0.9874 |
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+ | 0.417 | 18.0 | 6300 | 0.0200 | 0.7724 | 0.9392 | 0.9917 | nan | 0.9911 | 0.9909 | 0.7618 | 0.9556 | 0.9967 | 0.0 | 0.9869 | 0.9718 | 0.7468 | 0.9399 | 0.9893 |
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+ | 0.0405 | 19.0 | 6650 | 0.1657 | 0.7661 | 0.9474 | 0.9743 | nan | 0.9434 | 0.9863 | 0.8421 | 0.9661 | 0.9991 | 0.0 | 0.9421 | 0.9718 | 0.7877 | 0.9422 | 0.9528 |
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+ | 1.2414 | 20.0 | 7000 | 0.0275 | 0.7808 | 0.9593 | 0.9900 | nan | 0.9844 | 0.9838 | 0.8565 | 0.9733 | 0.9986 | 0.0 | 0.9824 | 0.9725 | 0.8000 | 0.9442 | 0.9855 |
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+ | 0.7539 | 21.0 | 7350 | 0.0200 | 0.7791 | 0.9509 | 0.9918 | nan | 0.9947 | 0.9857 | 0.8106 | 0.9698 | 0.9936 | 0.0 | 0.9872 | 0.9724 | 0.7813 | 0.9445 | 0.9895 |
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+ | 0.0158 | 22.0 | 7700 | 0.0159 | 0.7773 | 0.9468 | 0.9926 | nan | 0.9924 | 0.9854 | 0.7855 | 0.9736 | 0.9972 | 0.0 | 0.9889 | 0.9731 | 0.7657 | 0.9448 | 0.9910 |
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+ | 0.3368 | 23.0 | 8050 | 0.0176 | 0.7849 | 0.9678 | 0.9925 | nan | 0.9962 | 0.9844 | 0.8892 | 0.9758 | 0.9933 | 0.0 | 0.9882 | 0.9739 | 0.8113 | 0.9459 | 0.9904 |
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+ | 0.0526 | 24.0 | 8400 | 0.0168 | 0.7835 | 0.9629 | 0.9927 | nan | 0.9916 | 0.9895 | 0.8727 | 0.9629 | 0.9978 | 0.0 | 0.9888 | 0.9739 | 0.8030 | 0.9448 | 0.9908 |
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+ | 0.9409 | 25.0 | 8750 | 0.0205 | 0.7842 | 0.9681 | 0.9920 | nan | 0.9899 | 0.9829 | 0.8925 | 0.9773 | 0.9980 | 0.0 | 0.9873 | 0.9732 | 0.8096 | 0.9452 | 0.9897 |
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+ | 1.0493 | 26.0 | 9100 | 0.0187 | 0.7823 | 0.9542 | 0.9924 | nan | 0.9906 | 0.9877 | 0.8277 | 0.9670 | 0.9981 | 0.0 | 0.9881 | 0.9736 | 0.7966 | 0.9454 | 0.9903 |
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+ | 0.0594 | 28.0 | 9800 | 0.0172 | 0.7882 | 0.9705 | 0.9932 | nan | 0.9942 | 0.9849 | 0.9007 | 0.9761 | 0.9965 | 0.0 | 0.9898 | 0.9749 | 0.8251 | 0.9479 | 0.9917 |
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+ | 1.1676 | 29.0 | 10150 | 0.0166 | 0.7867 | 0.9726 | 0.9930 | nan | 0.9948 | 0.9834 | 0.9115 | 0.9777 | 0.9957 | 0.0 | 0.9896 | 0.9741 | 0.8178 | 0.9474 | 0.9915 |
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+ | 0.076 | 30.0 | 10500 | 0.0184 | 0.7845 | 0.9595 | 0.9928 | nan | 0.9925 | 0.9898 | 0.8578 | 0.9598 | 0.9976 | 0.0 | 0.9895 | 0.9728 | 0.8090 | 0.9439 | 0.9917 |
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+ | 0.0709 | 31.0 | 10850 | 0.0187 | 0.7876 | 0.9726 | 0.9931 | nan | 0.9934 | 0.9842 | 0.9118 | 0.9764 | 0.9972 | 0.0 | 0.9897 | 0.9744 | 0.8215 | 0.9480 | 0.9917 |
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+ | 0.9141 | 36.0 | 12600 | 0.0151 | 0.7892 | 0.9686 | 0.9938 | nan | 0.9946 | 0.9881 | 0.8920 | 0.9712 | 0.9973 | 0.0 | 0.9912 | 0.9759 | 0.8254 | 0.9497 | 0.9929 |
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+ | 0.0195 | 37.0 | 12950 | 0.0169 | 0.7880 | 0.9653 | 0.9932 | nan | 0.9918 | 0.9875 | 0.8770 | 0.9719 | 0.9985 | 0.0 | 0.9897 | 0.9755 | 0.8219 | 0.9493 | 0.9916 |
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+ | 0.07 | 39.0 | 13650 | 0.0165 | 0.7880 | 0.9736 | 0.9935 | nan | 0.9941 | 0.9848 | 0.9152 | 0.9765 | 0.9973 | 0.0 | 0.9906 | 0.9750 | 0.8209 | 0.9491 | 0.9924 |
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+ | 0.0679 | 41.0 | 14350 | 0.0157 | 0.7895 | 0.9707 | 0.9936 | nan | 0.9945 | 0.9858 | 0.9012 | 0.9750 | 0.9972 | 0.0 | 0.9908 | 0.9754 | 0.8284 | 0.9499 | 0.9926 |
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+ | 0.0498 | 42.0 | 14700 | 0.0164 | 0.7866 | 0.9765 | 0.9935 | nan | 0.9938 | 0.9839 | 0.9292 | 0.9781 | 0.9976 | 0.0 | 0.9907 | 0.9748 | 0.8122 | 0.9494 | 0.9925 |
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+ | 1.2941 | 45.0 | 15750 | 0.0150 | 0.7888 | 0.9714 | 0.9939 | nan | 0.9954 | 0.9862 | 0.9044 | 0.9742 | 0.9968 | 0.0 | 0.9915 | 0.9754 | 0.8228 | 0.9499 | 0.9932 |
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+ | 0.0113 | 46.0 | 16100 | 0.0151 | 0.7893 | 0.9732 | 0.9939 | nan | 0.9943 | 0.9866 | 0.9130 | 0.9741 | 0.9978 | 0.0 | 0.9914 | 0.9759 | 0.8251 | 0.9505 | 0.9930 |
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+ | 0.9812 | 47.0 | 16450 | 0.0185 | 0.7875 | 0.9754 | 0.9933 | nan | 0.9920 | 0.9864 | 0.9257 | 0.9745 | 0.9984 | 0.0 | 0.9898 | 0.9759 | 0.8175 | 0.9503 | 0.9917 |
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+ | 0.0126 | 48.0 | 16800 | 0.0152 | 0.7887 | 0.9743 | 0.9938 | nan | 0.9942 | 0.9856 | 0.9185 | 0.9755 | 0.9976 | 0.0 | 0.9911 | 0.9756 | 0.8221 | 0.9506 | 0.9929 |
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+ | 1.4415 | 49.0 | 17150 | 0.0154 | 0.7894 | 0.9674 | 0.9940 | nan | 0.9952 | 0.9872 | 0.8839 | 0.9734 | 0.9972 | 0.0 | 0.9917 | 0.9759 | 0.8255 | 0.9501 | 0.9934 |
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+ | 0.0285 | 50.0 | 17500 | 0.0162 | 0.7889 | 0.9743 | 0.9937 | nan | 0.9934 | 0.9859 | 0.9183 | 0.9759 | 0.9981 | 0.0 | 0.9909 | 0.9758 | 0.8239 | 0.9504 | 0.9926 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.32.1
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.14.4
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+ - Tokenizers 0.13.3
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,
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+ 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": "background",
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+ "1": "HAZ",
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+ "2": "matrix",
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+ "3": "porosity",
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+ "4": "carbides",
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+ "5": "substrate"
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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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+ "HAZ": 1,
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+ "background": 0,
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+ "carbides": 4,
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+ "matrix": 2,
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+ "porosity": 3,
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+ "substrate": 5
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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": "4.32.1"
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+ }
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