generated_from_trainer

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segformer-b0_DsA1

This model is a fine-tuned version of nvidia/mit-b0 on an unknown dataset. It achieves the following results on the evaluation set:

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

Training results

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
0.4915 1.0 390 0.0877 0.6229 0.7723 0.9723 nan 0.9770 0.9720 0.0 0.9346 0.9779 0.0 0.9501 0.9367 0.0 0.8867 0.9638
0.3601 2.0 780 0.0608 0.6259 0.7710 0.9744 nan 0.9881 0.9849 0.0 0.9085 0.9734 0.0 0.9556 0.9423 0.0 0.8919 0.9654
1.9097 3.0 1170 0.0419 0.6385 0.7837 0.9826 nan 0.9820 0.9784 0.0 0.9682 0.9901 0.0 0.9695 0.9610 0.0 0.9236 0.9767
2.401 4.0 1560 0.0658 0.6718 0.8261 0.9744 nan 0.9948 0.9852 0.2337 0.9574 0.9594 0.0 0.9465 0.9642 0.2333 0.9311 0.9556
2.4115 5.0 1950 0.0253 0.7479 0.9119 0.9880 nan 0.9925 0.9850 0.6293 0.9618 0.9909 0.0 0.9807 0.9669 0.6154 0.9389 0.9852
1.0366 6.0 2340 0.0523 0.7747 0.9475 0.9825 nan 0.9681 0.9832 0.8235 0.9653 0.9972 0.0 0.9633 0.9670 0.8049 0.9408 0.9722
1.4287 7.0 2730 0.0217 0.7834 0.9626 0.9888 nan 0.9944 0.9879 0.8795 0.9619 0.9893 0.0 0.9811 0.9701 0.8212 0.9426 0.9852
1.4637 8.0 3120 0.0212 0.7908 0.9692 0.9893 nan 0.9960 0.9822 0.9038 0.9752 0.9890 0.0 0.9822 0.9705 0.8611 0.9449 0.9861
1.2401 9.0 3510 0.0204 0.7905 0.9679 0.9902 nan 0.9921 0.9864 0.8999 0.9674 0.9939 0.0 0.9844 0.9712 0.8538 0.9453 0.9880
1.2133 10.0 3900 0.0181 0.7915 0.9714 0.9907 nan 0.9935 0.9860 0.9164 0.9673 0.9940 0.0 0.9858 0.9709 0.8578 0.9451 0.9892
0.0667 11.0 4290 0.0172 0.7945 0.9707 0.9913 nan 0.9917 0.9839 0.9064 0.9751 0.9965 0.0 0.9869 0.9722 0.8713 0.9469 0.9900
0.0292 12.0 4680 0.0168 0.7959 0.9723 0.9916 nan 0.9900 0.9867 0.9174 0.9687 0.9985 0.0 0.9876 0.9722 0.8774 0.9473 0.9906
1.0385 13.0 5070 0.0169 0.7955 0.9757 0.9914 nan 0.9981 0.9837 0.9300 0.9750 0.9916 0.0 0.9874 0.9721 0.8753 0.9476 0.9903
1.8648 14.0 5460 0.0231 0.7953 0.9733 0.9914 nan 0.9893 0.9856 0.9211 0.9722 0.9984 0.0 0.9871 0.9721 0.8744 0.9480 0.9904
0.1106 15.0 5850 0.0141 0.7972 0.9744 0.9927 nan 0.9965 0.9875 0.9228 0.9696 0.9954 0.0 0.9906 0.9733 0.8776 0.9488 0.9930
0.1963 16.0 6240 0.0131 0.7985 0.9756 0.9933 nan 0.9962 0.9876 0.9270 0.9703 0.9968 0.0 0.9921 0.9735 0.8822 0.9490 0.9944
0.0299 17.0 6630 0.0146 0.7984 0.9795 0.9930 nan 0.9942 0.9869 0.9467 0.9720 0.9976 0.0 0.9910 0.9738 0.8824 0.9500 0.9934
0.0464 18.0 7020 0.0126 0.7997 0.9796 0.9935 nan 0.9952 0.9859 0.9442 0.9749 0.9980 0.0 0.9924 0.9740 0.8871 0.9502 0.9945
0.0197 19.0 7410 0.0132 0.8002 0.9792 0.9931 nan 0.9981 0.9837 0.9408 0.9783 0.9950 0.0 0.9915 0.9735 0.8921 0.9502 0.9937
0.0691 20.0 7800 0.0131 0.8007 0.9793 0.9934 nan 0.9974 0.9832 0.9398 0.9798 0.9961 0.0 0.9923 0.9735 0.8939 0.9499 0.9944
0.0384 21.0 8190 0.0121 0.8004 0.9810 0.9937 nan 0.9970 0.9855 0.9504 0.9751 0.9971 0.0 0.9931 0.9740 0.8895 0.9510 0.9950
0.0125 22.0 8580 0.0115 0.8019 0.9779 0.9941 nan 0.9967 0.9862 0.9330 0.9757 0.9979 0.0 0.9938 0.9746 0.8962 0.9514 0.9955
0.8233 23.0 8970 0.0119 0.8012 0.9788 0.9938 nan 0.9972 0.9850 0.9372 0.9774 0.9969 0.0 0.9933 0.9741 0.8937 0.9511 0.9951
2.932 24.0 9360 0.0132 0.8008 0.9762 0.9938 nan 0.9968 0.9882 0.9270 0.9722 0.9970 0.0 0.9928 0.9749 0.8912 0.9513 0.9947
0.056 25.0 9750 0.0122 0.8014 0.9783 0.9939 nan 0.9959 0.9864 0.9358 0.9755 0.9981 0.0 0.9932 0.9747 0.8942 0.9514 0.9950
0.0626 26.0 10140 0.0116 0.8016 0.9799 0.9940 nan 0.9955 0.9857 0.9427 0.9767 0.9986 0.0 0.9937 0.9746 0.8945 0.9517 0.9955
0.0146 27.0 10530 0.0112 0.8019 0.9782 0.9943 nan 0.9966 0.9865 0.9338 0.9757 0.9983 0.0 0.9942 0.9749 0.8950 0.9518 0.9958
0.0879 28.0 10920 0.0117 0.8016 0.9795 0.9940 nan 0.9969 0.9886 0.9442 0.9699 0.9976 0.0 0.9937 0.9746 0.8947 0.9510 0.9955
0.0165 29.0 11310 0.0114 0.8020 0.9787 0.9942 nan 0.9966 0.9883 0.9385 0.9719 0.9981 0.0 0.9940 0.9750 0.8958 0.9517 0.9957
0.6593 30.0 11700 0.0115 0.8020 0.9814 0.9942 nan 0.9968 0.9873 0.9517 0.9730 0.9980 0.0 0.9940 0.9748 0.8955 0.9519 0.9957

Framework versions