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layoutlmv3-for-receipt-understanding

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layoutlmv3-for-receipt-understanding

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  1. README.md +55 -55
  2. runs/Oct08_15-21-59_92b670c4402e/events.out.tfevents.1728403802.92b670c4402e.4269.1 +3 -0
README.md CHANGED
@@ -21,11 +21,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1719
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- - Precision: 0.9739
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- - Recall: 0.9837
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- - F1: 0.9788
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- - Accuracy: 0.9784
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  ## Model description
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@@ -56,56 +56,56 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | No log | 0.3125 | 50 | 1.0562 | 0.6706 | 0.7585 | 0.7118 | 0.7602 |
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- | No log | 0.625 | 100 | 0.6576 | 0.8260 | 0.8548 | 0.8401 | 0.8379 |
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- | No log | 0.9375 | 150 | 0.4929 | 0.8312 | 0.8758 | 0.8529 | 0.8693 |
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- | No log | 1.25 | 200 | 0.4159 | 0.8685 | 0.9076 | 0.8876 | 0.9028 |
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- | No log | 1.5625 | 250 | 0.3272 | 0.8998 | 0.9340 | 0.9166 | 0.9342 |
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- | No log | 1.875 | 300 | 0.3002 | 0.8953 | 0.9293 | 0.9120 | 0.9261 |
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- | No log | 2.1875 | 350 | 0.2275 | 0.9289 | 0.9542 | 0.9414 | 0.9423 |
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- | No log | 2.5 | 400 | 0.2756 | 0.9147 | 0.9402 | 0.9273 | 0.9317 |
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- | No log | 2.8125 | 450 | 0.2767 | 0.9312 | 0.9457 | 0.9384 | 0.9397 |
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- | 0.5451 | 3.125 | 500 | 0.2000 | 0.9416 | 0.9635 | 0.9524 | 0.9529 |
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- | 0.5451 | 3.4375 | 550 | 0.1736 | 0.9564 | 0.9705 | 0.9634 | 0.9648 |
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- | 0.5451 | 3.75 | 600 | 0.1865 | 0.9511 | 0.9674 | 0.9592 | 0.9643 |
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- | 0.5451 | 4.0625 | 650 | 0.1916 | 0.9511 | 0.9666 | 0.9588 | 0.9622 |
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- | 0.5451 | 4.375 | 700 | 0.1681 | 0.9519 | 0.9674 | 0.9596 | 0.9648 |
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- | 0.5451 | 4.6875 | 750 | 0.1808 | 0.9463 | 0.9705 | 0.9582 | 0.9660 |
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- | 0.5451 | 5.0 | 800 | 0.2651 | 0.9299 | 0.9581 | 0.9438 | 0.9406 |
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- | 0.5451 | 5.3125 | 850 | 0.2116 | 0.9497 | 0.9682 | 0.9589 | 0.9614 |
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- | 0.5451 | 5.625 | 900 | 0.2377 | 0.9481 | 0.9643 | 0.9561 | 0.9554 |
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- | 0.5451 | 5.9375 | 950 | 0.1865 | 0.9473 | 0.9627 | 0.9549 | 0.9614 |
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- | 0.1 | 6.25 | 1000 | 0.1875 | 0.9639 | 0.9736 | 0.9687 | 0.9686 |
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- | 0.1 | 6.5625 | 1050 | 0.1848 | 0.9542 | 0.9713 | 0.9627 | 0.9652 |
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- | 0.1 | 6.875 | 1100 | 0.2124 | 0.9548 | 0.9666 | 0.9606 | 0.9618 |
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- | 0.1 | 7.1875 | 1150 | 0.1733 | 0.9602 | 0.9744 | 0.9672 | 0.9690 |
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- | 0.1 | 7.5 | 1200 | 0.1955 | 0.9580 | 0.9728 | 0.9653 | 0.9631 |
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- | 0.1 | 7.8125 | 1250 | 0.1986 | 0.9505 | 0.9697 | 0.9600 | 0.9643 |
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- | 0.1 | 8.125 | 1300 | 0.1908 | 0.9579 | 0.9713 | 0.9645 | 0.9677 |
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- | 0.1 | 8.4375 | 1350 | 0.1689 | 0.9625 | 0.9752 | 0.9688 | 0.9694 |
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- | 0.1 | 8.75 | 1400 | 0.1836 | 0.9570 | 0.9682 | 0.9626 | 0.9665 |
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- | 0.1 | 9.0625 | 1450 | 0.1955 | 0.9639 | 0.9744 | 0.9691 | 0.9682 |
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- | 0.0396 | 9.375 | 1500 | 0.1577 | 0.9716 | 0.9814 | 0.9764 | 0.9758 |
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- | 0.0396 | 9.6875 | 1550 | 0.1689 | 0.9663 | 0.9790 | 0.9726 | 0.9745 |
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- | 0.0396 | 10.0 | 1600 | 0.1700 | 0.9693 | 0.9806 | 0.9749 | 0.9754 |
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- | 0.0396 | 10.3125 | 1650 | 0.1666 | 0.9708 | 0.9821 | 0.9765 | 0.9754 |
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- | 0.0396 | 10.625 | 1700 | 0.1713 | 0.9708 | 0.9798 | 0.9753 | 0.9745 |
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- | 0.0396 | 10.9375 | 1750 | 0.1892 | 0.9648 | 0.9775 | 0.9711 | 0.9716 |
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- | 0.0396 | 11.25 | 1800 | 0.1881 | 0.9693 | 0.9790 | 0.9741 | 0.9728 |
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- | 0.0396 | 11.5625 | 1850 | 0.1820 | 0.9625 | 0.9759 | 0.9692 | 0.9720 |
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- | 0.0396 | 11.875 | 1900 | 0.1757 | 0.9723 | 0.9821 | 0.9772 | 0.9750 |
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- | 0.0396 | 12.1875 | 1950 | 0.1772 | 0.9655 | 0.9767 | 0.9711 | 0.9720 |
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- | 0.0185 | 12.5 | 2000 | 0.1685 | 0.9701 | 0.9821 | 0.9761 | 0.9758 |
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- | 0.0185 | 12.8125 | 2050 | 0.1716 | 0.9716 | 0.9814 | 0.9764 | 0.9762 |
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- | 0.0185 | 13.125 | 2100 | 0.1697 | 0.9723 | 0.9814 | 0.9768 | 0.9762 |
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- | 0.0185 | 13.4375 | 2150 | 0.1704 | 0.9723 | 0.9821 | 0.9772 | 0.9771 |
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- | 0.0185 | 13.75 | 2200 | 0.1686 | 0.9739 | 0.9837 | 0.9788 | 0.9788 |
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- | 0.0185 | 14.0625 | 2250 | 0.1714 | 0.9724 | 0.9829 | 0.9776 | 0.9779 |
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- | 0.0185 | 14.375 | 2300 | 0.1709 | 0.9731 | 0.9837 | 0.9784 | 0.9788 |
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- | 0.0185 | 14.6875 | 2350 | 0.1713 | 0.9739 | 0.9837 | 0.9788 | 0.9784 |
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- | 0.0185 | 15.0 | 2400 | 0.1715 | 0.9739 | 0.9837 | 0.9788 | 0.9784 |
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- | 0.0185 | 15.3125 | 2450 | 0.1717 | 0.9739 | 0.9837 | 0.9788 | 0.9784 |
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- | 0.0083 | 15.625 | 2500 | 0.1719 | 0.9739 | 0.9837 | 0.9788 | 0.9784 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1929
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+ - Precision: 0.9625
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+ - Recall: 0.9759
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+ - F1: 0.9692
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+ - Accuracy: 0.9711
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 2.1555 | 0.3125 | 50 | 1.2193 | 0.5472 | 0.6801 | 0.6064 | 0.7012 |
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+ | 1.0163 | 0.625 | 100 | 0.7732 | 0.7762 | 0.8323 | 0.8033 | 0.8145 |
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+ | 0.7451 | 0.9375 | 150 | 0.5322 | 0.8109 | 0.8657 | 0.8374 | 0.8553 |
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+ | 0.5237 | 1.25 | 200 | 0.4384 | 0.8228 | 0.8905 | 0.8553 | 0.8960 |
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+ | 0.4004 | 1.5625 | 250 | 0.3511 | 0.8772 | 0.9154 | 0.8959 | 0.9160 |
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+ | 0.3131 | 1.875 | 300 | 0.3527 | 0.8817 | 0.9255 | 0.9030 | 0.9138 |
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+ | 0.2565 | 2.1875 | 350 | 0.2919 | 0.9142 | 0.9511 | 0.9323 | 0.9334 |
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+ | 0.2381 | 2.5 | 400 | 0.2392 | 0.9218 | 0.9519 | 0.9366 | 0.9419 |
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+ | 0.2053 | 2.8125 | 450 | 0.2374 | 0.9189 | 0.9495 | 0.9339 | 0.9419 |
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+ | 0.1541 | 3.125 | 500 | 0.2738 | 0.9250 | 0.9581 | 0.9413 | 0.9385 |
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+ | 0.1557 | 3.4375 | 550 | 0.2274 | 0.9253 | 0.9519 | 0.9384 | 0.9491 |
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+ | 0.1534 | 3.75 | 600 | 0.2394 | 0.9445 | 0.9643 | 0.9543 | 0.9533 |
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+ | 0.1045 | 4.0625 | 650 | 0.2286 | 0.9425 | 0.9666 | 0.9544 | 0.9567 |
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+ | 0.1368 | 4.375 | 700 | 0.2270 | 0.9452 | 0.9643 | 0.9547 | 0.9516 |
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+ | 0.0747 | 4.6875 | 750 | 0.2470 | 0.9377 | 0.9589 | 0.9482 | 0.9495 |
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+ | 0.1099 | 5.0 | 800 | 0.2024 | 0.9467 | 0.9651 | 0.9558 | 0.9580 |
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+ | 0.0575 | 5.3125 | 850 | 0.2077 | 0.9534 | 0.9697 | 0.9615 | 0.9652 |
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+ | 0.0848 | 5.625 | 900 | 0.2099 | 0.9464 | 0.9596 | 0.9530 | 0.9559 |
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+ | 0.0913 | 5.9375 | 950 | 0.2399 | 0.9428 | 0.9604 | 0.9515 | 0.9482 |
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+ | 0.0482 | 6.25 | 1000 | 0.2054 | 0.9548 | 0.9682 | 0.9614 | 0.9622 |
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+ | 0.0793 | 6.5625 | 1050 | 0.2136 | 0.9579 | 0.9720 | 0.9649 | 0.9567 |
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+ | 0.0425 | 6.875 | 1100 | 0.2274 | 0.9535 | 0.9713 | 0.9623 | 0.9635 |
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+ | 0.0442 | 7.1875 | 1150 | 0.2033 | 0.9509 | 0.9627 | 0.9568 | 0.9597 |
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+ | 0.0425 | 7.5 | 1200 | 0.1676 | 0.9588 | 0.9759 | 0.9673 | 0.9682 |
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+ | 0.0425 | 7.8125 | 1250 | 0.1998 | 0.9536 | 0.9728 | 0.9631 | 0.9648 |
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+ | 0.0455 | 8.125 | 1300 | 0.1987 | 0.9639 | 0.9752 | 0.9695 | 0.9686 |
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+ | 0.0246 | 8.4375 | 1350 | 0.2094 | 0.9594 | 0.9713 | 0.9653 | 0.9626 |
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+ | 0.0502 | 8.75 | 1400 | 0.2046 | 0.9594 | 0.9720 | 0.9657 | 0.9605 |
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+ | 0.028 | 9.0625 | 1450 | 0.1927 | 0.9573 | 0.9752 | 0.9662 | 0.9648 |
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+ | 0.0223 | 9.375 | 1500 | 0.1728 | 0.9602 | 0.9752 | 0.9676 | 0.9703 |
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+ | 0.0346 | 9.6875 | 1550 | 0.2364 | 0.9571 | 0.9705 | 0.9638 | 0.9635 |
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+ | 0.0152 | 10.0 | 1600 | 0.1953 | 0.9610 | 0.9759 | 0.9684 | 0.9703 |
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+ | 0.0176 | 10.3125 | 1650 | 0.2045 | 0.9632 | 0.9744 | 0.9687 | 0.9682 |
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+ | 0.019 | 10.625 | 1700 | 0.2316 | 0.9587 | 0.9728 | 0.9657 | 0.9622 |
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+ | 0.0236 | 10.9375 | 1750 | 0.1931 | 0.9678 | 0.9790 | 0.9734 | 0.9711 |
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+ | 0.0238 | 11.25 | 1800 | 0.1935 | 0.9610 | 0.9767 | 0.9688 | 0.9707 |
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+ | 0.0206 | 11.5625 | 1850 | 0.1942 | 0.9602 | 0.9744 | 0.9672 | 0.9707 |
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+ | 0.0163 | 11.875 | 1900 | 0.1811 | 0.9641 | 0.9790 | 0.9715 | 0.9737 |
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+ | 0.0131 | 12.1875 | 1950 | 0.1731 | 0.9671 | 0.9806 | 0.9738 | 0.9758 |
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+ | 0.017 | 12.5 | 2000 | 0.1835 | 0.9574 | 0.9783 | 0.9677 | 0.9707 |
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+ | 0.0117 | 12.8125 | 2050 | 0.2070 | 0.9617 | 0.9759 | 0.9688 | 0.9669 |
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+ | 0.0074 | 13.125 | 2100 | 0.2049 | 0.9617 | 0.9759 | 0.9688 | 0.9669 |
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+ | 0.0093 | 13.4375 | 2150 | 0.2004 | 0.9625 | 0.9775 | 0.9700 | 0.9699 |
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+ | 0.0157 | 13.75 | 2200 | 0.1948 | 0.9678 | 0.9790 | 0.9734 | 0.9728 |
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+ | 0.01 | 14.0625 | 2250 | 0.1870 | 0.9648 | 0.9790 | 0.9719 | 0.9737 |
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+ | 0.0047 | 14.375 | 2300 | 0.2000 | 0.9617 | 0.9752 | 0.9684 | 0.9699 |
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+ | 0.0163 | 14.6875 | 2350 | 0.1951 | 0.9632 | 0.9767 | 0.9699 | 0.9711 |
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+ | 0.0118 | 15.0 | 2400 | 0.1936 | 0.9640 | 0.9767 | 0.9703 | 0.9716 |
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+ | 0.0093 | 15.3125 | 2450 | 0.1932 | 0.9625 | 0.9759 | 0.9692 | 0.9711 |
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+ | 0.0025 | 15.625 | 2500 | 0.1929 | 0.9625 | 0.9759 | 0.9692 | 0.9711 |
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  ### Framework versions
runs/Oct08_15-21-59_92b670c4402e/events.out.tfevents.1728403802.92b670c4402e.4269.1 ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:e9af7d347a2c0e1987b993a0a07d24e955f30ff8ef7817b05b273eadb90b6e4e
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+ size 560