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layoutlm-captive-corp-70

Token Classification
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layoutlmv3
Generated from Trainer
Eval Results (legacy)
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  1. README.md +141 -0
  2. logs/events.out.tfevents.1736666533.2e88403884b3.333.1 +2 -2
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  4. model.safetensors +1 -1
README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: cc-by-nc-sa-4.0
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+ base_model: microsoft/layoutlmv3-base
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - layoutlmv3
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+ metrics:
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+ - precision
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+ - recall
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+ - f1
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+ - accuracy
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+ model-index:
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+ - name: layoutlm-captive-corp-70
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+ results:
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+ - task:
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+ name: Token Classification
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+ type: token-classification
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+ dataset:
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+ name: layoutlmv3
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+ type: layoutlmv3
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+ config: FormsDataset
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+ split: test
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+ args: FormsDataset
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+ metrics:
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+ - name: Precision
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+ type: precision
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+ value: 0.9517271922054916
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+ - name: Recall
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+ type: recall
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+ value: 0.968018018018018
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+ - name: F1
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+ type: f1
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+ value: 0.9598034836980796
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.9712673165726013
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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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+ # layoutlm-captive-corp-70
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+
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+ This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the layoutlmv3 dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1795
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+ - Precision: 0.9517
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+ - Recall: 0.9680
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+ - F1: 0.9598
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+ - Accuracy: 0.9713
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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: 1e-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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - num_epochs: 50
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.0311 | 1.0 | 23 | 0.1756 | 0.9478 | 0.9658 | 0.9567 | 0.9708 |
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+ | 0.0282 | 2.0 | 46 | 0.1781 | 0.9486 | 0.9649 | 0.9567 | 0.9705 |
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+ | 0.0296 | 3.0 | 69 | 0.1780 | 0.9481 | 0.9635 | 0.9558 | 0.9697 |
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+ | 0.0252 | 4.0 | 92 | 0.1870 | 0.9463 | 0.9608 | 0.9535 | 0.9674 |
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+ | 0.0255 | 5.0 | 115 | 0.1780 | 0.9476 | 0.9622 | 0.9549 | 0.9697 |
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+ | 0.022 | 6.0 | 138 | 0.1779 | 0.9469 | 0.9644 | 0.9556 | 0.9700 |
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+ | 0.0196 | 7.0 | 161 | 0.1806 | 0.9503 | 0.9649 | 0.9575 | 0.9695 |
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+ | 0.0184 | 8.0 | 184 | 0.1827 | 0.9524 | 0.9653 | 0.9588 | 0.9705 |
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+ | 0.0173 | 9.0 | 207 | 0.1888 | 0.9489 | 0.9626 | 0.9557 | 0.9687 |
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+ | 0.0175 | 10.0 | 230 | 0.1799 | 0.9500 | 0.9667 | 0.9582 | 0.9708 |
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+ | 0.0155 | 11.0 | 253 | 0.1814 | 0.9486 | 0.9653 | 0.9569 | 0.9710 |
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+ | 0.0144 | 12.0 | 276 | 0.1853 | 0.9473 | 0.9640 | 0.9556 | 0.9702 |
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+ | 0.0139 | 13.0 | 299 | 0.1840 | 0.9469 | 0.9649 | 0.9558 | 0.9697 |
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+ | 0.0133 | 14.0 | 322 | 0.1797 | 0.9504 | 0.9662 | 0.9582 | 0.9718 |
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+ | 0.0126 | 15.0 | 345 | 0.1832 | 0.9508 | 0.9671 | 0.9589 | 0.9710 |
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+ | 0.0121 | 16.0 | 368 | 0.1795 | 0.9517 | 0.9680 | 0.9598 | 0.9713 |
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+ | 0.0117 | 17.0 | 391 | 0.1844 | 0.9504 | 0.9658 | 0.9580 | 0.9705 |
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+ | 0.0108 | 18.0 | 414 | 0.1850 | 0.9500 | 0.9662 | 0.9580 | 0.9702 |
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+ | 0.0105 | 19.0 | 437 | 0.1847 | 0.9517 | 0.9671 | 0.9593 | 0.9713 |
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+ | 0.0107 | 20.0 | 460 | 0.1846 | 0.9482 | 0.9653 | 0.9567 | 0.9702 |
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+ | 0.0098 | 21.0 | 483 | 0.1863 | 0.9495 | 0.9662 | 0.9578 | 0.9702 |
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+ | 0.0099 | 22.0 | 506 | 0.1871 | 0.9473 | 0.9635 | 0.9553 | 0.9692 |
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+ | 0.0091 | 23.0 | 529 | 0.1879 | 0.9482 | 0.9644 | 0.9562 | 0.9700 |
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+ | 0.0091 | 24.0 | 552 | 0.1859 | 0.9517 | 0.9671 | 0.9593 | 0.9713 |
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+ | 0.0091 | 25.0 | 575 | 0.1849 | 0.9479 | 0.9671 | 0.9574 | 0.9713 |
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+ | 0.0088 | 26.0 | 598 | 0.1883 | 0.9495 | 0.9662 | 0.9578 | 0.9702 |
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+ | 0.0083 | 27.0 | 621 | 0.1884 | 0.9495 | 0.9658 | 0.9576 | 0.9700 |
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+ | 0.0079 | 28.0 | 644 | 0.1890 | 0.9499 | 0.9658 | 0.9578 | 0.9710 |
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+ | 0.008 | 29.0 | 667 | 0.1921 | 0.9491 | 0.9658 | 0.9574 | 0.9700 |
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+ | 0.0075 | 30.0 | 690 | 0.1904 | 0.9504 | 0.9662 | 0.9582 | 0.9713 |
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+ | 0.0075 | 31.0 | 713 | 0.1907 | 0.9504 | 0.9667 | 0.9585 | 0.9710 |
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+ | 0.0075 | 32.0 | 736 | 0.1904 | 0.9504 | 0.9662 | 0.9582 | 0.9710 |
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+ | 0.008 | 33.0 | 759 | 0.1935 | 0.9508 | 0.9653 | 0.9580 | 0.9705 |
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+ | 0.0071 | 34.0 | 782 | 0.1950 | 0.9486 | 0.9644 | 0.9564 | 0.9700 |
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+ | 0.007 | 35.0 | 805 | 0.1934 | 0.9478 | 0.9644 | 0.9560 | 0.9705 |
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+ | 0.0072 | 36.0 | 828 | 0.1938 | 0.9486 | 0.9653 | 0.9569 | 0.9702 |
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+ | 0.0068 | 37.0 | 851 | 0.1946 | 0.9482 | 0.9649 | 0.9565 | 0.9697 |
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+ | 0.0066 | 38.0 | 874 | 0.1946 | 0.9486 | 0.9653 | 0.9569 | 0.9700 |
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+ | 0.0068 | 39.0 | 897 | 0.1947 | 0.9508 | 0.9658 | 0.9582 | 0.9705 |
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+ | 0.007 | 40.0 | 920 | 0.1942 | 0.9486 | 0.9640 | 0.9562 | 0.9697 |
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+ | 0.0066 | 41.0 | 943 | 0.1937 | 0.9490 | 0.9649 | 0.9569 | 0.9702 |
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+ | 0.0065 | 42.0 | 966 | 0.1943 | 0.9478 | 0.9644 | 0.9560 | 0.9695 |
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+ | 0.0067 | 43.0 | 989 | 0.1936 | 0.9508 | 0.9662 | 0.9584 | 0.9708 |
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+ | 0.0071 | 44.0 | 1012 | 0.1944 | 0.9521 | 0.9667 | 0.9593 | 0.9710 |
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+ | 0.0064 | 45.0 | 1035 | 0.1940 | 0.9517 | 0.9671 | 0.9593 | 0.9713 |
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+ | 0.0063 | 46.0 | 1058 | 0.1938 | 0.9499 | 0.9658 | 0.9578 | 0.9708 |
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+ | 0.0066 | 47.0 | 1081 | 0.1944 | 0.9499 | 0.9658 | 0.9578 | 0.9708 |
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+ | 0.0063 | 48.0 | 1104 | 0.1955 | 0.9495 | 0.9653 | 0.9573 | 0.9705 |
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+ | 0.007 | 49.0 | 1127 | 0.1955 | 0.9495 | 0.9653 | 0.9573 | 0.9705 |
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+ | 0.0063 | 50.0 | 1150 | 0.1954 | 0.9495 | 0.9653 | 0.9573 | 0.9705 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.49.0.dev0
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+ - Pytorch 2.5.1+cu121
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+ - Datasets 3.2.0
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+ - Tokenizers 0.21.0
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