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--- |
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license: cc-by-nc-sa-4.0 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: lmv2-g-rai-aRx-refill-230427 |
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results: [] |
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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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# lmv2-g-rai-aRx-refill-230427 |
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This model is a fine-tuned version of [microsoft/layoutlmv2-base-uncased](https://huggingface.co/microsoft/layoutlmv2-base-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0176 |
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- Dob Key Precision: 0.6846 |
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- Dob Key Recall: 0.7007 |
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- Dob Key F1: 0.6926 |
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- Dob Key Number: 598 |
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- Dob Value Precision: 0.9934 |
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- Dob Value Recall: 0.9983 |
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- Dob Value F1: 0.9958 |
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- Dob Value Number: 599 |
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- Patient Name Key Precision: 0.6852 |
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- Patient Name Key Recall: 0.7089 |
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- Patient Name Key F1: 0.6968 |
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- Patient Name Key Number: 608 |
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- Patient Name Value Precision: 0.9581 |
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- Patient Name Value Recall: 0.9738 |
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- Patient Name Value F1: 0.9659 |
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- Patient Name Value Number: 611 |
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- Provider Name Key Precision: 0.7875 |
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- Provider Name Key Recall: 0.7903 |
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- Provider Name Key F1: 0.7889 |
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- Provider Name Key Number: 558 |
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- Provider Name Value Precision: 0.9786 |
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- Provider Name Value Recall: 0.9751 |
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- Provider Name Value F1: 0.9768 |
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- Provider Name Value Number: 562 |
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- Overall Precision: 0.8460 |
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- Overall Recall: 0.8575 |
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- Overall F1: 0.8517 |
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- Overall Accuracy: 0.9936 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Dob Key Precision | Dob Key Recall | Dob Key F1 | Dob Key Number | Dob Value Precision | Dob Value Recall | Dob Value F1 | Dob Value Number | Patient Name Key Precision | Patient Name Key Recall | Patient Name Key F1 | Patient Name Key Number | Patient Name Value Precision | Patient Name Value Recall | Patient Name Value F1 | Patient Name Value Number | Provider Name Key Precision | Provider Name Key Recall | Provider Name Key F1 | Provider Name Key Number | Provider Name Value Precision | Provider Name Value Recall | Provider Name Value F1 | Provider Name Value Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:--------------:|:-------------------:|:----------------:|:------------:|:----------------:|:--------------------------:|:-----------------------:|:-------------------:|:-----------------------:|:----------------------------:|:-------------------------:|:---------------------:|:-------------------------:|:---------------------------:|:------------------------:|:--------------------:|:------------------------:|:-----------------------------:|:--------------------------:|:----------------------:|:--------------------------:|:-----------------:|:--------------:|:----------:|:----------------:| |
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| 0.5109 | 1.0 | 691 | 0.0829 | 0.6804 | 0.6906 | 0.6855 | 598 | 0.9469 | 0.9833 | 0.9648 | 599 | 0.6607 | 0.6628 | 0.6617 | 608 | 0.9331 | 0.9362 | 0.9346 | 611 | 0.5872 | 0.6577 | 0.6205 | 558 | 0.9442 | 0.9626 | 0.9533 | 562 | 0.7904 | 0.8159 | 0.8030 | 0.9921 | |
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| 0.0554 | 2.0 | 1382 | 0.0391 | 0.6838 | 0.6906 | 0.6872 | 598 | 0.9950 | 0.9983 | 0.9967 | 599 | 0.6546 | 0.6859 | 0.6699 | 608 | 0.9357 | 0.9525 | 0.9440 | 611 | 0.7431 | 0.7724 | 0.7575 | 558 | 0.9231 | 0.9609 | 0.9416 | 562 | 0.8214 | 0.8430 | 0.8321 | 0.9926 | |
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| 0.0298 | 3.0 | 2073 | 0.0255 | 0.6922 | 0.6957 | 0.6939 | 598 | 0.9934 | 0.9983 | 0.9958 | 599 | 0.6505 | 0.6859 | 0.6677 | 608 | 0.9560 | 0.9591 | 0.9575 | 611 | 0.7718 | 0.7760 | 0.7739 | 558 | 0.9459 | 0.9644 | 0.9551 | 562 | 0.8332 | 0.8462 | 0.8396 | 0.9931 | |
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| 0.0213 | 4.0 | 2764 | 0.0208 | 0.6264 | 0.6756 | 0.6500 | 598 | 0.9934 | 0.9983 | 0.9958 | 599 | 0.6762 | 0.6974 | 0.6866 | 608 | 0.9645 | 0.9787 | 0.9716 | 611 | 0.7334 | 0.7545 | 0.7438 | 558 | 0.9579 | 0.9715 | 0.9647 | 562 | 0.8222 | 0.8459 | 0.8338 | 0.9928 | |
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| 0.0177 | 5.0 | 3455 | 0.0185 | 0.6672 | 0.6973 | 0.6819 | 598 | 0.9934 | 0.9983 | 0.9958 | 599 | 0.6856 | 0.6957 | 0.6906 | 608 | 0.9686 | 0.9591 | 0.9638 | 611 | 0.7778 | 0.7778 | 0.7778 | 558 | 0.9444 | 0.9680 | 0.9561 | 562 | 0.8378 | 0.8490 | 0.8434 | 0.9933 | |
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| 0.0157 | 6.0 | 4146 | 0.0176 | 0.6846 | 0.7007 | 0.6926 | 598 | 0.9934 | 0.9983 | 0.9958 | 599 | 0.6852 | 0.7089 | 0.6968 | 608 | 0.9581 | 0.9738 | 0.9659 | 611 | 0.7875 | 0.7903 | 0.7889 | 558 | 0.9786 | 0.9751 | 0.9768 | 562 | 0.8460 | 0.8575 | 0.8517 | 0.9936 | |
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| 0.0144 | 7.0 | 4837 | 0.0176 | 0.6228 | 0.6656 | 0.6435 | 598 | 0.9950 | 0.9983 | 0.9967 | 599 | 0.6667 | 0.6974 | 0.6817 | 608 | 0.9677 | 0.9804 | 0.9740 | 611 | 0.7718 | 0.7760 | 0.7739 | 558 | 0.9658 | 0.9555 | 0.9606 | 562 | 0.8275 | 0.8453 | 0.8363 | 0.9931 | |
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| 0.0134 | 8.0 | 5528 | 0.0172 | 0.6551 | 0.6923 | 0.6732 | 598 | 0.9933 | 0.9967 | 0.995 | 599 | 0.6900 | 0.7138 | 0.7017 | 608 | 0.9741 | 0.9853 | 0.9797 | 611 | 0.7715 | 0.7867 | 0.7791 | 558 | 0.9713 | 0.9644 | 0.9679 | 562 | 0.8395 | 0.8563 | 0.8478 | 0.9937 | |
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| 0.0125 | 9.0 | 6219 | 0.0167 | 0.6571 | 0.6890 | 0.6727 | 598 | 0.9934 | 0.9983 | 0.9958 | 599 | 0.7 | 0.7138 | 0.7068 | 608 | 0.9676 | 0.9771 | 0.9723 | 611 | 0.7786 | 0.7814 | 0.7800 | 558 | 0.9715 | 0.9698 | 0.9706 | 562 | 0.8425 | 0.8546 | 0.8485 | 0.9936 | |
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| 0.0118 | 10.0 | 6910 | 0.0170 | 0.6683 | 0.6839 | 0.6760 | 598 | 0.9934 | 0.9983 | 0.9958 | 599 | 0.6949 | 0.7155 | 0.7050 | 608 | 0.9804 | 0.9820 | 0.9812 | 611 | 0.7583 | 0.7760 | 0.7671 | 558 | 0.9751 | 0.9751 | 0.9751 | 562 | 0.8432 | 0.8549 | 0.8490 | 0.9936 | |
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### Framework versions |
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- Transformers 4.28.0 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.2.2 |
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- Tokenizers 0.13.3 |
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