| --- |
| library_name: transformers |
| license: cc-by-nc-sa-4.0 |
| base_model: microsoft/layoutlmv3-large |
| tags: |
| - layoutlmv3 |
| - document-classification |
| - medical-documents |
| - model2aa |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: layoutlmv3-large-model2aa-visit-vs-progress |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # layoutlmv3-large-model2aa-visit-vs-progress |
|
|
| This model is a fine-tuned version of [microsoft/layoutlmv3-large](https://huggingface.co/microsoft/layoutlmv3-large) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3959 |
| - Accuracy: 0.8680 |
| - Macro Precision: 0.8680 |
| - Macro Recall: 0.8680 |
| - Macro F1: 0.8680 |
| - Weighted F1: 0.8680 |
| - Precision Visit Note Multiple Notes: 0.8644 |
| - Recall Visit Note Multiple Notes: 0.8724 |
| - F1 Visit Note Multiple Notes: 0.8684 |
| - Precision Progress Follow Up Note: 0.8717 |
| - Recall Progress Follow Up Note: 0.8636 |
| - F1 Progress Follow Up Note: 0.8676 |
|
|
| ## 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: |
| - learning_rate: 2e-05 |
| - train_batch_size: 1 |
| - eval_batch_size: 1 |
| - seed: 42 |
| - gradient_accumulation_steps: 16 |
| - total_train_batch_size: 16 |
| - optimizer: Use OptimizerNames.ADAFACTOR and the args are: |
| No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 3.0 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Accuracy | F1 Progress Follow Up Note | F1 Visit Note Multiple Notes | Validation Loss | Macro F1 | Macro Precision | Macro Recall | Precision Progress Follow Up Note | Precision Visit Note Multiple Notes | Recall Progress Follow Up Note | Recall Visit Note Multiple Notes | Weighted F1 | |
| |:-------------:|:------:|:----:|:--------:|:--------------------------:|:----------------------------:|:---------------:|:--------:|:---------------:|:------------:|:---------------------------------:|:-----------------------------------:|:------------------------------:|:--------------------------------:|:-----------:| |
| | 0.4912 | 0.3168 | 500 | 0.7062 | 0.6104 | 0.7641 | 0.5445 | 0.6873 | 0.7731 | 0.7066 | 0.9087 | 0.6374 | 0.4595 | 0.9537 | 0.6871 | |
| | 0.3608 | 0.6335 | 1000 | 0.8282 | 0.8418 | 0.8120 | 0.4213 | 0.8269 | 0.8378 | 0.8280 | 0.7812 | 0.8945 | 0.9126 | 0.7434 | 0.8269 | |
| | 0.3789 | 0.9503 | 1500 | 0.8485 | 0.8459 | 0.8509 | 0.3537 | 0.8484 | 0.8489 | 0.8485 | 0.8621 | 0.8357 | 0.8303 | 0.8667 | 0.8484 | |
| | 0.2658 | 1.2667 | 2000 | 0.8602 | 0.8596 | 0.8608 | 0.3743 | 0.8602 | 0.8602 | 0.8602 | 0.8648 | 0.8556 | 0.8544 | 0.8660 | 0.8602 | |
| | 0.3878 | 1.5835 | 2500 | 0.8641 | 0.8614 | 0.8667 | 0.3856 | 0.8641 | 0.8648 | 0.8641 | 0.8806 | 0.8489 | 0.8430 | 0.8852 | 0.8640 | |
| | 0.2924 | 1.9003 | 3000 | 0.8541 | 0.8499 | 0.8581 | 0.4044 | 0.8540 | 0.8554 | 0.8542 | 0.8769 | 0.8339 | 0.8246 | 0.8838 | 0.8540 | |
| | 0.3093 | 2.2167 | 3500 | 0.8680 | 0.8677 | 0.8683 | 0.3957 | 0.8680 | 0.8680 | 0.8680 | 0.8712 | 0.8649 | 0.8643 | 0.8717 | 0.8680 | |
| | 0.171 | 2.5334 | 4000 | 0.5077 | 0.8620 | 0.8632 | 0.8620 | 0.8619 | 0.8619 | 0.8418 | 0.8909 | 0.8657 | 0.8846 | 0.8331 | 0.8581 | |
| | 0.1688 | 2.8502 | 4500 | 0.5981 | 0.8623 | 0.8641 | 0.8624 | 0.8622 | 0.8622 | 0.8382 | 0.8974 | 0.8668 | 0.8900 | 0.8274 | 0.8576 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.57.6 |
| - Pytorch 2.10.0+cu128 |
| - Tokenizers 0.22.2 |
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|
