readme: ---
  license: cc-by-nc-sa-4.0
  tags:
  - generated_from_trainer
  model-index:
  - name: lmv2-g-rai2-732-doc-10-07
    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. -->
  
  # lmv2-g-rai2-732-doc-10-07
  
  This model is a fine-tuned version of [microsoft/layoutlmv2-base-uncased](https://huggingface.co/microsoft/layoutlmv2-base-uncased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0222
  - Dob Key Precision: 0.7810
  - Dob Key Recall: 0.8359
  - Dob Key F1: 0.8075
  - Dob Key Number: 128
  - Dob Value Precision: 0.9767
  - Dob Value Recall: 0.9618
  - Dob Value F1: 0.9692
  - Dob Value Number: 131
  - Doctor Name Key Precision: 0.5714
  - Doctor Name Key Recall: 0.6197
  - Doctor Name Key F1: 0.5946
  - Doctor Name Key Number: 71
  - Doctor Name Value Precision: 0.8861
  - Doctor Name Value Recall: 0.9091
  - Doctor Name Value F1: 0.8974
  - Doctor Name Value Number: 77
  - Patient Name Key Precision: 0.7639
  - Patient Name Key Recall: 0.7639
  - Patient Name Key F1: 0.7639
  - Patient Name Key Number: 144
  - Patient Name Value Precision: 0.9595
  - Patient Name Value Recall: 0.9530
  - Patient Name Value F1: 0.9562
  - Patient Name Value Number: 149
  - Overall Precision: 0.8389
  - Overall Recall: 0.8557
  - Overall F1: 0.8472
  - Overall Accuracy: 0.9939
  
  ## 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: 4e-05
  - train_batch_size: 1
  - eval_batch_size: 1
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: constant
  - num_epochs: 30
  
  ### Training results
  
  | 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 | Doctor Name Key Precision | Doctor Name Key Recall | Doctor Name Key F1 | Doctor Name Key Number | Doctor Name Value Precision | Doctor Name Value Recall | Doctor Name Value F1 | Doctor Name 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 | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:-----------------:|:--------------:|:----------:|:--------------:|:-------------------:|:----------------:|:------------:|:----------------:|:-------------------------:|:----------------------:|:------------------:|:----------------------:|:---------------------------:|:------------------------:|:--------------------:|:------------------------:|:--------------------------:|:-----------------------:|:-------------------:|:-----------------------:|:----------------------------:|:-------------------------:|:---------------------:|:-------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
  | 0.6913        | 1.0   | 585   | 0.1911          | 0.0               | 0.0            | 0.0        | 128            | 0.0                 | 0.0              | 0.0          | 131              | 0.0                       | 0.0                    | 0.0                | 71                     | 0.0                         | 0.0                      | 0.0                  | 77                       | 0.0                        | 0.0                     | 0.0                 | 144                     | 0.0                          | 0.0                       | 0.0                   | 149                       | 0.0               | 0.0            | 0.0        | 0.9671           |
  | 0.1083        | 2.0   | 1170  | 0.0588          | 0.7692            | 0.7812         | 0.7752     | 128            | 0.9615              | 0.9542           | 0.9579       | 131              | 0.5645                    | 0.4930                 | 0.5263             | 71                     | 0.9178                      | 0.8701                   | 0.8933               | 77                       | 0.7397                     | 0.75                    | 0.7448              | 144                     | 0.9346                       | 0.9597                    | 0.9470                | 149                       | 0.8329            | 0.8257         | 0.8293     | 0.9936           |
  | 0.0515        | 3.0   | 1755  | 0.0377          | 0.7803            | 0.8047         | 0.7923     | 128            | 0.875               | 0.9084           | 0.8914       | 131              | 0.5867                    | 0.6197                 | 0.6027             | 71                     | 0.9231                      | 0.9351                   | 0.9290               | 77           