readme: ---
  license: cc-by-nc-sa-4.0
  tags:
  - generated_from_trainer
  model-index:
  - name: lmv2-g-bnkstm-994-doc-09-10
    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-bnkstm-994-doc-09-10
  
  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: 0.0926
  - Account Number Precision: 0.8889
  - Account Number Recall: 0.9014
  - Account Number F1: 0.8951
  - Account Number Number: 142
  - Bank Name Precision: 0.7993
  - Bank Name Recall: 0.8484
  - Bank Name F1: 0.8231
  - Bank Name Number: 277
  - Cust Address Precision: 0.8563
  - Cust Address Recall: 0.8827
  - Cust Address F1: 0.8693
  - Cust Address Number: 162
  - Cust Name Precision: 0.9181
  - Cust Name Recall: 0.9290
  - Cust Name F1: 0.9235
  - Cust Name Number: 169
  - Ending Balance Precision: 0.7706
  - Ending Balance Recall: 0.7892
  - Ending Balance F1: 0.7798
  - Ending Balance Number: 166
  - Starting Balance Precision: 0.9051
  - Starting Balance Recall: 0.8720
  - Starting Balance F1: 0.8882
  - Starting Balance Number: 164
  - Statement Date Precision: 0.8817
  - Statement Date Recall: 0.8765
  - Statement Date F1: 0.8791
  - Statement Date Number: 170
  - Overall Precision: 0.8531
  - Overall Recall: 0.8688
  - Overall F1: 0.8609
  - Overall Accuracy: 0.9850
  
  ## 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 | Account Number Precision | Account Number Recall | Account Number F1 | Account Number Number | Bank Name Precision | Bank Name Recall | Bank Name F1 | Bank Name Number | Cust Address Precision | Cust Address Recall | Cust Address F1 | Cust Address Number | Cust Name Precision | Cust Name Recall | Cust Name F1 | Cust Name Number | Ending Balance Precision | Ending Balance Recall | Ending Balance F1 | Ending Balance Number | Starting Balance Precision | Starting Balance Recall | Starting Balance F1 | Starting Balance Number | Statement Date Precision | Statement Date Recall | Statement Date F1 | Statement Date Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:------------------------:|:---------------------:|:-----------------:|:---------------------:|:-------------------:|:----------------:|:------------:|:----------------:|:----------------------:|:-------------------:|:---------------:|:-------------------:|:-------------------:|:----------------:|:------------:|:----------------:|:------------------------:|:---------------------:|:-----------------:|:---------------------:|:--------------------------:|:-----------------------:|:-------------------:|:-----------------------:|:------------------------:|:---------------------:|:-----------------:|:---------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
  | 0.7648        | 1.0   | 795   | 0.2550          | 0.8514                   | 0.4437                | 0.5833            | 142                   | 0.6229              | 0.5307           | 0.5731       | 277              | 0.5650                 | 0.7778              | 0.6545          | 162                 | 0.6682              | 0.8698           | 0.7558       | 169              | 0.0                      | 0.0                   | 0.0               | 166                   | 0.0                        | 0.0                     | 0.0                 | 164                     | 0.6040                   | 0.3588                | 0.4502            | 170                   | 0.6370            | 0.4352         | 0.5171     | 0.9623           |
  | 0.1725        | 2.0   | 1590  | 0.1128          | 0.6067                   | 0.7606                | 0.675             | 142                   | 0.7294              | 0.7978           | 0.7621       | 277              | 0.8150                 | 0.8704              | 0.8418          | 162                 | 0.8966              | 0.9231           | 0.9096       | 169              | 0.7786                   | 0.6566                | 0.7124            | 166                   | 0.7576                     | 0.7622                  | 0.7599              | 164                     | 0.8509                   | 0.8059                | 0.8278            | 170                   | 0.7705            | 0.7976         | 0.7838     | 0.9816           |
  | 0.0877        | 3.0   | 2385  | 0.