readme: ---
  license: cc-by-nc-sa-4.0
  tags:
  - generated_from_trainer
  model-index:
  - name: lmv2-g-voterid-117-doc-09-13
    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-voterid-117-doc-09-13
  
  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: 0.1322
  - Age Precision: 1.0
  - Age Recall: 1.0
  - Age F1: 1.0
  - Age Number: 3
  - Dob Precision: 1.0
  - Dob Recall: 1.0
  - Dob F1: 1.0
  - Dob Number: 5
  - F H M Name Precision: 0.7917
  - F H M Name Recall: 0.7917
  - F H M Name F1: 0.7917
  - F H M Name Number: 24
  - Name Precision: 0.8462
  - Name Recall: 0.9167
  - Name F1: 0.8800
  - Name Number: 24
  - Sex Precision: 1.0
  - Sex Recall: 1.0
  - Sex F1: 1.0
  - Sex Number: 8
  - Voter Id Precision: 0.92
  - Voter Id Recall: 0.9583
  - Voter Id F1: 0.9388
  - Voter Id Number: 24
  - Overall Precision: 0.8791
  - Overall Recall: 0.9091
  - Overall F1: 0.8939
  - Overall Accuracy: 0.9836
  
  ## 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 | Age Precision | Age Recall | Age F1 | Age Number | Dob Precision | Dob Recall | Dob F1 | Dob Number | F H M Name Precision | F H M Name Recall | F H M Name F1 | F H M Name Number | Name Precision | Name Recall | Name F1 | Name Number | Sex Precision | Sex Recall | Sex F1 | Sex Number | Voter Id Precision | Voter Id Recall | Voter Id F1 | Voter Id Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:-------------:|:----------:|:------:|:----------:|:-------------:|:----------:|:------:|:----------:|:--------------------:|:-----------------:|:-------------:|:-----------------:|:--------------:|:-----------:|:-------:|:-----------:|:-------------:|:----------:|:------:|:----------:|:------------------:|:---------------:|:-----------:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|
  | 1.5488        | 1.0   | 93   | 1.2193          | 0.0           | 0.0        | 0.0    | 3          | 0.0           | 0.0        | 0.0    | 5          | 0.0                  | 0.0               | 0.0           | 24                | 0.0            | 0.0         | 0.0     | 24          | 0.0           | 0.0        | 0.0    | 8          | 1.0                | 0.0833          | 0.1538      | 24              | 1.0               | 0.0227         | 0.0444     | 0.9100           |
  | 1.0594        | 2.0   | 186  | 0.8695          | 0.0           | 0.0        | 0.0    | 3          | 0.0           | 0.0        | 0.0    | 5          | 0.0                  | 0.0               | 0.0           | 24                | 0.0            | 0.0         | 0.0     | 24          | 0.0           | 0.0        | 0.0    | 8          | 0.6286             | 0.9167          | 0.7458      | 24              | 0.6286            | 0.25           | 0.3577     | 0.9173           |
  | 0.763         | 3.0   | 279  | 0.6057          | 0.0           | 0.0        | 0.0    | 3          | 0.0           | 0.0        | 0.0    | 5          | 0.0667               | 0.0417            | 0.0513        | 24                | 0.0            | 0.0         | 0.0     | 24          | 0.0           | 0.0        | 0.0    | 8          | 0.6875             | 0.9167          | 0.7857      | 24              | 0.4694            | 0.2614         | 0.3358     | 0.9228           |
  | 0.5241        | 4.0   | 372  | 0.4257          | 0.0           | 0.0        | 0.0    | 3          | 0.0           | 0.0        | 0.0    | 5          | 0.0                  | 0.0               | 0.0           | 24                | 0.2381         | 0.4167      | 0.3030  | 24          | 0.0           | 0.0        | 0.0    | 8          | 0.7097             | 0.9167          | 0.8000      | 24              | 0.4384            | 0.3636         | 0.3975     | 0.9331           |
  | 0.3847        | 5.0   | 465  | 0.3317          | 0.0           | 0.0        | 0.0    | 3          | 0.3333        | 0.4        | 0.3636 | 5          | 0.3889               | 0.2917            | 0.3333        | 24                | 0.2745         | 0.5833      | 0.3733  | 24          | 1.0           | 0.75       | 0.8571 | 8          | 0.88               | 0.9167          | 0.8980      | 24              | 0.4811            | 0.5795         | 0.5258     | 0.9574           |
  | 0.30