readme: ---
  license: cc-by-nc-sa-4.0
  tags:
  - generated_from_trainer
  model-index:
  - name: lmv2-g-dl-243-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-dl-243-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: 0.2104
  - Address Precision: 0.725
  - Address Recall: 0.7632
  - Address F1: 0.7436
  - Address Number: 38
  - Blood Group Precision: 0.8636
  - Blood Group Recall: 0.8636
  - Blood Group F1: 0.8636
  - Blood Group Number: 22
  - Date Of Issue Precision: 0.9787
  - Date Of Issue Recall: 0.92
  - Date Of Issue F1: 0.9485
  - Date Of Issue Number: 50
  - Dob Precision: 1.0
  - Dob Recall: 0.9773
  - Dob F1: 0.9885
  - Dob Number: 44
  - Driving Licence No Precision: 0.9796
  - Driving Licence No Recall: 1.0
  - Driving Licence No F1: 0.9897
  - Driving Licence No Number: 48
  - Name Precision: 0.9388
  - Name Recall: 0.9388
  - Name F1: 0.9388
  - Name Number: 49
  - S D W Name Precision: 0.9388
  - S D W Name Recall: 0.9583
  - S D W Name F1: 0.9485
  - S D W Name Number: 48
  - Valid Till Nt Precision: 0.7826
  - Valid Till Nt Recall: 0.8780
  - Valid Till Nt F1: 0.8276
  - Valid Till Nt Number: 41
  - Valid Till T Tr Precision: 0.9231
  - Valid Till T Tr Recall: 0.8571
  - Valid Till T Tr F1: 0.8889
  - Valid Till T Tr Number: 14
  - Overall Precision: 0.9078
  - Overall Recall: 0.9181
  - Overall F1: 0.9129
  - Overall Accuracy: 0.9763
  
  ## 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 | Address Precision | Address Recall | Address F1 | Address Number | Blood Group Precision | Blood Group Recall | Blood Group F1 | Blood Group Number | Date Of Issue Precision | Date Of Issue Recall | Date Of Issue F1 | Date Of Issue Number | Dob Precision | Dob Recall | Dob F1 | Dob Number | Driving Licence No Precision | Driving Licence No Recall | Driving Licence No F1 | Driving Licence No Number | Name Precision | Name Recall | Name F1 | Name Number | S D W Name Precision | S D W Name Recall | S D W Name F1 | S D W Name Number | Valid Till Nt Precision | Valid Till Nt Recall | Valid Till Nt F1 | Valid Till Nt Number | Valid Till T Tr Precision | Valid Till T Tr Recall | Valid Till T Tr F1 | Valid Till T Tr Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:--------------:|:---------------------:|:------------------:|:--------------:|:------------------:|:-----------------------:|:--------------------:|:----------------:|:--------------------:|:-------------:|:----------:|:------:|:----------:|:----------------------------:|:-------------------------:|:---------------------:|:-------------------------:|:--------------:|:-----------:|:-------:|:-----------:|:--------------------:|:-----------------:|:-------------:|:-----------------:|:-----------------------:|:--------------------:|:----------------:|:--------------------:|:-------------------------:|:----------------------:|:------------------:|:----------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
  | 1.9194        | 1.0   | 194  | 1.3597          | 0.3099            | 0.5789         | 0.4037     | 38             | 0.0                   | 0.0                | 0.0            | 22                 | 0.3147                  | 0.9                  | 0.4663           | 50                   | 0.0           | 0.0        | 0.0    | 44         | 0.1059                       | 0.1875                    | 0.1353                | 48                        | 0.0246         | 0.0612      | 0.0351  | 49          | 0.0                  | 0.0               | 0.0           | 48                | 0.0                     | 0.0                  | 0.0              | 41                   | 0.0                       | 0.0                    | 0.0                | 14                     | 0.1876            | 0.2232         | 0.2039     | 0.8582           |
  | 1.099         | 2.0   | 388  | 0.7767          | 0.5333            | 0.6316         | 0.5783     | 38             | 0.0                   | 0.0                | 0.0            | 22                 | 0.4667                  | 0.98                 | 0.6323           | 50                   | 0.9773        | 0.9773     | 0.9773 | 44         | 0.