readme: ---
  tags:
  - generated_from_trainer
  datasets:
  - invoice
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: layoutlmv3-fine-tuning-invoice 
    results:
    - task:
        name: Token Classification
        type: token-classification
      dataset:
        name: Invoice
        type: invoice
        args: invoice
      metrics:
      - name: Precision
        type: precision
        value: 1.0
      - name: Recall
        type: recall
        value: 1.0
      - name: F1
        type: f1
        value: 1.0
      - name: Accuracy
        type: accuracy
        value: 1.0
  ---
  ## LayoutLMv3-Fine-Tuning-Invoice Model
  
  #### Model description
  **LayoutLMv3-Fine-Tuning-Invoice Model** is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the invoice dataset. For the fine-tuning, We used [Invoice Dataset](https://huggingface.co/datasets/darentang/generated) that includes 12 labels ('Other', 'ABN', 'BILLER', 'BILLER_ADDRESS', 'BILLER_POST_CODE', 'DUE_DATE', 'GST', 'INVOICE_DATE', 'INVOICE_NUMBER', 'SUBTOTAL', 'TOTAL', 'BILLER_ADDRESS').
  
  It achieves the following results on the evaluation set:
  - Loss: 0.005334
  - Precision: 1.0
  - Recall: 1.0
  - F1: 1.0
  - Accuracy: 1.0
  
  
  
  ## Training procedure
  ### Training hyperparameters
  The following hyperparameters were used during training:
  - learning_rate: 1.5e-05
  - train_batch_size: 2
  - eval_batch_size: 2
  - optimizer: epsilon=1e-08
  - lr_scheduler_type: cosine
  - training_steps: 1000
  
  ### Training results
  
  | Training Loss |  Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 100 | 0.070030         | 0.972000  | 0.985801 | 0.978852 | 0.997051  |
  | No log        | 200 | 0.017637         | 0.972000  | 0.985801 | 0.978852 | 0.997051   |
  | No log        | 300 | 0.015573         | 0.972000  | 0.985801 | 0.978852 | 0.997051   |
  | No log        | 400 | 0.011000         | 0.973737  | 0.977688 | 0.978852 | 0.996419   |
  | 0.110800      | 500 | 0.005334         | 1.0       | 1.0    | 1.0    | 1.0      |
  | 0.110800      | 600 | 0.002994         | 1.0       | 1.0    | 1.0    | 1.0      |
  | 0.110800      | 700 | 0.002330         | 1.0       | 1.0    | 1.0    | 1.0      |
  | 0.110800      | 800 | 0.002188         | 1.0       | 1.0    | 1.0    | 1.0      |
  | 0.110800      | 900 | 0.002105         | 1.0       | 1.0    | 1.0    | 1.0      |
  | 0.004900      | 1000 | 0.002111        | 1.0       | 1.0    | 1.0    | 1.0      |
  
  
  
  ### Framework versions
  
  - Transformers 4.20.1