readme: ---
  license: cc-by-nc-sa-4.0
  tags:
  - generated_from_trainer
  datasets:
  - dataset
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: Expediction
    results:
    - task:
        name: Token Classification
        type: token-classification
      dataset:
        name: dataset
        type: dataset
        config: discharge
        split: test
        args: discharge
      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
  ---
  
  <!-- 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. -->
  
  # Expediction
  
  This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the dataset dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0002
  - Precision: 1.0
  - Recall: 1.0
  - F1: 1.0
  - Accuracy: 1.0
  
  ## 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: 1e-05
  - train_batch_size: 2
  - eval_batch_size: 2
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - training_steps: 1000
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 7.14  | 100  | 0.0100          | 0.9111    | 0.8913 | 0.9011 | 0.9980   |
  | No log        | 14.29 | 200  | 0.0026          | 0.9670    | 0.9565 | 0.9617 | 0.9991   |
  | No log        | 21.43 | 300  | 0.0004          | 1.0       | 1.0    | 1.0    | 1.0      |
  | No log        | 28.57 | 400  | 0.0004          | 1.0       | 1.0    | 1.0    | 1.0      |
  | 0.0296        | 35.71 | 500  | 0.0002          | 1.0       | 1.0    | 1.0    | 1.0      |
  | 0.0296        | 42.86 | 600  | 0.0002          | 1.0       | 1.0    | 1.0    | 1.0      |
  | 0.0296        | 50.0  | 700  | 0.0001          | 1.0       | 1.0    | 1.0    | 1.0      |
  | 0.0296        | 57.14 | 800  | 0.0001          | 1.0       | 1.0    | 1.0    | 1.0      |
  | 0.0296        | 64.29 | 900  | 0.0001          | 1.0       | 1.0    | 1.0    | 1.0      |
  | 0.0003        | 71.43 | 1000 | 0.0001          | 1.0       | 1.0    | 1.0    | 1.0      |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  