readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: layoutlm-funsd
    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. -->
  
  # layoutlm-funsd
  
  This model is a fine-tuned version of [microsoft/layoutlm-base-uncased](https://huggingface.co/microsoft/layoutlm-base-uncased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.1473
  - Ame: {'precision': 0.7647058823529411, 'recall': 1.0, 'f1': 0.8666666666666666, 'number': 13}
  - Anguage: {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 1}
  - Areer: {'precision': 0.6666666666666666, 'recall': 0.2857142857142857, 'f1': 0.4, 'number': 14}
  - Ddress: {'precision': 0.6122448979591837, 'recall': 0.7894736842105263, 'f1': 0.6896551724137931, 'number': 38}
  - Du Degree: {'precision': 0.8245614035087719, 'recall': 0.7966101694915254, 'f1': 0.8103448275862069, 'number': 59}
  - Du End Date: {'precision': 0.7272727272727273, 'recall': 0.8421052631578947, 'f1': 0.7804878048780488, 'number': 19}
  - Du Start Date: {'precision': 1.0, 'recall': 0.6666666666666666, 'f1': 0.8, 'number': 3}
  - Du University: {'precision': 0.8222222222222222, 'recall': 0.8809523809523809, 'f1': 0.8505747126436781, 'number': 84}
  - Hone: {'precision': 0.7083333333333334, 'recall': 0.8095238095238095, 'f1': 0.7555555555555556, 'number': 21}
  - Kill: {'precision': 0.7416666666666667, 'recall': 0.5913621262458472, 'f1': 0.6580406654343807, 'number': 301}
  - Mail: {'precision': 0.7647058823529411, 'recall': 0.8666666666666667, 'f1': 0.8125, 'number': 15}
  - Umarize: {'precision': 0.6891891891891891, 'recall': 0.9532710280373832, 'f1': 0.8, 'number': 214}
  - X Company: {'precision': 0.75177304964539, 'recall': 0.848, 'f1': 0.7969924812030075, 'number': 125}
  - X Description: {'precision': 0.8356118706235411, 'recall': 0.9586840091813313, 'f1': 0.892927133440228, 'number': 2614}
  - X End Date: {'precision': 0.875, 'recall': 0.8484848484848485, 'f1': 0.8615384615384615, 'number': 33}
  - X Location: {'precision': 0.8, 'recall': 0.9090909090909091, 'f1': 0.8510638297872342, 'number': 66}
  - X Position: {'precision': 0.7593984962406015, 'recall': 0.8782608695652174, 'f1': 0.8145161290322581, 'number': 115}
  - X Start Date: {'precision': 0.7142857142857143, 'recall': 0.8974358974358975, 'f1': 0.7954545454545455, 'number': 39}
  - Overall Precision: 0.8082
  - Overall Recall: 0.9102
  - Overall F1: 0.8562
  - Overall Accuracy: 0.8177
  
  ## 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: 3e-05
  - train_batch_size: 4
  - eval_batch_size: 2
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 50
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Ame                                                                                                      | Anguage                                                                  | Areer                                                                                                     | Ddress                                                                                                    | Du Degree                                                                                               | Du End Date                                                                                              | Du Start Date                                                                                          | Du University                                                                                            | Hone                                                                                                    | Kill                                                                                                      | Mail                                                                                                    | Umarize                                                                                                  | X Company                                                                                   | X Description                                                                                             | X End Date                                                                                              | X Location                                                                                              | X Position                                                                                               | X Start Date                                                                                             | Overall Precision | Overall Recall | Overall F1 | Over