readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: layoutlm-funsd_30_8_4
    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_30_8_4
  
  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: 0.5511
  - Ame: {'precision': 0.8846153846153846, 'recall': 0.92, 'f1': 0.9019607843137256, 'number': 25}
  - Anguage: {'precision': 0.8, 'recall': 0.8, 'f1': 0.8000000000000002, 'number': 5}
  - Areer: {'precision': 0.6153846153846154, 'recall': 0.34782608695652173, 'f1': 0.4444444444444444, 'number': 23}
  - Ddress: {'precision': 0.6190476190476191, 'recall': 0.896551724137931, 'f1': 0.732394366197183, 'number': 29}
  - Du Degree: {'precision': 0.8837209302325582, 'recall': 0.8941176470588236, 'f1': 0.888888888888889, 'number': 85}
  - Du End Date: {'precision': 0.38095238095238093, 'recall': 1.0, 'f1': 0.5517241379310345, 'number': 8}
  - Du Start Date: {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 4}
  - Du University: {'precision': 0.9032258064516129, 'recall': 0.7671232876712328, 'f1': 0.8296296296296296, 'number': 73}
  - Hone: {'precision': 0.5789473684210527, 'recall': 0.7857142857142857, 'f1': 0.6666666666666667, 'number': 14}
  - Kill: {'precision': 0.7972972972972973, 'recall': 0.7023809523809523, 'f1': 0.7468354430379748, 'number': 84}
  - Mail: {'precision': 0.8, 'recall': 0.8, 'f1': 0.8000000000000002, 'number': 15}
  - Umarize: {'precision': 0.73568281938326, 'recall': 0.9175824175824175, 'f1': 0.8166259168704157, 'number': 182}
  - X Company: {'precision': 0.8560606060606061, 'recall': 0.738562091503268, 'f1': 0.792982456140351, 'number': 153}
  - X Description: {'precision': 0.9297334717895466, 'recall': 0.9817251461988304, 'f1': 0.9550222222222222, 'number': 2736}
  - X End Date: {'precision': 0.8333333333333334, 'recall': 0.9523809523809523, 'f1': 0.888888888888889, 'number': 42}
  - X Location: {'precision': 0.918918918918919, 'recall': 0.8947368421052632, 'f1': 0.9066666666666667, 'number': 76}
  - X Position: {'precision': 0.8345323741007195, 'recall': 0.8405797101449275, 'f1': 0.8375451263537906, 'number': 138}
  - X Start Date: {'precision': 0.9137931034482759, 'recall': 0.9298245614035088, 'f1': 0.9217391304347825, 'number': 57}
  - Overall Precision: 0.8973
  - Overall Recall: 0.9416
  - Overall F1: 0.9189
  - Overall Accuracy: 0.8925
  
  ## 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: 30
  
  ### 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 Reca