readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: model_WS_CV0
    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. -->
  
  # model_WS_CV0
  
  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: 0.2306
  - Ame: {'precision': 1.0, 'recall': 0.8076923076923077, 'f1': 0.8936170212765957, 'number': 26}
  - Anguage: {'precision': 0.8863636363636364, 'recall': 0.9285714285714286, 'f1': 0.9069767441860465, 'number': 42}
  - Du Degree: {'precision': 0.8, 'recall': 0.9411764705882353, 'f1': 0.8648648648648648, 'number': 51}
  - Du End Date: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2}
  - Du University: {'precision': 0.8676470588235294, 'recall': 0.921875, 'f1': 0.893939393939394, 'number': 64}
  - Ears Ex: {'precision': 0.9090909090909091, 'recall': 0.9090909090909091, 'f1': 0.9090909090909091, 'number': 22}
  - Er Name: {'precision': 0.4166666666666667, 'recall': 0.8333333333333334, 'f1': 0.5555555555555556, 'number': 6}
  - Kill: {'precision': 0.9810725552050473, 'recall': 0.9452887537993921, 'f1': 0.9628482972136223, 'number': 329}
  - Ractice: {'precision': 0.59375, 'recall': 0.6785714285714286, 'f1': 0.6333333333333334, 'number': 28}
  - Rade: {'precision': 0.8260869565217391, 'recall': 0.8260869565217391, 'f1': 0.8260869565217391, 'number': 23}
  - Ummarize: {'precision': 0.9935064935064936, 'recall': 1.0, 'f1': 0.9967426710097721, 'number': 459}
  - Xpertise: {'precision': 0.5555555555555556, 'recall': 0.9375, 'f1': 0.6976744186046512, 'number': 32}
  - X Company: {'precision': 0.884, 'recall': 0.9525862068965517, 'f1': 0.91701244813278, 'number': 232}
  - X Description: {'precision': 0.9895202608290639, 'recall': 0.9707562257253827, 'f1': 0.9800484373198017, 'number': 4377}
  - X End Date: {'precision': 1.0, 'recall': 0.6666666666666666, 'f1': 0.8, 'number': 3}
  - X Location: {'precision': 1.0, 'recall': 0.125, 'f1': 0.2222222222222222, 'number': 8}
  - X Position: {'precision': 0.7441860465116279, 'recall': 0.9171974522292994, 'f1': 0.8216833095577747, 'number': 314}
  - X Start Date: {'precision': 0.9, 'recall': 1.0, 'f1': 0.9473684210526316, 'number': 9}
  - Overall Precision: 0.9573
  - Overall Recall: 0.9623
  - Overall F1: 0.9598
  - Overall Accuracy: 0.9532
  
  ## 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: 20
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Ame                                                                                                     | Anguage                                                                                                   | Du Degree                                                                                               | Du End Date                                               | Du University                                                                                  | Ears Ex                                                                                                 | Er Name                                                                                                 | Kill                                                                                                     | Ractice                                                                                                 | Rade                                                                                                    | Ummarize                                                                                                 | Xpertise                                                                                      | X Company                                                                                                  | X Description                                                                                             | X End Date                                                               | X Location                                                                 | X Position                                                                                               | X Start Date                                                             | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:-------------------------------------------------------------------