readme: ---
  license: cc-by-nc-sa-4.0
  tags:
  - generated_from_trainer
  model-index:
  - name: modelv3_WS_CV1
    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. -->
  
  # modelv3_WS_CV1
  
  This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2507
  - Ame: {'precision': 0.9523809523809523, 'recall': 0.9090909090909091, 'f1': 0.9302325581395349, 'number': 22}
  - Anguage: {'precision': 0.7608695652173914, 'recall': 0.7777777777777778, 'f1': 0.7692307692307693, 'number': 45}
  - Du Degree: {'precision': 0.7857142857142857, 'recall': 0.8461538461538461, 'f1': 0.8148148148148148, 'number': 65}
  - Du End Date: {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 1}
  - Du University: {'precision': 0.8666666666666667, 'recall': 0.8571428571428571, 'f1': 0.861878453038674, 'number': 91}
  - Ears Ex: {'precision': 0.96, 'recall': 1.0, 'f1': 0.9795918367346939, 'number': 24}
  - Er Name: {'precision': 0.4, 'recall': 0.6666666666666666, 'f1': 0.5, 'number': 6}
  - Kill: {'precision': 0.9733727810650887, 'recall': 0.9426934097421203, 'f1': 0.9577874818049491, 'number': 349}
  - Ractice: {'precision': 0.4838709677419355, 'recall': 0.625, 'f1': 0.5454545454545454, 'number': 24}
  - Rade: {'precision': 0.8461538461538461, 'recall': 0.9166666666666666, 'f1': 0.8799999999999999, 'number': 24}
  - Ummarize: {'precision': 1.0, 'recall': 0.9963636363636363, 'f1': 0.9981785063752276, 'number': 550}
  - Xpertise: {'precision': 0.8571428571428571, 'recall': 0.9836065573770492, 'f1': 0.916030534351145, 'number': 61}
  - X Company: {'precision': 0.9698275862068966, 'recall': 0.9868421052631579, 'f1': 0.9782608695652174, 'number': 228}
  - X Description: {'precision': 0.9955926699141731, 'recall': 0.976120081874005, 'f1': 0.9857602204869087, 'number': 4397}
  - X End Date: {'precision': 0.5, 'recall': 1.0, 'f1': 0.6666666666666666, 'number': 2}
  - X Location: {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 4}
  - X Position: {'precision': 0.8416075650118203, 'recall': 0.978021978021978, 'f1': 0.9047013977128335, 'number': 364}
  - X Start Date: {'precision': 0.2, 'recall': 0.14285714285714285, 'f1': 0.16666666666666666, 'number': 7}
  - Overall Precision: 0.9706
  - Overall Recall: 0.9692
  - Overall F1: 0.9699
  - Overall Accuracy: 0.9603
  
  ## 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: 4
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 40
  - 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 |
  |:-------------:|:-----:|:----:|:-----------