readme: ---
  license: mit
  tags:
  - generated_from_trainer
  model-index:
  - name: LiLT_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. -->
  
  # LiLT_WS_CV1
  
  This model is a fine-tuned version of [SCUT-DLVCLab/lilt-roberta-en-base](https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2006
  - Ame: {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 19}
  - Anguage: {'precision': 0.7777777777777778, 'recall': 0.875, 'f1': 0.823529411764706, 'number': 32}
  - Du Degree: {'precision': 0.775, 'recall': 0.7560975609756098, 'f1': 0.7654320987654322, 'number': 41}
  - Du University: {'precision': 0.8068181818181818, 'recall': 0.9342105263157895, 'f1': 0.8658536585365854, 'number': 76}
  - Ears Ex: {'precision': 0.9130434782608695, 'recall': 0.875, 'f1': 0.8936170212765957, 'number': 24}
  - Er Name: {'precision': 0.45454545454545453, 'recall': 0.625, 'f1': 0.5263157894736842, 'number': 8}
  - Kill: {'precision': 0.8759398496240601, 'recall': 0.91015625, 'f1': 0.89272030651341, 'number': 256}
  - Ractice: {'precision': 0.7142857142857143, 'recall': 0.6818181818181818, 'f1': 0.6976744186046512, 'number': 22}
  - Rade: {'precision': 0.9047619047619048, 'recall': 0.76, 'f1': 0.8260869565217391, 'number': 25}
  - Ummarize: {'precision': 0.9411764705882353, 'recall': 0.9795918367346939, 'f1': 0.96, 'number': 343}
  - Xpertise: {'precision': 0.8115942028985508, 'recall': 0.9333333333333333, 'f1': 0.8682170542635659, 'number': 60}
  - X Company: {'precision': 0.9681274900398407, 'recall': 0.9274809160305344, 'f1': 0.9473684210526316, 'number': 262}
  - X Description: {'precision': 0.9860392967942089, 'recall': 0.9829896907216494, 'f1': 0.9845121321631389, 'number': 3880}
  - X End Date: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 4}
  - X Location: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 5}
  - X Position: {'precision': 0.8944337811900192, 'recall': 0.9648033126293996, 'f1': 0.9282868525896414, 'number': 483}
  - X Start Date: {'precision': 0.5714285714285714, 'recall': 1.0, 'f1': 0.7272727272727273, 'number': 8}
  - Overall Precision: 0.9567
  - Overall Recall: 0.9670
  - Overall F1: 0.9618
  - Overall Accuracy: 0.9528
  
  ## 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 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 |
  |:-------------:|:-----:|:----:|:---------------:|:--------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------:|:------------------------------------------------