readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - policies-named-insured
  model-index:
  - name: bert-large-uncased-whole-word-masking-finetuned-policy-named-insured
    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. -->
  
  # bert-large-uncased-whole-word-masking-finetuned-policy-named-insured
  
  This model is a fine-tuned version of [bert-large-uncased-whole-word-masking-finetuned-squad](https://huggingface.co/bert-large-uncased-whole-word-masking-finetuned-squad) on the policies-named-insured dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0264
  
  ## 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: 2e-05
  - train_batch_size: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 3
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | No log        | 1.0   | 478  | 0.0402          |
  | 0.0557        | 2.0   | 956  | 0.0326          |
  | 0.0106        | 3.0   | 1434 | 0.0264          |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.12.1
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  