readme: Training parameters:
  
  ```
  model_args = ClassificationArgs()
  model_args.max_seq_length = 512
  model_args.train_batch_size = 12
  model_args.eval_batch_size = 12
  model_args.num_train_epochs = 5
  model_args.evaluate_during_training = False
  model_args.learning_rate = 1e-5
  model_args.use_multiprocessing = False
  model_args.fp16 = False
  model_args.save_steps = -1
  model_args.save_eval_checkpoints = False
  model_args.no_cache = True
  model_args.reprocess_input_data = True
  model_args.overwrite_output_dir = True
  ```
  
  Evaluation on BoolQ Test Set:
  
  |              | Precision | Recall | F1-score |
  |:------------:|:---------:|:------:|:--------:|
  |       0      |    0.82   |  0.80  |   0.81   |
  |       1      |    0.88   |  0.89  |   0.88   |
  |   accuracy   |           |        |   0.86   |
  |   macro avg  |    0.85   |  0.84  |   0.85   |
  | weighted avg |    0.86   |  0.86  |   0.86   |
  
  ROC AUC Score: 0.844