mlf1_run1.py

training_args = {
    'train_batch_size':8, 
    'gradient_accumulation_steps':16, 
    'learning_rate': 2e-5, 
    'num_train_epochs': 3, 
    'max_seq_length': 60               # based on the histogram of number of words present in the headline
}

model_params = {
    'model_type': 'bert',
    'model_name': 'bert-base-uncased'
}

model, result, model_outputs, wrong_predictions = trainModel(model_params, training_args, mlf_run, 'bert_3epochs')