mlf1_run2.py

training_args = {
    'train_batch_size':8, 
    'gradient_accumulation_steps':16, 
    'learning_rate': 2e-5, 
    'num_train_epochs': 5,             # Change in 
    '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'
}

mlf_run_2 = mlf_api.create_run(project_name='financial-sentiment-analysis', run_name='bert_5epochs')
model2, result2, model_outputs2, wrong_predictions2 = trainModel(model_params, training_args, mlf_run_2, 'bert_5epochs')