Kaggle competition: Natural Language Processing with Disaster Tweets
<save_to_csv><EOS> 
!pip install --upgrade transformers simpletransformers
train_data = pd.read_csv('.. /input/nlp-with-disaster-tweets-cleaning-data/train_data_cleaning.csv')[['text', 'target']]
test_data = pd.read_csv('.. /input/nlp-with-disaster-tweets-cleaning-data/test_data_cleaning.csv')[['id','text']]
model = ClassificationModel('distilbert', 'distilbert-base-uncased', args={'fp16': False,'train_batch_size': 4, 'gradient_accumulation_steps': 2,
'learning_rate': 1e-05, 'do_lower_case': True, 'overwrite_output_dir': True, 'manual_seed': 100, 'num_train_epochs': 2}, weight = [0.44, 0.56])
 model.train_model(train_data)
 test_data["target"], _ = model.predict(test_data['text'])
 test_data.drop(columns=['text'] ).to_csv("submission.csv", index=False )