def METHOD_NAME():
    n_tasks = 5
    max_seq_len = 20
    dataset, metric, char_to_idx, = get_dataset(mode="classification",
                                                featurizer="smiles2seq",
                                                n_tasks=n_tasks,
                                                max_seq_len=max_seq_len)
    model = Smiles2Vec(char_to_idx=char_to_idx,
                       max_seq_len=max_seq_len,
                       use_conv=True,
                       n_tasks=n_tasks,
                       model_dir=None,
                       mode="classification")
    model.fit(dataset, nb_epoch=500)
    scores = model.evaluate(dataset, [metric], [])
    assert scores['mean-roc_auc_score'] >= 0.9