def METHOD_NAME(hf_tokenizer, smiles_regression_dataset):
    from transformers.models.roberta import (RobertaConfig,
                                             RobertaForSequenceClassification)
    config = RobertaConfig(vocab_size=hf_tokenizer.vocab_size,
                           problem_type='regression',
                           num_labels=1)
    model = RobertaForSequenceClassification(config)
    hf_model = HuggingFaceModel(model=model,
                                tokenizer=hf_tokenizer,
                                task='regression',
                                device=torch.device('cpu'))
    hf_model.fit(smiles_regression_dataset, nb_epoch=1)
    result = hf_model.predict(smiles_regression_dataset)
    assert result.all()
    score = hf_model.evaluate(smiles_regression_dataset,
                              metrics=dc.metrics.Metric(dc.metrics.mae_score))
    assert score