The paper evaluates the possibilities of using transformer architecture in creating headlines for news texts in Finnish. The authors statistically analyse the original and generated headlines according to three criteria: informativeness, relevance and impact. The study also substantiates for the first time the effectiveness of a fine-tuned text-to-text transfer transformer model within the task of generating headlines for news articles in Finnish. The results show that there is no statistically significant difference between the scores obtained by the original and generated headlines on the mentioned criteria of informativeness, relevance and impact.