Automatic Generation of Factual News Headlines in Finnish

5 Dec 2022 · Maximilian Koppatz, Khalid Alnajjar, Mika Hämäläinen, Thierry Poibeau ·

We present a novel approach to generating news headlines in Finnish for a given news story. We model this as a summarization task where a model is given a news article, and its task is to produce a concise headline describing the main topic of the article. Because there are no openly available GPT-2 models for Finnish, we will first build such a model using several corpora. The model is then fine-tuned for the headline generation task using a massive news corpus. The system is evaluated by 3 expert journalists working in a Finnish media house. The results showcase the usability of the presented approach as a headline suggestion tool to facilitate the news production process.

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Adam • Attention Dropout • BPE • Cosine Annealing • Dense Connections • Discriminative Fine-Tuning • Dropout • GELU • GPT-2 • Layer Normalization • Linear Layer • Linear Warmup With Cosine Annealing • Multi-Head Attention • Residual Connection • Scaled Dot-Product Attention • Softmax • Weight Decay

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Automatic Generation of Factual News Headlines in Finnish

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