FIN-bench-v2: A Unified and Robust Benchmark Suite for Evaluating Finnish Large Language Models

• URL: http://arxiv.org/abs/2512.13330v1
• Date: Mon, 15 Dec 2025 13:41:41 GMT
• Title: FIN-bench-v2: A Unified and Robust Benchmark Suite for Evaluating Finnish Large Language Models
• Abstract summary: FIN-bench-v2 is a unified benchmark suite for evaluating large language models in Finnish.<n>It consolidates Finnish versions of widely used benchmarks together with an updated and expanded version of the original FIN-bench.
• Score: 2.7752454749431306
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We introduce FIN-bench-v2, a unified benchmark suite for evaluating large language models in Finnish. FIN-bench-v2 consolidates Finnish versions of widely used benchmarks together with an updated and expanded version of the original FIN-bench into a single, consistently formatted collection, covering multiple-choice and generative tasks across reading comprehension, commonsense reasoning, sentiment analysis, world knowledge, and alignment. All datasets are converted to HuggingFace Datasets, which include both cloze and multiple-choice prompt formulations with five variants per task, and we incorporate human annotation or review for machine-translated resources such as GoldenSwag and XED. To select robust tasks, we pretrain a set of 2.15B-parameter decoder-only models and use their learning curves to compute monotonicity, signal-to-noise, non-random performance, and model ordering consistency, retaining only tasks that satisfy all criteria. We further evaluate a set of larger instruction-tuned models to characterize performance across tasks and prompt formulations. All datasets, prompts, and evaluation configurations are publicly available via our fork of the Language Model Evaluation Harness at https://github.com/LumiOpen/lm-evaluation-harness. Supplementary resources are released in a separate repository at https://github.com/TurkuNLP/FIN-bench-v2.

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