filbench/filbench-eval

Experiments and Analyses for FilBench: An Open LLM Leaderboard for Filipino (EMNLP Main '25)

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Experimental

This project helps researchers and developers working with Large Language Models (LLMs) to accurately assess how well their models understand and generate Filipino. You provide your LLM, and the system evaluates its performance across key capabilities like cultural knowledge and reading comprehension, giving you a score and detailed breakdown. This is for anyone creating, fine-tuning, or evaluating LLMs for Filipino language applications.

Use this if you need a standardized, comprehensive way to benchmark your LLM's proficiency in the Filipino language against other models.

Not ideal if you are looking to evaluate LLMs in languages other than Filipino, or if you need a tool for general-purpose model deployment rather than specific language evaluation.

Filipino-NLP LLM-evaluation language-modeling cultural-competence AI-benchmarking
No License No Package No Dependents
Maintenance 10 / 25
Adoption 5 / 25
Maturity 7 / 25
Community 0 / 25

How are scores calculated?

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Python

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Last pushed

Jan 20, 2026

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