FiQA Dataset for RAG Evaluation The FiQA (Financial Opinion Mining and Question Answering) dataset reformatted specifically for evaluating Retrieval Augmented Generation (RAG) systems. This dataset contains financial domain questions with ground truth answers and retrieved contexts, making it ideal for testing RAG pipelines on domain specific content. Recommended Usage: ragas eval v3 The ragas eval v3 configuration is the primary and recommended way to use this dataset. It contains pre generated RAG outputs ready for evaluation with a standardized schema. Dataset Structure ( ragas eval v3 ) Each sample contains: user input : The financial question to be answered reference : Ground truth answer for evaluation response : Generated answer from a RAG system retrieved contexts : List of retrieved context passages used to generate the answer Example Usage Alternative Configurations main Configuration Training/validation/test splits with questions and ground truth answers only (no generated answers or contexts). Structure: question : The financial question ground truths : List of reference answers Splits: train : 5,500 question answer pairs validation : 500 question answer pairs test : 64…
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