olaverse/qg-eval-multi-fresh

qg-eval-multi-fresh Held-out evaluation passages for olaverse/mist-qg-1.5b — provably never seen during training, used to compute the model's published round-trip keep-rate. Dataset Summary 625 passages (~25 per language, 25 languages), sampled from the same source as the training data but explicitly deduplicated against every passage used to train mist-qg-1.5b, so scores on this set measure generalization rather than memorization. Data Fields… See the full description on the dataset page: https://huggingface.co/datasets/olaverse/qg-eval-multi-fresh.