Zhikai Li

Per-fold leave-one-subject-out (LOSO) checkpoints for the scalp-EEG vs. in-ear-EEG sleep-staging benchmark in three datasets x two modalities x up to seven models, one checkpoint per held-out subject. 386 checkpoints, 14.3 GiB. These are fine-tuned task checkpoints, not pretrained encoders. Each file is the adapter statedict selected by the best validation balanced accuracy for that fold — the test set is never used for model selection. The tree mirrors the benchmark repo's own runs/, so a download can be dropped straight into runs/ and every training/eval script resolves it unchanged: is scalp-eeg or in-ear-eeg; fold-sub-sub-XXX names the held-out test subject. Only seed1 is published.…