PolyPlex Korean, Phase 1.0 and 1.5 adapters
Backup of the two Phase 1 stages of PolyPlex, which adds Korean to a frozen PersonaPlex 7B from text only.
These are adapter slices, not full models: each holds the appended Korean text rows and the session expert
(a correction on the FFNs of layers 8 to 31, rank 256). They load onto the vocabulary-expanded base
checkpoint (expanded_v2, 32,000 + 10,448 tokens) with the PolyPlex code
(polyplex_research.utils.assemble.Phase1Assemble.from_run).
| Folder | Stage | Trained on | Code |
|---|---|---|---|
phase1.0/ |
Dense text (no PAD frames), 26,000 steps | About 510M tokens of Korean web text (HAERAE KOREAN-WEBTEXT) and Korean Wikipedia | branch experiment/two-stage-dense-duplex (commit 2e00113) |
phase1.5/ |
Duplex dialogue layout with codec silence, 6,000 steps, started from phase1.0 |
384,000 of 602,677 dialogue samples (AI Hub multisession dialogue 011 and 141, colloquial translation sentences) | same branch |
Each folder holds the final adapter (config.json, text_rows.safetensors) and the last trainer checkpoint
(checkpoint-26000/, checkpoint-6000/) with optimizer, scheduler and RNG state for resuming.
Results of phase1.5/ (silent condition unless stated)
| Measure | Value |
|---|---|
| Korean word loss, 011 validation (8,348 utterances, training sentences removed) | 4.136 (PPL 62.6) |
| Korean word loss, 141 dialogue validation (2,000 dialogues) | 3.738 |
| Same-meaning comparison, 200 pairs: Korean / English (original model) | 4.067 / 3.835 |
| Timing cost on 011 (PAD/EPAD loss over the original model) | +0.056 |
| Korean word loss with real speech (KsponSpeech validation) | 9.322 |
Known limits: Korean does not carry over to the condition where the assistant channel holds real speech, and
with the session expert on the depth decoder's code prediction is broken (assistant code loss 7.87 against
4.38 with the expert off), so this adapter does not speak Korean. The full records are the ResearchTree pull
requests #17 (this stage) and #18, #19, #20 (later attempts) of latentforge/PolyPlex.
The training data licenses have not been reviewed for redistribution, which is why this repository is private.