docs: greedy correction — tha-g2p-small 2.85% PER; beam decode counterproductive - #36
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August 24, 2026 10:57
…l); beam decode counterproductive Re-measured through the shipped int4 zip and the Python runtime's ONNX KV decode (the exact path users get), true Levenshtein, full 1,219 sentences: greedy 2.85% PER / 88.93% EM vs the published beam-4 12.06% / 87.94%. Beam length-normalization systematically lengthens every non-exact output on this model's flat per-token distributions (top-1 logprob -4.6 vs uniform -5.6): EM barely moves, edit distance quadruples. Greedy is the optimal decode for these students; the runtime keeps greedy as default and exposes num_beams as a verified opt-in (batch-independence of the KV graph asserted against per-beam batch-1 references). All future gates decode greedy.
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Summary
Test plan