@@ -6,25 +6,33 @@ target: IPA
66tokenizer : bytes
77opset : 14
88decoder : kv
9- precision : fp32
9+ precision : int8
1010license : BSD-3-Clause
11- trained_from : >-
12- distilled from the recovered Thai umt5 teacher (transformers 5.14.1
13- re-finetune of B-K/umt5-thai-g2p-v2-0.5k on the 60K Kaikki+epitran
14- corpus; the secryst-saved umt5 artifacts are unusable — 5.15 dropped
15- the untied lm_head) via sequence-level KD; ByT5-small init
16- google/byt5-small; checkpoint
17- secryst-checkpoints:/secryst_thai_g2p_distill_small/run-002/best
11+ trained_from : ' sequence-level KD from the B-K/umt5-thai-g2p-v2-0.5k teacher (4.43%
12+ PER on this harness; the secryst-saved umt5 artifacts are unusable — transformers
13+ 5.15 dropped the untied lm_head); 48,757 usable beam-4 teacher-generated labels
14+ (51,321 raw, deduplicated, degenerate outputs filtered); ByT5-small init google/byt5-small;
15+ checkpoint secryst-checkpoints:/secryst_thai_g2p_distill_small/run-003/best. Client
16+ tier: capacity-limited at +7.63pp over the teacher — the +5pp gate is met by tha-g2p-base-1.0;
17+ this is the smallest rung that does not collapse (docs/RESULTS.md frontier table,
18+ ~300MB int8).'
1819metrics :
19- - name : per_teacher
20- value : 2.32
21- protocol : >-
22- greedy decode; 1,219 Kaikki Thai test sentences; umt5 teacher,
23- sentencepiece tokenizer; secryst RESULTS.md protocol
24- source : secryst/docs/RESULTS.md#thai-g2p
25- - name : per_student
26- value : PLACEHOLDER_STUDENT_PER
27- protocol : >-
28- greedy decode; same 1,219 test sentences, same harness as the
29- teacher (interscript/ml-models src/gpu/modal_distill.py::evaluate_per)
30- source : interscript/ml-models release tha-g2p-small-1.0
20+ - name : per_teacher
21+ value : 4.43
22+ protocol : beam-4, corpus-level PER (total_ed/total_gold over chars of joined-piece
23+ decode); 1,219 Kaikki Thai test sentences; B-K/ umt5-thai-g2p-v2-0.5k teacher;
24+ exact match 95.57%
25+ source : interscript/interscript-ml docs/RESULTS.md#tha-g2p-small-1.0
26+ - name : per_student
27+ value : 12.06
28+ protocol : beam-4, corpus-level PER, same harness as the teacher (src/gpu/ modal_distill.py::evaluate_per,
29+ run-003 checkpoint re-measured 2026-08-22); exact match 87.94%; +7.63pp client-tier
30+ shrink cost
31+ source : interscript/interscript-ml docs/RESULTS.md#tha-g2p-small-1.0
32+ parity :
33+ samples : 1219
34+ cer_delta : 0.0803
35+ sha256 :
36+ decoder-kv.onnx : b8d67ecbec9f4a29beafd3e6d431422f084c703a35467d836e81bdb8ceff4cba
37+ decoder.onnx : 81b3580d1d26f78e2aa1786218f50ebe970b23309386fa06bb73b0f27333c0a8
38+ encoder.onnx : 53416ec4c14ede50d2a5b3cd4b0de73c2b7c62e744a7d48d60e12a81ee89244d
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