release: heb-diac-small-1.0 registration (gated ByT5-small student, +5.58pp)

Author: Ronald Tse

docs/RESULTS.md

@@ -44,3 +44,18 @@ representation line are closed negative; v1 is final).
 
 Published reference: Homo-GE2PE homograph 76.89% — v1 is above the
 published SOTA on this benchmark.
+
+## heb-diac-small-1.0 — Hebrew student distillation (2026-08-20)
+
+Logit KD from the s43 teacher (rababa_hebrew_byt5_s43/run-001/best):
+KL + CE on hebrew-v4, ByT5-small init. Harness: greedy decode, Nakdimon
+IMF test split (1,864 long sentences), same harness for both models
+(`src/gpu/modal_distill.py::evaluate`).
+
+| Model | DER | CER |
+|---|---|---|
+| Teacher (s43, ByT5-base) | 24.79% | 22.14% |
+| **Student (ByT5-small, gate)** | **30.37%** | 24.47% |
+
+Shrink cost +5.58pp — inside the ~5.6pp budget pre-accepted for this
+pair (rababa docs/DISTILL-SOURCE-PROMPT.md section 2).

models/heb-diac-small/heb-diac-small-1.0.README.md

@@ -0,0 +1,15 @@
+# heb-diac-small-1.0
+
+Hebrew diacritization (adds nikud), client tier. ByT5-small student
+(300M) distilled from the s43 teacher via logit KD — same vocab
+(byte-level), so the teacher's soft distributions transfer directly.
+
+Gate: student 30.37% DER vs teacher 24.79% (greedy, Nakdimon IMF test
+split, 1,864 long sentences) = +5.58pp, inside the ~5.6pp shrink budget
+pre-accepted for this pair (docs/DISTILL-SOURCE-PROMPT.md section 2).
+
+```python
+from interscript_ml import Model
+model = Model.load("heb-diac-small-1.0")
+model.translate("שלום")
+```

models/heb-diac-small/heb-diac-small-1.0.metadata.yaml

@@ -0,0 +1,29 @@
+format: imf-v1
+id: heb-diac-small-1.0
+task: diacritization
+source_script: Hebr
+target: Hebr
+tokenizer: bytes
+opset: 14
+decoder: kv
+precision: fp32
+license: BSD-3-Clause
+trained_from: >-
+  logit KD from the s43 teacher (rababa_hebrew_byt5_s43/run-001/best,
+  RELEASE-FROZEN): KL(teacher_soft || student_soft) + CE on the
+  hebrew-v4 corpus, ByT5-small init google/byt5-small; checkpoint
+  rababa-checkpoints:/rababa_hebrew_distill_small/run-001/best
+metrics:
+  - name: der_teacher_greedy
+    value: 24.79
+    protocol: >-
+      greedy decode; Nakdimon IMF test split, 1,864 long sentences;
+      s43 teacher on the same harness as the student
+    source: interscript/ml-models docs/RESULTS.md#heb-diac-small-1.0
+  - name: der_student_greedy
+    value: 30.37
+    protocol: >-
+      greedy decode; same harness; +5.58pp shrink cost, inside the
+      ~5.6pp budget pre-accepted for this pair
+      (docs/DISTILL-SOURCE-PROMPT.md section 2)
+    source: interscript/ml-models docs/RESULTS.md#heb-diac-small-1.0

models/metrics-sources.yaml

@@ -58,3 +58,12 @@ fas-g2p-1.0:
   tables:
     - {row: "CER (v1 test split, greedy, editdistance)", as: cer}
     - {row: "SentenceBench homograph (ezafe-normalized)", as: sb_homograph_ezafe_norm}
+heb-diac-small-1.0:
+  repo: interscript/interscript-ml
+  ref: main
+  path: docs/RESULTS.md
+  anchor: heb-diac-small-1.0
+  protocol: "greedy decode; Nakdimon IMF test split, 1,864 long sentences"
+  tables:
+    - {row: "Teacher (s43, ByT5-base)", column: DER, as: der_teacher_greedy}
+    - {row: "Student (ByT5-small, gate)", column: DER, as: der_student_greedy}

src/gpu/modal_export.py

@@ -95,6 +95,15 @@
         "test_data": "urdu-diacrit/test.jsonl",
         "probe": "اردو",
     },
+    "heb-diac-small": {
+        "volume": "/volumes/rababa-checkpoints",
+        "checkpoint": "rababa_hebrew_distill_small/run-001/best",
+        "metadata": "models/heb-diac-small/heb-diac-small-1.0.metadata.yaml",
+        "readme": "models/heb-diac-small/heb-diac-small-1.0.README.md",
+        "test_volume": "/datasets/rababa",
+        "test_data": "nakdimon/test-imf.jsonl",
+        "probe": "שלום",
+    },
     "tha-g2p-base": {
         "volume": "/volumes/secryst-checkpoints",
         "checkpoint": "secryst_thai_g2p_distill_small/run-004/best",