dataset build 2026-08-24 09:40

README.md

@@ -1,60 +1,60 @@
----
-license: mit
-task_categories:
-- text2text-generation
-tags:
-- scheduler
-- text-to-json
-- tagalog
-- taglish
-- synthetic
-- from-scratch
-size_categories:
-- 100K<n<1M
----
-
-# Schedula dataset
-
-Fully synthetic, seeded, reproducible corpus for training **Schedula** - a tiny
-from-scratch model that turns messy natural language (English / Taglish /
-Filipino) into structured schedule JSON.
-
-## Modes
-| mode | input | output |
-|---|---|---|
-| `event_extract` | sentences, bullet dumps, decorated announcements (unicode stars/stylized headers), edit statements; embedded schedule JSON must be ignored | `{"events":[{title, category, date, start_time, duration_min, location, priority}]}` |
-| `duplicate_detect` | CURRENT LIST json (+ optional `"time_created": "... ##ignore"` metadata) + numbered NEW ITEMS (1-8) | `{"verdicts":[{duplicate, match_id, confidence, reason}]}` |
-
-## Conventions
-- `<today>` anchor date resolves every relative expression ("next week tue",
-  "bukas", "sa loob ng 2 linggo").
-- Fields suffixed ` ##ignore` are app-owned metadata: present in inputs,
-  never copied to outputs.
-- Items under "daily reminders"-style headers are undated (`null`) by design.
-- Category labels come from the per-example schema hint (default enum plus
-  alternate English/Tagalog sets) so the model learns hint-driven mapping.
-- Duplicate boundaries include numbered schoolwork (`quiz #2` vs `quiz #3`
-  never match) and EN<->Filipino translation pairs (do match).
-
-## Splits
-{
-  "train": {
-    "duplicate_detect": 63671,
-    "event_extract": 136329
-  },
-  "val": {
-    "duplicate_detect": 959,
-    "event_extract": 2041
-  },
-  "test": {
-    "duplicate_detect": 974,
-    "event_extract": 2026
-  }
-}
-
-Robustness noise (typos/filler/casing) appears only in val/test (18%).
-
-## Reproducibility
-Built by `python -m schedula.data.build --config configs/default.yaml`
-(seed 1337, created 2026-08-24). The generator lives at
-https://github.com/maxie-12321/schedula
+---
+license: mit
+task_categories:
+- text2text-generation
+tags:
+- scheduler
+- text-to-json
+- tagalog
+- taglish
+- synthetic
+- from-scratch
+size_categories:
+- 100K<n<1M
+---
+
+# Schedula dataset
+
+Fully synthetic, seeded, reproducible corpus for training **Schedula** - a tiny
+from-scratch model that turns messy natural language (English / Taglish /
+Filipino) into structured schedule JSON.
+
+## Modes
+| mode | input | output |
+|---|---|---|
+| `event_extract` | sentences, bullet dumps, decorated announcements (unicode stars/stylized headers), edit statements; embedded schedule JSON must be ignored | `{"events":[{title, category, date, start_time, duration_min, location, priority}]}` |
+| `duplicate_detect` | CURRENT LIST json (+ optional `"time_created": "... ##ignore"` metadata) + numbered NEW ITEMS (1-8) | `{"verdicts":[{duplicate, match_id, confidence, reason}]}` |
+
+## Conventions
+- `<today>` anchor date resolves every relative expression ("next week tue",
+  "bukas", "sa loob ng 2 linggo").
+- Fields suffixed ` ##ignore` are app-owned metadata: present in inputs,
+  never copied to outputs.
+- Items under "daily reminders"-style headers are undated (`null`) by design.
+- Category labels come from the per-example schema hint (default enum plus
+  alternate English/Tagalog sets) so the model learns hint-driven mapping.
+- Duplicate boundaries include numbered schoolwork (`quiz #2` vs `quiz #3`
+  never match) and EN<->Filipino translation pairs (do match).
+
+## Splits
+{
+  "train": {
+    "duplicate_detect": 1282,
+    "event_extract": 2718
+  },
+  "val": {
+    "duplicate_detect": 184,
+    "event_extract": 416
+  },
+  "test": {
+    "duplicate_detect": 174,
+    "event_extract": 426
+  }
+}
+
+Robustness noise (typos/filler/casing) appears only in val/test (16%).
+
+## Reproducibility
+Built by `python -m schedula.data.build --config configs/default.yaml`
+(seed 1337, created 2026-08-24). The generator lives at
+https://github.com/maxie-12321/schedula

manifest.json

@@ -1,26 +1,26 @@
-{
-  "seed": 1337,
-  "config_data": {
-    "out_dir": "data",
-    "n_train": 200000,
-    "n_val": 3000,
-    "n_test": 3000,
-    "robustness_frac": 0.2,
-    "max_input_chars": 2400,
-    "lang_mix": {
-      "en": 0.45,
-      "taglish": 0.35,
-      "fil": 0.2
-    },
-    "mix": {
-      "event_extract": 0.68,
-      "duplicate_detect": 0.32
-    }
-  },
-  "counts": {
-    "train": 200000,
-    "val": 3000,
-    "test": 3000
-  },
-  "created": "2026-08-24"
+{
+  "seed": 1337,
+  "config_data": {
+    "lang_mix": {
+      "en": 0.45,
+      "fil": 0.2,
+      "taglish": 0.35
+    },
+    "max_input_chars": 2400,
+    "mix": {
+      "duplicate_detect": 0.32,
+      "event_extract": 0.68
+    },
+    "n_test": 600,
+    "n_train": 4000,
+    "n_val": 600,
+    "out_dir": "data",
+    "robustness_frac": 0.2
+  },
+  "counts": {
+    "train": 4000,
+    "val": 600,
+    "test": 600
+  },
+  "created": "2026-08-24"
 }

train.jsonl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:1ae87c554ad1c79bbfdf0a37f1f4e466efca43b820a2eefd72df6f86e4ae4cec
-size 201240631
+oid sha256:42f7b797beed836646b6abe9a07b61ae4d8983107aa2f17ce56c8d143003d740
+size 4060289