This repository documents the completed Dakota1890 reinforcement-learning run on Thinking Machines Tinker. The repaired reward ledger reported correctly through the run, the final Tinker checkpoint is available, and the Hugging Face PEFT adapter artifacts needed for inference are published alongside this model card.
The work starts from Stephen Return Riggs' 1890 Dakota grammar and dictionary materials: scanned pages, extracted grammar rules, dictionary vocabulary, and a verifier environment built to reward short, answer-only Dakota grammar behavior. The goal is not to create a general cultural authority or a fluent speaker replacement. The goal is narrower and more testable: preserve a historical grammar source as machine-readable tasks, train an open model adapter against explicit grammar rewards, and publish the artifacts in a way that makes the provenance and limitations visible.
The visual source collage is composed only from local Dakota1890 source scans. It spans cover/front matter, grammar pages, dictionary vocabulary pages, and the late extraction range through scan/page 430. The source manifest is included at assets/collage_manifest.md.
Current Status
Training completed on May 27, 2026. This card now includes the audited final run findings and W&B-style result charts.
The reward-channel pilot completed before the full run and cost about $0.26. It verified that the repaired environment can emit nonzero pattern_raw and exact_match_raw channels locally and in W&B before scaling up.
Final Run Findings
Dakota1890 full run dashboard
The full run completed 199 metric rows, ending at training step 198. It cost $68.75 in Thinking Machines credits and processed 82.05 million tokens. The final audit found:
composite reward improved from 0.1664 to 0.2297;
character-overlap reward improved from 0.1424 to 0.4027;
affix reward stayed high and ended at 1.0000;
all-task pattern_raw was nonzero in 186 of 199 logged training rows;
identify_pattern pattern reward reached 0.90625 and was nonzero in 179 of 199 rows;
eval pattern_raw remained nonzero, ending at 0.0586;
exact-match reward stayed at 0.0 throughout the mixed-task run;
composite_diff stayed exactly 0.0, confirming that the emitted ledger reconstructs the scalar reward.
The key result is that the repaired pattern channel is live in a full paid Tinker run. Exact match remains a task-design and prompting problem for short answer-only completions, not a reward-plumbing failure.
Dakota1890 is built around historical Dakota language source material rather than generic web text. The local project contains the primary Riggs scan, 440 scanned page images, public visual artifacts used for documentation, extracted grammar rules, extracted dictionary vocabulary, generated RL tasks, and W&B/Tinker run logs.
JP2 source scans: 440 local page images under Dictionary/grammardictionar00riggrich_jp2
processed page images: 440 JPG conversions under data/processed_images
page-layout manifest: 440 rows, including 345 two-column pages and 84 single-column pages
grammar extraction: pages 1-92, with no missing pages in that intended range
dictionary extraction: pages 95-430, with no missing pages in that intended range
verified dictionary entries: 24,224
median dictionary entries per extracted page: 63
average extraction confidence: about 0.9245
first and last verified headwords: a through zig'zag
The current RL grammar dataset contains:
10,576 total packaged RL tasks
1,497 extracted grammar-rule records
684 grammar rules in the grammar extraction pass
350 interlinear texts in the grammar extraction pass
396 linguistic terms in the grammar extraction pass
33 special-character forms observed in the grammar extraction pass
1,497 rows with pattern-bearing verification metadata
514 rows with affix metadata
median reference answer length of about 4 words
Task family counts in the packaged dataset:
Task family
Count
word_translation
2,879
reverse_translation
2,137
morphology
1,934
identify_pattern
1,497
positive_negative_evidence
584
exception_trigger
584
syntax
420
sentence_translation
316
affix_insertion
115
multi_step_morphology
110
The dictionary extraction and synthetic Q&A generation work are adjacent dataset-building tracks. This Tinker RL run does not require OpenAI SFT data or a synthetic dictionary Q&A dump to start; it trains against the existing grammar-task environment and its reward function. The dictionary artifacts remain important for future evaluation, documentation, and broader Dakota lexical coverage.
Visual Project Artifacts
These local project images are included to preserve the visual record of the build alongside the model card:
Artifact
Preview
Grammar source page
Grammar source page
Dictionary source page
Dictionary source page
Training screenshot
Training screenshot
What Changed For This Run
Earlier public runs showed metrics/pattern_reward = 0.0 and metrics/exact_match_reward = 0.0 throughout the public W&B surface. The pattern channel was a real plumbing bug: the packaged dataset stores metadata under entry["info"], while the environment had been reading top-level fields such as entry["verification_pattern"], entry["task_type"], and entry["difficulty"].
That has been fixed. The environment now preserves:
task type
difficulty
rule id
hints
verification pattern, including info.pattern
special-character and affix metadata
The full run now logs the composite reward ledger under namespaces such as env/all/ledger/*, env/task/identify_pattern/ledger/*, and difficulty-specific ledgers. Early full-run metrics already showed nonzero pattern reward on identify_pattern tasks with composite_diff = 0.0, meaning the logged scalar reward matches the reconstructed component ledger.
Reward Function
The Dakota grammar verifier uses a composite reward:
Component
Weight
Purpose
exact match
40%
Rewards short answers that exactly match rigid references
character overlap
20%
Rewards lexical and orthographic overlap with the reference
pattern match
15%
Rewards structural matches for rule-bearing tasks
affix accuracy
10%
Rewards required Dakota affix behavior
length control
15%
Penalizes verbose completions when the gold answer is short
Difficulty multipliers are applied after the component sum. The run logs raw component values, normalized values, weights, weighted contributions, reconstructed composites, final reward scalar, and composite_diff for auditability.
Exact match is intentionally strict. In the older public 0.6B run, completions were often much longer than the reference answers, while the packaged dataset has a median reference answer length of about four words. That makes exact match a behavioral and prompting problem, not evidence that the exact-match function is dead. The new run keeps max generation short and logs enough ledger detail to diagnose whether exact-match-sensitive task families are improving.
Training Configuration
The active full run was launched with:
Setting
Value
model
Qwen/Qwen3.6-35B-A3B
batches planned
199
batch size
48
group size
16
max tokens
128
temperature
0.5
learning rate
4e-5
LoRA rank
32
eval interval
20 batches
save interval
20 batches
W&B sync
enabled
The local runtime gate passed before launch with current Tinker, Tinker cookbook, W&B, Gemini, tokenizer, and reward-channel smoke checks.
Intended Use
This adapter is intended for research and tool-building around historical Dakota grammar tasks:
grammar-rule drills
short translation and reverse-translation tasks
morphology and affix experiments
verifier-driven RL experiments for low-resource language work
reproducible study of reward components for historical grammar sources
It is not intended as a standalone Dakota language authority, a substitute for community language expertise, or a production translation system.
Limitations And Ethical Notes
The source material is a historical grammar and dictionary published in 1890. It reflects the terminology, analysis, orthography, and colonial-era framing of its time. Outputs from this model can inherit mistakes, omissions, and outdated descriptions from the source extraction process and from the base model.
Dakota language work should be reviewed with appropriate community and linguistic expertise. This repository should be treated as an experimental technical artifact: useful for transparent research, not authoritative for teaching, cultural interpretation, or official translation.
Usage
The Tinker final sampler checkpoint is available now for direct Tinker sampling:
Riggs, Stephen Return. 1890. A Dakota-English Dictionary. Contributions to North American Ethnology, Volume VII. Washington: Government Printing Office.
Training and experiment tracking:
Thinking Machines Tinker for the RL training run
W&B for experiment tracking and reward-ledger audit trails
Dakota1890 repository artifacts for extraction, task generation, and verifier code
