README.md

metadata

license: cc-by-sa-4.0
language:
  - zh
tags:
  - chiboard
  - pinyin
  - ime
  - sft
  - trl
base_model: LiquidAI/LFM2.5-350M-Base
datasets:
  - johnbean393/chiboard-1-sft

chiboard-1-m0

Bootstrap 350M SFT model for Chiboard mistake mining.

Prompt format:

<|startoftext|>{committed_context}<|reserved_6|>{raw_pinyin}<|reserved_7|>{display}<|reserved_8|>{target}<|im_end|>

The model was trained with completion-only loss on {target}<|im_end|>.

Serve with exactly one <|startoftext|> token. Most runtimes add it automatically, so do not also embed it in the prompt string.

This is M0, a data-generation tool for typing-prefix replay; it is not the shipped final model.

Training

• Base model: LiquidAI/LFM2.5-350M-Base
• Dataset: johnbean393/chiboard-1-sft
• Training layout: mixed_packed
• Max packed length: 4096
• Effective batch: 10 x 6 = 60 packed rows per optimizer step
• Steps: 14746 / 14746
• Final eval loss: 0.17373667657375336
• Final eval mean token accuracy: 0.9519697650369391
• Train runtime seconds: 3.506e+04
• Packed LFM2 short-conv boundary isolation: seq_idx collator enabled

Chiboard evaluation

• Harness: greedy decoding, population-weighted stratified sample (seed 20260714)
• Model revision: 0777e99abb4914f42cfebee33626f7c36638c671
• Evaluated: 2026-07-14
• Predictions: johnbean393/chiboard-1-eval/chiboard-1-m0-20260714

Split	Rows (population)	Exact match	CER	EOS rate	Empty rate
plain / dev	100,000 (1,139,609)	50.39%	0.1447	99.44%	0.19%
revision / dev	40,000 (60,305)	36.14%	0.1337	99.94%	0.00%

Aggregate metrics are population-weighted estimates from the deterministic base sample; exact match preserves whitespace and punctuation.