# Dense Training Plan

## Setup

Use the same JSONL checkpoint bundle as MoE. Keep random seed, batch token
target, learning-rate schedule, and validation split aligned.

## Curriculum

1. Start with short and medium records.
2. Add long FIM examples.
3. Add continuation/code generation records.
4. Evaluate FIM and next-token loss separately.

## Stop Conditions

- Validation loss diverges twice after LR reduction.
- FIM metrics regress while train loss improves.
- Tokenizer round-trip or special-token audit fails.