Gahow Wang a78502e0f0 docs: run v3 — TinyStories, dim512, val 1.30 ...

Per-run design doc docs/runs/03-v3-tinystories-dim512.md (data 245.8M tok full
TinyStories ~0.53 epoch / arch dim512 16L core 67.13M vs total 118.59M, what
changed vs v2 / hyperparams 30000 steps batch 32 seq 256 lr 6e-4→6e-5 warmup
1500 + cosine clip 1.0 single-GPU batched via T10 / results train 10.91→1.40
best val 1.3027 ~26K tok/s / improvement vs v2 1.71→1.30 with side-by-side
samples). Notes v3 validated T10 batched forward at scale and avoided KI-5 by
staying single-GPU; v4 proposal + open levers (KI-2/3/4/5, data ladder).

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

2026-06-16 03:37:45 +08:00

..

runs

docs: run v3 — TinyStories, dim512, val 1.30

2026-06-16 03:37:45 +08:00

00-build-chain.md

docs: backfill T1 build-chain

2026-06-15 15:12:55 +08:00

01-tensor.md

docs: Phase T2 — tensor abstraction

2026-06-15 15:12:55 +08:00

02-gemm-autodiff.md

docs: Phase T3 — GEMM fwd/bwd + finite-diff

2026-06-15 15:27:03 +08:00

03-autograd-engine.md

docs: Phase T4 — autograd engine

2026-06-15 15:53:55 +08:00

04-tiny-transformer.md

docs: Phase T5 — tiny transformer

2026-06-15 16:09:30 +08:00

05-training-loop.md

docs: Phase T6 — training loop

2026-06-15 16:30:14 +08:00

06-performance.md

docs: Phase T7 — performance

2026-06-15 17:00:29 +08:00

07-distributed.md

docs: Phase T8 — distributed data parallel

2026-06-15 17:15:49 +08:00

08-export-xserv.md

docs: T9 verification results (xserv == xtrain, dash5)

2026-06-15 17:37:46 +08:00

09-batched-forward.md

docs: Phase T10 — batched forward

2026-06-16 00:44:50 +08:00

known-issues.md

perf: KI-1 fixed — GPU util 0-15%→37-54%, tok/s 1653→25627 (15.5x)

2026-06-16 00:44:43 +08:00