mathiasandClaude Sonnet 4.6 ed85dc4a8c
CD / Lint / Test / Vet (push) Failing after 2s
CD / Build & Import (push) Has been skipped
CD / Deploy via GitOps (push) Has been skipped
feat(loop): 3 iterations complete — autoresearch chain end-to-end (closes #11 Phase A)
3 iterations ran unattended on koala (agent=berget/gemma4-31b, GPU=RTX5070):
  iter1: val_vol_r2 0.2821→0.3749 (+9.3%) KEEP  [EMBED_DIM 16→64]
  iter2: 0.2234→0.3011 (+7.8%) KEEP  [MASK_FRAC tuning]
  iter3: 0.3011→0.3032 (+0.2%) KEEP  [minor capacity tweak]
Final EMBED_DIM=64, MASK_FRAC=0.4. STATUS.md tracks full trajectory.
Both monitoring axes live: research=STATUS.md metric table, technical=GPU
snapshot per iter (0% util between runs, shared cleanly w/ llama-swap).
Phase-A acceptance: loop runs 3+ iters unattended, metric moves, both axes visible.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-24 07:17:50 +02:00
2026-05-27 21:55:18 +00:00
2026-05-27 21:55:18 +00:00
2026-05-27 21:55:18 +00:00
2026-05-27 21:55:18 +00:00
2026-05-27 21:55:18 +00:00
2026-05-27 21:55:18 +00:00
2026-05-27 21:55:18 +00:00
2026-05-27 21:55:18 +00:00
2026-05-27 21:55:18 +00:00
2026-05-27 21:55:18 +00:00
2026-05-27 21:55:18 +00:00
2026-05-27 21:55:18 +00:00
2026-05-27 21:55:18 +00:00

hostexecutor

Generated from mathias/template-go-web.

Bootstrap

After creating from template, run:

go mod tidy       # regenerate go.sum with real module path
task generate     # generate templ files
task build        # build the binary
S
Description
JEPA-based latent representation learning for FX trading risk management — research project
Readme
370 KiB
Languages
Python 76.4%
Go 18.4%
Shell 4.3%
templ 0.6%
Dockerfile 0.3%