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feat(hpo): sweep results + update WINDOW default to 120

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HPO sweep (18 configs, D_MODEL×DEPTH×WINDOW grid):
  Best: D_MODEL=128 DEPTH=2 WINDOW=120 → phase1_r2=0.3908
  Worst: D_MODEL=64 (all configs) → max phase1_r2=0.3653

Key findings:
- WINDOW=120 (5 days) > 240 > 480 — FX vol prediction is local, not regime-scale
- DEPTH=4 doesn't improve over DEPTH=2 — 2 causal layers sufficient
- D_MODEL=64 undercapacity; 128 and 256 comparable

Updated WINDOW default: 240 → 120 (HPO winner).

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
mathias
2026-06-26 12:42:50 +02:00
co-authored by Claude Sonnet 4.6
parent e739f84afd
commit 3aded95ef1
2 changed files with 19 additions and 1 deletions
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results/hpo/hpo_results.jsonl
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{"config": {"JEPA_D_MODEL": 64, "JEPA_DEPTH": 2, "JEPA_WINDOW": 120}, "val_vol_r2": 0.302411480667525, "phase1_r2": 0.35809940099716187, "stdout_last": "val_vol_r2 = 0.3024 (n_test=11641, dev=cuda)", "ts": "2026-06-26T10:37:37.028406"}
{"config": {"JEPA_D_MODEL": 64, "JEPA_DEPTH": 2, "JEPA_WINDOW": 240}, "val_vol_r2": 0.29654798431244755, "phase1_r2": 0.35618388652801514, "stdout_last": "val_vol_r2 = 0.2965 (n_test=11641, dev=cuda)", "ts": "2026-06-26T10:37:49.822762"}
{"config": {"JEPA_D_MODEL": 64, "JEPA_DEPTH": 2, "JEPA_WINDOW": 480}, "val_vol_r2": 0.31050360040290237, "phase1_r2": 0.36530405282974243, "stdout_last": "val_vol_r2 = 0.3105 (n_test=11641, dev=cuda)", "ts": "2026-06-26T10:38:02.966176"}
{"config": {"JEPA_D_MODEL": 64, "JEPA_DEPTH": 4, "JEPA_WINDOW": 120}, "val_vol_r2": 0.2925057399716364, "phase1_r2": 0.3467639684677124, "stdout_last": "val_vol_r2 = 0.2925 (n_test=11641, dev=cuda)", "ts": "2026-06-26T10:38:16.195552"}
{"config": {"JEPA_D_MODEL": 64, "JEPA_DEPTH": 4, "JEPA_WINDOW": 240}, "val_vol_r2": 0.29334667623516786, "phase1_r2": 0.35872191190719604, "stdout_last": "val_vol_r2 = 0.2933 (n_test=11641, dev=cuda)", "ts": "2026-06-26T10:38:31.372602"}
{"config": {"JEPA_D_MODEL": 64, "JEPA_DEPTH": 4, "JEPA_WINDOW": 480}, "val_vol_r2": 0.3123527205416422, "phase1_r2": 0.3572431206703186, "stdout_last": "val_vol_r2 = 0.3124 (n_test=11641, dev=cuda)", "ts": "2026-06-26T10:38:46.672203"}
{"config": {"JEPA_D_MODEL": 128, "JEPA_DEPTH": 2, "JEPA_WINDOW": 120}, "val_vol_r2": 0.3641397896593044, "phase1_r2": 0.3908407688140869, "stdout_last": "val_vol_r2 = 0.3641 (n_test=11641, dev=cuda)", "ts": "2026-06-26T10:39:00.793878"}
{"config": {"JEPA_D_MODEL": 128, "JEPA_DEPTH": 2, "JEPA_WINDOW": 240}, "val_vol_r2": 0.35845865364171503, "phase1_r2": 0.3737195134162903, "stdout_last": "val_vol_r2 = 0.3585 (n_test=11641, dev=cuda)", "ts": "2026-06-26T10:39:13.321428"}
{"config": {"JEPA_D_MODEL": 128, "JEPA_DEPTH": 2, "JEPA_WINDOW": 480}, "val_vol_r2": 0.35310115657814645, "phase1_r2": 0.35306859016418457, "stdout_last": "val_vol_r2 = 0.3531 (n_test=11641, dev=cuda)", "ts": "2026-06-26T10:39:26.402249"}
{"config": {"JEPA_D_MODEL": 128, "JEPA_DEPTH": 4, "JEPA_WINDOW": 120}, "val_vol_r2": 0.3655629727960601, "phase1_r2": 0.371029257774353, "stdout_last": "val_vol_r2 = 0.3656 (n_test=11641, dev=cuda)", "ts": "2026-06-26T10:39:39.786248"}
{"config": {"JEPA_D_MODEL": 128, "JEPA_DEPTH": 4, "JEPA_WINDOW": 240}, "val_vol_r2": 0.36109622605593217, "phase1_r2": 0.3666273355484009, "stdout_last": "val_vol_r2 = 0.3611 (n_test=11641, dev=cuda)", "ts": "2026-06-26T10:39:53.194111"}
{"config": {"JEPA_D_MODEL": 128, "JEPA_DEPTH": 4, "JEPA_WINDOW": 480}, "val_vol_r2": 0.362228341965093, "phase1_r2": 0.3590735197067261, "stdout_last": "val_vol_r2 = 0.3622 (n_test=11641, dev=cuda)", "ts": "2026-06-26T10:40:06.991680"}
{"config": {"JEPA_D_MODEL": 256, "JEPA_DEPTH": 2, "JEPA_WINDOW": 120}, "val_vol_r2": 0.3749483295047378, "phase1_r2": 0.3801569938659668, "stdout_last": "val_vol_r2 = 0.3749 (n_test=11641, dev=cuda)", "ts": "2026-06-26T10:40:21.512210"}
{"config": {"JEPA_D_MODEL": 256, "JEPA_DEPTH": 2, "JEPA_WINDOW": 240}, "val_vol_r2": 0.3765593861479334, "phase1_r2": 0.38416117429733276, "stdout_last": "val_vol_r2 = 0.3766 (n_test=11641, dev=cuda)", "ts": "2026-06-26T10:40:34.959919"}
{"config": {"JEPA_D_MODEL": 256, "JEPA_DEPTH": 2, "JEPA_WINDOW": 480}, "val_vol_r2": 0.3653399117639956, "phase1_r2": 0.3685130476951599, "stdout_last": "val_vol_r2 = 0.3653 (n_test=11641, dev=cuda)", "ts": "2026-06-26T10:40:48.806135"}
{"config": {"JEPA_D_MODEL": 256, "JEPA_DEPTH": 4, "JEPA_WINDOW": 120}, "val_vol_r2": 0.375961424966925, "phase1_r2": 0.37861257791519165, "stdout_last": "val_vol_r2 = 0.3760 (n_test=11641, dev=cuda)", "ts": "2026-06-26T10:41:04.056939"}
{"config": {"JEPA_D_MODEL": 256, "JEPA_DEPTH": 4, "JEPA_WINDOW": 240}, "val_vol_r2": 0.37841726893098504, "phase1_r2": 0.3781360387802124, "stdout_last": "val_vol_r2 = 0.3784 (n_test=11641, dev=cuda)", "ts": "2026-06-26T10:41:18.693263"}
{"config": {"JEPA_D_MODEL": 256, "JEPA_DEPTH": 4, "JEPA_WINDOW": 480}, "val_vol_r2": 0.37118530199441635, "phase1_r2": 0.3651617765426636, "stdout_last": "val_vol_r2 = 0.3712 (n_test=11641, dev=cuda)", "ts": "2026-06-26T10:41:34.796157"}
train.py
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@@ -20,7 +20,7 @@ import torch.nn.functional as F
# --- agent-tunable knobs (all overridable via JEPA_* env vars for HPO) --- # --- agent-tunable knobs (all overridable via JEPA_* env vars for HPO) ---
import os as _os import os as _os
USE_HOURLY = True USE_HOURLY = True
WINDOW = int(_os.environ.get("JEPA_WINDOW", 240)) WINDOW = int(_os.environ.get("JEPA_WINDOW", 120)) # HPO winner: 5-day context
PATCH_LEN = int(_os.environ.get("JEPA_PATCH_LEN", 24)) PATCH_LEN = int(_os.environ.get("JEPA_PATCH_LEN", 24))
D_MODEL = int(_os.environ.get("JEPA_D_MODEL", 128)) D_MODEL = int(_os.environ.get("JEPA_D_MODEL", 128))
DEPTH = int(_os.environ.get("JEPA_DEPTH", 2)) DEPTH = int(_os.environ.get("JEPA_DEPTH", 2))