Archive 4 checkpoints (1-4)

paper-releases/pbisc-diffusion/updates/20261003T103040Z-crosscohort-k1000-saturation/diffusion/dataset/server_1/model8/plans/paired_crosscohort_20261002/runs/hoL_imperial_eskd/K1000/lora16sat/RUN.json

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+}

paper-releases/pbisc-diffusion/updates/20261003T103040Z-crosscohort-k1000-saturation/diffusion/dataset/server_1/model8/plans/paired_crosscohort_20261002/runs/hoL_imperial_eskd/K1000/lora16sat/history.json

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paper-releases/pbisc-diffusion/updates/20261003T103040Z-crosscohort-k1000-saturation/diffusion/dataset/server_1/model8/plans/paired_crosscohort_20261002/runs/hoL_imperial_eskd/K1000/lora16sat/milestones.json

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+  "checkpoint_sha256": "e24ed58dacdd3a104a2d1bde626e0f1130bf6b8243591fe507821a4a88262e28"
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paper-releases/pbisc-diffusion/updates/20261003T103040Z-crosscohort-k1000-saturation/diffusion/dataset/server_1/model8/plans/paired_crosscohort_20261002/runs/hoL_imperial_eskd/K1000/lora16sat/train.log

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+2026-10-03T04:17:29 step 3500 train 0.10379 inner-val 0.10514 best 0.10514@3500 (158s) immicro=0.0990 ye2026_sepsis=0.1140 liu2021=0.1024
+2026-10-03T04:17:41 step 3750 train 0.10358 inner-val 0.10511 best 0.10511@3750 (170s) immicro=0.0989 ye2026_sepsis=0.1140 liu2021=0.1024
+2026-10-03T04:17:52 step 4000 train 0.10343 inner-val 0.10509 best 0.10509@4000 (181s) immicro=0.0989 ye2026_sepsis=0.1140 liu2021=0.1024
+2026-10-03T04:18:04 step 4250 train 0.10373 inner-val 0.10507 best 0.10507@4250 (193s) immicro=0.0989 ye2026_sepsis=0.1140 liu2021=0.1024
+2026-10-03T04:18:16 step 4500 train 0.10373 inner-val 0.10506 best 0.10506@4500 (204s) immicro=0.0988 ye2026_sepsis=0.1140 liu2021=0.1024
+2026-10-03T04:18:27 step 4750 train 0.10352 inner-val 0.10505 best 0.10505@4750 (216s) immicro=0.0988 ye2026_sepsis=0.1139 liu2021=0.1024
+2026-10-03T04:18:39 step 5000 train 0.10377 inner-val 0.10503 best 0.10503@5000 (228s) immicro=0.0988 ye2026_sepsis=0.1139 liu2021=0.1024
+2026-10-03T04:18:51 step 5250 train 0.10338 inner-val 0.10503 best 0.10503@5250 (240s) immicro=0.0988 ye2026_sepsis=0.1139 liu2021=0.1024
+2026-10-03T04:19:02 step 5500 train 0.10352 inner-val 0.10502 best 0.10502@5500 (251s) immicro=0.0988 ye2026_sepsis=0.1139 liu2021=0.1024
+2026-10-03T04:19:14 step 5750 train 0.10307 inner-val 0.10501 best 0.10501@5750 (263s) immicro=0.0988 ye2026_sepsis=0.1139 liu2021=0.1024
+2026-10-03T04:19:25 step 6000 train 0.10340 inner-val 0.10500 best 0.10500@6000 (274s) immicro=0.0987 ye2026_sepsis=0.1139 liu2021=0.1023
+2026-10-03T04:19:37 step 6250 train 0.10368 inner-val 0.10499 best 0.10499@6250 (285s) immicro=0.0987 ye2026_sepsis=0.1139 liu2021=0.1023
+2026-10-03T04:19:47 step 6500 train 0.10364 inner-val 0.10498 best 0.10498@6500 (296s) immicro=0.0987 ye2026_sepsis=0.1139 liu2021=0.1023
+2026-10-03T04:19:58 step 6750 train 0.10333 inner-val 0.10497 best 0.10497@6750 (307s) immicro=0.0987 ye2026_sepsis=0.1139 liu2021=0.1023
+2026-10-03T04:20:09 step 7000 train 0.10337 inner-val 0.10496 best 0.10496@7000 (318s) immicro=0.0987 ye2026_sepsis=0.1139 liu2021=0.1023
+2026-10-03T04:20:20 step 7250 train 0.10355 inner-val 0.10496 best 0.10496@7250 (329s) immicro=0.0987 ye2026_sepsis=0.1139 liu2021=0.1023
+2026-10-03T04:20:30 step 7500 train 0.10347 inner-val 0.10495 best 0.10495@7500 (338s) immicro=0.0987 ye2026_sepsis=0.1139 liu2021=0.1023
+2026-10-03T04:20:39 step 7750 train 0.10332 inner-val 0.10495 best 0.10495@7750 (348s) immicro=0.0987 ye2026_sepsis=0.1139 liu2021=0.1023
+2026-10-03T04:20:49 step 8000 train 0.10304 inner-val 0.10495 best 0.10495@7750 (358s) immicro=0.0987 ye2026_sepsis=0.1139 liu2021=0.1023
+2026-10-03T04:20:59 step 8250 train 0.10352 inner-val 0.10494 best 0.10494@8250 (368s) immicro=0.0987 ye2026_sepsis=0.1139 liu2021=0.1023
+2026-10-03T04:21:10 step 8500 train 0.10311 inner-val 0.10494 best 0.10494@8500 (379s) immicro=0.0987 ye2026_sepsis=0.1139 liu2021=0.1023
+2026-10-03T04:21:21 step 8750 train 0.10354 inner-val 0.10493 best 0.10493@8750 (390s) immicro=0.0986 ye2026_sepsis=0.1139 liu2021=0.1023
+2026-10-03T04:21:33 step 9000 train 0.10332 inner-val 0.10493 best 0.10493@9000 (402s) immicro=0.0986 ye2026_sepsis=0.1139 liu2021=0.1023
+2026-10-03T04:21:45 step 9250 train 0.10334 inner-val 0.10493 best 0.10493@9000 (413s) immicro=0.0986 ye2026_sepsis=0.1139 liu2021=0.1023
+2026-10-03T04:21:56 step 9500 train 0.10344 inner-val 0.10493 best 0.10493@9000 (425s) immicro=0.0986 ye2026_sepsis=0.1139 liu2021=0.1023
+2026-10-03T04:22:08 step 9750 train 0.10322 inner-val 0.10492 best 0.10492@9750 (436s) immicro=0.0986 ye2026_sepsis=0.1139 liu2021=0.1023
+2026-10-03T04:22:19 step 10000 train 0.10319 inner-val 0.10492 best 0.10492@10000 (448s) immicro=0.0986 ye2026_sepsis=0.1139 liu2021=0.1023
+2026-10-03T04:22:31 step 10250 train 0.10333 inner-val 0.10491 best 0.10491@10250 (460s) immicro=0.0986 ye2026_sepsis=0.1139 liu2021=0.1022
+2026-10-03T04:22:42 step 10500 train 0.10343 inner-val 0.10491 best 0.10491@10500 (471s) immicro=0.0986 ye2026_sepsis=0.1139 liu2021=0.1022
+2026-10-03T04:22:54 step 10750 train 0.10338 inner-val 0.10491 best 0.10491@10500 (482s) immicro=0.0986 ye2026_sepsis=0.1139 liu2021=0.1023
+2026-10-03T04:23:05 step 11000 train 0.10348 inner-val 0.10490 best 0.10490@11000 (494s) immicro=0.0986 ye2026_sepsis=0.1138 liu2021=0.1022
+2026-10-03T04:23:17 step 11250 train 0.10317 inner-val 0.10490 best 0.10490@11250 (506s) immicro=0.0986 ye2026_sepsis=0.1138 liu2021=0.1022
+2026-10-03T04:23:28 step 11500 train 0.10341 inner-val 0.10490 best 0.10490@11250 (517s) immicro=0.0986 ye2026_sepsis=0.1139 liu2021=0.1022
+2026-10-03T04:23:40 step 11750 train 0.10327 inner-val 0.10490 best 0.10490@11750 (529s) immicro=0.0986 ye2026_sepsis=0.1139 liu2021=0.1022
+2026-10-03T04:23:52 step 12000 train 0.10301 inner-val 0.10490 best 0.10490@12000 (540s) immicro=0.0986 ye2026_sepsis=0.1139 liu2021=0.1022
+2026-10-03T04:24:03 step 12250 train 0.10314 inner-val 0.10489 best 0.10489@12250 (552s) immicro=0.0986 ye2026_sepsis=0.1139 liu2021=0.1022
+2026-10-03T04:24:15 step 12500 train 0.10340 inner-val 0.10489 best 0.10489@12500 (564s) immicro=0.0986 ye2026_sepsis=0.1139 liu2021=0.1022
+2026-10-03T04:24:26 step 12750 train 0.10329 inner-val 0.10489 best 0.10489@12500 (575s) immicro=0.0986 ye2026_sepsis=0.1139 liu2021=0.1022
+2026-10-03T04:24:38 step 13000 train 0.10348 inner-val 0.10489 best 0.10489@13000 (587s) immicro=0.0986 ye2026_sepsis=0.1139 liu2021=0.1022
+2026-10-03T04:24:50 step 13250 train 0.10346 inner-val 0.10488 best 0.10489@13000 (598s) immicro=0.0986 ye2026_sepsis=0.1139 liu2021=0.1022
+2026-10-03T04:25:01 step 13500 train 0.10334 inner-val 0.10489 best 0.10489@13000 (610s) immicro=0.0986 ye2026_sepsis=0.1139 liu2021=0.1022
+2026-10-03T04:25:13 step 13750 train 0.10334 inner-val 0.10488 best 0.10488@13750 (622s) immicro=0.0986 ye2026_sepsis=0.1139 liu2021=0.1022
+2026-10-03T04:25:24 step 14000 train 0.10331 inner-val 0.10488 best 0.10488@14000 (633s) immicro=0.0986 ye2026_sepsis=0.1139 liu2021=0.1022
+2026-10-03T04:25:36 step 14250 train 0.10305 inner-val 0.10487 best 0.10487@14250 (645s) immicro=0.0986 ye2026_sepsis=0.1139 liu2021=0.1022
+2026-10-03T04:25:47 step 14500 train 0.10347 inner-val 0.10487 best 0.10487@14500 (656s) immicro=0.0986 ye2026_sepsis=0.1139 liu2021=0.1022
+2026-10-03T04:25:59 step 14750 train 0.10343 inner-val 0.10487 best 0.10487@14500 (668s) immicro=0.0986 ye2026_sepsis=0.1139 liu2021=0.1022
+2026-10-03T04:26:11 step 15000 train 0.10357 inner-val 0.10487 best 0.10487@14500 (679s) immicro=0.0986 ye2026_sepsis=0.1139 liu2021=0.1022
+2026-10-03T04:26:22 step 15250 train 0.10318 inner-val 0.10487 best 0.10487@14500 (691s) immicro=0.0985 ye2026_sepsis=0.1139 liu2021=0.1022
+2026-10-03T04:26:34 step 15500 train 0.10350 inner-val 0.10487 best 0.10487@15500 (703s) immicro=0.0985 ye2026_sepsis=0.1139 liu2021=0.1022
+2026-10-03T04:26:46 step 15750 train 0.10316 inner-val 0.10486 best 0.10486@15750 (714s) immicro=0.0985 ye2026_sepsis=0.1139 liu2021=0.1022
+2026-10-03T04:26:57 step 16000 train 0.10313 inner-val 0.10486 best 0.10486@16000 (726s) immicro=0.0985 ye2026_sepsis=0.1138 liu2021=0.1022
+2026-10-03T04:27:09 step 16250 train 0.10331 inner-val 0.10486 best 0.10486@16000 (738s) immicro=0.0985 ye2026_sepsis=0.1138 liu2021=0.1022
+2026-10-03T04:27:20 step 16500 train 0.10337 inner-val 0.10486 best 0.10486@16500 (749s) immicro=0.0985 ye2026_sepsis=0.1138 liu2021=0.1022
+2026-10-03T04:27:32 step 16750 train 0.10301 inner-val 0.10486 best 0.10486@16750 (760s) immicro=0.0985 ye2026_sepsis=0.1139 liu2021=0.1022
+2026-10-03T04:27:43 step 17000 train 0.10337 inner-val 0.10486 best 0.10486@16750 (772s) immicro=0.0985 ye2026_sepsis=0.1139 liu2021=0.1022
+2026-10-03T04:27:55 step 17250 train 0.10348 inner-val 0.10486 best 0.10486@16750 (784s) immicro=0.0985 ye2026_sepsis=0.1139 liu2021=0.1022
+2026-10-03T04:28:06 step 17500 train 0.10323 inner-val 0.10485 best 0.10485@17500 (795s) immicro=0.0985 ye2026_sepsis=0.1139 liu2021=0.1022
+2026-10-03T04:28:18 step 17750 train 0.10298 inner-val 0.10485 best 0.10485@17500 (807s) immicro=0.0985 ye2026_sepsis=0.1139 liu2021=0.1022
+2026-10-03T04:28:30 step 18000 train 0.10367 inner-val 0.10485 best 0.10485@18000 (818s) immicro=0.0985 ye2026_sepsis=0.1139 liu2021=0.1022
+2026-10-03T04:28:41 step 18250 train 0.10301 inner-val 0.10485 best 0.10485@18250 (830s) immicro=0.0985 ye2026_sepsis=0.1139 liu2021=0.1022
+2026-10-03T04:28:52 step 18500 train 0.10341 inner-val 0.10485 best 0.10485@18500 (841s) immicro=0.0985 ye2026_sepsis=0.1139 liu2021=0.1022
+2026-10-03T04:29:04 step 18750 train 0.10308 inner-val 0.10485 best 0.10485@18750 (853s) immicro=0.0985 ye2026_sepsis=0.1139 liu2021=0.1022
+2026-10-03T04:29:14 step 19000 train 0.10316 inner-val 0.10484 best 0.10484@19000 (862s) immicro=0.0985 ye2026_sepsis=0.1139 liu2021=0.1022
+2026-10-03T04:29:24 step 19250 train 0.10317 inner-val 0.10484 best 0.10484@19250 (873s) immicro=0.0985 ye2026_sepsis=0.1138 liu2021=0.1022
+2026-10-03T04:29:34 step 19500 train 0.10318 inner-val 0.10483 best 0.10483@19500 (883s) immicro=0.0985 ye2026_sepsis=0.1138 liu2021=0.1022
+2026-10-03T04:29:44 step 19750 train 0.10321 inner-val 0.10483 best 0.10483@19750 (893s) immicro=0.0985 ye2026_sepsis=0.1138 liu2021=0.1022
+2026-10-03T04:29:55 step 20000 train 0.10326 inner-val 0.10483 best 0.10483@19750 (904s) immicro=0.0985 ye2026_sepsis=0.1138 liu2021=0.1022
+2026-10-03T04:29:57 block end 20000: best 0.10483@19750; block improvement 0.008867 (100.00 % of total 0.008867) -> continue
+2026-10-03T04:30:08 step 20250 train 0.10314 inner-val 0.10483 best 0.10483@19750 (917s) immicro=0.0985 ye2026_sepsis=0.1138 liu2021=0.1022
+2026-10-03T04:30:20 step 20500 train 0.10307 inner-val 0.10483 best 0.10483@19750 (929s) immicro=0.0985 ye2026_sepsis=0.1138 liu2021=0.1022
+2026-10-03T04:30:31 step 20750 train 0.10326 inner-val 0.10483 best 0.10483@20750 (940s) immicro=0.0985 ye2026_sepsis=0.1138 liu2021=0.1022
+2026-10-03T04:30:41 step 21000 train 0.10328 inner-val 0.10483 best 0.10483@21000 (949s) immicro=0.0985 ye2026_sepsis=0.1138 liu2021=0.1022
+2026-10-03T04:30:51 step 21250 train 0.10293 inner-val 0.10483 best 0.10483@21000 (960s) immicro=0.0985 ye2026_sepsis=0.1138 liu2021=0.1022
+2026-10-03T04:31:01 step 21500 train 0.10289 inner-val 0.10483 best 0.10483@21500 (970s) immicro=0.0985 ye2026_sepsis=0.1138 liu2021=0.1022
+2026-10-03T04:31:12 step 21750 train 0.10329 inner-val 0.10483 best 0.10483@21750 (980s) immicro=0.0985 ye2026_sepsis=0.1138 liu2021=0.1022
+2026-10-03T04:31:22 step 22000 train 0.10329 inner-val 0.10483 best 0.10483@21750 (991s) immicro=0.0985 ye2026_sepsis=0.1138 liu2021=0.1022
+2026-10-03T04:31:33 step 22250 train 0.10316 inner-val 0.10483 best 0.10483@21750 (1002s) immicro=0.0985 ye2026_sepsis=0.1138 liu2021=0.1022
+2026-10-03T04:31:44 step 22500 train 0.10313 inner-val 0.10483 best 0.10483@21750 (1013s) immicro=0.0985 ye2026_sepsis=0.1138 liu2021=0.1022
+2026-10-03T04:31:55 step 22750 train 0.10309 inner-val 0.10483 best 0.10483@21750 (1024s) immicro=0.0985 ye2026_sepsis=0.1138 liu2021=0.1022
+2026-10-03T04:32:07 step 23000 train 0.10347 inner-val 0.10483 best 0.10483@23000 (1036s) immicro=0.0985 ye2026_sepsis=0.1138 liu2021=0.1022
+2026-10-03T04:32:19 step 23250 train 0.10346 inner-val 0.10482 best 0.10482@23250 (1047s) immicro=0.0985 ye2026_sepsis=0.1138 liu2021=0.1022
+2026-10-03T04:32:30 step 23500 train 0.10326 inner-val 0.10482 best 0.10482@23500 (1059s) immicro=0.0985 ye2026_sepsis=0.1138 liu2021=0.1022
+2026-10-03T04:32:41 step 23750 train 0.10312 inner-val 0.10482 best 0.10482@23750 (1070s) immicro=0.0985 ye2026_sepsis=0.1138 liu2021=0.1022
+2026-10-03T04:32:51 step 24000 train 0.10338 inner-val 0.10482 best 0.10482@23750 (1080s) immicro=0.0985 ye2026_sepsis=0.1138 liu2021=0.1022
+2026-10-03T04:33:00 step 24250 train 0.10293 inner-val 0.10482 best 0.10482@23750 (1089s) immicro=0.0985 ye2026_sepsis=0.1138 liu2021=0.1022
+2026-10-03T04:33:10 step 24500 train 0.10298 inner-val 0.10482 best 0.10482@23750 (1099s) immicro=0.0985 ye2026_sepsis=0.1138 liu2021=0.1022
+2026-10-03T04:33:20 step 24750 train 0.10311 inner-val 0.10482 best 0.10482@24750 (1109s) immicro=0.0985 ye2026_sepsis=0.1138 liu2021=0.1022
+2026-10-03T04:33:30 step 25000 train 0.10295 inner-val 0.10481 best 0.10481@25000 (1119s) immicro=0.0985 ye2026_sepsis=0.1138 liu2021=0.1022
+2026-10-03T04:33:41 step 25250 train 0.10297 inner-val 0.10481 best 0.10481@25000 (1130s) immicro=0.0985 ye2026_sepsis=0.1138 liu2021=0.1022
+2026-10-03T04:33:53 step 25500 train 0.10313 inner-val 0.10481 best 0.10481@25000 (1141s) immicro=0.0985 ye2026_sepsis=0.1138 liu2021=0.1022
+2026-10-03T04:34:03 step 25750 train 0.10308 inner-val 0.10481 best 0.10481@25000 (1152s) immicro=0.0985 ye2026_sepsis=0.1138 liu2021=0.1022
+2026-10-03T04:34:14 step 26000 train 0.10318 inner-val 0.10481 best 0.10481@26000 (1162s) immicro=0.0985 ye2026_sepsis=0.1138 liu2021=0.1022
+2026-10-03T04:34:25 step 26250 train 0.10320 inner-val 0.10481 best 0.10481@26250 (1174s) immicro=0.0985 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:34:37 step 26500 train 0.10322 inner-val 0.10481 best 0.10481@26250 (1186s) immicro=0.0985 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:34:49 step 26750 train 0.10304 inner-val 0.10481 best 0.10481@26250 (1197s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:35:00 step 27000 train 0.10341 inner-val 0.10481 best 0.10481@26250 (1209s) immicro=0.0985 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:35:11 step 27250 train 0.10331 inner-val 0.10481 best 0.10481@26250 (1220s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:35:23 step 27500 train 0.10309 inner-val 0.10481 best 0.10481@26250 (1232s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:35:35 step 27750 train 0.10324 inner-val 0.10481 best 0.10481@26250 (1243s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1022
+2026-10-03T04:35:46 step 28000 train 0.10303 inner-val 0.10480 best 0.10480@28000 (1255s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:35:58 step 28250 train 0.10313 inner-val 0.10480 best 0.10480@28250 (1266s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1022
+2026-10-03T04:36:09 step 28500 train 0.10287 inner-val 0.10480 best 0.10480@28250 (1278s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1022
+2026-10-03T04:36:21 step 28750 train 0.10308 inner-val 0.10480 best 0.10480@28750 (1290s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:36:32 step 29000 train 0.10310 inner-val 0.10480 best 0.10480@29000 (1301s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:36:44 step 29250 train 0.10341 inner-val 0.10479 best 0.10479@29250 (1313s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:36:56 step 29500 train 0.10285 inner-val 0.10479 best 0.10479@29250 (1324s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:37:07 step 29750 train 0.10305 inner-val 0.10479 best 0.10479@29250 (1336s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:37:19 step 30000 train 0.10280 inner-val 0.10479 best 0.10479@30000 (1348s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:37:31 step 30250 train 0.10296 inner-val 0.10479 best 0.10479@30250 (1359s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:37:42 step 30500 train 0.10292 inner-val 0.10479 best 0.10479@30500 (1371s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:37:54 step 30750 train 0.10315 inner-val 0.10479 best 0.10479@30500 (1382s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:38:05 step 31000 train 0.10279 inner-val 0.10479 best 0.10479@31000 (1394s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:38:17 step 31250 train 0.10305 inner-val 0.10479 best 0.10479@31000 (1406s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:38:29 step 31500 train 0.10271 inner-val 0.10479 best 0.10479@31000 (1417s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:38:40 step 31750 train 0.10310 inner-val 0.10479 best 0.10479@31000 (1429s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:38:51 step 32000 train 0.10305 inner-val 0.10478 best 0.10478@32000 (1440s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:39:03 step 32250 train 0.10312 inner-val 0.10478 best 0.10478@32250 (1452s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:39:15 step 32500 train 0.10290 inner-val 0.10478 best 0.10478@32250 (1464s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:39:26 step 32750 train 0.10313 inner-val 0.10478 best 0.10478@32250 (1475s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:39:38 step 33000 train 0.10306 inner-val 0.10478 best 0.10478@33000 (1487s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:39:49 step 33250 train 0.10306 inner-val 0.10478 best 0.10478@33000 (1498s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:40:01 step 33500 train 0.10270 inner-val 0.10478 best 0.10478@33000 (1510s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:40:12 step 33750 train 0.10301 inner-val 0.10478 best 0.10478@33750 (1521s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:40:24 step 34000 train 0.10318 inner-val 0.10477 best 0.10477@34000 (1533s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:40:35 step 34250 train 0.10308 inner-val 0.10477 best 0.10477@34000 (1544s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:40:47 step 34500 train 0.10308 inner-val 0.10477 best 0.10477@34000 (1556s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:40:58 step 34750 train 0.10310 inner-val 0.10477 best 0.10477@34750 (1567s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:41:10 step 35000 train 0.10323 inner-val 0.10477 best 0.10477@35000 (1579s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:41:22 step 35250 train 0.10288 inner-val 0.10476 best 0.10477@35000 (1590s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:41:33 step 35500 train 0.10330 inner-val 0.10476 best 0.10476@35500 (1602s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:41:45 step 35750 train 0.10300 inner-val 0.10476 best 0.10476@35500 (1613s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:41:56 step 36000 train 0.10310 inner-val 0.10476 best 0.10476@35500 (1625s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:42:08 step 36250 train 0.10312 inner-val 0.10476 best 0.10476@35500 (1636s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:42:19 step 36500 train 0.10278 inner-val 0.10476 best 0.10476@36500 (1648s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:42:31 step 36750 train 0.10307 inner-val 0.10476 best 0.10476@36750 (1660s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:42:43 step 37000 train 0.10280 inner-val 0.10476 best 0.10476@36750 (1671s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:42:54 step 37250 train 0.10300 inner-val 0.10476 best 0.10476@36750 (1683s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:43:06 step 37500 train 0.10318 inner-val 0.10476 best 0.10476@36750 (1695s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:43:17 step 37750 train 0.10298 inner-val 0.10476 best 0.10476@36750 (1706s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:43:29 step 38000 train 0.10322 inner-val 0.10476 best 0.10476@36750 (1718s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:43:40 step 38250 train 0.10314 inner-val 0.10476 best 0.10476@38250 (1729s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:43:52 step 38500 train 0.10300 inner-val 0.10476 best 0.10476@38250 (1741s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:44:04 step 38750 train 0.10291 inner-val 0.10476 best 0.10476@38250 (1752s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:44:15 step 39000 train 0.10299 inner-val 0.10475 best 0.10475@39000 (1764s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:44:27 step 39250 train 0.10295 inner-val 0.10475 best 0.10475@39000 (1776s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:44:39 step 39500 train 0.10315 inner-val 0.10475 best 0.10475@39000 (1787s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:44:50 step 39750 train 0.10311 inner-val 0.10475 best 0.10475@39750 (1799s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:45:02 step 40000 train 0.10298 inner-val 0.10476 best 0.10475@39750 (1811s) immicro=0.0984 ye2026_sepsis=0.1138 liu2021=0.1021
+2026-10-03T04:45:03 block end 40000: best 0.10475@39750; block improvement 0.000082 (0.92 % of total 0.008949) -> saturated, stop
+2026-10-03T04:45:07 saved /home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_crosscohort_20261002/runs/hoL_imperial_eskd/K1000/lora16sat/checkpoint_ft.pt (selected step 39750, inner-val 0.10475 vs pretrained 0.11370); sha 98eaa829ed17