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_giroux2022/K1000/lora64/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_giroux2022/K1000/lora64/train.log

@@ -0,0 +1,83 @@
+2026-10-03T01:07:34 split=hoL_giroux2022 K=1000 mode=lora trainable=5,184,896 balance=cohort immicro: train 95 rows / 347,061 cells, inner 12; ye2026_sepsis: train 73 rows / 529,816 cells, inner 9; imperial_eskd: train 146 rows / 462,172 cells, inner 11; liu2021: train 40 rows / 147,532 cells, inner 4
+2026-10-03T01:07:37 step 0 inner-val loss 0.11250 (pretrained) {'immicro': 0.10636159498244524, 'ye2026_sepsis': 0.12489082664251328, 'imperial_eskd': 0.10889218679883263, 'liu2021': 0.10984707903116941}
+2026-10-03T01:07:49 step 250 train 0.10608 inner-val 0.11153 best 0.11153@250 (12s) immicro=0.1055 ye2026_sepsis=0.1239 imperial_eskd=0.1078 liu2021=0.1089
+2026-10-03T01:08:01 step 500 train 0.10373 inner-val 0.10973 best 0.10973@500 (25s) immicro=0.1040 ye2026_sepsis=0.1220 imperial_eskd=0.1057 liu2021=0.1072
+2026-10-03T01:08:14 step 750 train 0.10381 inner-val 0.10783 best 0.10783@750 (37s) immicro=0.1026 ye2026_sepsis=0.1196 imperial_eskd=0.1035 liu2021=0.1056
+2026-10-03T01:08:27 step 1000 train 0.10334 inner-val 0.10629 best 0.10629@1000 (50s) immicro=0.1015 ye2026_sepsis=0.1175 imperial_eskd=0.1018 liu2021=0.1044
+2026-10-03T01:08:39 step 1250 train 0.10349 inner-val 0.10532 best 0.10532@1250 (63s) immicro=0.1007 ye2026_sepsis=0.1160 imperial_eskd=0.1009 liu2021=0.1036
+2026-10-03T01:08:52 step 1500 train 0.10313 inner-val 0.10472 best 0.10472@1500 (75s) immicro=0.1002 ye2026_sepsis=0.1152 imperial_eskd=0.1004 liu2021=0.1031
+2026-10-03T01:09:04 step 1750 train 0.10313 inner-val 0.10435 best 0.10435@1750 (87s) immicro=0.0998 ye2026_sepsis=0.1147 imperial_eskd=0.1001 liu2021=0.1028
+2026-10-03T01:09:17 step 2000 train 0.10297 inner-val 0.10410 best 0.10410@2000 (100s) immicro=0.0995 ye2026_sepsis=0.1144 imperial_eskd=0.0999 liu2021=0.1027
+2026-10-03T01:09:29 step 2250 train 0.10300 inner-val 0.10393 best 0.10393@2250 (112s) immicro=0.0992 ye2026_sepsis=0.1142 imperial_eskd=0.0997 liu2021=0.1025
+2026-10-03T01:09:41 step 2500 train 0.10314 inner-val 0.10381 best 0.10381@2500 (124s) immicro=0.0991 ye2026_sepsis=0.1141 imperial_eskd=0.0996 liu2021=0.1025
+2026-10-03T01:09:53 step 2750 train 0.10307 inner-val 0.10372 best 0.10372@2750 (137s) immicro=0.0990 ye2026_sepsis=0.1140 imperial_eskd=0.0995 liu2021=0.1024
+2026-10-03T01:10:06 step 3000 train 0.10306 inner-val 0.10365 best 0.10365@3000 (149s) immicro=0.0989 ye2026_sepsis=0.1139 imperial_eskd=0.0995 liu2021=0.1024
+2026-10-03T01:10:18 step 3250 train 0.10306 inner-val 0.10360 best 0.10360@3250 (161s) immicro=0.0988 ye2026_sepsis=0.1139 imperial_eskd=0.0994 liu2021=0.1023
+2026-10-03T01:10:30 step 3500 train 0.10305 inner-val 0.10356 best 0.10356@3500 (173s) immicro=0.0988 ye2026_sepsis=0.1138 imperial_eskd=0.0994 liu2021=0.1023
+2026-10-03T01:10:40 step 3750 train 0.10291 inner-val 0.10353 best 0.10353@3750 (184s) immicro=0.0987 ye2026_sepsis=0.1138 imperial_eskd=0.0993 liu2021=0.1023
+2026-10-03T01:10:51 step 4000 train 0.10273 inner-val 0.10351 best 0.10351@4000 (194s) immicro=0.0987 ye2026_sepsis=0.1138 imperial_eskd=0.0993 liu2021=0.1023
+2026-10-03T01:11:03 step 4250 train 0.10312 inner-val 0.10349 best 0.10349@4250 (207s) immicro=0.0986 ye2026_sepsis=0.1138 imperial_eskd=0.0993 liu2021=0.1022
+2026-10-03T01:11:16 step 4500 train 0.10296 inner-val 0.10348 best 0.10348@4500 (219s) immicro=0.0986 ye2026_sepsis=0.1138 imperial_eskd=0.0993 liu2021=0.1022
+2026-10-03T01:11:28 step 4750 train 0.10292 inner-val 0.10346 best 0.10346@4750 (232s) immicro=0.0986 ye2026_sepsis=0.1137 imperial_eskd=0.0993 liu2021=0.1022
+2026-10-03T01:11:41 step 5000 train 0.10314 inner-val 0.10344 best 0.10344@5000 (244s) immicro=0.0986 ye2026_sepsis=0.1137 imperial_eskd=0.0992 liu2021=0.1022
+2026-10-03T01:11:53 step 5250 train 0.10275 inner-val 0.10343 best 0.10343@5250 (256s) immicro=0.0986 ye2026_sepsis=0.1137 imperial_eskd=0.0992 liu2021=0.1022
+2026-10-03T01:12:06 step 5500 train 0.10284 inner-val 0.10342 best 0.10342@5500 (269s) immicro=0.0985 ye2026_sepsis=0.1137 imperial_eskd=0.0992 liu2021=0.1022
+2026-10-03T01:12:18 step 5750 train 0.10242 inner-val 0.10341 best 0.10341@5750 (281s) immicro=0.0985 ye2026_sepsis=0.1137 imperial_eskd=0.0992 liu2021=0.1022
+2026-10-03T01:12:30 step 6000 train 0.10262 inner-val 0.10340 best 0.10340@6000 (294s) immicro=0.0985 ye2026_sepsis=0.1137 imperial_eskd=0.0992 liu2021=0.1022
+2026-10-03T01:12:43 step 6250 train 0.10287 inner-val 0.10339 best 0.10339@6250 (306s) immicro=0.0985 ye2026_sepsis=0.1137 imperial_eskd=0.0992 liu2021=0.1022
+2026-10-03T01:12:55 step 6500 train 0.10292 inner-val 0.10338 best 0.10338@6500 (319s) immicro=0.0985 ye2026_sepsis=0.1137 imperial_eskd=0.0991 liu2021=0.1022
+2026-10-03T01:13:08 step 6750 train 0.10253 inner-val 0.10337 best 0.10337@6750 (331s) immicro=0.0985 ye2026_sepsis=0.1137 imperial_eskd=0.0991 liu2021=0.1022
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+2026-10-03T01:13:33 step 7250 train 0.10299 inner-val 0.10335 best 0.10335@7250 (356s) immicro=0.0984 ye2026_sepsis=0.1137 imperial_eskd=0.0991 liu2021=0.1021
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+2026-10-03T01:23:37 step 19500 train 0.10228 inner-val 0.10310 best 0.10310@19500 (960s) immicro=0.0981 ye2026_sepsis=0.1135 imperial_eskd=0.0989 liu2021=0.1019
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+2026-10-03T01:23:59 step 20000 train 0.10244 inner-val 0.10309 best 0.10309@20000 (982s) immicro=0.0981 ye2026_sepsis=0.1135 imperial_eskd=0.0989 liu2021=0.1019
+2026-10-03T01:24:02 saved /home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_crosscohort_20261002/runs/hoL_giroux2022/K1000/lora64/checkpoint_ft.pt (selected step 20000, inner-val 0.10309 vs pretrained 0.11250); sha 09e7beb77bc2

paper-releases/pbisc-diffusion/updates/20261003T103040Z-crosscohort-k1000-saturation/diffusion/dataset/server_1/model8/plans/paired_crosscohort_20261002/runs/hoL_giroux2022/K1000/lora64sat/RUN.json

@@ -0,0 +1,563 @@
+{
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+ "source_checkpoint_sha256": "8c7cd0e83e2bc19fe03dfcbc084919a1e2f61be8cc8bc12f4caf543dfda91633",
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+  {
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paper-releases/pbisc-diffusion/updates/20261003T103040Z-crosscohort-k1000-saturation/diffusion/dataset/server_1/model8/plans/paired_crosscohort_20261002/runs/hoL_giroux2022/K1000/lora64sat/history.json

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