Archive 4 checkpoints (1-4)
Browse files- paper-releases/pbisc-diffusion/updates/20261003T103040Z-crosscohort-k1000-saturation/diffusion/dataset/server_1/model8/plans/paired_crosscohort_20261002/runs/hoL_ji2025_chili/K1000/lora64sat/RUN.json +594 -0
- paper-releases/pbisc-diffusion/updates/20261003T103040Z-crosscohort-k1000-saturation/diffusion/dataset/server_1/model8/plans/paired_crosscohort_20261002/runs/hoL_ji2025_chili/K1000/lora64sat/history.json +2497 -0
- paper-releases/pbisc-diffusion/updates/20261003T103040Z-crosscohort-k1000-saturation/diffusion/dataset/server_1/model8/plans/paired_crosscohort_20261002/runs/hoL_ji2025_chili/K1000/lora64sat/milestones.json +32 -0
- paper-releases/pbisc-diffusion/updates/20261003T103040Z-crosscohort-k1000-saturation/diffusion/dataset/server_1/model8/plans/paired_crosscohort_20261002/runs/hoL_ji2025_chili/K1000/lora64sat/train.log +213 -0
paper-releases/pbisc-diffusion/updates/20261003T103040Z-crosscohort-k1000-saturation/diffusion/dataset/server_1/model8/plans/paired_crosscohort_20261002/runs/hoL_ji2025_chili/K1000/lora64sat/RUN.json
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| 1 |
+
{
|
| 2 |
+
"schema": "pbisc_sdd.ft_crosscohort.run.v1",
|
| 3 |
+
"source_checkpoint": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/runs/f01_6k_1x_seed20260627/checkpoint_epoch_016.pt",
|
| 4 |
+
"source_checkpoint_sha256": "8c7cd0e83e2bc19fe03dfcbc084919a1e2f61be8cc8bc12f4caf543dfda91633",
|
| 5 |
+
"split": "hoL_ji2025_chili",
|
| 6 |
+
"split_file": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_crosscohort_20261002/splits/hoL_ji2025_chili.json",
|
| 7 |
+
"split_sha256": "1efe2e8a540137380f689ea29d64f99189981b8fcc636824c7ae858db989f787",
|
| 8 |
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"held_out": "ji2025_chili",
|
| 9 |
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"recipe_k": 1000,
|
| 10 |
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"balance": "cohort",
|
| 11 |
+
"mode": "lora",
|
| 12 |
+
"trainable": {
|
| 13 |
+
"mode": "lora",
|
| 14 |
+
"lora_layers": [
|
| 15 |
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|
| 16 |
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|
| 17 |
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|
| 18 |
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|
| 19 |
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|
| 20 |
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"down_blocks.0.input_projection",
|
| 21 |
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"down_blocks.0.context_projection.1",
|
| 22 |
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"down_blocks.1.input_projection",
|
| 23 |
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"down_blocks.1.context_projection.1",
|
| 24 |
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"down_blocks.2.input_projection",
|
| 25 |
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|
| 26 |
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|
| 27 |
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|
| 28 |
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|
| 29 |
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|
| 30 |
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|
| 31 |
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|
| 32 |
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|
| 33 |
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"up_blocks.2.context_projection.1",
|
| 34 |
+
"output_trunk.0",
|
| 35 |
+
"value_head",
|
| 36 |
+
"active_head"
|
| 37 |
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],
|
| 38 |
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|
| 39 |
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"lora_alpha": 64.0,
|
| 40 |
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"n_trainable": 5184896,
|
| 41 |
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|
| 42 |
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|
| 43 |
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},
|
| 44 |
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|
| 45 |
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"warmup": 200,
|
| 46 |
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"batch_size": 256,
|
| 47 |
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|
| 48 |
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|
| 49 |
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|
| 50 |
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"eval_every": 250,
|
| 51 |
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"patience": 8,
|
| 52 |
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|
| 53 |
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"selected_inner_val_loss": 0.10236734301416259,
|
| 54 |
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"pretrained_inner_val_loss": 0.11206555419432168,
|
| 55 |
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"cohorts": [
|
| 56 |
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{
|
| 57 |
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"cohort": "immicro",
|
| 58 |
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"condition_npz": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_crosscohort_20261002/data/immicro/conditions_raw_K1000.npz",
|
| 59 |
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"condition_npz_sha256": "2be5717d19e86bdf38e4838d4bd2886a211ba78bfbfe749c458305a3e0ac2dcc",
|
| 60 |
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| 61 |
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| 66 |
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| 69 |
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| 70 |
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| 71 |
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| 73 |
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| 80 |
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| 81 |
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paper-releases/pbisc-diffusion/updates/20261003T103040Z-crosscohort-k1000-saturation/diffusion/dataset/server_1/model8/plans/paired_crosscohort_20261002/runs/hoL_ji2025_chili/K1000/lora64sat/history.json
ADDED
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@@ -0,0 +1,2497 @@
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|
| 2496 |
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|
| 2497 |
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|
paper-releases/pbisc-diffusion/updates/20261003T103040Z-crosscohort-k1000-saturation/diffusion/dataset/server_1/model8/plans/paired_crosscohort_20261002/runs/hoL_ji2025_chili/K1000/lora64sat/milestones.json
ADDED
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[
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| 10 |
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"checkpoint_sha256": "2d11ba981678b0ea87ee36dbd21def73537f2e6a2b5869b9472c2513cfffcb15"
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{
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|
| 20 |
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"checkpoint_sha256": "9d57b12a01993cb5cb592dd34672c89de1aa662ee69e45354f790cbff342cbf6"
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| 21 |
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| 22 |
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| 23 |
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"checkpoint_sha256": "c6d0e7a0ec782d365f3eb32a958f76dc905e94bf720b2b86f0ab8f663a4bbe1f"
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| 32 |
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]
|
paper-releases/pbisc-diffusion/updates/20261003T103040Z-crosscohort-k1000-saturation/diffusion/dataset/server_1/model8/plans/paired_crosscohort_20261002/runs/hoL_ji2025_chili/K1000/lora64sat/train.log
ADDED
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| 1 |
+
2026-10-03T06:08:32 split=hoL_ji2025_chili 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; giroux2022: train 24 rows / 254,250 cells, inner 0; liu2021: train 40 rows / 147,532 cells, inner 4
|
| 2 |
+
2026-10-03T06:08:34 step 0 inner-val loss 0.11207 (pretrained) {'immicro': 0.10636159498244524, 'ye2026_sepsis': 0.12489082664251328, 'imperial_eskd': 0.10889218679883263, 'liu2021': 0.1081176083534956}
|
| 3 |
+
2026-10-03T06:08:45 step 250 train 0.10514 inner-val 0.11108 best 0.11108@250 (11s) immicro=0.1055 ye2026_sepsis=0.1240 imperial_eskd=0.1078 liu2021=0.1071
|
| 4 |
+
2026-10-03T06:08:56 step 500 train 0.10291 inner-val 0.10926 best 0.10926@500 (22s) immicro=0.1040 ye2026_sepsis=0.1220 imperial_eskd=0.1057 liu2021=0.1054
|
| 5 |
+
2026-10-03T06:09:07 step 750 train 0.10261 inner-val 0.10736 best 0.10736@750 (33s) immicro=0.1026 ye2026_sepsis=0.1196 imperial_eskd=0.1035 liu2021=0.1037
|
| 6 |
+
2026-10-03T06:09:18 step 1000 train 0.10272 inner-val 0.10587 best 0.10587@1000 (44s) immicro=0.1016 ye2026_sepsis=0.1175 imperial_eskd=0.1019 liu2021=0.1025
|
| 7 |
+
2026-10-03T06:09:29 step 1250 train 0.10265 inner-val 0.10493 best 0.10493@1250 (54s) immicro=0.1008 ye2026_sepsis=0.1162 imperial_eskd=0.1009 liu2021=0.1017
|
| 8 |
+
2026-10-03T06:09:41 step 1500 train 0.10225 inner-val 0.10434 best 0.10434@1500 (67s) immicro=0.1002 ye2026_sepsis=0.1154 imperial_eskd=0.1004 liu2021=0.1013
|
| 9 |
+
2026-10-03T06:09:54 step 1750 train 0.10229 inner-val 0.10396 best 0.10396@1750 (79s) immicro=0.0998 ye2026_sepsis=0.1149 imperial_eskd=0.1001 liu2021=0.1011
|
| 10 |
+
2026-10-03T06:10:06 step 2000 train 0.10193 inner-val 0.10371 best 0.10371@2000 (92s) immicro=0.0995 ye2026_sepsis=0.1146 imperial_eskd=0.0998 liu2021=0.1009
|
| 11 |
+
2026-10-03T06:10:18 step 2250 train 0.10215 inner-val 0.10355 best 0.10355@2250 (104s) immicro=0.0993 ye2026_sepsis=0.1144 imperial_eskd=0.0997 liu2021=0.1008
|
| 12 |
+
2026-10-03T06:10:30 step 2500 train 0.10213 inner-val 0.10342 best 0.10342@2500 (116s) immicro=0.0991 ye2026_sepsis=0.1142 imperial_eskd=0.0996 liu2021=0.1008
|
| 13 |
+
2026-10-03T06:10:42 step 2750 train 0.10214 inner-val 0.10334 best 0.10334@2750 (128s) immicro=0.0990 ye2026_sepsis=0.1141 imperial_eskd=0.0995 liu2021=0.1007
|
| 14 |
+
2026-10-03T06:10:55 step 3000 train 0.10225 inner-val 0.10328 best 0.10328@3000 (140s) immicro=0.0989 ye2026_sepsis=0.1140 imperial_eskd=0.0995 liu2021=0.1007
|
| 15 |
+
2026-10-03T06:11:07 step 3250 train 0.10233 inner-val 0.10324 best 0.10324@3250 (152s) immicro=0.0989 ye2026_sepsis=0.1140 imperial_eskd=0.0994 liu2021=0.1006
|
| 16 |
+
2026-10-03T06:11:19 step 3500 train 0.10205 inner-val 0.10320 best 0.10320@3500 (165s) immicro=0.0988 ye2026_sepsis=0.1139 imperial_eskd=0.0994 liu2021=0.1006
|
| 17 |
+
2026-10-03T06:11:31 step 3750 train 0.10202 inner-val 0.10317 best 0.10317@3750 (177s) immicro=0.0988 ye2026_sepsis=0.1139 imperial_eskd=0.0994 liu2021=0.1006
|
| 18 |
+
2026-10-03T06:11:44 step 4000 train 0.10210 inner-val 0.10315 best 0.10315@4000 (189s) immicro=0.0988 ye2026_sepsis=0.1139 imperial_eskd=0.0994 liu2021=0.1006
|
| 19 |
+
2026-10-03T06:11:56 step 4250 train 0.10229 inner-val 0.10313 best 0.10313@4250 (201s) immicro=0.0987 ye2026_sepsis=0.1139 imperial_eskd=0.0993 liu2021=0.1006
|
| 20 |
+
2026-10-03T06:12:08 step 4500 train 0.10168 inner-val 0.10311 best 0.10311@4500 (214s) immicro=0.0987 ye2026_sepsis=0.1139 imperial_eskd=0.0993 liu2021=0.1006
|
| 21 |
+
2026-10-03T06:12:20 step 4750 train 0.10184 inner-val 0.10310 best 0.10310@4750 (226s) immicro=0.0987 ye2026_sepsis=0.1139 imperial_eskd=0.0993 liu2021=0.1006
|
| 22 |
+
2026-10-03T06:12:31 step 5000 train 0.10204 inner-val 0.10308 best 0.10308@5000 (237s) immicro=0.0987 ye2026_sepsis=0.1138 imperial_eskd=0.0993 liu2021=0.1005
|
| 23 |
+
2026-10-03T06:12:42 step 5250 train 0.10191 inner-val 0.10307 best 0.10307@5250 (248s) immicro=0.0986 ye2026_sepsis=0.1138 imperial_eskd=0.0993 liu2021=0.1005
|
| 24 |
+
2026-10-03T06:12:53 step 5500 train 0.10172 inner-val 0.10305 best 0.10305@5500 (259s) immicro=0.0986 ye2026_sepsis=0.1138 imperial_eskd=0.0992 liu2021=0.1005
|
| 25 |
+
2026-10-03T06:13:04 step 5750 train 0.10181 inner-val 0.10304 best 0.10304@5750 (270s) immicro=0.0986 ye2026_sepsis=0.1138 imperial_eskd=0.0992 liu2021=0.1005
|
| 26 |
+
2026-10-03T06:13:17 step 6000 train 0.10203 inner-val 0.10303 best 0.10303@6000 (282s) immicro=0.0986 ye2026_sepsis=0.1138 imperial_eskd=0.0992 liu2021=0.1005
|
| 27 |
+
2026-10-03T06:13:29 step 6250 train 0.10207 inner-val 0.10302 best 0.10302@6250 (295s) immicro=0.0986 ye2026_sepsis=0.1138 imperial_eskd=0.0992 liu2021=0.1005
|
| 28 |
+
2026-10-03T06:13:42 step 6500 train 0.10179 inner-val 0.10302 best 0.10302@6500 (308s) immicro=0.0986 ye2026_sepsis=0.1138 imperial_eskd=0.0992 liu2021=0.1005
|
| 29 |
+
2026-10-03T06:13:54 step 6750 train 0.10176 inner-val 0.10301 best 0.10301@6750 (319s) immicro=0.0986 ye2026_sepsis=0.1138 imperial_eskd=0.0992 liu2021=0.1005
|
| 30 |
+
2026-10-03T06:14:05 step 7000 train 0.10189 inner-val 0.10300 best 0.10300@7000 (330s) immicro=0.0985 ye2026_sepsis=0.1138 imperial_eskd=0.0992 liu2021=0.1005
|
| 31 |
+
2026-10-03T06:14:15 step 7250 train 0.10191 inner-val 0.10299 best 0.10299@7250 (341s) immicro=0.0985 ye2026_sepsis=0.1138 imperial_eskd=0.0992 liu2021=0.1005
|
| 32 |
+
2026-10-03T06:14:26 step 7500 train 0.10184 inner-val 0.10298 best 0.10298@7500 (352s) immicro=0.0985 ye2026_sepsis=0.1138 imperial_eskd=0.0992 liu2021=0.1005
|
| 33 |
+
2026-10-03T06:14:37 step 7750 train 0.10182 inner-val 0.10298 best 0.10298@7750 (363s) immicro=0.0985 ye2026_sepsis=0.1138 imperial_eskd=0.0991 liu2021=0.1005
|
| 34 |
+
2026-10-03T06:14:48 step 8000 train 0.10151 inner-val 0.10297 best 0.10297@8000 (374s) immicro=0.0985 ye2026_sepsis=0.1138 imperial_eskd=0.0991 liu2021=0.1004
|
| 35 |
+
2026-10-03T06:15:01 step 8250 train 0.10181 inner-val 0.10296 best 0.10296@8250 (386s) immicro=0.0985 ye2026_sepsis=0.1138 imperial_eskd=0.0991 liu2021=0.1004
|
| 36 |
+
2026-10-03T06:15:13 step 8500 train 0.10145 inner-val 0.10296 best 0.10296@8500 (399s) immicro=0.0985 ye2026_sepsis=0.1138 imperial_eskd=0.0991 liu2021=0.1004
|
| 37 |
+
2026-10-03T06:15:26 step 8750 train 0.10200 inner-val 0.10295 best 0.10295@8750 (411s) immicro=0.0985 ye2026_sepsis=0.1138 imperial_eskd=0.0991 liu2021=0.1004
|
| 38 |
+
2026-10-03T06:15:38 step 9000 train 0.10191 inner-val 0.10294 best 0.10294@9000 (424s) immicro=0.0985 ye2026_sepsis=0.1138 imperial_eskd=0.0991 liu2021=0.1004
|
| 39 |
+
2026-10-03T06:15:51 step 9250 train 0.10184 inner-val 0.10293 best 0.10293@9250 (436s) immicro=0.0984 ye2026_sepsis=0.1138 imperial_eskd=0.0991 liu2021=0.1004
|
| 40 |
+
2026-10-03T06:16:03 step 9500 train 0.10146 inner-val 0.10293 best 0.10293@9500 (449s) immicro=0.0984 ye2026_sepsis=0.1138 imperial_eskd=0.0991 liu2021=0.1004
|
| 41 |
+
2026-10-03T06:16:15 step 9750 train 0.10142 inner-val 0.10292 best 0.10292@9750 (461s) immicro=0.0984 ye2026_sepsis=0.1138 imperial_eskd=0.0991 liu2021=0.1004
|
| 42 |
+
2026-10-03T06:16:28 step 10000 train 0.10154 inner-val 0.10292 best 0.10292@10000 (474s) immicro=0.0984 ye2026_sepsis=0.1138 imperial_eskd=0.0991 liu2021=0.1004
|
| 43 |
+
2026-10-03T06:16:40 step 10250 train 0.10164 inner-val 0.10291 best 0.10291@10250 (486s) immicro=0.0984 ye2026_sepsis=0.1138 imperial_eskd=0.0991 liu2021=0.1004
|
| 44 |
+
2026-10-03T06:16:53 step 10500 train 0.10175 inner-val 0.10291 best 0.10291@10500 (498s) immicro=0.0984 ye2026_sepsis=0.1138 imperial_eskd=0.0991 liu2021=0.1004
|
| 45 |
+
2026-10-03T06:17:05 step 10750 train 0.10154 inner-val 0.10290 best 0.10290@10750 (511s) immicro=0.0984 ye2026_sepsis=0.1138 imperial_eskd=0.0991 liu2021=0.1004
|
| 46 |
+
2026-10-03T06:17:18 step 11000 train 0.10174 inner-val 0.10289 best 0.10289@11000 (524s) immicro=0.0984 ye2026_sepsis=0.1138 imperial_eskd=0.0991 liu2021=0.1004
|
| 47 |
+
2026-10-03T06:17:31 step 11250 train 0.10133 inner-val 0.10289 best 0.10289@11250 (536s) immicro=0.0984 ye2026_sepsis=0.1138 imperial_eskd=0.0991 liu2021=0.1004
|
| 48 |
+
2026-10-03T06:17:43 step 11500 train 0.10165 inner-val 0.10288 best 0.10288@11500 (549s) immicro=0.0984 ye2026_sepsis=0.1138 imperial_eskd=0.0991 liu2021=0.1003
|
| 49 |
+
2026-10-03T06:17:56 step 11750 train 0.10167 inner-val 0.10287 best 0.10287@11750 (561s) immicro=0.0984 ye2026_sepsis=0.1137 imperial_eskd=0.0990 liu2021=0.1003
|
| 50 |
+
2026-10-03T06:18:08 step 12000 train 0.10122 inner-val 0.10287 best 0.10287@12000 (574s) immicro=0.0984 ye2026_sepsis=0.1137 imperial_eskd=0.0990 liu2021=0.1003
|
| 51 |
+
2026-10-03T06:18:21 step 12250 train 0.10167 inner-val 0.10287 best 0.10287@12250 (586s) immicro=0.0984 ye2026_sepsis=0.1137 imperial_eskd=0.0990 liu2021=0.1003
|
| 52 |
+
2026-10-03T06:18:34 step 12500 train 0.10155 inner-val 0.10287 best 0.10287@12500 (599s) immicro=0.0984 ye2026_sepsis=0.1137 imperial_eskd=0.0990 liu2021=0.1003
|
| 53 |
+
2026-10-03T06:18:46 step 12750 train 0.10163 inner-val 0.10286 best 0.10286@12750 (612s) immicro=0.0983 ye2026_sepsis=0.1137 imperial_eskd=0.0990 liu2021=0.1003
|
| 54 |
+
2026-10-03T06:18:59 step 13000 train 0.10181 inner-val 0.10286 best 0.10286@13000 (624s) immicro=0.0983 ye2026_sepsis=0.1137 imperial_eskd=0.0990 liu2021=0.1003
|
| 55 |
+
2026-10-03T06:19:11 step 13250 train 0.10168 inner-val 0.10285 best 0.10285@13250 (637s) immicro=0.0983 ye2026_sepsis=0.1137 imperial_eskd=0.0990 liu2021=0.1003
|
| 56 |
+
2026-10-03T06:19:24 step 13500 train 0.10150 inner-val 0.10284 best 0.10284@13500 (650s) immicro=0.0983 ye2026_sepsis=0.1137 imperial_eskd=0.0990 liu2021=0.1003
|
| 57 |
+
2026-10-03T06:19:36 step 13750 train 0.10177 inner-val 0.10284 best 0.10284@13750 (662s) immicro=0.0983 ye2026_sepsis=0.1137 imperial_eskd=0.0990 liu2021=0.1003
|
| 58 |
+
2026-10-03T06:19:49 step 14000 train 0.10133 inner-val 0.10283 best 0.10283@14000 (674s) immicro=0.0983 ye2026_sepsis=0.1137 imperial_eskd=0.0990 liu2021=0.1003
|
| 59 |
+
2026-10-03T06:20:01 step 14250 train 0.10135 inner-val 0.10283 best 0.10283@14250 (687s) immicro=0.0983 ye2026_sepsis=0.1137 imperial_eskd=0.0990 liu2021=0.1003
|
| 60 |
+
2026-10-03T06:20:14 step 14500 train 0.10138 inner-val 0.10282 best 0.10282@14500 (700s) immicro=0.0983 ye2026_sepsis=0.1137 imperial_eskd=0.0990 liu2021=0.1003
|
| 61 |
+
2026-10-03T06:20:26 step 14750 train 0.10158 inner-val 0.10282 best 0.10282@14750 (712s) immicro=0.0983 ye2026_sepsis=0.1137 imperial_eskd=0.0990 liu2021=0.1003
|
| 62 |
+
2026-10-03T06:20:39 step 15000 train 0.10165 inner-val 0.10281 best 0.10281@15000 (725s) immicro=0.0983 ye2026_sepsis=0.1137 imperial_eskd=0.0990 liu2021=0.1003
|
| 63 |
+
2026-10-03T06:20:52 step 15250 train 0.10137 inner-val 0.10281 best 0.10281@15250 (738s) immicro=0.0983 ye2026_sepsis=0.1137 imperial_eskd=0.0990 liu2021=0.1003
|
| 64 |
+
2026-10-03T06:21:04 step 15500 train 0.10189 inner-val 0.10280 best 0.10280@15500 (750s) immicro=0.0983 ye2026_sepsis=0.1137 imperial_eskd=0.0990 liu2021=0.1002
|
| 65 |
+
2026-10-03T06:21:17 step 15750 train 0.10140 inner-val 0.10279 best 0.10279@15750 (763s) immicro=0.0983 ye2026_sepsis=0.1137 imperial_eskd=0.0990 liu2021=0.1002
|
| 66 |
+
2026-10-03T06:21:30 step 16000 train 0.10129 inner-val 0.10279 best 0.10279@16000 (775s) immicro=0.0982 ye2026_sepsis=0.1137 imperial_eskd=0.0990 liu2021=0.1002
|
| 67 |
+
2026-10-03T06:21:42 step 16250 train 0.10157 inner-val 0.10278 best 0.10278@16250 (788s) immicro=0.0982 ye2026_sepsis=0.1137 imperial_eskd=0.0990 liu2021=0.1002
|
| 68 |
+
2026-10-03T06:21:55 step 16500 train 0.10150 inner-val 0.10278 best 0.10278@16500 (800s) immicro=0.0982 ye2026_sepsis=0.1137 imperial_eskd=0.0990 liu2021=0.1002
|
| 69 |
+
2026-10-03T06:22:07 step 16750 train 0.10148 inner-val 0.10277 best 0.10277@16750 (813s) immicro=0.0982 ye2026_sepsis=0.1137 imperial_eskd=0.0990 liu2021=0.1002
|
| 70 |
+
2026-10-03T06:22:20 step 17000 train 0.10163 inner-val 0.10277 best 0.10277@17000 (825s) immicro=0.0982 ye2026_sepsis=0.1137 imperial_eskd=0.0990 liu2021=0.1002
|
| 71 |
+
2026-10-03T06:22:32 step 17250 train 0.10168 inner-val 0.10276 best 0.10276@17250 (838s) immicro=0.0982 ye2026_sepsis=0.1136 imperial_eskd=0.0990 liu2021=0.1002
|
| 72 |
+
2026-10-03T06:22:45 step 17500 train 0.10140 inner-val 0.10276 best 0.10276@17500 (851s) immicro=0.0982 ye2026_sepsis=0.1136 imperial_eskd=0.0990 liu2021=0.1002
|
| 73 |
+
2026-10-03T06:22:58 step 17750 train 0.10119 inner-val 0.10275 best 0.10275@17750 (863s) immicro=0.0982 ye2026_sepsis=0.1136 imperial_eskd=0.0990 liu2021=0.1002
|
| 74 |
+
2026-10-03T06:23:10 step 18000 train 0.10172 inner-val 0.10275 best 0.10275@18000 (876s) immicro=0.0982 ye2026_sepsis=0.1137 imperial_eskd=0.0990 liu2021=0.1002
|
| 75 |
+
2026-10-03T06:23:23 step 18250 train 0.10125 inner-val 0.10275 best 0.10275@18250 (888s) immicro=0.0982 ye2026_sepsis=0.1137 imperial_eskd=0.0990 liu2021=0.1002
|
| 76 |
+
2026-10-03T06:23:35 step 18500 train 0.10116 inner-val 0.10275 best 0.10275@18250 (901s) immicro=0.0982 ye2026_sepsis=0.1137 imperial_eskd=0.0990 liu2021=0.1002
|
| 77 |
+
2026-10-03T06:23:48 step 18750 train 0.10147 inner-val 0.10275 best 0.10275@18750 (913s) immicro=0.0982 ye2026_sepsis=0.1137 imperial_eskd=0.0989 liu2021=0.1002
|
| 78 |
+
2026-10-03T06:24:00 step 19000 train 0.10153 inner-val 0.10274 best 0.10274@19000 (926s) immicro=0.0982 ye2026_sepsis=0.1137 imperial_eskd=0.0989 liu2021=0.1002
|
| 79 |
+
2026-10-03T06:24:11 step 19250 train 0.10149 inner-val 0.10274 best 0.10274@19250 (936s) immicro=0.0982 ye2026_sepsis=0.1137 imperial_eskd=0.0989 liu2021=0.1002
|
| 80 |
+
2026-10-03T06:24:22 step 19500 train 0.10127 inner-val 0.10273 best 0.10273@19500 (947s) immicro=0.0982 ye2026_sepsis=0.1136 imperial_eskd=0.0989 liu2021=0.1002
|
| 81 |
+
2026-10-03T06:24:33 step 19750 train 0.10124 inner-val 0.10272 best 0.10272@19750 (958s) immicro=0.0982 ye2026_sepsis=0.1136 imperial_eskd=0.0989 liu2021=0.1002
|
| 82 |
+
2026-10-03T06:24:44 step 20000 train 0.10140 inner-val 0.10272 best 0.10272@20000 (969s) immicro=0.0982 ye2026_sepsis=0.1136 imperial_eskd=0.0989 liu2021=0.1002
|
| 83 |
+
2026-10-03T06:24:45 block end 20000: best 0.10272@20000; block improvement 0.009347 (100.00 % of total 0.009347) -> continue
|
| 84 |
+
2026-10-03T06:24:57 step 20250 train 0.10133 inner-val 0.10272 best 0.10272@20000 (983s) immicro=0.0982 ye2026_sepsis=0.1136 imperial_eskd=0.0989 liu2021=0.1002
|
| 85 |
+
2026-10-03T06:25:10 step 20500 train 0.10111 inner-val 0.10271 best 0.10271@20500 (995s) immicro=0.0982 ye2026_sepsis=0.1136 imperial_eskd=0.0989 liu2021=0.1001
|
| 86 |
+
2026-10-03T06:25:21 step 20750 train 0.10142 inner-val 0.10271 best 0.10271@20750 (1007s) immicro=0.0981 ye2026_sepsis=0.1136 imperial_eskd=0.0989 liu2021=0.1002
|
| 87 |
+
2026-10-03T06:25:32 step 21000 train 0.10142 inner-val 0.10270 best 0.10270@21000 (1018s) immicro=0.0981 ye2026_sepsis=0.1136 imperial_eskd=0.0989 liu2021=0.1001
|
| 88 |
+
2026-10-03T06:25:43 step 21250 train 0.10128 inner-val 0.10270 best 0.10270@21250 (1029s) immicro=0.0981 ye2026_sepsis=0.1136 imperial_eskd=0.0989 liu2021=0.1001
|
| 89 |
+
2026-10-03T06:25:54 step 21500 train 0.10115 inner-val 0.10270 best 0.10270@21500 (1040s) immicro=0.0981 ye2026_sepsis=0.1136 imperial_eskd=0.0989 liu2021=0.1001
|
| 90 |
+
2026-10-03T06:26:07 step 21750 train 0.10131 inner-val 0.10270 best 0.10270@21500 (1053s) immicro=0.0981 ye2026_sepsis=0.1136 imperial_eskd=0.0989 liu2021=0.1001
|
| 91 |
+
2026-10-03T06:26:19 step 22000 train 0.10156 inner-val 0.10270 best 0.10270@22000 (1065s) immicro=0.0981 ye2026_sepsis=0.1136 imperial_eskd=0.0989 liu2021=0.1001
|
| 92 |
+
2026-10-03T06:26:32 step 22250 train 0.10129 inner-val 0.10269 best 0.10269@22250 (1077s) immicro=0.0981 ye2026_sepsis=0.1136 imperial_eskd=0.0989 liu2021=0.1001
|
| 93 |
+
2026-10-03T06:26:43 step 22500 train 0.10144 inner-val 0.10269 best 0.10269@22500 (1088s) immicro=0.0981 ye2026_sepsis=0.1136 imperial_eskd=0.0989 liu2021=0.1001
|
| 94 |
+
2026-10-03T06:26:54 step 22750 train 0.10128 inner-val 0.10268 best 0.10268@22750 (1099s) immicro=0.0981 ye2026_sepsis=0.1136 imperial_eskd=0.0989 liu2021=0.1001
|
| 95 |
+
2026-10-03T06:27:05 step 23000 train 0.10169 inner-val 0.10268 best 0.10268@23000 (1110s) immicro=0.0981 ye2026_sepsis=0.1136 imperial_eskd=0.0989 liu2021=0.1001
|
| 96 |
+
2026-10-03T06:27:15 step 23250 train 0.10147 inner-val 0.10268 best 0.10268@23250 (1121s) immicro=0.0981 ye2026_sepsis=0.1136 imperial_eskd=0.0989 liu2021=0.1001
|
| 97 |
+
2026-10-03T06:27:26 step 23500 train 0.10123 inner-val 0.10268 best 0.10268@23500 (1132s) immicro=0.0981 ye2026_sepsis=0.1136 imperial_eskd=0.0989 liu2021=0.1001
|
| 98 |
+
2026-10-03T06:27:37 step 23750 train 0.10125 inner-val 0.10267 best 0.10267@23750 (1143s) immicro=0.0981 ye2026_sepsis=0.1136 imperial_eskd=0.0989 liu2021=0.1001
|
| 99 |
+
2026-10-03T06:27:49 step 24000 train 0.10146 inner-val 0.10266 best 0.10266@24000 (1154s) immicro=0.0981 ye2026_sepsis=0.1136 imperial_eskd=0.0989 liu2021=0.1001
|
| 100 |
+
2026-10-03T06:28:00 step 24250 train 0.10113 inner-val 0.10266 best 0.10266@24250 (1165s) immicro=0.0981 ye2026_sepsis=0.1136 imperial_eskd=0.0989 liu2021=0.1001
|
| 101 |
+
2026-10-03T06:28:10 step 24500 train 0.10101 inner-val 0.10266 best 0.10266@24500 (1176s) immicro=0.0981 ye2026_sepsis=0.1135 imperial_eskd=0.0989 liu2021=0.1001
|
| 102 |
+
2026-10-03T06:28:21 step 24750 train 0.10103 inner-val 0.10265 best 0.10265@24750 (1187s) immicro=0.0981 ye2026_sepsis=0.1135 imperial_eskd=0.0989 liu2021=0.1001
|
| 103 |
+
2026-10-03T06:28:33 step 25000 train 0.10127 inner-val 0.10265 best 0.10265@25000 (1199s) immicro=0.0981 ye2026_sepsis=0.1135 imperial_eskd=0.0989 liu2021=0.1001
|
| 104 |
+
2026-10-03T06:28:46 step 25250 train 0.10120 inner-val 0.10264 best 0.10264@25250 (1211s) immicro=0.0980 ye2026_sepsis=0.1135 imperial_eskd=0.0989 liu2021=0.1001
|
| 105 |
+
2026-10-03T06:28:57 step 25500 train 0.10132 inner-val 0.10264 best 0.10264@25500 (1223s) immicro=0.0980 ye2026_sepsis=0.1135 imperial_eskd=0.0989 liu2021=0.1001
|
| 106 |
+
2026-10-03T06:29:08 step 25750 train 0.10127 inner-val 0.10263 best 0.10263@25750 (1234s) immicro=0.0980 ye2026_sepsis=0.1135 imperial_eskd=0.0989 liu2021=0.1001
|
| 107 |
+
2026-10-03T06:29:19 step 26000 train 0.10132 inner-val 0.10263 best 0.10263@26000 (1244s) immicro=0.0980 ye2026_sepsis=0.1135 imperial_eskd=0.0989 liu2021=0.1001
|
| 108 |
+
2026-10-03T06:29:30 step 26250 train 0.10142 inner-val 0.10263 best 0.10263@26250 (1256s) immicro=0.0980 ye2026_sepsis=0.1135 imperial_eskd=0.0989 liu2021=0.1001
|
| 109 |
+
2026-10-03T06:29:41 step 26500 train 0.10142 inner-val 0.10262 best 0.10262@26500 (1266s) immicro=0.0980 ye2026_sepsis=0.1135 imperial_eskd=0.0989 liu2021=0.1001
|
| 110 |
+
2026-10-03T06:29:52 step 26750 train 0.10111 inner-val 0.10262 best 0.10262@26750 (1278s) immicro=0.0980 ye2026_sepsis=0.1135 imperial_eskd=0.0989 liu2021=0.1001
|
| 111 |
+
2026-10-03T06:30:05 step 27000 train 0.10152 inner-val 0.10262 best 0.10262@27000 (1290s) immicro=0.0980 ye2026_sepsis=0.1135 imperial_eskd=0.0989 liu2021=0.1001
|
| 112 |
+
2026-10-03T06:30:17 step 27250 train 0.10146 inner-val 0.10261 best 0.10261@27250 (1302s) immicro=0.0980 ye2026_sepsis=0.1135 imperial_eskd=0.0988 liu2021=0.1001
|
| 113 |
+
2026-10-03T06:30:29 step 27500 train 0.10123 inner-val 0.10261 best 0.10261@27500 (1315s) immicro=0.0980 ye2026_sepsis=0.1135 imperial_eskd=0.0988 liu2021=0.1001
|
| 114 |
+
2026-10-03T06:30:41 step 27750 train 0.10119 inner-val 0.10261 best 0.10261@27750 (1327s) immicro=0.0980 ye2026_sepsis=0.1135 imperial_eskd=0.0988 liu2021=0.1001
|
| 115 |
+
2026-10-03T06:30:52 step 28000 train 0.10136 inner-val 0.10260 best 0.10260@28000 (1338s) immicro=0.0980 ye2026_sepsis=0.1135 imperial_eskd=0.0988 liu2021=0.1001
|
| 116 |
+
2026-10-03T06:31:03 step 28250 train 0.10115 inner-val 0.10260 best 0.10260@28250 (1349s) immicro=0.0980 ye2026_sepsis=0.1135 imperial_eskd=0.0988 liu2021=0.1001
|
| 117 |
+
2026-10-03T06:31:15 step 28500 train 0.10122 inner-val 0.10260 best 0.10260@28250 (1361s) immicro=0.0980 ye2026_sepsis=0.1135 imperial_eskd=0.0988 liu2021=0.1001
|
| 118 |
+
2026-10-03T06:31:28 step 28750 train 0.10112 inner-val 0.10259 best 0.10259@28750 (1373s) immicro=0.0980 ye2026_sepsis=0.1135 imperial_eskd=0.0988 liu2021=0.1001
|
| 119 |
+
2026-10-03T06:31:40 step 29000 train 0.10101 inner-val 0.10259 best 0.10259@28750 (1386s) immicro=0.0980 ye2026_sepsis=0.1135 imperial_eskd=0.0988 liu2021=0.1000
|
| 120 |
+
2026-10-03T06:31:51 step 29250 train 0.10126 inner-val 0.10259 best 0.10259@29250 (1396s) immicro=0.0980 ye2026_sepsis=0.1135 imperial_eskd=0.0988 liu2021=0.1000
|
| 121 |
+
2026-10-03T06:32:03 step 29500 train 0.10081 inner-val 0.10259 best 0.10259@29250 (1408s) immicro=0.0980 ye2026_sepsis=0.1135 imperial_eskd=0.0988 liu2021=0.1000
|
| 122 |
+
2026-10-03T06:32:15 step 29750 train 0.10115 inner-val 0.10258 best 0.10258@29750 (1421s) immicro=0.0980 ye2026_sepsis=0.1135 imperial_eskd=0.0988 liu2021=0.1000
|
| 123 |
+
2026-10-03T06:32:28 step 30000 train 0.10127 inner-val 0.10258 best 0.10258@30000 (1433s) immicro=0.0980 ye2026_sepsis=0.1135 imperial_eskd=0.0988 liu2021=0.1000
|
| 124 |
+
2026-10-03T06:32:40 step 30250 train 0.10098 inner-val 0.10258 best 0.10258@30250 (1446s) immicro=0.0980 ye2026_sepsis=0.1135 imperial_eskd=0.0988 liu2021=0.1000
|
| 125 |
+
2026-10-03T06:32:53 step 30500 train 0.10100 inner-val 0.10258 best 0.10258@30500 (1458s) immicro=0.0980 ye2026_sepsis=0.1135 imperial_eskd=0.0988 liu2021=0.1000
|
| 126 |
+
2026-10-03T06:33:05 step 30750 train 0.10111 inner-val 0.10257 best 0.10257@30750 (1471s) immicro=0.0980 ye2026_sepsis=0.1135 imperial_eskd=0.0988 liu2021=0.1000
|
| 127 |
+
2026-10-03T06:33:18 step 31000 train 0.10107 inner-val 0.10256 best 0.10256@31000 (1483s) immicro=0.0980 ye2026_sepsis=0.1135 imperial_eskd=0.0988 liu2021=0.1000
|
| 128 |
+
2026-10-03T06:33:30 step 31250 train 0.10143 inner-val 0.10255 best 0.10255@31250 (1496s) immicro=0.0979 ye2026_sepsis=0.1134 imperial_eskd=0.0988 liu2021=0.1000
|
| 129 |
+
2026-10-03T06:33:41 step 31500 train 0.10140 inner-val 0.10255 best 0.10255@31250 (1506s) immicro=0.0979 ye2026_sepsis=0.1135 imperial_eskd=0.0988 liu2021=0.1000
|
| 130 |
+
2026-10-03T06:33:53 step 31750 train 0.10144 inner-val 0.10255 best 0.10255@31750 (1518s) immicro=0.0979 ye2026_sepsis=0.1134 imperial_eskd=0.0988 liu2021=0.1000
|
| 131 |
+
2026-10-03T06:34:05 step 32000 train 0.10094 inner-val 0.10255 best 0.10255@32000 (1530s) immicro=0.0979 ye2026_sepsis=0.1134 imperial_eskd=0.0988 liu2021=0.1000
|
| 132 |
+
2026-10-03T06:34:16 step 32250 train 0.10140 inner-val 0.10254 best 0.10254@32250 (1542s) immicro=0.0979 ye2026_sepsis=0.1134 imperial_eskd=0.0988 liu2021=0.1000
|
| 133 |
+
2026-10-03T06:34:29 step 32500 train 0.10090 inner-val 0.10253 best 0.10253@32500 (1555s) immicro=0.0979 ye2026_sepsis=0.1134 imperial_eskd=0.0988 liu2021=0.1000
|
| 134 |
+
2026-10-03T06:34:41 step 32750 train 0.10129 inner-val 0.10253 best 0.10253@32750 (1567s) immicro=0.0979 ye2026_sepsis=0.1134 imperial_eskd=0.0988 liu2021=0.1000
|
| 135 |
+
2026-10-03T06:34:54 step 33000 train 0.10110 inner-val 0.10253 best 0.10253@32750 (1579s) immicro=0.0979 ye2026_sepsis=0.1134 imperial_eskd=0.0988 liu2021=0.1000
|
| 136 |
+
2026-10-03T06:35:06 step 33250 train 0.10123 inner-val 0.10252 best 0.10252@33250 (1592s) immicro=0.0979 ye2026_sepsis=0.1134 imperial_eskd=0.0988 liu2021=0.1000
|
| 137 |
+
2026-10-03T06:35:19 step 33500 train 0.10110 inner-val 0.10252 best 0.10252@33500 (1604s) immicro=0.0979 ye2026_sepsis=0.1134 imperial_eskd=0.0988 liu2021=0.1000
|
| 138 |
+
2026-10-03T06:35:31 step 33750 train 0.10094 inner-val 0.10252 best 0.10252@33750 (1617s) immicro=0.0979 ye2026_sepsis=0.1134 imperial_eskd=0.0988 liu2021=0.1000
|
| 139 |
+
2026-10-03T06:35:42 step 34000 train 0.10131 inner-val 0.10252 best 0.10252@33750 (1628s) immicro=0.0979 ye2026_sepsis=0.1134 imperial_eskd=0.0988 liu2021=0.1000
|
| 140 |
+
2026-10-03T06:35:53 step 34250 train 0.10141 inner-val 0.10252 best 0.10252@33750 (1638s) immicro=0.0979 ye2026_sepsis=0.1134 imperial_eskd=0.0988 liu2021=0.1000
|
| 141 |
+
2026-10-03T06:36:04 step 34500 train 0.10124 inner-val 0.10251 best 0.10251@34500 (1649s) immicro=0.0979 ye2026_sepsis=0.1134 imperial_eskd=0.0988 liu2021=0.1000
|
| 142 |
+
2026-10-03T06:36:14 step 34750 train 0.10110 inner-val 0.10251 best 0.10251@34750 (1660s) immicro=0.0979 ye2026_sepsis=0.1134 imperial_eskd=0.0988 liu2021=0.1000
|
| 143 |
+
2026-10-03T06:36:25 step 35000 train 0.10119 inner-val 0.10251 best 0.10251@34750 (1671s) immicro=0.0979 ye2026_sepsis=0.1134 imperial_eskd=0.0988 liu2021=0.0999
|
| 144 |
+
2026-10-03T06:36:36 step 35250 train 0.10113 inner-val 0.10250 best 0.10250@35250 (1682s) immicro=0.0979 ye2026_sepsis=0.1134 imperial_eskd=0.0988 liu2021=0.0999
|
| 145 |
+
2026-10-03T06:36:47 step 35500 train 0.10127 inner-val 0.10250 best 0.10250@35500 (1693s) immicro=0.0979 ye2026_sepsis=0.1134 imperial_eskd=0.0988 liu2021=0.0999
|
| 146 |
+
2026-10-03T06:36:58 step 35750 train 0.10112 inner-val 0.10250 best 0.10250@35750 (1704s) immicro=0.0979 ye2026_sepsis=0.1134 imperial_eskd=0.0988 liu2021=0.0999
|
| 147 |
+
2026-10-03T06:37:09 step 36000 train 0.10118 inner-val 0.10250 best 0.10250@35750 (1714s) immicro=0.0979 ye2026_sepsis=0.1134 imperial_eskd=0.0988 liu2021=0.0999
|
| 148 |
+
2026-10-03T06:37:19 step 36250 train 0.10122 inner-val 0.10250 best 0.10250@35750 (1725s) immicro=0.0979 ye2026_sepsis=0.1134 imperial_eskd=0.0988 liu2021=0.0999
|
| 149 |
+
2026-10-03T06:37:30 step 36500 train 0.10111 inner-val 0.10249 best 0.10249@36500 (1736s) immicro=0.0979 ye2026_sepsis=0.1134 imperial_eskd=0.0988 liu2021=0.0999
|
| 150 |
+
2026-10-03T06:37:41 step 36750 train 0.10114 inner-val 0.10249 best 0.10249@36750 (1747s) immicro=0.0979 ye2026_sepsis=0.1134 imperial_eskd=0.0988 liu2021=0.0999
|
| 151 |
+
2026-10-03T06:37:52 step 37000 train 0.10085 inner-val 0.10249 best 0.10249@37000 (1758s) immicro=0.0979 ye2026_sepsis=0.1134 imperial_eskd=0.0988 liu2021=0.0999
|
| 152 |
+
2026-10-03T06:38:03 step 37250 train 0.10083 inner-val 0.10248 best 0.10248@37250 (1769s) immicro=0.0979 ye2026_sepsis=0.1134 imperial_eskd=0.0988 liu2021=0.0999
|
| 153 |
+
2026-10-03T06:38:14 step 37500 train 0.10094 inner-val 0.10248 best 0.10248@37500 (1779s) immicro=0.0979 ye2026_sepsis=0.1134 imperial_eskd=0.0988 liu2021=0.0999
|
| 154 |
+
2026-10-03T06:38:25 step 37750 train 0.10094 inner-val 0.10247 best 0.10247@37750 (1790s) immicro=0.0979 ye2026_sepsis=0.1134 imperial_eskd=0.0988 liu2021=0.0999
|
| 155 |
+
2026-10-03T06:38:35 step 38000 train 0.10081 inner-val 0.10247 best 0.10247@38000 (1801s) immicro=0.0979 ye2026_sepsis=0.1134 imperial_eskd=0.0988 liu2021=0.0999
|
| 156 |
+
2026-10-03T06:38:46 step 38250 train 0.10123 inner-val 0.10247 best 0.10247@38000 (1812s) immicro=0.0978 ye2026_sepsis=0.1134 imperial_eskd=0.0988 liu2021=0.0999
|
| 157 |
+
2026-10-03T06:38:57 step 38500 train 0.10148 inner-val 0.10247 best 0.10247@38000 (1823s) immicro=0.0978 ye2026_sepsis=0.1134 imperial_eskd=0.0988 liu2021=0.0999
|
| 158 |
+
2026-10-03T06:39:08 step 38750 train 0.10119 inner-val 0.10247 best 0.10247@38000 (1834s) immicro=0.0978 ye2026_sepsis=0.1134 imperial_eskd=0.0988 liu2021=0.0999
|
| 159 |
+
2026-10-03T06:39:19 step 39000 train 0.10090 inner-val 0.10247 best 0.10247@39000 (1844s) immicro=0.0978 ye2026_sepsis=0.1134 imperial_eskd=0.0988 liu2021=0.0999
|
| 160 |
+
2026-10-03T06:39:30 step 39250 train 0.10097 inner-val 0.10247 best 0.10247@39250 (1856s) immicro=0.0978 ye2026_sepsis=0.1134 imperial_eskd=0.0988 liu2021=0.0999
|
| 161 |
+
2026-10-03T06:39:41 step 39500 train 0.10122 inner-val 0.10247 best 0.10247@39500 (1866s) immicro=0.0978 ye2026_sepsis=0.1134 imperial_eskd=0.0988 liu2021=0.0999
|
| 162 |
+
2026-10-03T06:39:52 step 39750 train 0.10110 inner-val 0.10247 best 0.10247@39500 (1877s) immicro=0.0978 ye2026_sepsis=0.1134 imperial_eskd=0.0988 liu2021=0.0999
|
| 163 |
+
2026-10-03T06:40:02 step 40000 train 0.10120 inner-val 0.10247 best 0.10247@39500 (1888s) immicro=0.0978 ye2026_sepsis=0.1134 imperial_eskd=0.0988 liu2021=0.0999
|
| 164 |
+
2026-10-03T06:40:04 block end 40000: best 0.10247@39500; block improvement 0.000253 (2.64 % of total 0.009600) -> continue
|
| 165 |
+
2026-10-03T06:40:15 step 40250 train 0.10096 inner-val 0.10247 best 0.10247@39500 (1901s) immicro=0.0978 ye2026_sepsis=0.1134 imperial_eskd=0.0988 liu2021=0.0999
|
| 166 |
+
2026-10-03T06:40:26 step 40500 train 0.10107 inner-val 0.10246 best 0.10246@40500 (1912s) immicro=0.0978 ye2026_sepsis=0.1134 imperial_eskd=0.0988 liu2021=0.0999
|
| 167 |
+
2026-10-03T06:40:37 step 40750 train 0.10074 inner-val 0.10246 best 0.10246@40750 (1923s) immicro=0.0978 ye2026_sepsis=0.1134 imperial_eskd=0.0988 liu2021=0.0999
|
| 168 |
+
2026-10-03T06:40:48 step 41000 train 0.10099 inner-val 0.10245 best 0.10245@41000 (1934s) immicro=0.0978 ye2026_sepsis=0.1133 imperial_eskd=0.0987 liu2021=0.0999
|
| 169 |
+
2026-10-03T06:41:00 step 41250 train 0.10114 inner-val 0.10245 best 0.10245@41000 (1946s) immicro=0.0978 ye2026_sepsis=0.1133 imperial_eskd=0.0987 liu2021=0.0999
|
| 170 |
+
2026-10-03T06:41:13 step 41500 train 0.10121 inner-val 0.10245 best 0.10245@41000 (1958s) immicro=0.0978 ye2026_sepsis=0.1134 imperial_eskd=0.0987 liu2021=0.0999
|
| 171 |
+
2026-10-03T06:41:25 step 41750 train 0.10094 inner-val 0.10245 best 0.10245@41000 (1970s) immicro=0.0978 ye2026_sepsis=0.1134 imperial_eskd=0.0987 liu2021=0.0999
|
| 172 |
+
2026-10-03T06:41:37 step 42000 train 0.10083 inner-val 0.10245 best 0.10245@42000 (1983s) immicro=0.0978 ye2026_sepsis=0.1133 imperial_eskd=0.0987 liu2021=0.0999
|
| 173 |
+
2026-10-03T06:41:49 step 42250 train 0.10097 inner-val 0.10244 best 0.10244@42250 (1995s) immicro=0.0978 ye2026_sepsis=0.1133 imperial_eskd=0.0987 liu2021=0.0999
|
| 174 |
+
2026-10-03T06:42:02 step 42500 train 0.10122 inner-val 0.10244 best 0.10244@42500 (2007s) immicro=0.0978 ye2026_sepsis=0.1133 imperial_eskd=0.0987 liu2021=0.0999
|
| 175 |
+
2026-10-03T06:42:14 step 42750 train 0.10087 inner-val 0.10244 best 0.10244@42750 (2020s) immicro=0.0978 ye2026_sepsis=0.1133 imperial_eskd=0.0987 liu2021=0.0999
|
| 176 |
+
2026-10-03T06:42:27 step 43000 train 0.10083 inner-val 0.10244 best 0.10244@43000 (2032s) immicro=0.0978 ye2026_sepsis=0.1133 imperial_eskd=0.0987 liu2021=0.0999
|
| 177 |
+
2026-10-03T06:42:39 step 43250 train 0.10122 inner-val 0.10243 best 0.10243@43250 (2044s) immicro=0.0978 ye2026_sepsis=0.1133 imperial_eskd=0.0987 liu2021=0.0999
|
| 178 |
+
2026-10-03T06:42:51 step 43500 train 0.10091 inner-val 0.10244 best 0.10243@43250 (2057s) immicro=0.0978 ye2026_sepsis=0.1133 imperial_eskd=0.0987 liu2021=0.0999
|
| 179 |
+
2026-10-03T06:43:03 step 43750 train 0.10122 inner-val 0.10243 best 0.10243@43750 (2069s) immicro=0.0978 ye2026_sepsis=0.1133 imperial_eskd=0.0987 liu2021=0.0999
|
| 180 |
+
2026-10-03T06:43:16 step 44000 train 0.10092 inner-val 0.10243 best 0.10243@44000 (2081s) immicro=0.0978 ye2026_sepsis=0.1133 imperial_eskd=0.0987 liu2021=0.0999
|
| 181 |
+
2026-10-03T06:43:28 step 44250 train 0.10117 inner-val 0.10242 best 0.10242@44250 (2094s) immicro=0.0978 ye2026_sepsis=0.1133 imperial_eskd=0.0987 liu2021=0.0999
|
| 182 |
+
2026-10-03T06:43:40 step 44500 train 0.10121 inner-val 0.10242 best 0.10242@44500 (2106s) immicro=0.0978 ye2026_sepsis=0.1133 imperial_eskd=0.0987 liu2021=0.0999
|
| 183 |
+
2026-10-03T06:43:53 step 44750 train 0.10105 inner-val 0.10242 best 0.10242@44500 (2118s) immicro=0.0978 ye2026_sepsis=0.1133 imperial_eskd=0.0987 liu2021=0.0999
|
| 184 |
+
2026-10-03T06:44:05 step 45000 train 0.10066 inner-val 0.10242 best 0.10242@44500 (2130s) immicro=0.0978 ye2026_sepsis=0.1133 imperial_eskd=0.0987 liu2021=0.0999
|
| 185 |
+
2026-10-03T06:44:17 step 45250 train 0.10118 inner-val 0.10242 best 0.10242@45250 (2143s) immicro=0.0978 ye2026_sepsis=0.1133 imperial_eskd=0.0987 liu2021=0.0999
|
| 186 |
+
2026-10-03T06:44:30 step 45500 train 0.10135 inner-val 0.10242 best 0.10242@45250 (2156s) immicro=0.0978 ye2026_sepsis=0.1133 imperial_eskd=0.0987 liu2021=0.0999
|
| 187 |
+
2026-10-03T06:44:42 step 45750 train 0.10116 inner-val 0.10241 best 0.10241@45750 (2168s) immicro=0.0978 ye2026_sepsis=0.1133 imperial_eskd=0.0987 liu2021=0.0999
|
| 188 |
+
2026-10-03T06:44:55 step 46000 train 0.10134 inner-val 0.10241 best 0.10241@45750 (2181s) immicro=0.0978 ye2026_sepsis=0.1133 imperial_eskd=0.0987 liu2021=0.0999
|
| 189 |
+
2026-10-03T06:45:07 step 46250 train 0.10109 inner-val 0.10241 best 0.10241@45750 (2193s) immicro=0.0978 ye2026_sepsis=0.1133 imperial_eskd=0.0987 liu2021=0.0999
|
| 190 |
+
2026-10-03T06:45:20 step 46500 train 0.10106 inner-val 0.10240 best 0.10240@46500 (2206s) immicro=0.0978 ye2026_sepsis=0.1133 imperial_eskd=0.0987 liu2021=0.0999
|
| 191 |
+
2026-10-03T06:45:33 step 46750 train 0.10088 inner-val 0.10240 best 0.10240@46750 (2218s) immicro=0.0978 ye2026_sepsis=0.1133 imperial_eskd=0.0987 liu2021=0.0999
|
| 192 |
+
2026-10-03T06:45:45 step 47000 train 0.10081 inner-val 0.10240 best 0.10240@47000 (2231s) immicro=0.0977 ye2026_sepsis=0.1133 imperial_eskd=0.0987 liu2021=0.0999
|
| 193 |
+
2026-10-03T06:45:58 step 47250 train 0.10121 inner-val 0.10239 best 0.10239@47250 (2243s) immicro=0.0977 ye2026_sepsis=0.1133 imperial_eskd=0.0987 liu2021=0.0999
|
| 194 |
+
2026-10-03T06:46:10 step 47500 train 0.10103 inner-val 0.10239 best 0.10239@47500 (2256s) immicro=0.0977 ye2026_sepsis=0.1133 imperial_eskd=0.0987 liu2021=0.0998
|
| 195 |
+
2026-10-03T06:46:22 step 47750 train 0.10100 inner-val 0.10239 best 0.10239@47750 (2268s) immicro=0.0977 ye2026_sepsis=0.1133 imperial_eskd=0.0987 liu2021=0.0998
|
| 196 |
+
2026-10-03T06:46:35 step 48000 train 0.10108 inner-val 0.10239 best 0.10239@48000 (2280s) immicro=0.0977 ye2026_sepsis=0.1133 imperial_eskd=0.0987 liu2021=0.0998
|
| 197 |
+
2026-10-03T06:46:47 step 48250 train 0.10099 inner-val 0.10238 best 0.10238@48250 (2293s) immicro=0.0977 ye2026_sepsis=0.1133 imperial_eskd=0.0987 liu2021=0.0998
|
| 198 |
+
2026-10-03T06:47:00 step 48500 train 0.10090 inner-val 0.10238 best 0.10238@48500 (2305s) immicro=0.0977 ye2026_sepsis=0.1133 imperial_eskd=0.0987 liu2021=0.0998
|
| 199 |
+
2026-10-03T06:47:12 step 48750 train 0.10088 inner-val 0.10238 best 0.10238@48500 (2318s) immicro=0.0977 ye2026_sepsis=0.1133 imperial_eskd=0.0987 liu2021=0.0998
|
| 200 |
+
2026-10-03T06:47:25 step 49000 train 0.10112 inner-val 0.10238 best 0.10238@49000 (2330s) immicro=0.0977 ye2026_sepsis=0.1133 imperial_eskd=0.0987 liu2021=0.0998
|
| 201 |
+
2026-10-03T06:47:37 step 49250 train 0.10096 inner-val 0.10238 best 0.10238@49250 (2343s) immicro=0.0977 ye2026_sepsis=0.1133 imperial_eskd=0.0987 liu2021=0.0998
|
| 202 |
+
2026-10-03T06:47:50 step 49500 train 0.10075 inner-val 0.10237 best 0.10237@49500 (2355s) immicro=0.0977 ye2026_sepsis=0.1133 imperial_eskd=0.0987 liu2021=0.0998
|
| 203 |
+
2026-10-03T06:48:02 step 49750 train 0.10101 inner-val 0.10237 best 0.10237@49750 (2367s) immicro=0.0977 ye2026_sepsis=0.1132 imperial_eskd=0.0987 liu2021=0.0998
|
| 204 |
+
2026-10-03T06:48:14 step 50000 train 0.10062 inner-val 0.10237 best 0.10237@49750 (2380s) immicro=0.0977 ye2026_sepsis=0.1132 imperial_eskd=0.0987 liu2021=0.0998
|
| 205 |
+
2026-10-03T06:48:26 step 50250 train 0.10094 inner-val 0.10238 best 0.10237@49750 (2392s) immicro=0.0977 ye2026_sepsis=0.1132 imperial_eskd=0.0987 liu2021=0.0999
|
| 206 |
+
2026-10-03T06:48:38 step 50500 train 0.10105 inner-val 0.10238 best 0.10237@49750 (2404s) immicro=0.0977 ye2026_sepsis=0.1132 imperial_eskd=0.0987 liu2021=0.0999
|
| 207 |
+
2026-10-03T06:48:51 step 50750 train 0.10072 inner-val 0.10238 best 0.10237@49750 (2416s) immicro=0.0977 ye2026_sepsis=0.1132 imperial_eskd=0.0987 liu2021=0.0999
|
| 208 |
+
2026-10-03T06:49:03 step 51000 train 0.10097 inner-val 0.10238 best 0.10237@49750 (2428s) immicro=0.0977 ye2026_sepsis=0.1133 imperial_eskd=0.0987 liu2021=0.0999
|
| 209 |
+
2026-10-03T06:49:15 step 51250 train 0.10117 inner-val 0.10238 best 0.10237@49750 (2440s) immicro=0.0977 ye2026_sepsis=0.1133 imperial_eskd=0.0987 liu2021=0.0999
|
| 210 |
+
2026-10-03T06:49:27 step 51500 train 0.10087 inner-val 0.10238 best 0.10237@49750 (2453s) immicro=0.0977 ye2026_sepsis=0.1132 imperial_eskd=0.0987 liu2021=0.0999
|
| 211 |
+
2026-10-03T06:49:39 step 51750 train 0.10097 inner-val 0.10237 best 0.10237@49750 (2465s) immicro=0.0977 ye2026_sepsis=0.1132 imperial_eskd=0.0987 liu2021=0.0999
|
| 212 |
+
2026-10-03T06:49:39 early stop: no improvement in 8 evaluations
|
| 213 |
+
2026-10-03T06:49:45 saved /home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_crosscohort_20261002/runs/hoL_ji2025_chili/K1000/lora64sat/checkpoint_ft.pt (selected step 49750, inner-val 0.10237 vs pretrained 0.11207); sha 52de55c873e5
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