Archive 4 checkpoints (1-4)
Browse files- paper-releases/pbisc-diffusion/updates/20261005T063808Z-no-pretraining-ablation-f0/diffusion/dataset/server_1/model8/plans/paired_finetune_intradataset_20260927/runs/ye2026_sepsis/fold0/scratch_full/RUN.json +139 -0
- paper-releases/pbisc-diffusion/updates/20261005T063808Z-no-pretraining-ablation-f0/diffusion/dataset/server_1/model8/plans/paired_finetune_intradataset_20260927/runs/ye2026_sepsis/fold0/scratch_full/checkpoint_ft.pt.moved +6 -0
- paper-releases/pbisc-diffusion/updates/20261005T063808Z-no-pretraining-ablation-f0/diffusion/dataset/server_1/model8/plans/paired_finetune_intradataset_20260927/runs/ye2026_sepsis/fold0/scratch_full/history.json +607 -0
- paper-releases/pbisc-diffusion/updates/20261005T063808Z-no-pretraining-ablation-f0/diffusion/dataset/server_1/model8/plans/paired_finetune_intradataset_20260927/runs/ye2026_sepsis/fold0/scratch_full/train.log +104 -0
paper-releases/pbisc-diffusion/updates/20261005T063808Z-no-pretraining-ablation-f0/diffusion/dataset/server_1/model8/plans/paired_finetune_intradataset_20260927/runs/ye2026_sepsis/fold0/scratch_full/RUN.json
ADDED
|
@@ -0,0 +1,139 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"schema": "pbisc_sdd.ft_intradataset.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 |
+
"dataset_dir": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/data/ye2026_sepsis",
|
| 6 |
+
"condition_npz": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/data/ye2026_sepsis/conditions_raw_fixed.npz",
|
| 7 |
+
"condition_npz_sha256": "ce8b61d7dcd3e62b9e63d52189cfb5bba881f87a661384277a7949a629231cb4",
|
| 8 |
+
"fold": 0,
|
| 9 |
+
"mode": "full",
|
| 10 |
+
"trainable": {
|
| 11 |
+
"mode": "full",
|
| 12 |
+
"n_trainable": 54185184,
|
| 13 |
+
"n_total_base": 54185184,
|
| 14 |
+
"trainable_tensors": 64
|
| 15 |
+
},
|
| 16 |
+
"lr": 0.0002,
|
| 17 |
+
"warmup": 200,
|
| 18 |
+
"batch_size": 256,
|
| 19 |
+
"ema_decay": 0.999,
|
| 20 |
+
"max_steps": 100000,
|
| 21 |
+
"steps_run": 100000,
|
| 22 |
+
"eval_every": 1000,
|
| 23 |
+
"patience": 10,
|
| 24 |
+
"train_subset": null,
|
| 25 |
+
"init": "random",
|
| 26 |
+
"init_seed": 20260627,
|
| 27 |
+
"n_tensors": 64,
|
| 28 |
+
"kept_from_checkpoint": [
|
| 29 |
+
"model_config",
|
| 30 |
+
"diffusion_config",
|
| 31 |
+
"gene panel",
|
| 32 |
+
"value_scaler",
|
| 33 |
+
"conditioner z-score constants"
|
| 34 |
+
],
|
| 35 |
+
"augmentation": {
|
| 36 |
+
"multi_k": [],
|
| 37 |
+
"recipe_frac": 0.0,
|
| 38 |
+
"recipe_cells_per_step": 0,
|
| 39 |
+
"recipe_k_grid": null
|
| 40 |
+
},
|
| 41 |
+
"selected_step": 100000,
|
| 42 |
+
"selected_inner_val_loss": 0.11543921647327286,
|
| 43 |
+
"pretrained_inner_val_loss": 1.7818074481827872,
|
| 44 |
+
"train_rows": [
|
| 45 |
+
"Abd-PS04",
|
| 46 |
+
"Abd-PS05",
|
| 47 |
+
"Abd-PS07",
|
| 48 |
+
"Abd-PS20",
|
| 49 |
+
"Abd-PS27",
|
| 50 |
+
"Abd-S102",
|
| 51 |
+
"Abd-S103",
|
| 52 |
+
"Abd-S120",
|
| 53 |
+
"Abd-S156",
|
| 54 |
+
"Abd-S42",
|
| 55 |
+
"Abd-S51",
|
| 56 |
+
"Abd-S54",
|
| 57 |
+
"Abd-S57",
|
| 58 |
+
"Abd-S79",
|
| 59 |
+
"Abd-S83",
|
| 60 |
+
"Abd-S98",
|
| 61 |
+
"HC05",
|
| 62 |
+
"HC09",
|
| 63 |
+
"HC12",
|
| 64 |
+
"HC13",
|
| 65 |
+
"IC10",
|
| 66 |
+
"IC15",
|
| 67 |
+
"IC16",
|
| 68 |
+
"IC22",
|
| 69 |
+
"PHC01",
|
| 70 |
+
"PHC02",
|
| 71 |
+
"PHC05",
|
| 72 |
+
"PIC01",
|
| 73 |
+
"PIC02",
|
| 74 |
+
"PIC05",
|
| 75 |
+
"Res-PS02",
|
| 76 |
+
"Res-PS03",
|
| 77 |
+
"Res-PS12",
|
| 78 |
+
"Res-PS16",
|
| 79 |
+
"Res-PS21",
|
| 80 |
+
"Res-PS22",
|
| 81 |
+
"Res-S125",
|
| 82 |
+
"Res-S146",
|
| 83 |
+
"Res-S149",
|
| 84 |
+
"Res-S150",
|
| 85 |
+
"Res-S164",
|
| 86 |
+
"Res-S166",
|
| 87 |
+
"Res-S174",
|
| 88 |
+
"Res-S177",
|
| 89 |
+
"Res-S184",
|
| 90 |
+
"Res-S19",
|
| 91 |
+
"Res-S40",
|
| 92 |
+
"Res-S87",
|
| 93 |
+
"Skin-S142",
|
| 94 |
+
"Skin-S152",
|
| 95 |
+
"Skin-S38",
|
| 96 |
+
"Skin-S46",
|
| 97 |
+
"Skin-S52",
|
| 98 |
+
"Skin-S74",
|
| 99 |
+
"Uri-S134",
|
| 100 |
+
"Uri-S157",
|
| 101 |
+
"Uri-S20",
|
| 102 |
+
"Uri-S93"
|
| 103 |
+
],
|
| 104 |
+
"inner_val_rows": [
|
| 105 |
+
"HC16",
|
| 106 |
+
"IC19",
|
| 107 |
+
"Res-PS26",
|
| 108 |
+
"Res-S10",
|
| 109 |
+
"Res-S127",
|
| 110 |
+
"Res-S136",
|
| 111 |
+
"Skin-S43"
|
| 112 |
+
],
|
| 113 |
+
"test_rows_never_loaded_for_training": [
|
| 114 |
+
"Abd-PS19",
|
| 115 |
+
"Abd-PS23",
|
| 116 |
+
"Abd-S123",
|
| 117 |
+
"Abd-S39",
|
| 118 |
+
"Abd-S47",
|
| 119 |
+
"Abd-S66",
|
| 120 |
+
"HC01",
|
| 121 |
+
"HC07",
|
| 122 |
+
"IC23",
|
| 123 |
+
"PHC03",
|
| 124 |
+
"PIC04",
|
| 125 |
+
"Res-PS25",
|
| 126 |
+
"Res-S139",
|
| 127 |
+
"Res-S26",
|
| 128 |
+
"Res-S77",
|
| 129 |
+
"Skin-S140",
|
| 130 |
+
"Uri-S147"
|
| 131 |
+
],
|
| 132 |
+
"max_abs_weight_change": 17.891483306884766,
|
| 133 |
+
"n_tensors_changed": 64,
|
| 134 |
+
"seed": 20260927,
|
| 135 |
+
"wall_seconds": 4738.5,
|
| 136 |
+
"written_utc": "2026-10-05T02:25:27.812732+00:00",
|
| 137 |
+
"checkpoint_sha256": "de6a5f0feac4d56bb60bdda0581f9e36b6737b25c8edb2f8390b0e76dfd3a093",
|
| 138 |
+
"reload_forward_max_abs_diff": 0.0
|
| 139 |
+
}
|
paper-releases/pbisc-diffusion/updates/20261005T063808Z-no-pretraining-ablation-f0/diffusion/dataset/server_1/model8/plans/paired_finetune_intradataset_20260927/runs/ye2026_sepsis/fold0/scratch_full/checkpoint_ft.pt.moved
ADDED
|
@@ -0,0 +1,6 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"moved_to": "spark-0110",
|
| 3 |
+
"path": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/runs/ye2026_sepsis/fold0/scratch_full/checkpoint_ft.pt",
|
| 4 |
+
"sha256": "de6a5f0feac4d56bb60bdda0581f9e36b6737b25c8edb2f8390b0e76dfd3a093",
|
| 5 |
+
"at": "2026-10-05T15:36:34.327332"
|
| 6 |
+
}
|
paper-releases/pbisc-diffusion/updates/20261005T063808Z-no-pretraining-ablation-f0/diffusion/dataset/server_1/model8/plans/paired_finetune_intradataset_20260927/runs/ye2026_sepsis/fold0/scratch_full/history.json
ADDED
|
@@ -0,0 +1,607 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
[
|
| 2 |
+
{
|
| 3 |
+
"step": 0,
|
| 4 |
+
"inner_val_loss": 1.7818074481827872,
|
| 5 |
+
"train_loss": null
|
| 6 |
+
},
|
| 7 |
+
{
|
| 8 |
+
"step": 1000,
|
| 9 |
+
"inner_val_loss": 0.3617558947631291,
|
| 10 |
+
"train_loss": 0.23480229634046554,
|
| 11 |
+
"sec": 42.5
|
| 12 |
+
},
|
| 13 |
+
{
|
| 14 |
+
"step": 2000,
|
| 15 |
+
"inner_val_loss": 0.18583933051143373,
|
| 16 |
+
"train_loss": 0.1489966948032379,
|
| 17 |
+
"sec": 90.6
|
| 18 |
+
},
|
| 19 |
+
{
|
| 20 |
+
"step": 3000,
|
| 21 |
+
"inner_val_loss": 0.15468829976660864,
|
| 22 |
+
"train_loss": 0.14529584404826165,
|
| 23 |
+
"sec": 139.7
|
| 24 |
+
},
|
| 25 |
+
{
|
| 26 |
+
"step": 4000,
|
| 27 |
+
"inner_val_loss": 0.1482239067554474,
|
| 28 |
+
"train_loss": 0.14264038267731666,
|
| 29 |
+
"sec": 189.0
|
| 30 |
+
},
|
| 31 |
+
{
|
| 32 |
+
"step": 5000,
|
| 33 |
+
"inner_val_loss": 0.1459613506283079,
|
| 34 |
+
"train_loss": 0.1419006452858448,
|
| 35 |
+
"sec": 237.5
|
| 36 |
+
},
|
| 37 |
+
{
|
| 38 |
+
"step": 6000,
|
| 39 |
+
"inner_val_loss": 0.14498246035405568,
|
| 40 |
+
"train_loss": 0.14087264470756053,
|
| 41 |
+
"sec": 286.9
|
| 42 |
+
},
|
| 43 |
+
{
|
| 44 |
+
"step": 7000,
|
| 45 |
+
"inner_val_loss": 0.14431396765368326,
|
| 46 |
+
"train_loss": 0.14021397273242472,
|
| 47 |
+
"sec": 334.7
|
| 48 |
+
},
|
| 49 |
+
{
|
| 50 |
+
"step": 8000,
|
| 51 |
+
"inner_val_loss": 0.14380189669983728,
|
| 52 |
+
"train_loss": 0.13969597867131234,
|
| 53 |
+
"sec": 384.1
|
| 54 |
+
},
|
| 55 |
+
{
|
| 56 |
+
"step": 9000,
|
| 57 |
+
"inner_val_loss": 0.14328549589429582,
|
| 58 |
+
"train_loss": 0.13912463635206224,
|
| 59 |
+
"sec": 433.0
|
| 60 |
+
},
|
| 61 |
+
{
|
| 62 |
+
"step": 10000,
|
| 63 |
+
"inner_val_loss": 0.14282755979469844,
|
| 64 |
+
"train_loss": 0.1385519172847271,
|
| 65 |
+
"sec": 482.3
|
| 66 |
+
},
|
| 67 |
+
{
|
| 68 |
+
"step": 11000,
|
| 69 |
+
"inner_val_loss": 0.1423271575144359,
|
| 70 |
+
"train_loss": 0.13820364804565907,
|
| 71 |
+
"sec": 529.1
|
| 72 |
+
},
|
| 73 |
+
{
|
| 74 |
+
"step": 12000,
|
| 75 |
+
"inner_val_loss": 0.14184519116367614,
|
| 76 |
+
"train_loss": 0.1376941778510809,
|
| 77 |
+
"sec": 577.8
|
| 78 |
+
},
|
| 79 |
+
{
|
| 80 |
+
"step": 13000,
|
| 81 |
+
"inner_val_loss": 0.1412026924746377,
|
| 82 |
+
"train_loss": 0.13686130821704864,
|
| 83 |
+
"sec": 624.4
|
| 84 |
+
},
|
| 85 |
+
{
|
| 86 |
+
"step": 14000,
|
| 87 |
+
"inner_val_loss": 0.1403366880757468,
|
| 88 |
+
"train_loss": 0.13603241059184074,
|
| 89 |
+
"sec": 669.0
|
| 90 |
+
},
|
| 91 |
+
{
|
| 92 |
+
"step": 15000,
|
| 93 |
+
"inner_val_loss": 0.13918964245489665,
|
| 94 |
+
"train_loss": 0.13497026316821575,
|
| 95 |
+
"sec": 715.5
|
| 96 |
+
},
|
| 97 |
+
{
|
| 98 |
+
"step": 16000,
|
| 99 |
+
"inner_val_loss": 0.137855521270207,
|
| 100 |
+
"train_loss": 0.1336007233262062,
|
| 101 |
+
"sec": 759.4
|
| 102 |
+
},
|
| 103 |
+
{
|
| 104 |
+
"step": 17000,
|
| 105 |
+
"inner_val_loss": 0.13646107060568674,
|
| 106 |
+
"train_loss": 0.13196209254860877,
|
| 107 |
+
"sec": 808.2
|
| 108 |
+
},
|
| 109 |
+
{
|
| 110 |
+
"step": 18000,
|
| 111 |
+
"inner_val_loss": 0.13516551788364137,
|
| 112 |
+
"train_loss": 0.13098813547939062,
|
| 113 |
+
"sec": 854.4
|
| 114 |
+
},
|
| 115 |
+
{
|
| 116 |
+
"step": 19000,
|
| 117 |
+
"inner_val_loss": 0.13400550239852496,
|
| 118 |
+
"train_loss": 0.1298879310488701,
|
| 119 |
+
"sec": 901.0
|
| 120 |
+
},
|
| 121 |
+
{
|
| 122 |
+
"step": 20000,
|
| 123 |
+
"inner_val_loss": 0.1328950109226363,
|
| 124 |
+
"train_loss": 0.12874326338618994,
|
| 125 |
+
"sec": 948.4
|
| 126 |
+
},
|
| 127 |
+
{
|
| 128 |
+
"step": 21000,
|
| 129 |
+
"inner_val_loss": 0.1319212509053094,
|
| 130 |
+
"train_loss": 0.12781331166625023,
|
| 131 |
+
"sec": 994.5
|
| 132 |
+
},
|
| 133 |
+
{
|
| 134 |
+
"step": 22000,
|
| 135 |
+
"inner_val_loss": 0.1310313381254673,
|
| 136 |
+
"train_loss": 0.1267336530610919,
|
| 137 |
+
"sec": 1041.0
|
| 138 |
+
},
|
| 139 |
+
{
|
| 140 |
+
"step": 23000,
|
| 141 |
+
"inner_val_loss": 0.13019464537501335,
|
| 142 |
+
"train_loss": 0.12586170244961978,
|
| 143 |
+
"sec": 1089.4
|
| 144 |
+
},
|
| 145 |
+
{
|
| 146 |
+
"step": 24000,
|
| 147 |
+
"inner_val_loss": 0.12946667788284166,
|
| 148 |
+
"train_loss": 0.1252509091347456,
|
| 149 |
+
"sec": 1136.0
|
| 150 |
+
},
|
| 151 |
+
{
|
| 152 |
+
"step": 25000,
|
| 153 |
+
"inner_val_loss": 0.12872777985674994,
|
| 154 |
+
"train_loss": 0.12433422987908124,
|
| 155 |
+
"sec": 1183.0
|
| 156 |
+
},
|
| 157 |
+
{
|
| 158 |
+
"step": 26000,
|
| 159 |
+
"inner_val_loss": 0.12797676133258,
|
| 160 |
+
"train_loss": 0.1235926092788577,
|
| 161 |
+
"sec": 1229.0
|
| 162 |
+
},
|
| 163 |
+
{
|
| 164 |
+
"step": 27000,
|
| 165 |
+
"inner_val_loss": 0.12730004904525621,
|
| 166 |
+
"train_loss": 0.12282455990463495,
|
| 167 |
+
"sec": 1275.5
|
| 168 |
+
},
|
| 169 |
+
{
|
| 170 |
+
"step": 28000,
|
| 171 |
+
"inner_val_loss": 0.12666800352079527,
|
| 172 |
+
"train_loss": 0.12219609786570072,
|
| 173 |
+
"sec": 1323.5
|
| 174 |
+
},
|
| 175 |
+
{
|
| 176 |
+
"step": 29000,
|
| 177 |
+
"inner_val_loss": 0.12609786008085525,
|
| 178 |
+
"train_loss": 0.1217848539724946,
|
| 179 |
+
"sec": 1369.8
|
| 180 |
+
},
|
| 181 |
+
{
|
| 182 |
+
"step": 30000,
|
| 183 |
+
"inner_val_loss": 0.12559437059930392,
|
| 184 |
+
"train_loss": 0.12110507083684206,
|
| 185 |
+
"sec": 1416.5
|
| 186 |
+
},
|
| 187 |
+
{
|
| 188 |
+
"step": 31000,
|
| 189 |
+
"inner_val_loss": 0.12507352552243642,
|
| 190 |
+
"train_loss": 0.12058917447179555,
|
| 191 |
+
"sec": 1462.3
|
| 192 |
+
},
|
| 193 |
+
{
|
| 194 |
+
"step": 32000,
|
| 195 |
+
"inner_val_loss": 0.12458380524601255,
|
| 196 |
+
"train_loss": 0.12002437047660351,
|
| 197 |
+
"sec": 1510.1
|
| 198 |
+
},
|
| 199 |
+
{
|
| 200 |
+
"step": 33000,
|
| 201 |
+
"inner_val_loss": 0.1241427840931075,
|
| 202 |
+
"train_loss": 0.1199131126999855,
|
| 203 |
+
"sec": 1556.5
|
| 204 |
+
},
|
| 205 |
+
{
|
| 206 |
+
"step": 34000,
|
| 207 |
+
"inner_val_loss": 0.12375103629061154,
|
| 208 |
+
"train_loss": 0.11917648924887181,
|
| 209 |
+
"sec": 1602.5
|
| 210 |
+
},
|
| 211 |
+
{
|
| 212 |
+
"step": 35000,
|
| 213 |
+
"inner_val_loss": 0.12332479975053243,
|
| 214 |
+
"train_loss": 0.11839115908741951,
|
| 215 |
+
"sec": 1649.6
|
| 216 |
+
},
|
| 217 |
+
{
|
| 218 |
+
"step": 36000,
|
| 219 |
+
"inner_val_loss": 0.12295581347176007,
|
| 220 |
+
"train_loss": 0.11829834950715304,
|
| 221 |
+
"sec": 1697.4
|
| 222 |
+
},
|
| 223 |
+
{
|
| 224 |
+
"step": 37000,
|
| 225 |
+
"inner_val_loss": 0.12259351834654808,
|
| 226 |
+
"train_loss": 0.11778196669369936,
|
| 227 |
+
"sec": 1746.8
|
| 228 |
+
},
|
| 229 |
+
{
|
| 230 |
+
"step": 38000,
|
| 231 |
+
"inner_val_loss": 0.12222727547798838,
|
| 232 |
+
"train_loss": 0.11738987892866135,
|
| 233 |
+
"sec": 1796.1
|
| 234 |
+
},
|
| 235 |
+
{
|
| 236 |
+
"step": 39000,
|
| 237 |
+
"inner_val_loss": 0.12190202570387296,
|
| 238 |
+
"train_loss": 0.1172406503111124,
|
| 239 |
+
"sec": 1845.4
|
| 240 |
+
},
|
| 241 |
+
{
|
| 242 |
+
"step": 40000,
|
| 243 |
+
"inner_val_loss": 0.12158123084477016,
|
| 244 |
+
"train_loss": 0.11676804707199336,
|
| 245 |
+
"sec": 1894.5
|
| 246 |
+
},
|
| 247 |
+
{
|
| 248 |
+
"step": 41000,
|
| 249 |
+
"inner_val_loss": 0.12127977290323802,
|
| 250 |
+
"train_loss": 0.11644379718601704,
|
| 251 |
+
"sec": 1940.2
|
| 252 |
+
},
|
| 253 |
+
{
|
| 254 |
+
"step": 42000,
|
| 255 |
+
"inner_val_loss": 0.12101246150476593,
|
| 256 |
+
"train_loss": 0.11636611497402191,
|
| 257 |
+
"sec": 1986.3
|
| 258 |
+
},
|
| 259 |
+
{
|
| 260 |
+
"step": 43000,
|
| 261 |
+
"inner_val_loss": 0.12075386781777654,
|
| 262 |
+
"train_loss": 0.11591150046885014,
|
| 263 |
+
"sec": 2031.9
|
| 264 |
+
},
|
| 265 |
+
{
|
| 266 |
+
"step": 44000,
|
| 267 |
+
"inner_val_loss": 0.1205042792218072,
|
| 268 |
+
"train_loss": 0.11568558400124311,
|
| 269 |
+
"sec": 2079.4
|
| 270 |
+
},
|
| 271 |
+
{
|
| 272 |
+
"step": 45000,
|
| 273 |
+
"inner_val_loss": 0.12023724828447614,
|
| 274 |
+
"train_loss": 0.11536223304271698,
|
| 275 |
+
"sec": 2124.5
|
| 276 |
+
},
|
| 277 |
+
{
|
| 278 |
+
"step": 46000,
|
| 279 |
+
"inner_val_loss": 0.11999163829854556,
|
| 280 |
+
"train_loss": 0.11502615962922573,
|
| 281 |
+
"sec": 2171.8
|
| 282 |
+
},
|
| 283 |
+
{
|
| 284 |
+
"step": 47000,
|
| 285 |
+
"inner_val_loss": 0.11977356459413256,
|
| 286 |
+
"train_loss": 0.11473615449666977,
|
| 287 |
+
"sec": 2217.8
|
| 288 |
+
},
|
| 289 |
+
{
|
| 290 |
+
"step": 48000,
|
| 291 |
+
"inner_val_loss": 0.11957669790302004,
|
| 292 |
+
"train_loss": 0.11438696250319481,
|
| 293 |
+
"sec": 2265.9
|
| 294 |
+
},
|
| 295 |
+
{
|
| 296 |
+
"step": 49000,
|
| 297 |
+
"inner_val_loss": 0.11941238705601011,
|
| 298 |
+
"train_loss": 0.11473074097931385,
|
| 299 |
+
"sec": 2312.1
|
| 300 |
+
},
|
| 301 |
+
{
|
| 302 |
+
"step": 50000,
|
| 303 |
+
"inner_val_loss": 0.11924929118582181,
|
| 304 |
+
"train_loss": 0.114058812238276,
|
| 305 |
+
"sec": 2359.1
|
| 306 |
+
},
|
| 307 |
+
{
|
| 308 |
+
"step": 51000,
|
| 309 |
+
"inner_val_loss": 0.11904857360890933,
|
| 310 |
+
"train_loss": 0.1139026626572013,
|
| 311 |
+
"sec": 2406.1
|
| 312 |
+
},
|
| 313 |
+
{
|
| 314 |
+
"step": 52000,
|
| 315 |
+
"inner_val_loss": 0.11888326757720538,
|
| 316 |
+
"train_loss": 0.1136448061466217,
|
| 317 |
+
"sec": 2451.0
|
| 318 |
+
},
|
| 319 |
+
{
|
| 320 |
+
"step": 53000,
|
| 321 |
+
"inner_val_loss": 0.11870529555848666,
|
| 322 |
+
"train_loss": 0.11348695230484009,
|
| 323 |
+
"sec": 2498.7
|
| 324 |
+
},
|
| 325 |
+
{
|
| 326 |
+
"step": 54000,
|
| 327 |
+
"inner_val_loss": 0.11856710644704956,
|
| 328 |
+
"train_loss": 0.11339245654642582,
|
| 329 |
+
"sec": 2546.3
|
| 330 |
+
},
|
| 331 |
+
{
|
| 332 |
+
"step": 55000,
|
| 333 |
+
"inner_val_loss": 0.11841848226530212,
|
| 334 |
+
"train_loss": 0.11302479877322912,
|
| 335 |
+
"sec": 2593.6
|
| 336 |
+
},
|
| 337 |
+
{
|
| 338 |
+
"step": 56000,
|
| 339 |
+
"inner_val_loss": 0.1182337940803596,
|
| 340 |
+
"train_loss": 0.11311893320083619,
|
| 341 |
+
"sec": 2639.8
|
| 342 |
+
},
|
| 343 |
+
{
|
| 344 |
+
"step": 57000,
|
| 345 |
+
"inner_val_loss": 0.11807100315179143,
|
| 346 |
+
"train_loss": 0.11267659799009562,
|
| 347 |
+
"sec": 2687.9
|
| 348 |
+
},
|
| 349 |
+
{
|
| 350 |
+
"step": 58000,
|
| 351 |
+
"inner_val_loss": 0.1179443576506206,
|
| 352 |
+
"train_loss": 0.11299417734146118,
|
| 353 |
+
"sec": 2736.6
|
| 354 |
+
},
|
| 355 |
+
{
|
| 356 |
+
"step": 59000,
|
| 357 |
+
"inner_val_loss": 0.11783176394445556,
|
| 358 |
+
"train_loss": 0.11258843979239463,
|
| 359 |
+
"sec": 2782.9
|
| 360 |
+
},
|
| 361 |
+
{
|
| 362 |
+
"step": 60000,
|
| 363 |
+
"inner_val_loss": 0.11767819364156042,
|
| 364 |
+
"train_loss": 0.1123829357996583,
|
| 365 |
+
"sec": 2830.1
|
| 366 |
+
},
|
| 367 |
+
{
|
| 368 |
+
"step": 61000,
|
| 369 |
+
"inner_val_loss": 0.117593522050551,
|
| 370 |
+
"train_loss": 0.11234327441453934,
|
| 371 |
+
"sec": 2876.7
|
| 372 |
+
},
|
| 373 |
+
{
|
| 374 |
+
"step": 62000,
|
| 375 |
+
"inner_val_loss": 0.117514254791396,
|
| 376 |
+
"train_loss": 0.11231860252469777,
|
| 377 |
+
"sec": 2923.2
|
| 378 |
+
},
|
| 379 |
+
{
|
| 380 |
+
"step": 63000,
|
| 381 |
+
"inner_val_loss": 0.11739418070231165,
|
| 382 |
+
"train_loss": 0.11196062943339348,
|
| 383 |
+
"sec": 2968.3
|
| 384 |
+
},
|
| 385 |
+
{
|
| 386 |
+
"step": 64000,
|
| 387 |
+
"inner_val_loss": 0.11729942634701729,
|
| 388 |
+
"train_loss": 0.11190995406359434,
|
| 389 |
+
"sec": 3015.5
|
| 390 |
+
},
|
| 391 |
+
{
|
| 392 |
+
"step": 65000,
|
| 393 |
+
"inner_val_loss": 0.11722857398646218,
|
| 394 |
+
"train_loss": 0.11196828432381153,
|
| 395 |
+
"sec": 3062.7
|
| 396 |
+
},
|
| 397 |
+
{
|
| 398 |
+
"step": 66000,
|
| 399 |
+
"inner_val_loss": 0.11715164461306163,
|
| 400 |
+
"train_loss": 0.11176340838521719,
|
| 401 |
+
"sec": 3110.9
|
| 402 |
+
},
|
| 403 |
+
{
|
| 404 |
+
"step": 67000,
|
| 405 |
+
"inner_val_loss": 0.11706299068672317,
|
| 406 |
+
"train_loss": 0.11146858774870634,
|
| 407 |
+
"sec": 3159.2
|
| 408 |
+
},
|
| 409 |
+
{
|
| 410 |
+
"step": 68000,
|
| 411 |
+
"inner_val_loss": 0.11697563848325185,
|
| 412 |
+
"train_loss": 0.11143718066811562,
|
| 413 |
+
"sec": 3204.3
|
| 414 |
+
},
|
| 415 |
+
{
|
| 416 |
+
"step": 69000,
|
| 417 |
+
"inner_val_loss": 0.11688968007053648,
|
| 418 |
+
"train_loss": 0.11137567707151175,
|
| 419 |
+
"sec": 3251.4
|
| 420 |
+
},
|
| 421 |
+
{
|
| 422 |
+
"step": 70000,
|
| 423 |
+
"inner_val_loss": 0.11683664790221623,
|
| 424 |
+
"train_loss": 0.11132148785889148,
|
| 425 |
+
"sec": 3300.3
|
| 426 |
+
},
|
| 427 |
+
{
|
| 428 |
+
"step": 71000,
|
| 429 |
+
"inner_val_loss": 0.1167648397386074,
|
| 430 |
+
"train_loss": 0.11113779219985008,
|
| 431 |
+
"sec": 3346.1
|
| 432 |
+
},
|
| 433 |
+
{
|
| 434 |
+
"step": 72000,
|
| 435 |
+
"inner_val_loss": 0.11666633188724518,
|
| 436 |
+
"train_loss": 0.11103232715278864,
|
| 437 |
+
"sec": 3392.4
|
| 438 |
+
},
|
| 439 |
+
{
|
| 440 |
+
"step": 73000,
|
| 441 |
+
"inner_val_loss": 0.11656014461602483,
|
| 442 |
+
"train_loss": 0.1107224071919918,
|
| 443 |
+
"sec": 3438.7
|
| 444 |
+
},
|
| 445 |
+
{
|
| 446 |
+
"step": 74000,
|
| 447 |
+
"inner_val_loss": 0.11646763235330582,
|
| 448 |
+
"train_loss": 0.11062478782981634,
|
| 449 |
+
"sec": 3485.6
|
| 450 |
+
},
|
| 451 |
+
{
|
| 452 |
+
"step": 75000,
|
| 453 |
+
"inner_val_loss": 0.11641783586570195,
|
| 454 |
+
"train_loss": 0.11074889083206653,
|
| 455 |
+
"sec": 3529.6
|
| 456 |
+
},
|
| 457 |
+
{
|
| 458 |
+
"step": 76000,
|
| 459 |
+
"inner_val_loss": 0.11638653970190457,
|
| 460 |
+
"train_loss": 0.11052554166316986,
|
| 461 |
+
"sec": 3575.6
|
| 462 |
+
},
|
| 463 |
+
{
|
| 464 |
+
"step": 77000,
|
| 465 |
+
"inner_val_loss": 0.11634727567434311,
|
| 466 |
+
"train_loss": 0.11067023944109679,
|
| 467 |
+
"sec": 3624.5
|
| 468 |
+
},
|
| 469 |
+
{
|
| 470 |
+
"step": 78000,
|
| 471 |
+
"inner_val_loss": 0.1162930295935699,
|
| 472 |
+
"train_loss": 0.11054412370175123,
|
| 473 |
+
"sec": 3673.0
|
| 474 |
+
},
|
| 475 |
+
{
|
| 476 |
+
"step": 79000,
|
| 477 |
+
"inner_val_loss": 0.11622767948678561,
|
| 478 |
+
"train_loss": 0.11020309539884329,
|
| 479 |
+
"sec": 3721.0
|
| 480 |
+
},
|
| 481 |
+
{
|
| 482 |
+
"step": 80000,
|
| 483 |
+
"inner_val_loss": 0.11618293928248542,
|
| 484 |
+
"train_loss": 0.11022292832285166,
|
| 485 |
+
"sec": 3766.0
|
| 486 |
+
},
|
| 487 |
+
{
|
| 488 |
+
"step": 81000,
|
| 489 |
+
"inner_val_loss": 0.11611318428601537,
|
| 490 |
+
"train_loss": 0.11029741955548525,
|
| 491 |
+
"sec": 3810.3
|
| 492 |
+
},
|
| 493 |
+
{
|
| 494 |
+
"step": 82000,
|
| 495 |
+
"inner_val_loss": 0.11607073566743306,
|
| 496 |
+
"train_loss": 0.11041857808828354,
|
| 497 |
+
"sec": 3854.6
|
| 498 |
+
},
|
| 499 |
+
{
|
| 500 |
+
"step": 83000,
|
| 501 |
+
"inner_val_loss": 0.11602820243154253,
|
| 502 |
+
"train_loss": 0.10991998321563005,
|
| 503 |
+
"sec": 3899.5
|
| 504 |
+
},
|
| 505 |
+
{
|
| 506 |
+
"step": 84000,
|
| 507 |
+
"inner_val_loss": 0.11595984016145978,
|
| 508 |
+
"train_loss": 0.11007652903348207,
|
| 509 |
+
"sec": 3949.0
|
| 510 |
+
},
|
| 511 |
+
{
|
| 512 |
+
"step": 85000,
|
| 513 |
+
"inner_val_loss": 0.11591382590787751,
|
| 514 |
+
"train_loss": 0.10983772321045399,
|
| 515 |
+
"sec": 3998.2
|
| 516 |
+
},
|
| 517 |
+
{
|
| 518 |
+
"step": 86000,
|
| 519 |
+
"inner_val_loss": 0.11590214180094856,
|
| 520 |
+
"train_loss": 0.10988585097342729,
|
| 521 |
+
"sec": 4047.7
|
| 522 |
+
},
|
| 523 |
+
{
|
| 524 |
+
"step": 87000,
|
| 525 |
+
"inner_val_loss": 0.11589577581201281,
|
| 526 |
+
"train_loss": 0.10988790262490511,
|
| 527 |
+
"sec": 4096.7
|
| 528 |
+
},
|
| 529 |
+
{
|
| 530 |
+
"step": 88000,
|
| 531 |
+
"inner_val_loss": 0.11583746118204934,
|
| 532 |
+
"train_loss": 0.10977583003044128,
|
| 533 |
+
"sec": 4146.1
|
| 534 |
+
},
|
| 535 |
+
{
|
| 536 |
+
"step": 89000,
|
| 537 |
+
"inner_val_loss": 0.11578961142471858,
|
| 538 |
+
"train_loss": 0.1098302694633603,
|
| 539 |
+
"sec": 4192.9
|
| 540 |
+
},
|
| 541 |
+
{
|
| 542 |
+
"step": 90000,
|
| 543 |
+
"inner_val_loss": 0.11575427704623767,
|
| 544 |
+
"train_loss": 0.10967790186405182,
|
| 545 |
+
"sec": 4239.5
|
| 546 |
+
},
|
| 547 |
+
{
|
| 548 |
+
"step": 91000,
|
| 549 |
+
"inner_val_loss": 0.11571810979928289,
|
| 550 |
+
"train_loss": 0.10964124870300293,
|
| 551 |
+
"sec": 4289.0
|
| 552 |
+
},
|
| 553 |
+
{
|
| 554 |
+
"step": 92000,
|
| 555 |
+
"inner_val_loss": 0.11570848843881062,
|
| 556 |
+
"train_loss": 0.10969569721072912,
|
| 557 |
+
"sec": 4339.0
|
| 558 |
+
},
|
| 559 |
+
{
|
| 560 |
+
"step": 93000,
|
| 561 |
+
"inner_val_loss": 0.1156788659947259,
|
| 562 |
+
"train_loss": 0.10961083090305328,
|
| 563 |
+
"sec": 4388.3
|
| 564 |
+
},
|
| 565 |
+
{
|
| 566 |
+
"step": 94000,
|
| 567 |
+
"inner_val_loss": 0.11566239488976342,
|
| 568 |
+
"train_loss": 0.10965150147676468,
|
| 569 |
+
"sec": 4437.6
|
| 570 |
+
},
|
| 571 |
+
{
|
| 572 |
+
"step": 95000,
|
| 573 |
+
"inner_val_loss": 0.11564572208694049,
|
| 574 |
+
"train_loss": 0.10935813515633344,
|
| 575 |
+
"sec": 4487.3
|
| 576 |
+
},
|
| 577 |
+
{
|
| 578 |
+
"step": 96000,
|
| 579 |
+
"inner_val_loss": 0.11562352680734225,
|
| 580 |
+
"train_loss": 0.10956273563951253,
|
| 581 |
+
"sec": 4536.6
|
| 582 |
+
},
|
| 583 |
+
{
|
| 584 |
+
"step": 97000,
|
| 585 |
+
"inner_val_loss": 0.11556422603981835,
|
| 586 |
+
"train_loss": 0.10944434737414122,
|
| 587 |
+
"sec": 4585.9
|
| 588 |
+
},
|
| 589 |
+
{
|
| 590 |
+
"step": 98000,
|
| 591 |
+
"inner_val_loss": 0.11551191870655332,
|
| 592 |
+
"train_loss": 0.10939323338121176,
|
| 593 |
+
"sec": 4635.8
|
| 594 |
+
},
|
| 595 |
+
{
|
| 596 |
+
"step": 99000,
|
| 597 |
+
"inner_val_loss": 0.11548084233488355,
|
| 598 |
+
"train_loss": 0.10913373067229987,
|
| 599 |
+
"sec": 4685.5
|
| 600 |
+
},
|
| 601 |
+
{
|
| 602 |
+
"step": 100000,
|
| 603 |
+
"inner_val_loss": 0.11543921647327286,
|
| 604 |
+
"train_loss": 0.10934427569806576,
|
| 605 |
+
"sec": 4735.1
|
| 606 |
+
}
|
| 607 |
+
]
|
paper-releases/pbisc-diffusion/updates/20261005T063808Z-no-pretraining-ablation-f0/diffusion/dataset/server_1/model8/plans/paired_finetune_intradataset_20260927/runs/ye2026_sepsis/fold0/scratch_full/train.log
ADDED
|
@@ -0,0 +1,104 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
2026-10-05T10:06:23 random init of every denoiser weight (seed 20260627); no pretrained weights used
|
| 2 |
+
2026-10-05T10:06:27 mode=full trainable=54,185,184 rows train/inner/test=58/7/17 cells(train)=413,130
|
| 3 |
+
2026-10-05T10:06:29 step 0 inner-val loss 1.78181 (random init)
|
| 4 |
+
2026-10-05T10:07:13 step 1000 train 0.23480 inner-val 0.36176 best 0.36176@1000 (42s)
|
| 5 |
+
2026-10-05T10:08:01 step 2000 train 0.14900 inner-val 0.18584 best 0.18584@2000 (91s)
|
| 6 |
+
2026-10-05T10:08:50 step 3000 train 0.14530 inner-val 0.15469 best 0.15469@3000 (140s)
|
| 7 |
+
2026-10-05T10:09:39 step 4000 train 0.14264 inner-val 0.14822 best 0.14822@4000 (189s)
|
| 8 |
+
2026-10-05T10:10:28 step 5000 train 0.14190 inner-val 0.14596 best 0.14596@5000 (238s)
|
| 9 |
+
2026-10-05T10:11:17 step 6000 train 0.14087 inner-val 0.14498 best 0.14498@6000 (287s)
|
| 10 |
+
2026-10-05T10:12:05 step 7000 train 0.14021 inner-val 0.14431 best 0.14431@7000 (335s)
|
| 11 |
+
2026-10-05T10:12:54 step 8000 train 0.13970 inner-val 0.14380 best 0.14380@8000 (384s)
|
| 12 |
+
2026-10-05T10:13:43 step 9000 train 0.13912 inner-val 0.14329 best 0.14329@9000 (433s)
|
| 13 |
+
2026-10-05T10:14:32 step 10000 train 0.13855 inner-val 0.14283 best 0.14283@10000 (482s)
|
| 14 |
+
2026-10-05T10:15:19 step 11000 train 0.13820 inner-val 0.14233 best 0.14233@11000 (529s)
|
| 15 |
+
2026-10-05T10:16:08 step 12000 train 0.13769 inner-val 0.14185 best 0.14185@12000 (578s)
|
| 16 |
+
2026-10-05T10:16:54 step 13000 train 0.13686 inner-val 0.14120 best 0.14120@13000 (624s)
|
| 17 |
+
2026-10-05T10:17:39 step 14000 train 0.13603 inner-val 0.14034 best 0.14034@14000 (669s)
|
| 18 |
+
2026-10-05T10:18:26 step 15000 train 0.13497 inner-val 0.13919 best 0.13919@15000 (716s)
|
| 19 |
+
2026-10-05T10:19:10 step 16000 train 0.13360 inner-val 0.13786 best 0.13786@16000 (759s)
|
| 20 |
+
2026-10-05T10:19:58 step 17000 train 0.13196 inner-val 0.13646 best 0.13646@17000 (808s)
|
| 21 |
+
2026-10-05T10:20:45 step 18000 train 0.13099 inner-val 0.13517 best 0.13517@18000 (854s)
|
| 22 |
+
2026-10-05T10:21:31 step 19000 train 0.12989 inner-val 0.13401 best 0.13401@19000 (901s)
|
| 23 |
+
2026-10-05T10:22:18 step 20000 train 0.12874 inner-val 0.13290 best 0.13290@20000 (948s)
|
| 24 |
+
2026-10-05T10:23:05 step 21000 train 0.12781 inner-val 0.13192 best 0.13192@21000 (994s)
|
| 25 |
+
2026-10-05T10:23:51 step 22000 train 0.12673 inner-val 0.13103 best 0.13103@22000 (1041s)
|
| 26 |
+
2026-10-05T10:24:39 step 23000 train 0.12586 inner-val 0.13019 best 0.13019@23000 (1089s)
|
| 27 |
+
2026-10-05T10:25:26 step 24000 train 0.12525 inner-val 0.12947 best 0.12947@24000 (1136s)
|
| 28 |
+
2026-10-05T10:26:13 step 25000 train 0.12433 inner-val 0.12873 best 0.12873@25000 (1183s)
|
| 29 |
+
2026-10-05T10:26:59 step 26000 train 0.12359 inner-val 0.12798 best 0.12798@26000 (1229s)
|
| 30 |
+
2026-10-05T10:27:46 step 27000 train 0.12282 inner-val 0.12730 best 0.12730@27000 (1276s)
|
| 31 |
+
2026-10-05T10:28:34 step 28000 train 0.12220 inner-val 0.12667 best 0.12667@28000 (1324s)
|
| 32 |
+
2026-10-05T10:29:20 step 29000 train 0.12178 inner-val 0.12610 best 0.12610@29000 (1370s)
|
| 33 |
+
2026-10-05T10:30:07 step 30000 train 0.12111 inner-val 0.12559 best 0.12559@30000 (1416s)
|
| 34 |
+
2026-10-05T10:30:53 step 31000 train 0.12059 inner-val 0.12507 best 0.12507@31000 (1462s)
|
| 35 |
+
2026-10-05T10:31:40 step 32000 train 0.12002 inner-val 0.12458 best 0.12458@32000 (1510s)
|
| 36 |
+
2026-10-05T10:32:27 step 33000 train 0.11991 inner-val 0.12414 best 0.12414@33000 (1556s)
|
| 37 |
+
2026-10-05T10:33:13 step 34000 train 0.11918 inner-val 0.12375 best 0.12375@34000 (1602s)
|
| 38 |
+
2026-10-05T10:34:00 step 35000 train 0.11839 inner-val 0.12332 best 0.12332@35000 (1650s)
|
| 39 |
+
2026-10-05T10:34:48 step 36000 train 0.11830 inner-val 0.12296 best 0.12296@36000 (1697s)
|
| 40 |
+
2026-10-05T10:35:37 step 37000 train 0.11778 inner-val 0.12259 best 0.12259@37000 (1747s)
|
| 41 |
+
2026-10-05T10:36:26 step 38000 train 0.11739 inner-val 0.12223 best 0.12223@38000 (1796s)
|
| 42 |
+
2026-10-05T10:37:16 step 39000 train 0.11724 inner-val 0.12190 best 0.12190@39000 (1845s)
|
| 43 |
+
2026-10-05T10:38:05 step 40000 train 0.11677 inner-val 0.12158 best 0.12158@40000 (1894s)
|
| 44 |
+
2026-10-05T10:38:50 step 41000 train 0.11644 inner-val 0.12128 best 0.12128@41000 (1940s)
|
| 45 |
+
2026-10-05T10:39:36 step 42000 train 0.11637 inner-val 0.12101 best 0.12101@42000 (1986s)
|
| 46 |
+
2026-10-05T10:40:22 step 43000 train 0.11591 inner-val 0.12075 best 0.12075@43000 (2032s)
|
| 47 |
+
2026-10-05T10:41:09 step 44000 train 0.11569 inner-val 0.12050 best 0.12050@44000 (2079s)
|
| 48 |
+
2026-10-05T10:41:55 step 45000 train 0.11536 inner-val 0.12024 best 0.12024@45000 (2124s)
|
| 49 |
+
2026-10-05T10:42:42 step 46000 train 0.11503 inner-val 0.11999 best 0.11999@46000 (2172s)
|
| 50 |
+
2026-10-05T10:43:28 step 47000 train 0.11474 inner-val 0.11977 best 0.11977@47000 (2218s)
|
| 51 |
+
2026-10-05T10:44:16 step 48000 train 0.11439 inner-val 0.11958 best 0.11958@48000 (2266s)
|
| 52 |
+
2026-10-05T10:45:02 step 49000 train 0.11473 inner-val 0.11941 best 0.11941@49000 (2312s)
|
| 53 |
+
2026-10-05T10:45:49 step 50000 train 0.11406 inner-val 0.11925 best 0.11925@50000 (2359s)
|
| 54 |
+
2026-10-05T10:46:36 step 51000 train 0.11390 inner-val 0.11905 best 0.11905@51000 (2406s)
|
| 55 |
+
2026-10-05T10:47:21 step 52000 train 0.11364 inner-val 0.11888 best 0.11888@52000 (2451s)
|
| 56 |
+
2026-10-05T10:48:09 step 53000 train 0.11349 inner-val 0.11871 best 0.11871@53000 (2499s)
|
| 57 |
+
2026-10-05T10:48:57 step 54000 train 0.11339 inner-val 0.11857 best 0.11857@54000 (2546s)
|
| 58 |
+
2026-10-05T10:49:44 step 55000 train 0.11302 inner-val 0.11842 best 0.11842@55000 (2594s)
|
| 59 |
+
2026-10-05T10:50:30 step 56000 train 0.11312 inner-val 0.11823 best 0.11823@56000 (2640s)
|
| 60 |
+
2026-10-05T10:51:18 step 57000 train 0.11268 inner-val 0.11807 best 0.11807@57000 (2688s)
|
| 61 |
+
2026-10-05T10:52:07 step 58000 train 0.11299 inner-val 0.11794 best 0.11794@58000 (2737s)
|
| 62 |
+
2026-10-05T10:52:53 step 59000 train 0.11259 inner-val 0.11783 best 0.11783@59000 (2783s)
|
| 63 |
+
2026-10-05T10:53:40 step 60000 train 0.11238 inner-val 0.11768 best 0.11768@60000 (2830s)
|
| 64 |
+
2026-10-05T10:54:27 step 61000 train 0.11234 inner-val 0.11759 best 0.11759@61000 (2877s)
|
| 65 |
+
2026-10-05T10:55:13 step 62000 train 0.11232 inner-val 0.11751 best 0.11751@62000 (2923s)
|
| 66 |
+
2026-10-05T10:55:58 step 63000 train 0.11196 inner-val 0.11739 best 0.11739@63000 (2968s)
|
| 67 |
+
2026-10-05T10:56:45 step 64000 train 0.11191 inner-val 0.11730 best 0.11730@64000 (3016s)
|
| 68 |
+
2026-10-05T10:57:33 step 65000 train 0.11197 inner-val 0.11723 best 0.11723@65000 (3063s)
|
| 69 |
+
2026-10-05T10:58:21 step 66000 train 0.11176 inner-val 0.11715 best 0.11715@66000 (3111s)
|
| 70 |
+
2026-10-05T10:59:09 step 67000 train 0.11147 inner-val 0.11706 best 0.11706@67000 (3159s)
|
| 71 |
+
2026-10-05T10:59:54 step 68000 train 0.11144 inner-val 0.11698 best 0.11698@68000 (3204s)
|
| 72 |
+
2026-10-05T11:00:41 step 69000 train 0.11138 inner-val 0.11689 best 0.11689@69000 (3251s)
|
| 73 |
+
2026-10-05T11:01:30 step 70000 train 0.11132 inner-val 0.11684 best 0.11684@70000 (3300s)
|
| 74 |
+
2026-10-05T11:02:16 step 71000 train 0.11114 inner-val 0.11676 best 0.11676@71000 (3346s)
|
| 75 |
+
2026-10-05T11:03:02 step 72000 train 0.11103 inner-val 0.11667 best 0.11667@72000 (3392s)
|
| 76 |
+
2026-10-05T11:03:49 step 73000 train 0.11072 inner-val 0.11656 best 0.11656@73000 (3439s)
|
| 77 |
+
2026-10-05T11:04:36 step 74000 train 0.11062 inner-val 0.11647 best 0.11647@74000 (3486s)
|
| 78 |
+
2026-10-05T11:05:20 step 75000 train 0.11075 inner-val 0.11642 best 0.11642@75000 (3530s)
|
| 79 |
+
2026-10-05T11:06:06 step 76000 train 0.11053 inner-val 0.11639 best 0.11639@76000 (3576s)
|
| 80 |
+
2026-10-05T11:06:55 step 77000 train 0.11067 inner-val 0.11635 best 0.11635@77000 (3624s)
|
| 81 |
+
2026-10-05T11:07:43 step 78000 train 0.11054 inner-val 0.11629 best 0.11629@78000 (3673s)
|
| 82 |
+
2026-10-05T11:08:31 step 79000 train 0.11020 inner-val 0.11623 best 0.11623@79000 (3721s)
|
| 83 |
+
2026-10-05T11:09:16 step 80000 train 0.11022 inner-val 0.11618 best 0.11618@80000 (3766s)
|
| 84 |
+
2026-10-05T11:10:01 step 81000 train 0.11030 inner-val 0.11611 best 0.11611@81000 (3810s)
|
| 85 |
+
2026-10-05T11:10:45 step 82000 train 0.11042 inner-val 0.11607 best 0.11607@82000 (3855s)
|
| 86 |
+
2026-10-05T11:11:30 step 83000 train 0.10992 inner-val 0.11603 best 0.11603@83000 (3900s)
|
| 87 |
+
2026-10-05T11:12:19 step 84000 train 0.11008 inner-val 0.11596 best 0.11596@84000 (3949s)
|
| 88 |
+
2026-10-05T11:13:09 step 85000 train 0.10984 inner-val 0.11591 best 0.11591@85000 (3998s)
|
| 89 |
+
2026-10-05T11:13:58 step 86000 train 0.10989 inner-val 0.11590 best 0.11590@86000 (4048s)
|
| 90 |
+
2026-10-05T11:14:47 step 87000 train 0.10989 inner-val 0.11590 best 0.11590@87000 (4097s)
|
| 91 |
+
2026-10-05T11:15:36 step 88000 train 0.10978 inner-val 0.11584 best 0.11584@88000 (4146s)
|
| 92 |
+
2026-10-05T11:16:23 step 89000 train 0.10983 inner-val 0.11579 best 0.11579@89000 (4193s)
|
| 93 |
+
2026-10-05T11:17:10 step 90000 train 0.10968 inner-val 0.11575 best 0.11575@90000 (4240s)
|
| 94 |
+
2026-10-05T11:18:00 step 91000 train 0.10964 inner-val 0.11572 best 0.11572@91000 (4289s)
|
| 95 |
+
2026-10-05T11:18:49 step 92000 train 0.10970 inner-val 0.11571 best 0.11571@92000 (4339s)
|
| 96 |
+
2026-10-05T11:19:39 step 93000 train 0.10961 inner-val 0.11568 best 0.11568@93000 (4388s)
|
| 97 |
+
2026-10-05T11:20:28 step 94000 train 0.10965 inner-val 0.11566 best 0.11566@94000 (4438s)
|
| 98 |
+
2026-10-05T11:21:18 step 95000 train 0.10936 inner-val 0.11565 best 0.11565@95000 (4487s)
|
| 99 |
+
2026-10-05T11:22:07 step 96000 train 0.10956 inner-val 0.11562 best 0.11562@96000 (4537s)
|
| 100 |
+
2026-10-05T11:22:56 step 97000 train 0.10944 inner-val 0.11556 best 0.11556@97000 (4586s)
|
| 101 |
+
2026-10-05T11:23:46 step 98000 train 0.10939 inner-val 0.11551 best 0.11551@98000 (4636s)
|
| 102 |
+
2026-10-05T11:24:36 step 99000 train 0.10913 inner-val 0.11548 best 0.11548@99000 (4686s)
|
| 103 |
+
2026-10-05T11:25:26 step 100000 train 0.10934 inner-val 0.11544 best 0.11544@100000 (4735s)
|
| 104 |
+
2026-10-05T11:25:32 saved /home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/runs/ye2026_sepsis/fold0/scratch_full/checkpoint_ft.pt (selected step 100000, inner-val 0.11544 vs pretrained 1.78181); sha de6a5f0feac4
|