加入实验输出（批次 11/14）

2026-09-23 23:36:24 +08:00
parent dc0003fa53
commit d4c11396e0
281 changed files with 139 additions and 0 deletions
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+[start] samples=100 groups=37 folds=5 seeds=[42, 3407, 2026] device=cuda
+[fold 1/5] train=80 validation=20 train_video_ids=31 validation_video_ids=6
+[fold 1] evaluate M1 and train identical probes
+[fold 1] evaluate M2 and train identical probes
+[fold 1] train M3, seed=42
+In file included from /usr/include/python3.14/pyconfig.h:6,
+                 from /usr/include/python3.14/Python.h:14,
+                 from /home/gloamxun/modeling_zhaocui/Q1/.venv/lib/python3.14/site-packages/triton/backends/nvidia/driver.c:9:
+/usr/include/python3.14/pyconfig-64.h:2031:9: warning: ‘_POSIX_C_SOURCE’ redefined
+ 2031 | #define _POSIX_C_SOURCE 200809L
+      |         ^~~~~~~~~~~~~~~
+In file included from /usr/include/bits/libc-header-start.h:33,
+                 from /usr/include/stdlib.h:26,
+                 from /home/gloamxun/modeling_zhaocui/Q1/.venv/lib/python3.14/site-packages/triton/backends/nvidia/include/cuda.h:56,
+                 from /home/gloamxun/modeling_zhaocui/Q1/.venv/lib/python3.14/site-packages/triton/backends/nvidia/driver.c:1:
+/usr/include/features.h:319:10: note: this is the location of the previous definition
+  319 | # define _POSIX_C_SOURCE        202405L
+      |          ^~~~~~~~~~~~~~~
+[fold 1] M3, seed=42 best_epoch=50 val_objective=4.93766; running frozen probes
+[fold 1] train M4, seed=42
+[fold 1] M4, seed=42 best_epoch=4 val_objective=6.07687; running frozen probes
+[fold 1] train M3, seed=3407
+[fold 1] M3, seed=3407 best_epoch=50 val_objective=4.98259; running frozen probes
+[fold 1] train M4, seed=3407
+[fold 1] M4, seed=3407 best_epoch=4 val_objective=5.87185; running frozen probes
+[fold 1] train M3, seed=2026
+[fold 1] M3, seed=2026 best_epoch=50 val_objective=5.10248; running frozen probes
+[fold 1] train M4, seed=2026
+[fold 1] M4, seed=2026 best_epoch=3 val_objective=6.09901; running frozen probes
+[fold 2/5] train=80 validation=20 train_video_ids=30 validation_video_ids=7
+[fold 2] evaluate M1 and train identical probes
+[fold 2] evaluate M2 and train identical probes
+[fold 2] train M3, seed=42
+[fold 2] M3, seed=42 best_epoch=1 val_objective=6.12588; running frozen probes
+[fold 2] train M4, seed=42
+[fold 2] M4, seed=42 best_epoch=1 val_objective=5.94268; running frozen probes
+[fold 2] train M3, seed=3407
+[fold 2] M3, seed=3407 best_epoch=50 val_objective=5.14454; running frozen probes
+[fold 2] train M4, seed=3407
+[fold 2] M4, seed=3407 best_epoch=3 val_objective=6.06774; running frozen probes
+[fold 2] train M3, seed=2026
+[fold 2] M3, seed=2026 best_epoch=50 val_objective=5.17416; running frozen probes
+[fold 2] train M4, seed=2026
+[fold 2] M4, seed=2026 best_epoch=1 val_objective=5.96431; running frozen probes
+[fold 3/5] train=80 validation=20 train_video_ids=29 validation_video_ids=8
+[fold 3] evaluate M1 and train identical probes
+[fold 3] evaluate M2 and train identical probes
+[fold 3] train M3, seed=42
+[fold 3] M3, seed=42 best_epoch=50 val_objective=4.97643; running frozen probes
+[fold 3] train M4, seed=42
+[fold 3] M4, seed=42 best_epoch=3 val_objective=6.19582; running frozen probes
+[fold 3] train M3, seed=3407
+[fold 3] M3, seed=3407 best_epoch=50 val_objective=4.65949; running frozen probes
+[fold 3] train M4, seed=3407
+[fold 3] M4, seed=3407 best_epoch=9 val_objective=5.91066; running frozen probes
+[fold 3] train M3, seed=2026
+[fold 3] M3, seed=2026 best_epoch=50 val_objective=4.99993; running frozen probes
+[fold 3] train M4, seed=2026
+[fold 3] M4, seed=2026 best_epoch=3 val_objective=6.02409; running frozen probes
+[fold 4/5] train=80 validation=20 train_video_ids=29 validation_video_ids=8
+[fold 4] evaluate M1 and train identical probes
+[fold 4] evaluate M2 and train identical probes
+[fold 4] train M3, seed=42
+[fold 4] M3, seed=42 best_epoch=50 val_objective=5.15230; running frozen probes
+[fold 4] train M4, seed=42
+[fold 4] M4, seed=42 best_epoch=1 val_objective=5.99857; running frozen probes
+[fold 4] train M3, seed=3407
+[fold 4] M3, seed=3407 best_epoch=50 val_objective=5.09800; running frozen probes
+[fold 4] train M4, seed=3407
+[fold 4] M4, seed=3407 best_epoch=2 val_objective=6.03456; running frozen probes
+[fold 4] train M3, seed=2026
+[fold 4] M3, seed=2026 best_epoch=50 val_objective=5.26026; running frozen probes
+[fold 4] train M4, seed=2026
+[fold 4] M4, seed=2026 best_epoch=2 val_objective=6.08121; running frozen probes
+[fold 5/5] train=80 validation=20 train_video_ids=29 validation_video_ids=8
+[fold 5] evaluate M1 and train identical probes
+[fold 5] evaluate M2 and train identical probes
+[fold 5] train M3, seed=42
+[fold 5] M3, seed=42 best_epoch=50 val_objective=5.29874; running frozen probes
+[fold 5] train M4, seed=42
+[fold 5] M4, seed=42 best_epoch=4 val_objective=6.02189; running frozen probes
+[fold 5] train M3, seed=3407
+[fold 5] M3, seed=3407 best_epoch=50 val_objective=4.95355; running frozen probes
+[fold 5] train M4, seed=3407
+[fold 5] M4, seed=3407 best_epoch=8 val_objective=6.05872; running frozen probes
+[fold 5] train M3, seed=2026
+[fold 5] M3, seed=2026 best_epoch=50 val_objective=5.13369; running frozen probes
+[fold 5] train M4, seed=2026
+[fold 5] M4, seed=2026 best_epoch=1 val_objective=5.88269; running frozen probes
+[done] elapsed_seconds=516.3 output=/home/gloamxun/modeling_zhaocui/Q1/outputs/method_comparison
+{
+  "created_utc": "2026-09-23T09:07:49.626404+00:00",
+  "sample_count": 100,
+  "group_count": 37,
+  "folds": 5,
+  "seeds": [
+    42,
+    3407,
+    2026
+  ],
+  "device": "cuda",
+  "gpu_name": "NVIDIA GeForce RTX 5070 Ti",
+  "python": "3.14.7",
+  "torch": "2.14.0+cu130",
+  "parameters": {
+    "grid_size": 50,
+    "hidden_size": 128,
+    "heads": 4,
+    "dropout": 0.1,
+    "batch_size": 8,
+    "epochs_max": 50,
+    "early_stopping_patience": 8,
+    "learning_rate": 0.0001,
+    "mask_ratio": 0.2,
+    "retrieval_probe_epochs": 20,
+    "reconstruction_probe_epochs": 25,
+    "mvr_epsilon": 0.02
+  },
+  "objective": "masked reconstruction + cross-modal contrastive + temporal monotonicity; emotion labels unused",
+  "split_rule": "GroupKFold by group_id/video_id",
+  "example_sample_id": "-tPCytz4rww/12",
+  "elapsed_seconds": 516.2944533824921,
+  "interpretation_limits": [
+    "Grid-index retrieval is a representation-consistency probe, not independent temporal ground truth.",
+    "Masked reconstruction uses a decoder trained on the training fold and reports standardized-feature errors.",
+    "The emotion probe is a small-sample downstream utility check, not a claim of generalization to MOSEI.",
+    "No human event timestamps are available, so human IoU/MATE is not reported."
+  ]
+}