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============================================================
SCALED REGULARIZATION GRID SEARCH - DEPTH 4
Job ID: 15348084 | Node: gpub054
Start: Mon Jan 5 13:00:47 CST 2026
============================================================
Grid: λ_reg=[0.01, 0.05, 0.1, 0.3] × reg_type=[mult_linear, mult_log]
Total: 8 experiments
============================================================
NVIDIA A40, 46068 MiB
============================================================
======================================================================
SCALED REGULARIZATION GRID SEARCH
======================================================================
Depth: 4
Epochs: 100
Device: cuda
GPU: NVIDIA A40
======================================================================
Grid: 4 λ_reg × 2 reg_types = 8 experiments
λ_reg values: [0.01, 0.05, 0.1, 0.3]
reg_types: ['mult_linear', 'mult_log']
Loading CIFAR-100...
Train: 50000, Test: 10000
============================================================
Config: depth=4, reg_type=mult_linear, λ_reg=0.01
============================================================
Training Vanilla...
Epoch 10: test=0.501
Epoch 20: test=0.558
Epoch 30: test=0.585
Epoch 40: test=0.594
Epoch 50: test=0.609
Epoch 60: test=0.615
Epoch 70: test=0.624
Epoch 80: test=0.629
Epoch 90: test=0.631
Epoch 100: test=0.635
Training Lyapunov (mult_linear, λ_reg=0.01)...
Epoch 10: test=0.478 λ=1.879
Epoch 20: test=0.538 λ=1.853
Epoch 30: test=0.549 λ=1.838
Epoch 40: test=0.571 λ=1.841
Epoch 50: test=0.578 λ=1.821
Epoch 60: test=0.582 λ=1.826
Epoch 70: test=0.594 λ=1.828
Epoch 80: test=0.595 λ=1.825
Epoch 90: test=0.592 λ=1.828
Epoch 100: test=0.594 λ=1.827
Result: Vanilla=0.635, Lyap=0.595, Δ=-0.039
============================================================
Config: depth=4, reg_type=mult_log, λ_reg=0.01
============================================================
Training Vanilla...
Epoch 10: test=0.487
Epoch 20: test=0.550
Epoch 30: test=0.580
Epoch 40: test=0.590
Epoch 50: test=0.598
Epoch 60: test=0.607
Epoch 70: test=0.618
Epoch 80: test=0.622
Epoch 90: test=0.622
Epoch 100: test=0.618
Training Lyapunov (mult_log, λ_reg=0.01)...
Epoch 10: test=0.497 λ=1.881
Epoch 20: test=0.561 λ=1.850
Epoch 30: test=0.582 λ=1.844
Epoch 40: test=0.588 λ=1.837
Epoch 50: test=0.602 λ=1.842
Epoch 60: test=0.607 λ=1.853
Epoch 70: test=0.613 λ=1.854
Epoch 80: test=0.616 λ=1.861
Epoch 90: test=0.616 λ=1.862
Epoch 100: test=0.619 λ=1.860
Result: Vanilla=0.622, Lyap=0.619, Δ=-0.003
============================================================
Config: depth=4, reg_type=mult_linear, λ_reg=0.05
============================================================
Training Vanilla...
Epoch 10: test=0.485
Epoch 20: test=0.556
Epoch 30: test=0.587
Epoch 40: test=0.601
Epoch 50: test=0.608
Epoch 60: test=0.613
Epoch 70: test=0.618
Epoch 80: test=0.616
Epoch 90: test=0.625
Epoch 100: test=0.627
Training Lyapunov (mult_linear, λ_reg=0.05)...
Epoch 10: test=0.075 λ=1.435
Epoch 20: test=0.033 λ=1.436
Epoch 30: test=0.016 λ=1.440
Epoch 40: test=0.019 λ=1.445
Epoch 50: test=0.019 λ=1.444
Epoch 60: test=0.017 λ=1.448
Epoch 70: test=0.019 λ=1.452
Epoch 80: test=0.018 λ=1.454
Epoch 90: test=0.018 λ=1.454
Epoch 100: test=0.019 λ=1.456
Result: Vanilla=0.627, Lyap=0.075, Δ=-0.552
============================================================
Config: depth=4, reg_type=mult_log, λ_reg=0.05
============================================================
Training Vanilla...
Epoch 10: test=0.487
Epoch 20: test=0.553
Epoch 30: test=0.576
Epoch 40: test=0.593
Epoch 50: test=0.606
Epoch 60: test=0.616
Epoch 70: test=0.616
Epoch 80: test=0.623
Epoch 90: test=0.623
Epoch 100: test=0.628
Training Lyapunov (mult_log, λ_reg=0.05)...
Epoch 10: test=0.134 λ=1.473
Epoch 20: test=0.027 λ=1.442
Epoch 30: test=0.028 λ=1.447
Epoch 40: test=0.024 λ=1.453
Epoch 50: test=0.017 λ=1.452
Epoch 60: test=0.024 λ=1.457
Epoch 70: test=0.027 λ=1.454
Epoch 80: test=0.020 λ=1.455
Epoch 90: test=0.018 λ=1.457
Epoch 100: test=0.022 λ=1.458
Result: Vanilla=0.628, Lyap=0.134, Δ=-0.494
============================================================
Config: depth=4, reg_type=mult_linear, λ_reg=0.1
============================================================
Training Vanilla...
Epoch 10: test=0.496
Epoch 20: test=0.552
Epoch 30: test=0.578
Epoch 40: test=0.597
Epoch 50: test=0.604
Epoch 60: test=0.610
Epoch 70: test=0.615
Epoch 80: test=0.617
Epoch 90: test=0.621
Epoch 100: test=0.622
Training Lyapunov (mult_linear, λ_reg=0.1)...
Epoch 10: test=0.102 λ=1.477
Epoch 20: test=0.015 λ=1.473
Epoch 30: test=0.025 λ=1.478
Epoch 40: test=0.026 λ=1.480
Epoch 50: test=0.027 λ=1.482
Epoch 60: test=0.029 λ=1.489
Epoch 70: test=0.040 λ=1.490
Epoch 80: test=0.043 λ=1.492
Epoch 90: test=0.041 λ=1.490
Epoch 100: test=0.039 λ=1.491
Result: Vanilla=0.622, Lyap=0.102, Δ=-0.521
============================================================
Config: depth=4, reg_type=mult_log, λ_reg=0.1
============================================================
Training Vanilla...
Epoch 10: test=0.499
Epoch 20: test=0.560
Epoch 30: test=0.583
Epoch 40: test=0.601
Epoch 50: test=0.605
Epoch 60: test=0.608
Epoch 70: test=0.614
Epoch 80: test=0.621
Epoch 90: test=0.623
Epoch 100: test=0.622
Training Lyapunov (mult_log, λ_reg=0.1)...
Epoch 10: test=0.108 λ=1.444
Epoch 20: test=0.042 λ=1.436
Epoch 30: test=0.032 λ=1.445
Epoch 40: test=0.030 λ=1.447
Epoch 50: test=0.037 λ=1.452
Epoch 60: test=0.031 λ=1.455
Epoch 70: test=0.022 λ=1.457
Epoch 80: test=0.029 λ=1.463
Epoch 90: test=0.029 λ=1.466
Epoch 100: test=0.028 λ=1.464
Result: Vanilla=0.623, Lyap=0.108, Δ=-0.515
============================================================
Config: depth=4, reg_type=mult_linear, λ_reg=0.3
============================================================
Training Vanilla...
Epoch 10: test=0.507
Epoch 20: test=0.559
Epoch 30: test=0.582
Epoch 40: test=0.595
Epoch 50: test=0.609
Epoch 60: test=0.612
Epoch 70: test=0.621
Epoch 80: test=0.622
Epoch 90: test=0.624
Epoch 100: test=0.624
Training Lyapunov (mult_linear, λ_reg=0.3)...
Epoch 10: test=0.014 λ=1.526
Epoch 20: test=0.016 λ=1.498
Epoch 30: test=0.016 λ=1.440
Epoch 40: test=0.018 λ=1.437
Epoch 50: test=0.011 λ=1.446
Epoch 60: test=0.024 λ=1.447
Epoch 70: test=0.024 λ=1.447
Epoch 80: test=0.034 λ=1.446
Epoch 90: test=0.034 λ=1.444
Epoch 100: test=0.031 λ=1.442
Result: Vanilla=0.624, Lyap=0.034, Δ=-0.590
============================================================
Config: depth=4, reg_type=mult_log, λ_reg=0.3
============================================================
Training Vanilla...
Epoch 10: test=0.491
Epoch 20: test=0.557
Epoch 30: test=0.583
Epoch 40: test=0.600
Epoch 50: test=0.607
Epoch 60: test=0.611
Epoch 70: test=0.623
Epoch 80: test=0.628
Epoch 90: test=0.626
Epoch 100: test=0.630
Training Lyapunov (mult_log, λ_reg=0.3)...
Epoch 10: test=0.038 λ=1.509
Epoch 20: test=0.026 λ=1.527
Epoch 30: test=0.012 λ=1.516
Epoch 40: test=0.020 λ=1.500
Epoch 50: test=0.016 λ=1.500
Epoch 60: test=0.015 λ=1.498
Epoch 70: test=0.021 λ=1.505
Epoch 80: test=0.020 λ=1.503
Epoch 90: test=0.018 λ=1.513
Epoch 100: test=0.018 λ=1.514
Result: Vanilla=0.630, Lyap=0.038, Δ=-0.593
======================================================================
SUMMARY: DEPTH = 4
======================================================================
reg_type λ_reg Vanilla Lyapunov Δ Final λ
----------------------------------------------------------------------
mult_linear 0.01 0.635 0.595 -0.039 1.827
mult_log 0.01 0.622 0.619 -0.003 1.860
mult_linear 0.05 0.627 0.075 -0.552 1.456
mult_log 0.05 0.628 0.134 -0.494 1.458
mult_linear 0.10 0.622 0.102 -0.521 1.491
mult_log 0.10 0.623 0.108 -0.515 1.464
mult_linear 0.30 0.624 0.034 -0.590 1.442
mult_log 0.30 0.630 0.038 -0.593 1.514
----------------------------------------------------------------------
BEST: mult_log, λ_reg=0.01 → 0.619 (Δ=-0.003)
Results saved to: ./runs/scaled_grid/depth4_results.json
======================================================================
GRID SEARCH COMPLETE
======================================================================
============================================================
Finished: Tue Jan 6 00:32:27 CST 2026
============================================================
|
