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Diffstat (limited to 'runs/slurm_logs/14360867_depth_exp.out')
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diff --git a/runs/slurm_logs/14360867_depth_exp.out b/runs/slurm_logs/14360867_depth_exp.out new file mode 100644 index 0000000..06d658d --- /dev/null +++ b/runs/slurm_logs/14360867_depth_exp.out @@ -0,0 +1,116 @@ +============================================================ +Job ID: 14360867 +Node: gpub040 +Start time: Sat Dec 27 06:04:46 CST 2025 +============================================================ +Configuration: + EPOCHS: 30 + DEPTHS: 2 4 6 8 10 12 + HIDDEN_DIM: 128 + LAMBDA_REG: 0.1 + LR: 0.001 + USE_SYNTHETIC: true +============================================================ +NVIDIA A40, 46068 MiB +============================================================ +Running: python files/experiments/depth_comparison.py --epochs 30 --depths 2 4 6 8 10 12 --hidden_dim 128 --lambda_reg 0.1 --lr 0.001 --seed 42 --out_dir runs/depth_comparison --device cuda --synthetic +============================================================ +====================================================================== +Experiment: Vanilla vs Lyapunov-Regularized SNN +====================================================================== +Depths: [2, 4, 6, 8, 10, 12] +Hidden dim: 128 +Epochs: 30 +Lambda_reg: 0.1 +Device: cuda + +Using SYNTHETIC data for quick testing +Data: T=50, D=100, classes=10 + +================================================== +Depth = 2 layers +================================================== + + Training VANILLA... + Final: loss=0.0000 acc=1.000 val_acc=1.000 λ=N/A ∇=0.00 + + Training LYAPUNOV... + Final: loss=0.0087 acc=1.000 val_acc=1.000 λ=0.295 ∇=0.00 + +================================================== +Depth = 4 layers +================================================== + + Training VANILLA... + Final: loss=0.0000 acc=1.000 val_acc=1.000 λ=N/A ∇=0.00 + + Training LYAPUNOV... + Final: loss=0.0429 acc=1.000 val_acc=1.000 λ=0.654 ∇=0.07 + +================================================== +Depth = 6 layers +================================================== + + Training VANILLA... + Final: loss=0.0000 acc=1.000 val_acc=1.000 λ=N/A ∇=0.00 + + Training LYAPUNOV... + Final: loss=0.0746 acc=1.000 val_acc=1.000 λ=0.859 ∇=0.20 + +================================================== +Depth = 8 layers +================================================== + + Training VANILLA... + Final: loss=0.0000 acc=1.000 val_acc=1.000 λ=N/A ∇=0.00 + + Training LYAPUNOV... + Final: loss=0.1389 acc=0.986 val_acc=0.978 λ=1.003 ∇=1.11 + +================================================== +Depth = 10 layers +================================================== + + Training VANILLA... + Final: loss=2.3013 acc=0.107 val_acc=0.084 λ=N/A ∇=0.59 + + Training LYAPUNOV... + Final: loss=0.8785 acc=0.667 val_acc=0.666 λ=1.116 ∇=7.17 + +================================================== +Depth = 12 layers +================================================== + + Training VANILLA... + Final: loss=2.3013 acc=0.107 val_acc=0.084 λ=N/A ∇=0.63 + + Training LYAPUNOV... + Final: loss=2.4441 acc=0.107 val_acc=0.084 λ=1.196 ∇=0.63 + +====================================================================== +SUMMARY: Final Validation Accuracy by Depth +====================================================================== +Depth Vanilla Lyapunov Difference +---------------------------------------------------------------------- +2 1.000 1.000 0.000 +4 1.000 1.000 0.000 +6 1.000 1.000 0.000 +8 1.000 0.978 -0.022 +10 0.084 0.666 +0.582 +12 0.084 0.084 0.000 +====================================================================== + +Gradient Norm Analysis (final epoch): +---------------------------------------------------------------------- +Depth Vanilla ∇ Lyapunov ∇ +---------------------------------------------------------------------- +2 0.00 0.00 +4 0.00 0.07 +6 0.00 0.20 +8 0.00 1.11 +10 0.59 7.17 +12 0.63 0.63 + +Results saved to runs/depth_comparison/20251227-071838 +============================================================ +Generating plots for: runs/depth_comparison/20251227-071838/ |