PSO/benchmark_results/pso_v4_ablation_benchmark.csv at 89850f592e5fcc4a3dfe3a25f40eca05d48ba052

mirror of https://github.com/jung-geun/PSO.git synced 2026-09-20 14:11:48 +09:00

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jung-geun 813433000a feat: modernize PSO and add convergence research

Migrate the package and examples to the tensor-native PyTorch implementation, add benchmark evidence, and add the guarded post-training convergence protocol with TensorBoard progress monitoring and hash-verified recovery.

Constraint: Preserve one-shot official-test sealing and auditable research artifacts

Rejected: Commit local .omc runs and downloaded datasets | multi-gigabyte runtime state is machine-local

Confidence: high

Scope-risk: broad

Not-tested: Production CUDA run on pieroot-server

2026-09-07 22:03:25 +09:00

2.1 KiB

Raw Blame History

1	profile	dataset	method	n_particles	epochs	n_seeds	eval_acc_mean	eval_acc_std	eval_acc_median	eval_acc_iqr	eval_acc_ci95	eval_loss_mean	eval_loss_std	eval_loss_median	eval_loss_iqr	eval_loss_ci95	eval_mse_mean	eval_mse_std	train_acc_mean	train_loss_mean	runtime_seconds_mean	runtime_seconds_std	rank_acc	rank_loss
2	adaptive_moment_.10	MNIST	adaptive_moment	30	80	5	0.63	0.018276	0.641	0.027	0.022692	1.243339	0.102561	1.253713	0.068197	0.127344	0.051633	0.002578	0.7099	0.978244	4.286662	0.289397	2	5
3	adaptive_moment_.25	MNIST	adaptive_moment	30	80	5	0.5632	0.02938	0.569	0.034	0.03648	1.499979	0.119449	1.483628	0.043413	0.148313	0.06119	0.003677	0.6379	1.228023	3.290951	0.425997	8	7
4	adaptive_moment_.50	MNIST	adaptive_moment	30	80	5	0.5186	0.039087	0.51	0.019	0.048532	1.683781	0.121571	1.683062	0.08627	0.150948	0.067331	0.003822	0.5705	1.4637	3.202502	0.269844	9	9
5	inertia_canonical	MNIST	inertia	30	80	5	0.4676	0.024358	0.472	0.033	0.030244	1.720983	0.118092	1.699598	0.020267	0.146628	0.070356	0.002531	0.5277	1.528197	3.119898	0.30594	10	10
6	inertia_tuned	MNIST	inertia	30	80	5	0.6162	0.05131	0.635	0.007	0.063709	1.2366	0.124281	1.194831	0.029657	0.154312	0.05278	0.005923	0.6931	0.999514	3.131882	0.408534	4	3
7	tuned_adam_100_lr.01	MNIST	inertia	30	80	5	0.8558	0.002387	0.856	0.003	0.002964	0.470271	0.011931	0.472233	0.019931	0.014814	0.02164	0.000368	0.9158	0.298524	4.990688	0.434352	1	1
8	tuned_full_evaluation	MNIST	inertia	30	80	5	0.6254	0.02805	0.624	0.029	0.034828	1.179009	0.050059	1.194071	0.052015	0.062156	0.051537	0.00241	0.687867	1.00514	3.377083	0.469302	3	2
9	tuned_no_mutation	MNIST	inertia	30	80	5	0.6042	0.030376	0.607	0.003	0.037716	1.249836	0.084985	1.215945	0.022012	0.105521	0.053483	0.003055	0.6686	1.074396	3.347668	0.3431	6	6
10	tuned_particle_reset	MNIST	inertia	30	80	5	0.6162	0.05131	0.635	0.007	0.063709	1.2366	0.124281	1.194831	0.029657	0.154312	0.05278	0.005923	0.6931	0.999514	4.176388	0.449217	5	4
11	tuned_uniform_initialization	MNIST	inertia	30	80	5	0.5698	0.023952	0.575	0.017	0.02974	1.619196	0.157329	1.641514	0.149905	0.195347	0.061757	0.0042	0.616	1.345857	4.306866	0.442651	7	8

2.1 KiB Raw Blame History

2.1 KiB

Raw Blame History