mirror of
https://github.com/jung-geun/PSO.git
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jung-geun
813433000a
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
53 lines
2.0 KiB
JSON
53 lines
2.0 KiB
JSON
{
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"evaluator_version": "POST-TRAINING-PSO-ENSEMBLE-EVALUATOR 1.2.0",
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"pass": true,
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"score": 22.55299842776338,
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"development_pass": true,
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"confirmation_pass": true,
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"failed_hard_gate_count": 0,
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"issues": {
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"schema": [],
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"config": [],
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"finite": [],
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"weights": [],
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"accounting": [],
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"leakage": [],
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"tuning": [],
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"slsqp": [],
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"consistency": [],
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"gates": []
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},
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"development_gates": {
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"all_values_finite": true,
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"simplex_tolerance": true,
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"validation_pool_forward_passes_each_dataset": true,
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"optimization_base_model_forward_passes": true,
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"official_test_data_loaded_before_freeze": true,
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"official_test_evaluations_before_freeze": true,
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"query_and_sample_accounting_exact": true,
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"maximum_pso_nll_regression_vs_uniform": true,
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"maximum_pso_accuracy_regression_vs_uniform_pp": true,
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"pso_nll_below_reference_single": true,
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"maximum_pso_nll_regression_vs_equal_budget_single": true,
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"maximum_relative_pso_nll_gap_vs_slsqp": true,
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"cross_dataset_mean_relative_pso_nll_reduction_vs_uniform_minimum": true,
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"maximum_median_one_seed_pso_to_pool_training_wall_ratio": true
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},
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"confirmation_gates": {
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"all_values_finite": true,
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"official_test_dataset_loads_each_dataset": true,
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"official_test_pool_forward_passes_each_dataset": true,
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"official_test_long_single_forward_passes_each_dataset": true,
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"frozen_policy_consistency": true,
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"maximum_pso_accuracy_regression_vs_uniform_pp": true,
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"pso_nll_below_reference_single": true,
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"maximum_pso_nll_regression_vs_equal_budget_single": true,
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"post_test_tuning_or_reruns": true
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},
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"metrics": {
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"mean_val_relative_nll_reduction_vs_equal_budget_single": 0.197261519715641,
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"mean_val_accuracy_gain_vs_equal_budget_single_pp": 0.09500000000000597,
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"mean_test_relative_nll_reduction_vs_equal_budget_single": 0.2263299842776338,
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"mean_test_accuracy_gain_vs_equal_budget_single_pp": -0.0799999999999983
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}
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} |