| { |
| "best_score": 0.8655489015815032, |
| "best_model_path": "/root/.AUQUA-S/ULTIMATE-PERFECTION-A/iteration3_refine9_ensemble_top3_iter3", |
| "best_strategy": "ensemble_top3_iter3", |
| "best_metrics": { |
| "mel_cepstral_distortion": 0.9073272806506648, |
| "word_error_rate": 0.05749150298303143, |
| "naturalness": 0.908867224918475, |
| "intelligibility": 0.9581711548352847, |
| "speaker_similarity": 0.9349065653548081, |
| "prosody": 0.957910091322422, |
| "overall_quality": 0.8781141441008122, |
| "weighted_score": 0.8655489015815032 |
| }, |
| "iterations_performed": 3, |
| "final_model_path": "/root/.AUQUA-S/ULTIMATE-PERFECTION-A/top1_optimized_model", |
| "optimization_timestamp": "2025-05-20T00:54:58.100566", |
| "seed": 1747700296, |
| "total_strategies_tested": 34, |
| "strategy_effectiveness": { |
| "attention_scale": 1.5467091255380836, |
| "output_scale": 1.326645437230958, |
| "projection_scale": 1.4733545627690419, |
| "encoder_scale": 1.226645437230958, |
| "decoder_scale": 1.4467091255380837, |
| "base_enhancement": 0.0020902292920400084, |
| "importance_factor": 1.7600658159621485 |
| } |
| } |
