diff --git a/Analysis_code/5.optima/deepgbm_ctgan10000/deepgbm_ctgan10000_busan.py b/Analysis_code/5.optima/deepgbm_ctgan10000/deepgbm_ctgan10000_busan.py deleted file mode 100644 index 788cea44053ad670194c8eecd929c48f284078dc..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/deepgbm_ctgan10000/deepgbm_ctgan10000_busan.py +++ /dev/null @@ -1,98 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="deepgbm", region="busan", data_sample='ctgan10000'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/deepgbm_ctgan10000_busan_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="deepgbm", - region="busan", - data_sample='ctgan10000', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - - diff --git a/Analysis_code/5.optima/deepgbm_ctgan10000/deepgbm_ctgan10000_daegu.py b/Analysis_code/5.optima/deepgbm_ctgan10000/deepgbm_ctgan10000_daegu.py deleted file mode 100644 index 1d5a39d710cea7d01ca8ccc2e2e31d3c98c4eae1..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/deepgbm_ctgan10000/deepgbm_ctgan10000_daegu.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="deepgbm", region="daegu", data_sample='ctgan10000'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/deepgbm_ctgan10000_daegu_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="deepgbm", - region="daegu", - data_sample='ctgan10000', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/deepgbm_ctgan10000/deepgbm_ctgan10000_daejeon.py b/Analysis_code/5.optima/deepgbm_ctgan10000/deepgbm_ctgan10000_daejeon.py deleted file mode 100644 index c8efef41d596aaaf953f543e366e57b528b92275..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/deepgbm_ctgan10000/deepgbm_ctgan10000_daejeon.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="deepgbm", region="daejeon", data_sample='ctgan10000'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/deepgbm_ctgan10000_daejeon_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="deepgbm", - region="daejeon", - data_sample='ctgan10000', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/deepgbm_ctgan10000/deepgbm_ctgan10000_gwangju.py b/Analysis_code/5.optima/deepgbm_ctgan10000/deepgbm_ctgan10000_gwangju.py deleted file mode 100644 index c540a056a07f7393ca64a8b9e089ea4ae9549963..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/deepgbm_ctgan10000/deepgbm_ctgan10000_gwangju.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="deepgbm", region="gwangju", data_sample='ctgan10000'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/deepgbm_ctgan10000_gwangju_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="deepgbm", - region="gwangju", - data_sample='ctgan10000', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/deepgbm_ctgan10000/deepgbm_ctgan10000_incheon.py b/Analysis_code/5.optima/deepgbm_ctgan10000/deepgbm_ctgan10000_incheon.py deleted file mode 100644 index a922d8672e246c19407c698ac1e176ed04faa68e..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/deepgbm_ctgan10000/deepgbm_ctgan10000_incheon.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="deepgbm", region="incheon", data_sample='ctgan10000'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/deepgbm_ctgan10000_incheon_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="deepgbm", - region="incheon", - data_sample='ctgan10000', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/deepgbm_ctgan10000/deepgbm_ctgan10000_seoul.py b/Analysis_code/5.optima/deepgbm_ctgan10000/deepgbm_ctgan10000_seoul.py deleted file mode 100644 index 857377bc5eee04cba68aa40fa45771dd5c3233ac..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/deepgbm_ctgan10000/deepgbm_ctgan10000_seoul.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="deepgbm", region="seoul", data_sample='ctgan10000'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/deepgbm_ctgan10000_seoul_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="deepgbm", - region="seoul", - data_sample='ctgan10000', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/deepgbm_ctgan10000/utils.py b/Analysis_code/5.optima/deepgbm_ctgan10000/utils.py deleted file mode 100644 index f10f57cf1d7068283adc210ebbe768b3ec03a98d..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/deepgbm_ctgan10000/utils.py +++ /dev/null @@ -1,721 +0,0 @@ -import torch -import torch.nn as nn -import torch.optim as optim -import numpy as np -import random -import os -import copy -from sklearn.preprocessing import QuantileTransformer, LabelEncoder -from torch.utils.data import DataLoader, TensorDataset -from sklearn.metrics import confusion_matrix -from sklearn.utils.class_weight import compute_class_weight -import pandas as pd -import optuna -from sklearn.metrics import accuracy_score, f1_score -import joblib - - -import sys -# 파일 위치 기반으로 models 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -models_path = os.path.abspath(os.path.join(current_file_dir, '../../models')) -sys.path.insert(0, models_path) -from ft_transformer import FTTransformer -from resnet_like import ResNetLike -from deepgbm import DeepGBM -import warnings -warnings.filterwarnings('ignore') - - -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - -# PyTorch 시드 고정 -torch.manual_seed(seed) -torch.cuda.manual_seed(seed) -torch.cuda.manual_seed_all(seed) # Multi-GPU 환경에서 동일한 시드 적용 - -# PyTorch 연산의 결정적 모드 설정 -torch.backends.cudnn.deterministic = True # 실행마다 동일한 결과를 보장 -torch.backends.cudnn.benchmark = True # 성능 최적화를 활성화 (가능한 한 빠른 연산 수행) - - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - - -# 데이터셋 준비 함수 -def prepare_dataset(region, data_sample='pure', target='multi', fold=3): - - # 파일 위치 기반으로 데이터 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) - - # 데이터 경로 지정 - dat_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_train.csv") - if data_sample == 'pure': - train_path = dat_path - else: - train_path = os.path.join(data_base_dir, f'data_oversampled/{data_sample}/{data_sample}_{fold}_{region}.csv') - test_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_test.csv") - drop_col = ['multi_class','year'] - target_col = f'{target}_class' - - # 데이터 로드 - region_dat = preprocessing(pd.read_csv(dat_path, index_col=0)) - if data_sample == 'pure': - region_train = region_dat.loc[~region_dat['year'].isin([2021-fold]), :] - else: - region_train = preprocessing(pd.read_csv(train_path)) - region_val = region_dat.loc[region_dat['year'].isin([2021-fold]), :] - region_test = preprocessing(pd.read_csv(test_path)) - - # 컬럼 정렬 (일관성 유지) - common_columns = region_train.columns.to_list() - train_data = region_train[common_columns] - val_data = region_val[common_columns] - test_data = region_test[common_columns] - - # 설명변수 & 타겟 분리 - X_train = train_data.drop(columns=drop_col) - y_train = train_data[target_col] - X_val = val_data.drop(columns=drop_col) - y_val = val_data[target_col] - X_test = test_data.drop(columns=drop_col) - y_test = test_data[target_col] - - # 범주형 & 연속형 변수 분리 - categorical_cols = X_train.select_dtypes(include=['object', 'category', 'int64']).columns - numerical_cols = X_train.select_dtypes(include=['float64']).columns - - # 범주형 변수 Label Encoding - label_encoders = {} - for col in categorical_cols: - le = LabelEncoder() - le.fit(X_train[col]) # Train 데이터 기준으로 학습 - label_encoders[col] = le - - # 변환 적용 - for col in categorical_cols: - X_train[col] = label_encoders[col].transform(X_train[col]) - X_val[col] = label_encoders[col].transform(X_val[col]) - X_test[col] = label_encoders[col].transform(X_test[col]) - - # 연속형 변수 Quantile Transformation - scaler = QuantileTransformer(output_distribution='normal') - scaler.fit(X_train[numerical_cols]) # Train 데이터 기준으로 학습 - - # 변환 적용 - X_train[numerical_cols] = scaler.transform(X_train[numerical_cols]) - X_val[numerical_cols] = scaler.transform(X_val[numerical_cols]) - X_test[numerical_cols] = scaler.transform(X_test[numerical_cols]) - - return X_train, X_val, X_test, y_train, y_val, y_test, categorical_cols, numerical_cols - - - -# 데이터 변환 및 dataloader 생성 함수 -def prepare_dataloader(region, data_sample='pure', target='multi', fold=3, random_state=None): - - # 파일 위치 기반으로 데이터 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) - - # 데이터 경로 지정 - dat_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_train.csv") - if data_sample == 'pure': - train_path = dat_path - else: - train_path = os.path.join(data_base_dir, f'data_oversampled/{data_sample}/{data_sample}_{fold}_{region}.csv') - test_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_test.csv") - drop_col = ['multi_class','year'] - target_col = f'{target}_class' - - # 데이터 로드 - region_dat = preprocessing(pd.read_csv(dat_path, index_col=0)) - if data_sample == 'pure': - region_train = region_dat.loc[~region_dat['year'].isin([2021-fold]), :] - else: - region_train = preprocessing(pd.read_csv(train_path)) - region_val = region_dat.loc[region_dat['year'].isin([2021-fold]), :] - region_test = preprocessing(pd.read_csv(test_path)) - - # 컬럼 정렬 (일관성 유지) - common_columns = region_train.columns.to_list() - train_data = region_train[common_columns] - val_data = region_val[common_columns] - test_data = region_test[common_columns] - - # 설명변수 & 타겟 분리 - X_train = train_data.drop(columns=drop_col) - y_train = train_data[target_col] - X_val = val_data.drop(columns=drop_col) - y_val = val_data[target_col] - X_test = test_data.drop(columns=drop_col) - y_test = test_data[target_col] - - # 범주형 & 연속형 변수 분리 - categorical_cols = X_train.select_dtypes(include=['object', 'category', 'int64']).columns - numerical_cols = X_train.select_dtypes(include=['float64']).columns - - # 범주형 변수 Label Encoding - label_encoders = {} - for col in categorical_cols: - le = LabelEncoder() - le.fit(X_train[col]) # Train 데이터 기준으로 학습 - label_encoders[col] = le - - # 변환 적용 - for col in categorical_cols: - X_train[col] = label_encoders[col].transform(X_train[col]) - X_val[col] = label_encoders[col].transform(X_val[col]) - X_test[col] = label_encoders[col].transform(X_test[col]) - - # 연속형 변수 Quantile Transformation - scaler = QuantileTransformer(output_distribution='normal') - scaler.fit(X_train[numerical_cols]) # Train 데이터 기준으로 학습 - - # 변환 적용 - X_train[numerical_cols] = scaler.transform(X_train[numerical_cols]) - X_val[numerical_cols] = scaler.transform(X_val[numerical_cols]) - X_test[numerical_cols] = scaler.transform(X_test[numerical_cols]) - - # 연속형 변수와 범주형 변수 분리 - X_train_num = torch.tensor(X_train[numerical_cols].values, dtype=torch.float32) - X_train_cat = torch.tensor(X_train[categorical_cols].values, dtype=torch.long) - - X_val_num = torch.tensor(X_val[numerical_cols].values, dtype=torch.float32) - X_val_cat = torch.tensor(X_val[categorical_cols].values, dtype=torch.long) - - X_test_num = torch.tensor(X_test[numerical_cols].values, dtype=torch.float32) - X_test_cat = torch.tensor(X_test[categorical_cols].values, dtype=torch.long) - - # 레이블 변환 - if target == "binary": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.float32) # 이진 분류 → float32 - y_val_tensor = torch.tensor(y_val.values, dtype=torch.float32) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.float32) - elif target == "multi": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.long) # 다중 분류 → long - y_val_tensor = torch.tensor(y_val.values, dtype=torch.long) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.long) - else: - raise ValueError("target must be 'binary' or 'multi'") - - # TensorDataset 생성 - train_dataset = TensorDataset(X_train_num, X_train_cat, y_train_tensor) - val_dataset = TensorDataset(X_val_num, X_val_cat, y_val_tensor) - test_dataset = TensorDataset(X_test_num, X_test_cat, y_test_tensor) - - # DataLoader 생성 - if random_state == None: - train_loader = DataLoader(train_dataset, batch_size=64, shuffle=True) - else: - train_loader = DataLoader(train_dataset, batch_size=64, shuffle=True, generator=torch.Generator().manual_seed(random_state)) - val_loader = DataLoader(val_dataset, batch_size=64, shuffle=False) - test_loader = DataLoader(test_dataset, batch_size=64, shuffle=False) - - return X_train, categorical_cols, numerical_cols, train_loader, val_loader, test_loader - -# 데이터 변환 및 dataloader 생성 함수 (batch_size 파라미터 추가 버전) -def prepare_dataloader_with_batchsize(region, data_sample='pure', target='multi', fold=3, random_state=None, batch_size=64): - # 파일 위치 기반으로 데이터 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) - - # 데이터 경로 지정 - dat_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_train.csv") - if data_sample == 'pure': - train_path = dat_path - else: - train_path = os.path.join(data_base_dir, f'data_oversampled/{data_sample}/{data_sample}_{fold}_{region}.csv') - test_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_test.csv") - drop_col = ['multi_class','year'] - target_col = f'{target}_class' - - # 데이터 로드 - region_dat = preprocessing(pd.read_csv(dat_path, index_col=0)) - if data_sample == 'pure': - region_train = region_dat.loc[~region_dat['year'].isin([2021-fold]), :] - else: - region_train = preprocessing(pd.read_csv(train_path)) - region_val = region_dat.loc[region_dat['year'].isin([2021-fold]), :] - region_test = preprocessing(pd.read_csv(test_path)) - - # 컬럼 정렬 (일관성 유지) - common_columns = region_train.columns.to_list() - train_data = region_train[common_columns] - val_data = region_val[common_columns] - test_data = region_test[common_columns] - - # 설명변수 & 타겟 분리 - X_train = train_data.drop(columns=drop_col) - y_train = train_data[target_col] - X_val = val_data.drop(columns=drop_col) - y_val = val_data[target_col] - X_test = test_data.drop(columns=drop_col) - y_test = test_data[target_col] - - # 범주형 & 연속형 변수 분리 - categorical_cols = X_train.select_dtypes(include=['object', 'category', 'int64']).columns - numerical_cols = X_train.select_dtypes(include=['float64']).columns - - # 범주형 변수 Label Encoding - label_encoders = {} - for col in categorical_cols: - le = LabelEncoder() - le.fit(X_train[col]) # Train 데이터 기준으로 학습 - label_encoders[col] = le - - # 변환 적용 - for col in categorical_cols: - X_train[col] = label_encoders[col].transform(X_train[col]) - X_val[col] = label_encoders[col].transform(X_val[col]) - X_test[col] = label_encoders[col].transform(X_test[col]) - - # 연속형 변수 Quantile Transformation - scaler = QuantileTransformer(output_distribution='normal') - scaler.fit(X_train[numerical_cols]) # Train 데이터 기준으로 학습 - - # 변환 적용 - X_train[numerical_cols] = scaler.transform(X_train[numerical_cols]) - X_val[numerical_cols] = scaler.transform(X_val[numerical_cols]) - X_test[numerical_cols] = scaler.transform(X_test[numerical_cols]) - - # 연속형 변수와 범주형 변수 분리 - X_train_num = torch.tensor(X_train[numerical_cols].values, dtype=torch.float32) - X_train_cat = torch.tensor(X_train[categorical_cols].values, dtype=torch.long) - - X_val_num = torch.tensor(X_val[numerical_cols].values, dtype=torch.float32) - X_val_cat = torch.tensor(X_val[categorical_cols].values, dtype=torch.long) - - X_test_num = torch.tensor(X_test[numerical_cols].values, dtype=torch.float32) - X_test_cat = torch.tensor(X_test[categorical_cols].values, dtype=torch.long) - - # 레이블 변환 - if target == "binary": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.float32) # 이진 분류 → float32 - y_val_tensor = torch.tensor(y_val.values, dtype=torch.float32) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.float32) - elif target == "multi": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.long) # 다중 분류 → long - y_val_tensor = torch.tensor(y_val.values, dtype=torch.long) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.long) - else: - raise ValueError("target must be 'binary' or 'multi'") - - # TensorDataset 생성 - train_dataset = TensorDataset(X_train_num, X_train_cat, y_train_tensor) - val_dataset = TensorDataset(X_val_num, X_val_cat, y_val_tensor) - test_dataset = TensorDataset(X_test_num, X_test_cat, y_test_tensor) - - # DataLoader 생성 (batch_size 파라미터 사용) - if random_state == None: - train_loader = DataLoader(train_dataset, batch_size=batch_size, shuffle=True) - else: - train_loader = DataLoader(train_dataset, batch_size=batch_size, shuffle=True, generator=torch.Generator().manual_seed(random_state)) - val_loader = DataLoader(val_dataset, batch_size=batch_size, shuffle=False) - test_loader = DataLoader(test_dataset, batch_size=batch_size, shuffle=False) - - return X_train, categorical_cols, numerical_cols, train_loader, val_loader, test_loader, y_train, scaler - - -def calculate_csi(y_true, pred): - - cm = confusion_matrix(y_true, pred) # 변수 이름을 cm으로 변경 - # 혼동 행렬에서 H, F, M 추출 - H = (cm[0, 0] + cm[1, 1]) - - F = (cm[1, 0] + cm[2, 0] + - cm[0, 1] + cm[2, 1]) - - M = (cm[0, 2] + cm[1, 2]) - - # CSI 계산 - CSI = H / (H + F + M + 1e-10) - return CSI - -def sample_weight(y_train): - class_weights = compute_class_weight( - class_weight='balanced', - classes=np.unique(y_train), # 고유 클래스 - y=y_train # 학습 데이터 레이블 - ) - sample_weights = np.array([class_weights[label] for label in y_train]) - - return sample_weights - -# 하이퍼파라미터 최적화 함수 정의 -def objective(trial, model_choose, region, data_sample='pure', target='multi', n_folds=3, random_state=42): - # GPU 사용 가능 여부 확인 및 device 설정 - device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') - val_scores = [] - - # --- 1. 하이퍼파라미터 탐색 범위 정의 (수정됨) --- - if model_choose == "ft_transformer": - d_token = trial.suggest_int("d_token", 64, 256, step=32) - n_blocks = trial.suggest_int("n_blocks", 2, 6) # 깊이 축소로 과적합 방지 - n_heads = trial.suggest_categorical("n_heads", [4, 8]) - # d_token은 n_heads의 배수여야 함 (FT-Transformer의 구조적 제약 대응) - if d_token % n_heads != 0: - d_token = (d_token // n_heads) * n_heads - - attention_dropout = trial.suggest_float("attention_dropout", 0.1, 0.4) - ffn_dropout = trial.suggest_float("ffn_dropout", 0.1, 0.4) - lr = trial.suggest_float("lr", 1e-5, 1e-2, log=True) # 범위 확대 - weight_decay = trial.suggest_float("weight_decay", 1e-4, 1e-1, log=True) # 더 공격적인 범위로 확장 - batch_size = trial.suggest_categorical("batch_size", [32, 64, 128, 256]) # Batch Size 추가 - - elif model_choose == 'resnet_like': - d_main = trial.suggest_int("d_main", 64, 256, step=32) - d_hidden = trial.suggest_int("d_hidden", 64, 512, step=64) - n_blocks = trial.suggest_int("n_blocks", 2, 5) # 너무 깊지 않게 조절 - dropout_first = trial.suggest_float("dropout_first", 0.1, 0.4) - dropout_second = trial.suggest_float("dropout_second", 0.0, 0.2) - lr = trial.suggest_float("lr", 1e-5, 1e-2, log=True) - weight_decay = trial.suggest_float("weight_decay", 1e-4, 1e-1, log=True) # 더 공격적인 범위로 확장 - batch_size = trial.suggest_categorical("batch_size", [32, 64, 128, 256]) # Batch Size 추가 - - elif model_choose == 'deepgbm': - # DeepGBM의 경우 모델 특성에 맞춰 ResNet 블록 및 임베딩 차원 조절 - d_main = trial.suggest_int("d_main", 64, 256, step=32) - d_hidden = trial.suggest_int("d_hidden", 64, 256, step=64) - n_blocks = trial.suggest_int("n_blocks", 2, 6) - dropout = trial.suggest_float("dropout", 0.1, 0.4) - lr = trial.suggest_float("lr", 1e-5, 1e-2, log=True) - weight_decay = trial.suggest_float("weight_decay", 1e-4, 1e-1, log=True) # 더 공격적인 범위로 확장 - batch_size = trial.suggest_categorical("batch_size", [32, 64, 128, 256]) # Batch Size 추가 - - # --- 2. Fold별 학습 및 교차 검증 --- - for fold in range(1, n_folds + 1): - X_train_df, categorical_cols, numerical_cols, train_loader, val_loader, _, y_train, _ = prepare_dataloader_with_batchsize( - region, data_sample=data_sample, target=target, fold=fold, random_state=random_state, batch_size=batch_size - ) - - # 모델 초기화 - if model_choose == "ft_transformer": - model = FTTransformer( - num_features=len(numerical_cols), - cat_cardinalities=[len(X_train_df[col].unique()) for col in categorical_cols], - d_token=d_token, - n_blocks=n_blocks, - n_heads=n_heads, - attention_dropout=attention_dropout, - ffn_dropout=ffn_dropout, - num_classes=3 - ).to(device) - elif model_choose == 'resnet_like': - input_dim = len(numerical_cols) + len(categorical_cols) - model = ResNetLike( - input_dim=input_dim, - d_main=d_main, - d_hidden=d_hidden, - n_blocks=n_blocks, - dropout_first=dropout_first, - dropout_second=dropout_second, - num_classes=3 - ).to(device) - elif model_choose == 'deepgbm': - model = DeepGBM( - num_features=len(numerical_cols), - cat_features=[len(X_train_df[col].unique()) for col in categorical_cols], - d_main=d_main, - d_hidden=d_hidden, - n_blocks=n_blocks, - dropout=dropout, - num_classes=3 - ).to(device) - - # 클래스 가중치 계산 및 손실 함수 설정 (Label Smoothing 적용) - if target == 'multi': - class_weights = compute_class_weight( - class_weight='balanced', - classes=np.unique(y_train), - y=y_train - ) - # 클래스별 가중치 로그 출력 - unique_classes = np.unique(y_train) - class_counts = {cls: np.sum(y_train == cls) for cls in unique_classes} - print(f" Fold {fold} - 클래스별 가중치: {dict(zip(unique_classes, class_weights))} (클래스별 샘플 수: {class_counts})") - class_weights_tensor = torch.tensor(class_weights, dtype=torch.float32).to(device) - criterion = nn.CrossEntropyLoss(weight=class_weights_tensor, label_smoothing=0.0) # Label Smoothing 추가 - else: - criterion = nn.BCEWithLogitsLoss() - optimizer = optim.AdamW(model.parameters(), lr=lr, weight_decay=weight_decay) - - # 학습률 스케줄러 추가: 성능 정체 시 LR을 0.5배 감소 (검증 CSI 기준) - scheduler = optim.lr_scheduler.ReduceLROnPlateau(optimizer, mode='max', factor=0.5, patience=3) - - # 학습 설정 (에폭 및 페이션스 상향) - epochs = 200 - patience = 12 # 딥러닝의 정체 구간을 고려하여 소폭 상향 - best_fold_csi = 0 - counter = 0 - - for epoch in range(epochs): - model.train() - for x_num_batch, x_cat_batch, y_batch in train_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - - optimizer.zero_grad() - y_pred = model(x_num_batch, x_cat_batch) - loss = criterion(y_pred, y_batch if target == 'multi' else y_batch.float()) - loss.backward() - optimizer.step() - - # Validation 평가 - model.eval() - y_pred_val, y_true_val = [], [] - with torch.no_grad(): - for x_num_batch, x_cat_batch, y_batch in val_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - output = model(x_num_batch, x_cat_batch) - pred = output.argmax(dim=1) if target == 'multi' else (torch.sigmoid(output) >= 0.5).long() - - y_pred_val.extend(pred.cpu().numpy()) - y_true_val.extend(y_batch.cpu().numpy()) - - # CSI 계산 및 스케줄러 업데이트 - val_csi = calculate_csi(y_true_val, y_pred_val) - scheduler.step(val_csi) - - # Optuna Pruning 적용 (첫 번째 Fold에서 조기 종료 판단 강화) - trial.report(val_csi, epoch) - if trial.should_prune(): - raise optuna.exceptions.TrialPruned() - - # Early Stopping 체크 - if val_csi > best_fold_csi: - best_fold_csi = val_csi - counter = 0 - else: - counter += 1 - - if counter >= patience: - break - - val_scores.append(best_fold_csi) - - # 모든 fold의 평균 성능 반환 - return np.mean(val_scores) - - -# 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 함수 -def train_final_model(best_params, model_choose, region, data_sample='pure', target='multi', n_folds=3, random_state=42): - """ - 최적화된 하이퍼파라미터로 최종 모델을 학습하고 저장합니다. - - Args: - best_params: 최적화된 하이퍼파라미터 딕셔너리 - model_choose: 모델 선택 ('ft_transformer', 'resnet_like', 'deepgbm') - region: 지역명 - data_sample: 데이터 샘플 타입 ('pure', 'smote', etc.) - target: 타겟 타입 ('multi', 'binary') - n_folds: 교차 검증 fold 수 - random_state: 랜덤 시드 - - Returns: - 저장된 모델 경로 리스트 - """ - # GPU 사용 가능 여부 확인 및 device 설정 - device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') - - models = [] - scalers = [] # scaler 리스트 추가 - - print("최종 모델 학습 시작...") - - for fold in range(1, n_folds + 1): - print(f"Fold {fold} 학습 중...") - - # 최적화된 batch_size 사용 - batch_size = best_params.get("batch_size", 64) - X_train_df, categorical_cols, numerical_cols, train_loader, val_loader, _, y_train, scaler = prepare_dataloader_with_batchsize( - region, data_sample=data_sample, target=target, fold=fold, random_state=random_state, batch_size=batch_size - ) - - # 모델 초기화 - if model_choose == "ft_transformer": - d_token = best_params["d_token"] - n_heads = best_params.get("n_heads", 8) - # d_token은 n_heads의 배수여야 함 (FT-Transformer의 구조적 제약 대응) - if d_token % n_heads != 0: - d_token = (d_token // n_heads) * n_heads - - model = FTTransformer( - num_features=len(numerical_cols), - cat_cardinalities=[len(X_train_df[col].unique()) for col in categorical_cols], - d_token=d_token, - n_blocks=best_params["n_blocks"], - n_heads=n_heads, - attention_dropout=best_params["attention_dropout"], - ffn_dropout=best_params["ffn_dropout"], - num_classes=3 - ).to(device) - elif model_choose == 'resnet_like': - input_dim = len(numerical_cols) + len(categorical_cols) - model = ResNetLike( - input_dim=input_dim, - d_main=best_params["d_main"], - d_hidden=best_params["d_hidden"], - n_blocks=best_params["n_blocks"], - dropout_first=best_params["dropout_first"], - dropout_second=best_params["dropout_second"], - num_classes=3 - ).to(device) - elif model_choose == 'deepgbm': - model = DeepGBM( - num_features=len(numerical_cols), - cat_features=[len(X_train_df[col].unique()) for col in categorical_cols], - d_main=best_params["d_main"], - d_hidden=best_params["d_hidden"], - n_blocks=best_params["n_blocks"], - dropout=best_params["dropout"], - num_classes=3 - ).to(device) - else: - raise ValueError(f"Unknown model_choose: {model_choose}") - - # 클래스 가중치 계산 및 손실 함수 설정 (Label Smoothing 적용) - if target == 'multi': - class_weights = compute_class_weight( - class_weight='balanced', - classes=np.unique(y_train), - y=y_train - ) - class_weights_tensor = torch.tensor(class_weights, dtype=torch.float32).to(device) - criterion = nn.CrossEntropyLoss(weight=class_weights_tensor, label_smoothing=0.0) # Label Smoothing 추가 - else: - criterion = nn.BCEWithLogitsLoss() - optimizer = optim.AdamW(model.parameters(), lr=best_params["lr"], weight_decay=best_params["weight_decay"]) - - # 학습률 스케줄러 - scheduler = optim.lr_scheduler.ReduceLROnPlateau(optimizer, mode='max', factor=0.5, patience=3) - - # 학습 설정 - epochs = 200 - patience = 12 - best_fold_csi = 0 - counter = 0 - best_model = None - - for epoch in range(epochs): - model.train() - for x_num_batch, x_cat_batch, y_batch in train_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - - optimizer.zero_grad() - y_pred = model(x_num_batch, x_cat_batch) - loss = criterion(y_pred, y_batch if target == 'multi' else y_batch.float()) - loss.backward() - optimizer.step() - - # Validation 평가 - model.eval() - y_pred_val, y_true_val = [], [] - with torch.no_grad(): - for x_num_batch, x_cat_batch, y_batch in val_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - output = model(x_num_batch, x_cat_batch) - pred = output.argmax(dim=1) if target == 'multi' else (torch.sigmoid(output) >= 0.5).long() - - y_pred_val.extend(pred.cpu().numpy()) - y_true_val.extend(y_batch.cpu().numpy()) - - # CSI 계산 및 스케줄러 업데이트 - val_csi = calculate_csi(y_true_val, y_pred_val) - scheduler.step(val_csi) - - # Early Stopping 체크 - if val_csi > best_fold_csi: - best_fold_csi = val_csi - counter = 0 - best_model = copy.deepcopy(model) - else: - counter += 1 - - if counter >= patience: - print(f" Early stopping at epoch {epoch+1}, Best CSI: {best_fold_csi:.4f}") - break - - if best_model is None: - best_model = model - - scalers.append(scaler) # scaler 저장 (fold 순서대로) - models.append(best_model) - print(f" Fold {fold} 학습 완료 (검증 CSI: {best_fold_csi:.4f})") - - # 모델 저장 경로 설정 - save_dir = f'../save_model/{model_choose}_optima' - os.makedirs(save_dir, exist_ok=True) - - # 파일명 생성 - if data_sample == 'pure': - model_filename = f'{model_choose}_pure_{region}.pkl' - else: - model_filename = f'{model_choose}_{data_sample}_{region}.pkl' - - model_path = f'{save_dir}/{model_filename}' - - # 리스트에 담아 한 번에 저장 - joblib.dump(models, model_path) - print(f"\n모든 모델 저장 완료: {model_path} (총 {len(models)}개 fold)") - - # Scaler 별도 저장 - scaler_save_dir = f'../save_model/{model_choose}_optima/scaler' - os.makedirs(scaler_save_dir, exist_ok=True) - - # 파일명 생성 (모델과 동일한 패턴) - if data_sample == 'pure': - scaler_filename = f'{model_choose}_pure_{region}_scaler.pkl' - else: - scaler_filename = f'{model_choose}_{data_sample}_{region}_scaler.pkl' - - scaler_path = f'{scaler_save_dir}/{scaler_filename}' - joblib.dump(scalers, scaler_path) - print(f"Scaler 저장 완료: {scaler_path} (총 {len(scalers)}개 fold)") - - return model_path - diff --git a/Analysis_code/5.optima/deepgbm_pure/deepgbm_pure_busan.py b/Analysis_code/5.optima/deepgbm_pure/deepgbm_pure_busan.py deleted file mode 100644 index 286ee0105659d8941c4ed7ea29d196d5803de771..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/deepgbm_pure/deepgbm_pure_busan.py +++ /dev/null @@ -1,98 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="deepgbm", region="busan"), - n_trials=100, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/deepgbm_pure_busan_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_paths = train_final_model( - best_params=best_params, - model_choose="deepgbm", - region="busan", - data_sample='pure', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로:") - for path in model_paths: - print(f" - {path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/deepgbm_pure/deepgbm_pure_daegu.py b/Analysis_code/5.optima/deepgbm_pure/deepgbm_pure_daegu.py deleted file mode 100644 index 7c28e81040da22168ab264755cc3dafe24656ec4..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/deepgbm_pure/deepgbm_pure_daegu.py +++ /dev/null @@ -1,99 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="deepgbm", region="daegu"), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/deepgbm_pure_daegu_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_paths = train_final_model( - best_params=best_params, - model_choose="deepgbm", - region="daegu", - data_sample='pure', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로:") - for path in model_paths: - print(f" - {path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/deepgbm_pure/deepgbm_pure_daejeon.py b/Analysis_code/5.optima/deepgbm_pure/deepgbm_pure_daejeon.py deleted file mode 100644 index bbfe5d75baff1e318e3afb8fb8613cd280fcfe94..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/deepgbm_pure/deepgbm_pure_daejeon.py +++ /dev/null @@ -1,99 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="deepgbm", region="daejeon"), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/deepgbm_pure_daejeon_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_paths = train_final_model( - best_params=best_params, - model_choose="deepgbm", - region="daejeon", - data_sample='pure', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로:") - for path in model_paths: - print(f" - {path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/deepgbm_pure/deepgbm_pure_gwangju.py b/Analysis_code/5.optima/deepgbm_pure/deepgbm_pure_gwangju.py deleted file mode 100644 index 76ab3bca8dad3ec4b257eebb61ffdd8f6eea40af..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/deepgbm_pure/deepgbm_pure_gwangju.py +++ /dev/null @@ -1,99 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="deepgbm", region="gwangju"), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/deepgbm_pure_gwangju_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_paths = train_final_model( - best_params=best_params, - model_choose="deepgbm", - region="gwangju", - data_sample='pure', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로:") - for path in model_paths: - print(f" - {path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/deepgbm_pure/deepgbm_pure_incheon.py b/Analysis_code/5.optima/deepgbm_pure/deepgbm_pure_incheon.py deleted file mode 100644 index bd64cfd1dce00a569689b4f76e5449d233496591..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/deepgbm_pure/deepgbm_pure_incheon.py +++ /dev/null @@ -1,99 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="deepgbm", region="incheon"), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/deepgbm_pure_incheon_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_paths = train_final_model( - best_params=best_params, - model_choose="deepgbm", - region="incheon", - data_sample='pure', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로:") - for path in model_paths: - print(f" - {path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/deepgbm_pure/deepgbm_pure_seoul.py b/Analysis_code/5.optima/deepgbm_pure/deepgbm_pure_seoul.py deleted file mode 100644 index fca07269f52d8adf691a7027ceff07b22901688f..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/deepgbm_pure/deepgbm_pure_seoul.py +++ /dev/null @@ -1,99 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="deepgbm", region="seoul"), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/deepgbm_pure_seoul_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_paths = train_final_model( - best_params=best_params, - model_choose="deepgbm", - region="seoul", - data_sample='pure', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로:") - for path in model_paths: - print(f" - {path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/deepgbm_pure/utils.py b/Analysis_code/5.optima/deepgbm_pure/utils.py deleted file mode 100644 index 43d496ecda4c82ad96e7ed6c5a87409fd31b53cb..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/deepgbm_pure/utils.py +++ /dev/null @@ -1,720 +0,0 @@ -import torch -import torch.nn as nn -import torch.optim as optim -import numpy as np -import random -import os -import copy -from sklearn.preprocessing import QuantileTransformer, LabelEncoder -from torch.utils.data import DataLoader, TensorDataset -from sklearn.metrics import confusion_matrix -from sklearn.utils.class_weight import compute_class_weight -import pandas as pd -import optuna -from sklearn.metrics import accuracy_score, f1_score -import joblib - - -import sys -# 파일 위치 기반으로 models 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -models_path = os.path.abspath(os.path.join(current_file_dir, '../../models')) -sys.path.insert(0, models_path) -from ft_transformer import FTTransformer -from resnet_like import ResNetLike -from deepgbm import DeepGBM -import warnings -warnings.filterwarnings('ignore') - - -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - -# PyTorch 시드 고정 -torch.manual_seed(seed) -torch.cuda.manual_seed(seed) -torch.cuda.manual_seed_all(seed) # Multi-GPU 환경에서 동일한 시드 적용 - -# PyTorch 연산의 결정적 모드 설정 -torch.backends.cudnn.deterministic = True # 실행마다 동일한 결과를 보장 -torch.backends.cudnn.benchmark = True # 성능 최적화를 활성화 (가능한 한 빠른 연산 수행) - - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - - -# 데이터셋 준비 함수 -def prepare_dataset(region, data_sample='pure', target='multi', fold=3): - - # 파일 위치 기반으로 데이터 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) - - # 데이터 경로 지정 - dat_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_train.csv") - if data_sample == 'pure': - train_path = dat_path - else: - train_path = os.path.join(data_base_dir, f'data_oversampled/{data_sample}/{data_sample}_{fold}_{region}.csv') - test_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_test.csv") - drop_col = ['multi_class','year'] - target_col = f'{target}_class' - - # 데이터 로드 - region_dat = preprocessing(pd.read_csv(dat_path, index_col=0)) - if data_sample == 'pure': - region_train = region_dat.loc[~region_dat['year'].isin([2021-fold]), :] - else: - region_train = preprocessing(pd.read_csv(train_path)) - region_val = region_dat.loc[region_dat['year'].isin([2021-fold]), :] - region_test = preprocessing(pd.read_csv(test_path)) - - # 컬럼 정렬 (일관성 유지) - common_columns = region_train.columns.to_list() - train_data = region_train[common_columns] - val_data = region_val[common_columns] - test_data = region_test[common_columns] - - # 설명변수 & 타겟 분리 - X_train = train_data.drop(columns=drop_col) - y_train = train_data[target_col] - X_val = val_data.drop(columns=drop_col) - y_val = val_data[target_col] - X_test = test_data.drop(columns=drop_col) - y_test = test_data[target_col] - - # 범주형 & 연속형 변수 분리 - categorical_cols = X_train.select_dtypes(include=['object', 'category', 'int64']).columns - numerical_cols = X_train.select_dtypes(include=['float64']).columns - - # 범주형 변수 Label Encoding - label_encoders = {} - for col in categorical_cols: - le = LabelEncoder() - le.fit(X_train[col]) # Train 데이터 기준으로 학습 - label_encoders[col] = le - - # 변환 적용 - for col in categorical_cols: - X_train[col] = label_encoders[col].transform(X_train[col]) - X_val[col] = label_encoders[col].transform(X_val[col]) - X_test[col] = label_encoders[col].transform(X_test[col]) - - # 연속형 변수 Quantile Transformation - scaler = QuantileTransformer(output_distribution='normal') - scaler.fit(X_train[numerical_cols]) # Train 데이터 기준으로 학습 - - # 변환 적용 - X_train[numerical_cols] = scaler.transform(X_train[numerical_cols]) - X_val[numerical_cols] = scaler.transform(X_val[numerical_cols]) - X_test[numerical_cols] = scaler.transform(X_test[numerical_cols]) - - return X_train, X_val, X_test, y_train, y_val, y_test, categorical_cols, numerical_cols - - - -# 데이터 변환 및 dataloader 생성 함수 -def prepare_dataloader(region, data_sample='pure', target='multi', fold=3, random_state=None): - - # 파일 위치 기반으로 데이터 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) - - # 데이터 경로 지정 - dat_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_train.csv") - if data_sample == 'pure': - train_path = dat_path - else: - train_path = os.path.join(data_base_dir, f'data_oversampled/{data_sample}/{data_sample}_{fold}_{region}.csv') - test_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_test.csv") - drop_col = ['multi_class','year'] - target_col = f'{target}_class' - - # 데이터 로드 - region_dat = preprocessing(pd.read_csv(dat_path, index_col=0)) - if data_sample == 'pure': - region_train = region_dat.loc[~region_dat['year'].isin([2021-fold]), :] - else: - region_train = preprocessing(pd.read_csv(train_path)) - region_val = region_dat.loc[region_dat['year'].isin([2021-fold]), :] - region_test = preprocessing(pd.read_csv(test_path)) - - # 컬럼 정렬 (일관성 유지) - common_columns = region_train.columns.to_list() - train_data = region_train[common_columns] - val_data = region_val[common_columns] - test_data = region_test[common_columns] - - # 설명변수 & 타겟 분리 - X_train = train_data.drop(columns=drop_col) - y_train = train_data[target_col] - X_val = val_data.drop(columns=drop_col) - y_val = val_data[target_col] - X_test = test_data.drop(columns=drop_col) - y_test = test_data[target_col] - - # 범주형 & 연속형 변수 분리 - categorical_cols = X_train.select_dtypes(include=['object', 'category', 'int64']).columns - numerical_cols = X_train.select_dtypes(include=['float64']).columns - - # 범주형 변수 Label Encoding - label_encoders = {} - for col in categorical_cols: - le = LabelEncoder() - le.fit(X_train[col]) # Train 데이터 기준으로 학습 - label_encoders[col] = le - - # 변환 적용 - for col in categorical_cols: - X_train[col] = label_encoders[col].transform(X_train[col]) - X_val[col] = label_encoders[col].transform(X_val[col]) - X_test[col] = label_encoders[col].transform(X_test[col]) - - # 연속형 변수 Quantile Transformation - scaler = QuantileTransformer(output_distribution='normal') - scaler.fit(X_train[numerical_cols]) # Train 데이터 기준으로 학습 - - # 변환 적용 - X_train[numerical_cols] = scaler.transform(X_train[numerical_cols]) - X_val[numerical_cols] = scaler.transform(X_val[numerical_cols]) - X_test[numerical_cols] = scaler.transform(X_test[numerical_cols]) - - # 연속형 변수와 범주형 변수 분리 - X_train_num = torch.tensor(X_train[numerical_cols].values, dtype=torch.float32) - X_train_cat = torch.tensor(X_train[categorical_cols].values, dtype=torch.long) - - X_val_num = torch.tensor(X_val[numerical_cols].values, dtype=torch.float32) - X_val_cat = torch.tensor(X_val[categorical_cols].values, dtype=torch.long) - - X_test_num = torch.tensor(X_test[numerical_cols].values, dtype=torch.float32) - X_test_cat = torch.tensor(X_test[categorical_cols].values, dtype=torch.long) - - # 레이블 변환 - if target == "binary": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.float32) # 이진 분류 → float32 - y_val_tensor = torch.tensor(y_val.values, dtype=torch.float32) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.float32) - elif target == "multi": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.long) # 다중 분류 → long - y_val_tensor = torch.tensor(y_val.values, dtype=torch.long) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.long) - else: - raise ValueError("target must be 'binary' or 'multi'") - - # TensorDataset 생성 - train_dataset = TensorDataset(X_train_num, X_train_cat, y_train_tensor) - val_dataset = TensorDataset(X_val_num, X_val_cat, y_val_tensor) - test_dataset = TensorDataset(X_test_num, X_test_cat, y_test_tensor) - - # DataLoader 생성 - if random_state == None: - train_loader = DataLoader(train_dataset, batch_size=64, shuffle=True) - else: - train_loader = DataLoader(train_dataset, batch_size=64, shuffle=True, generator=torch.Generator().manual_seed(random_state)) - val_loader = DataLoader(val_dataset, batch_size=64, shuffle=False) - test_loader = DataLoader(test_dataset, batch_size=64, shuffle=False) - - return X_train, categorical_cols, numerical_cols, train_loader, val_loader, test_loader - -# 데이터 변환 및 dataloader 생성 함수 (batch_size 파라미터 추가 버전) -def prepare_dataloader_with_batchsize(region, data_sample='pure', target='multi', fold=3, random_state=None, batch_size=64): - # 파일 위치 기반으로 데이터 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) - - # 데이터 경로 지정 - dat_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_train.csv") - if data_sample == 'pure': - train_path = dat_path - else: - train_path = os.path.join(data_base_dir, f'data_oversampled/{data_sample}/{data_sample}_{fold}_{region}.csv') - test_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_test.csv") - drop_col = ['multi_class','year'] - target_col = f'{target}_class' - - # 데이터 로드 - region_dat = preprocessing(pd.read_csv(dat_path, index_col=0)) - if data_sample == 'pure': - region_train = region_dat.loc[~region_dat['year'].isin([2021-fold]), :] - else: - region_train = preprocessing(pd.read_csv(train_path)) - region_val = region_dat.loc[region_dat['year'].isin([2021-fold]), :] - region_test = preprocessing(pd.read_csv(test_path)) - - # 컬럼 정렬 (일관성 유지) - common_columns = region_train.columns.to_list() - train_data = region_train[common_columns] - val_data = region_val[common_columns] - test_data = region_test[common_columns] - - # 설명변수 & 타겟 분리 - X_train = train_data.drop(columns=drop_col) - y_train = train_data[target_col] - X_val = val_data.drop(columns=drop_col) - y_val = val_data[target_col] - X_test = test_data.drop(columns=drop_col) - y_test = test_data[target_col] - - # 범주형 & 연속형 변수 분리 - categorical_cols = X_train.select_dtypes(include=['object', 'category', 'int64']).columns - numerical_cols = X_train.select_dtypes(include=['float64']).columns - - # 범주형 변수 Label Encoding - label_encoders = {} - for col in categorical_cols: - le = LabelEncoder() - le.fit(X_train[col]) # Train 데이터 기준으로 학습 - label_encoders[col] = le - - # 변환 적용 - for col in categorical_cols: - X_train[col] = label_encoders[col].transform(X_train[col]) - X_val[col] = label_encoders[col].transform(X_val[col]) - X_test[col] = label_encoders[col].transform(X_test[col]) - - # 연속형 변수 Quantile Transformation - scaler = QuantileTransformer(output_distribution='normal') - scaler.fit(X_train[numerical_cols]) # Train 데이터 기준으로 학습 - - # 변환 적용 - X_train[numerical_cols] = scaler.transform(X_train[numerical_cols]) - X_val[numerical_cols] = scaler.transform(X_val[numerical_cols]) - X_test[numerical_cols] = scaler.transform(X_test[numerical_cols]) - - # 연속형 변수와 범주형 변수 분리 - X_train_num = torch.tensor(X_train[numerical_cols].values, dtype=torch.float32) - X_train_cat = torch.tensor(X_train[categorical_cols].values, dtype=torch.long) - - X_val_num = torch.tensor(X_val[numerical_cols].values, dtype=torch.float32) - X_val_cat = torch.tensor(X_val[categorical_cols].values, dtype=torch.long) - - X_test_num = torch.tensor(X_test[numerical_cols].values, dtype=torch.float32) - X_test_cat = torch.tensor(X_test[categorical_cols].values, dtype=torch.long) - - # 레이블 변환 - if target == "binary": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.float32) # 이진 분류 → float32 - y_val_tensor = torch.tensor(y_val.values, dtype=torch.float32) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.float32) - elif target == "multi": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.long) # 다중 분류 → long - y_val_tensor = torch.tensor(y_val.values, dtype=torch.long) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.long) - else: - raise ValueError("target must be 'binary' or 'multi'") - - # TensorDataset 생성 - train_dataset = TensorDataset(X_train_num, X_train_cat, y_train_tensor) - val_dataset = TensorDataset(X_val_num, X_val_cat, y_val_tensor) - test_dataset = TensorDataset(X_test_num, X_test_cat, y_test_tensor) - - # DataLoader 생성 (batch_size 파라미터 사용) - if random_state == None: - train_loader = DataLoader(train_dataset, batch_size=batch_size, shuffle=True) - else: - train_loader = DataLoader(train_dataset, batch_size=batch_size, shuffle=True, generator=torch.Generator().manual_seed(random_state)) - val_loader = DataLoader(val_dataset, batch_size=batch_size, shuffle=False) - test_loader = DataLoader(test_dataset, batch_size=batch_size, shuffle=False) - - return X_train, categorical_cols, numerical_cols, train_loader, val_loader, test_loader, y_train, scaler - - -def calculate_csi(y_true, pred): - - cm = confusion_matrix(y_true, pred) # 변수 이름을 cm으로 변경 - # 혼동 행렬에서 H, F, M 추출 - H = (cm[0, 0] + cm[1, 1]) - - F = (cm[1, 0] + cm[2, 0] + - cm[0, 1] + cm[2, 1]) - - M = (cm[0, 2] + cm[1, 2]) - - # CSI 계산 - CSI = H / (H + F + M + 1e-10) - return CSI - -def sample_weight(y_train): - class_weights = compute_class_weight( - class_weight='balanced', - classes=np.unique(y_train), # 고유 클래스 - y=y_train # 학습 데이터 레이블 - ) - sample_weights = np.array([class_weights[label] for label in y_train]) - - return sample_weights - -# 하이퍼파라미터 최적화 함수 정의 -def objective(trial, model_choose, region, data_sample='pure', target='multi', n_folds=3, random_state=42): - # GPU 사용 가능 여부 확인 및 device 설정 - device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') - val_scores = [] - - # --- 1. 하이퍼파라미터 탐색 범위 정의 (수정됨) --- - if model_choose == "ft_transformer": - d_token = trial.suggest_int("d_token", 64, 256, step=32) - n_blocks = trial.suggest_int("n_blocks", 2, 6) # 깊이 축소로 과적합 방지 - n_heads = trial.suggest_categorical("n_heads", [4, 8]) - # d_token은 n_heads의 배수여야 함 (FT-Transformer의 구조적 제약 대응) - if d_token % n_heads != 0: - d_token = (d_token // n_heads) * n_heads - - attention_dropout = trial.suggest_float("attention_dropout", 0.1, 0.4) - ffn_dropout = trial.suggest_float("ffn_dropout", 0.1, 0.4) - lr = trial.suggest_float("lr", 1e-5, 1e-2, log=True) # 범위 확대 - weight_decay = trial.suggest_float("weight_decay", 1e-4, 1e-1, log=True) # 더 공격적인 범위로 확장 - batch_size = trial.suggest_categorical("batch_size", [32, 64, 128, 256]) # Batch Size 추가 - - elif model_choose == 'resnet_like': - d_main = trial.suggest_int("d_main", 64, 256, step=32) - d_hidden = trial.suggest_int("d_hidden", 64, 512, step=64) - n_blocks = trial.suggest_int("n_blocks", 2, 5) # 너무 깊지 않게 조절 - dropout_first = trial.suggest_float("dropout_first", 0.1, 0.4) - dropout_second = trial.suggest_float("dropout_second", 0.0, 0.2) - lr = trial.suggest_float("lr", 1e-5, 1e-2, log=True) - weight_decay = trial.suggest_float("weight_decay", 1e-4, 1e-1, log=True) # 더 공격적인 범위로 확장 - batch_size = trial.suggest_categorical("batch_size", [32, 64, 128, 256]) # Batch Size 추가 - - elif model_choose == 'deepgbm': - # DeepGBM의 경우 모델 특성에 맞춰 ResNet 블록 및 임베딩 차원 조절 - d_main = trial.suggest_int("d_main", 64, 256, step=32) - d_hidden = trial.suggest_int("d_hidden", 64, 256, step=64) - n_blocks = trial.suggest_int("n_blocks", 2, 6) - dropout = trial.suggest_float("dropout", 0.1, 0.4) - lr = trial.suggest_float("lr", 1e-5, 1e-2, log=True) - weight_decay = trial.suggest_float("weight_decay", 1e-4, 1e-1, log=True) # 더 공격적인 범위로 확장 - batch_size = trial.suggest_categorical("batch_size", [32, 64, 128, 256]) # Batch Size 추가 - - # --- 2. Fold별 학습 및 교차 검증 --- - for fold in range(1, n_folds + 1): - X_train_df, categorical_cols, numerical_cols, train_loader, val_loader, _, y_train, _ = prepare_dataloader_with_batchsize( - region, data_sample=data_sample, target=target, fold=fold, random_state=random_state, batch_size=batch_size - ) - - # 모델 초기화 - if model_choose == "ft_transformer": - model = FTTransformer( - num_features=len(numerical_cols), - cat_cardinalities=[len(X_train_df[col].unique()) for col in categorical_cols], - d_token=d_token, - n_blocks=n_blocks, - n_heads=n_heads, - attention_dropout=attention_dropout, - ffn_dropout=ffn_dropout, - num_classes=3 - ).to(device) - elif model_choose == 'resnet_like': - input_dim = len(numerical_cols) + len(categorical_cols) - model = ResNetLike( - input_dim=input_dim, - d_main=d_main, - d_hidden=d_hidden, - n_blocks=n_blocks, - dropout_first=dropout_first, - dropout_second=dropout_second, - num_classes=3 - ).to(device) - elif model_choose == 'deepgbm': - model = DeepGBM( - num_features=len(numerical_cols), - cat_features=[len(X_train_df[col].unique()) for col in categorical_cols], - d_main=d_main, - d_hidden=d_hidden, - n_blocks=n_blocks, - dropout=dropout, - num_classes=3 - ).to(device) - - # 클래스 가중치 계산 및 손실 함수 설정 (Label Smoothing 적용) - if target == 'multi': - class_weights = compute_class_weight( - class_weight='balanced', - classes=np.unique(y_train), - y=y_train - ) - # 클래스별 가중치 로그 출력 - unique_classes = np.unique(y_train) - class_counts = {cls: np.sum(y_train == cls) for cls in unique_classes} - print(f" Fold {fold} - 클래스별 가중치: {dict(zip(unique_classes, class_weights))} (클래스별 샘플 수: {class_counts})") - class_weights_tensor = torch.tensor(class_weights, dtype=torch.float32).to(device) - criterion = nn.CrossEntropyLoss(weight=class_weights_tensor, label_smoothing=0.0) # Label Smoothing 추가 - else: - criterion = nn.BCEWithLogitsLoss() - optimizer = optim.AdamW(model.parameters(), lr=lr, weight_decay=weight_decay) - - # 학습률 스케줄러 추가: 성능 정체 시 LR을 0.5배 감소 (검증 CSI 기준) - scheduler = optim.lr_scheduler.ReduceLROnPlateau(optimizer, mode='max', factor=0.5, patience=3) - - # 학습 설정 (에폭 및 페이션스 상향) - epochs = 200 - patience = 12 # 딥러닝의 정체 구간을 고려하여 소폭 상향 - best_fold_csi = 0 - counter = 0 - - for epoch in range(epochs): - model.train() - for x_num_batch, x_cat_batch, y_batch in train_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - - optimizer.zero_grad() - y_pred = model(x_num_batch, x_cat_batch) - loss = criterion(y_pred, y_batch if target == 'multi' else y_batch.float()) - loss.backward() - optimizer.step() - - # Validation 평가 - model.eval() - y_pred_val, y_true_val = [], [] - with torch.no_grad(): - for x_num_batch, x_cat_batch, y_batch in val_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - output = model(x_num_batch, x_cat_batch) - pred = output.argmax(dim=1) if target == 'multi' else (torch.sigmoid(output) >= 0.5).long() - - y_pred_val.extend(pred.cpu().numpy()) - y_true_val.extend(y_batch.cpu().numpy()) - - # CSI 계산 및 스케줄러 업데이트 - val_csi = calculate_csi(y_true_val, y_pred_val) - scheduler.step(val_csi) - - # Optuna Pruning 적용 (첫 번째 Fold에서 조기 종료 판단 강화) - trial.report(val_csi, epoch) - if trial.should_prune(): - raise optuna.exceptions.TrialPruned() - - # Early Stopping 체크 - if val_csi > best_fold_csi: - best_fold_csi = val_csi - counter = 0 - else: - counter += 1 - - if counter >= patience: - break - - val_scores.append(best_fold_csi) - - # 모든 fold의 평균 성능 반환 - return np.mean(val_scores) - - -# 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 함수 -def train_final_model(best_params, model_choose, region, data_sample='pure', target='multi', n_folds=3, random_state=42): - """ - 최적화된 하이퍼파라미터로 최종 모델을 학습하고 저장합니다. - - Args: - best_params: 최적화된 하이퍼파라미터 딕셔너리 - model_choose: 모델 선택 ('ft_transformer', 'resnet_like', 'deepgbm') - region: 지역명 - data_sample: 데이터 샘플 타입 ('pure', 'smote', etc.) - target: 타겟 타입 ('multi', 'binary') - n_folds: 교차 검증 fold 수 - random_state: 랜덤 시드 - - Returns: - 저장된 모델 경로 리스트 - """ - # GPU 사용 가능 여부 확인 및 device 설정 - device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') - - models = [] - scalers = [] # scaler 리스트 추가 - - print("최종 모델 학습 시작...") - - for fold in range(1, n_folds + 1): - print(f"Fold {fold} 학습 중...") - - # 최적화된 batch_size 사용 - batch_size = best_params.get("batch_size", 64) - X_train_df, categorical_cols, numerical_cols, train_loader, val_loader, _, y_train, scaler = prepare_dataloader_with_batchsize( - region, data_sample=data_sample, target=target, fold=fold, random_state=random_state, batch_size=batch_size - ) - - # 모델 초기화 - if model_choose == "ft_transformer": - d_token = best_params["d_token"] - n_heads = best_params.get("n_heads", 8) - # d_token은 n_heads의 배수여야 함 (FT-Transformer의 구조적 제약 대응) - if d_token % n_heads != 0: - d_token = (d_token // n_heads) * n_heads - - model = FTTransformer( - num_features=len(numerical_cols), - cat_cardinalities=[len(X_train_df[col].unique()) for col in categorical_cols], - d_token=d_token, - n_blocks=best_params["n_blocks"], - n_heads=n_heads, - attention_dropout=best_params["attention_dropout"], - ffn_dropout=best_params["ffn_dropout"], - num_classes=3 - ).to(device) - elif model_choose == 'resnet_like': - input_dim = len(numerical_cols) + len(categorical_cols) - model = ResNetLike( - input_dim=input_dim, - d_main=best_params["d_main"], - d_hidden=best_params["d_hidden"], - n_blocks=best_params["n_blocks"], - dropout_first=best_params["dropout_first"], - dropout_second=best_params["dropout_second"], - num_classes=3 - ).to(device) - elif model_choose == 'deepgbm': - model = DeepGBM( - num_features=len(numerical_cols), - cat_features=[len(X_train_df[col].unique()) for col in categorical_cols], - d_main=best_params["d_main"], - d_hidden=best_params["d_hidden"], - n_blocks=best_params["n_blocks"], - dropout=best_params["dropout"], - num_classes=3 - ).to(device) - else: - raise ValueError(f"Unknown model_choose: {model_choose}") - - # 클래스 가중치 계산 및 손실 함수 설정 (Label Smoothing 적용) - if target == 'multi': - class_weights = compute_class_weight( - class_weight='balanced', - classes=np.unique(y_train), - y=y_train - ) - class_weights_tensor = torch.tensor(class_weights, dtype=torch.float32).to(device) - criterion = nn.CrossEntropyLoss(weight=class_weights_tensor, label_smoothing=0.0) # Label Smoothing 추가 - else: - criterion = nn.BCEWithLogitsLoss() - optimizer = optim.AdamW(model.parameters(), lr=best_params["lr"], weight_decay=best_params["weight_decay"]) - - # 학습률 스케줄러 - scheduler = optim.lr_scheduler.ReduceLROnPlateau(optimizer, mode='max', factor=0.5, patience=3) - - # 학습 설정 - epochs = 200 - patience = 12 - best_fold_csi = 0 - counter = 0 - best_model = None - - for epoch in range(epochs): - model.train() - for x_num_batch, x_cat_batch, y_batch in train_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - - optimizer.zero_grad() - y_pred = model(x_num_batch, x_cat_batch) - loss = criterion(y_pred, y_batch if target == 'multi' else y_batch.float()) - loss.backward() - optimizer.step() - - # Validation 평가 - model.eval() - y_pred_val, y_true_val = [], [] - with torch.no_grad(): - for x_num_batch, x_cat_batch, y_batch in val_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - output = model(x_num_batch, x_cat_batch) - pred = output.argmax(dim=1) if target == 'multi' else (torch.sigmoid(output) >= 0.5).long() - - y_pred_val.extend(pred.cpu().numpy()) - y_true_val.extend(y_batch.cpu().numpy()) - - # CSI 계산 및 스케줄러 업데이트 - val_csi = calculate_csi(y_true_val, y_pred_val) - scheduler.step(val_csi) - - # Early Stopping 체크 - if val_csi > best_fold_csi: - best_fold_csi = val_csi - counter = 0 - best_model = copy.deepcopy(model) - else: - counter += 1 - - if counter >= patience: - print(f" Early stopping at epoch {epoch+1}, Best CSI: {best_fold_csi:.4f}") - break - - if best_model is None: - best_model = model - - scalers.append(scaler) # scaler 저장 (fold 순서대로) - models.append(best_model) - print(f" Fold {fold} 학습 완료 (검증 CSI: {best_fold_csi:.4f})") - - # 모델 저장 경로 설정 - save_dir = f'../save_model/{model_choose}_optima' - os.makedirs(save_dir, exist_ok=True) - - # 파일명 생성 - if data_sample == 'pure': - model_filename = f'{model_choose}_pure_{region}.pkl' - else: - model_filename = f'{model_choose}_{data_sample}_{region}.pkl' - - model_path = f'{save_dir}/{model_filename}' - - # 리스트에 담아 한 번에 저장 - joblib.dump(models, model_path) - print(f"\n모든 모델 저장 완료: {model_path} (총 {len(models)}개 fold)") - - # Scaler 별도 저장 - scaler_save_dir = f'../save_model/{model_choose}_optima/scaler' - os.makedirs(scaler_save_dir, exist_ok=True) - - # 파일명 생성 (모델과 동일한 패턴) - if data_sample == 'pure': - scaler_filename = f'{model_choose}_pure_{region}_scaler.pkl' - else: - scaler_filename = f'{model_choose}_{data_sample}_{region}_scaler.pkl' - - scaler_path = f'{scaler_save_dir}/{scaler_filename}' - joblib.dump(scalers, scaler_path) - print(f"Scaler 저장 완료: {scaler_path} (총 {len(scalers)}개 fold)") - - return model_path diff --git a/Analysis_code/5.optima/deepgbm_smote/deepgbm_smote_busan.py b/Analysis_code/5.optima/deepgbm_smote/deepgbm_smote_busan.py deleted file mode 100644 index 549f966e3b41fe1d98fb3cbf5c044d5a2f15dc5b..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/deepgbm_smote/deepgbm_smote_busan.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="deepgbm", region="busan", data_sample='smote'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/deepgbm_smote_busan_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="deepgbm", - region="busan", - data_sample='smote', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/deepgbm_smote/deepgbm_smote_daegu.py b/Analysis_code/5.optima/deepgbm_smote/deepgbm_smote_daegu.py deleted file mode 100644 index e94405ef5415c679867039729d094aa00c9ff04e..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/deepgbm_smote/deepgbm_smote_daegu.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="deepgbm", region="daegu", data_sample='smote'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/deepgbm_smote_daegu_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="deepgbm", - region="daegu", - data_sample='smote', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/deepgbm_smote/deepgbm_smote_daejeon.py b/Analysis_code/5.optima/deepgbm_smote/deepgbm_smote_daejeon.py deleted file mode 100644 index e654c3428ae9ee57f9525e8541728fcf4c95da6e..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/deepgbm_smote/deepgbm_smote_daejeon.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="deepgbm", region="daejeon", data_sample='smote'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/deepgbm_smote_daejeon_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="deepgbm", - region="daejeon", - data_sample='smote', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/deepgbm_smote/deepgbm_smote_gwangju.py b/Analysis_code/5.optima/deepgbm_smote/deepgbm_smote_gwangju.py deleted file mode 100644 index c884fe0ff568632ff39b58879f25d5d0971e1cff..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/deepgbm_smote/deepgbm_smote_gwangju.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="deepgbm", region="gwangju", data_sample='smote'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/deepgbm_smote_gwangju_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="deepgbm", - region="gwangju", - data_sample='smote', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/deepgbm_smote/deepgbm_smote_incheon.py b/Analysis_code/5.optima/deepgbm_smote/deepgbm_smote_incheon.py deleted file mode 100644 index 9994f02c6d9cce4096a0164e66f33a9304128df1..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/deepgbm_smote/deepgbm_smote_incheon.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="deepgbm", region="incheon", data_sample='smote'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/deepgbm_smote_incheon_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="deepgbm", - region="incheon", - data_sample='smote', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/deepgbm_smote/deepgbm_smote_seoul.py b/Analysis_code/5.optima/deepgbm_smote/deepgbm_smote_seoul.py deleted file mode 100644 index 0e382a87f007fac0d3e67d2ee398afe94a002ab1..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/deepgbm_smote/deepgbm_smote_seoul.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="deepgbm", region="seoul", data_sample='smote'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/deepgbm_smote_seoul_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="deepgbm", - region="seoul", - data_sample='smote', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/deepgbm_smote/utils.py b/Analysis_code/5.optima/deepgbm_smote/utils.py deleted file mode 100644 index 43d496ecda4c82ad96e7ed6c5a87409fd31b53cb..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/deepgbm_smote/utils.py +++ /dev/null @@ -1,720 +0,0 @@ -import torch -import torch.nn as nn -import torch.optim as optim -import numpy as np -import random -import os -import copy -from sklearn.preprocessing import QuantileTransformer, LabelEncoder -from torch.utils.data import DataLoader, TensorDataset -from sklearn.metrics import confusion_matrix -from sklearn.utils.class_weight import compute_class_weight -import pandas as pd -import optuna -from sklearn.metrics import accuracy_score, f1_score -import joblib - - -import sys -# 파일 위치 기반으로 models 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -models_path = os.path.abspath(os.path.join(current_file_dir, '../../models')) -sys.path.insert(0, models_path) -from ft_transformer import FTTransformer -from resnet_like import ResNetLike -from deepgbm import DeepGBM -import warnings -warnings.filterwarnings('ignore') - - -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - -# PyTorch 시드 고정 -torch.manual_seed(seed) -torch.cuda.manual_seed(seed) -torch.cuda.manual_seed_all(seed) # Multi-GPU 환경에서 동일한 시드 적용 - -# PyTorch 연산의 결정적 모드 설정 -torch.backends.cudnn.deterministic = True # 실행마다 동일한 결과를 보장 -torch.backends.cudnn.benchmark = True # 성능 최적화를 활성화 (가능한 한 빠른 연산 수행) - - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - - -# 데이터셋 준비 함수 -def prepare_dataset(region, data_sample='pure', target='multi', fold=3): - - # 파일 위치 기반으로 데이터 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) - - # 데이터 경로 지정 - dat_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_train.csv") - if data_sample == 'pure': - train_path = dat_path - else: - train_path = os.path.join(data_base_dir, f'data_oversampled/{data_sample}/{data_sample}_{fold}_{region}.csv') - test_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_test.csv") - drop_col = ['multi_class','year'] - target_col = f'{target}_class' - - # 데이터 로드 - region_dat = preprocessing(pd.read_csv(dat_path, index_col=0)) - if data_sample == 'pure': - region_train = region_dat.loc[~region_dat['year'].isin([2021-fold]), :] - else: - region_train = preprocessing(pd.read_csv(train_path)) - region_val = region_dat.loc[region_dat['year'].isin([2021-fold]), :] - region_test = preprocessing(pd.read_csv(test_path)) - - # 컬럼 정렬 (일관성 유지) - common_columns = region_train.columns.to_list() - train_data = region_train[common_columns] - val_data = region_val[common_columns] - test_data = region_test[common_columns] - - # 설명변수 & 타겟 분리 - X_train = train_data.drop(columns=drop_col) - y_train = train_data[target_col] - X_val = val_data.drop(columns=drop_col) - y_val = val_data[target_col] - X_test = test_data.drop(columns=drop_col) - y_test = test_data[target_col] - - # 범주형 & 연속형 변수 분리 - categorical_cols = X_train.select_dtypes(include=['object', 'category', 'int64']).columns - numerical_cols = X_train.select_dtypes(include=['float64']).columns - - # 범주형 변수 Label Encoding - label_encoders = {} - for col in categorical_cols: - le = LabelEncoder() - le.fit(X_train[col]) # Train 데이터 기준으로 학습 - label_encoders[col] = le - - # 변환 적용 - for col in categorical_cols: - X_train[col] = label_encoders[col].transform(X_train[col]) - X_val[col] = label_encoders[col].transform(X_val[col]) - X_test[col] = label_encoders[col].transform(X_test[col]) - - # 연속형 변수 Quantile Transformation - scaler = QuantileTransformer(output_distribution='normal') - scaler.fit(X_train[numerical_cols]) # Train 데이터 기준으로 학습 - - # 변환 적용 - X_train[numerical_cols] = scaler.transform(X_train[numerical_cols]) - X_val[numerical_cols] = scaler.transform(X_val[numerical_cols]) - X_test[numerical_cols] = scaler.transform(X_test[numerical_cols]) - - return X_train, X_val, X_test, y_train, y_val, y_test, categorical_cols, numerical_cols - - - -# 데이터 변환 및 dataloader 생성 함수 -def prepare_dataloader(region, data_sample='pure', target='multi', fold=3, random_state=None): - - # 파일 위치 기반으로 데이터 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) - - # 데이터 경로 지정 - dat_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_train.csv") - if data_sample == 'pure': - train_path = dat_path - else: - train_path = os.path.join(data_base_dir, f'data_oversampled/{data_sample}/{data_sample}_{fold}_{region}.csv') - test_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_test.csv") - drop_col = ['multi_class','year'] - target_col = f'{target}_class' - - # 데이터 로드 - region_dat = preprocessing(pd.read_csv(dat_path, index_col=0)) - if data_sample == 'pure': - region_train = region_dat.loc[~region_dat['year'].isin([2021-fold]), :] - else: - region_train = preprocessing(pd.read_csv(train_path)) - region_val = region_dat.loc[region_dat['year'].isin([2021-fold]), :] - region_test = preprocessing(pd.read_csv(test_path)) - - # 컬럼 정렬 (일관성 유지) - common_columns = region_train.columns.to_list() - train_data = region_train[common_columns] - val_data = region_val[common_columns] - test_data = region_test[common_columns] - - # 설명변수 & 타겟 분리 - X_train = train_data.drop(columns=drop_col) - y_train = train_data[target_col] - X_val = val_data.drop(columns=drop_col) - y_val = val_data[target_col] - X_test = test_data.drop(columns=drop_col) - y_test = test_data[target_col] - - # 범주형 & 연속형 변수 분리 - categorical_cols = X_train.select_dtypes(include=['object', 'category', 'int64']).columns - numerical_cols = X_train.select_dtypes(include=['float64']).columns - - # 범주형 변수 Label Encoding - label_encoders = {} - for col in categorical_cols: - le = LabelEncoder() - le.fit(X_train[col]) # Train 데이터 기준으로 학습 - label_encoders[col] = le - - # 변환 적용 - for col in categorical_cols: - X_train[col] = label_encoders[col].transform(X_train[col]) - X_val[col] = label_encoders[col].transform(X_val[col]) - X_test[col] = label_encoders[col].transform(X_test[col]) - - # 연속형 변수 Quantile Transformation - scaler = QuantileTransformer(output_distribution='normal') - scaler.fit(X_train[numerical_cols]) # Train 데이터 기준으로 학습 - - # 변환 적용 - X_train[numerical_cols] = scaler.transform(X_train[numerical_cols]) - X_val[numerical_cols] = scaler.transform(X_val[numerical_cols]) - X_test[numerical_cols] = scaler.transform(X_test[numerical_cols]) - - # 연속형 변수와 범주형 변수 분리 - X_train_num = torch.tensor(X_train[numerical_cols].values, dtype=torch.float32) - X_train_cat = torch.tensor(X_train[categorical_cols].values, dtype=torch.long) - - X_val_num = torch.tensor(X_val[numerical_cols].values, dtype=torch.float32) - X_val_cat = torch.tensor(X_val[categorical_cols].values, dtype=torch.long) - - X_test_num = torch.tensor(X_test[numerical_cols].values, dtype=torch.float32) - X_test_cat = torch.tensor(X_test[categorical_cols].values, dtype=torch.long) - - # 레이블 변환 - if target == "binary": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.float32) # 이진 분류 → float32 - y_val_tensor = torch.tensor(y_val.values, dtype=torch.float32) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.float32) - elif target == "multi": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.long) # 다중 분류 → long - y_val_tensor = torch.tensor(y_val.values, dtype=torch.long) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.long) - else: - raise ValueError("target must be 'binary' or 'multi'") - - # TensorDataset 생성 - train_dataset = TensorDataset(X_train_num, X_train_cat, y_train_tensor) - val_dataset = TensorDataset(X_val_num, X_val_cat, y_val_tensor) - test_dataset = TensorDataset(X_test_num, X_test_cat, y_test_tensor) - - # DataLoader 생성 - if random_state == None: - train_loader = DataLoader(train_dataset, batch_size=64, shuffle=True) - else: - train_loader = DataLoader(train_dataset, batch_size=64, shuffle=True, generator=torch.Generator().manual_seed(random_state)) - val_loader = DataLoader(val_dataset, batch_size=64, shuffle=False) - test_loader = DataLoader(test_dataset, batch_size=64, shuffle=False) - - return X_train, categorical_cols, numerical_cols, train_loader, val_loader, test_loader - -# 데이터 변환 및 dataloader 생성 함수 (batch_size 파라미터 추가 버전) -def prepare_dataloader_with_batchsize(region, data_sample='pure', target='multi', fold=3, random_state=None, batch_size=64): - # 파일 위치 기반으로 데이터 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) - - # 데이터 경로 지정 - dat_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_train.csv") - if data_sample == 'pure': - train_path = dat_path - else: - train_path = os.path.join(data_base_dir, f'data_oversampled/{data_sample}/{data_sample}_{fold}_{region}.csv') - test_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_test.csv") - drop_col = ['multi_class','year'] - target_col = f'{target}_class' - - # 데이터 로드 - region_dat = preprocessing(pd.read_csv(dat_path, index_col=0)) - if data_sample == 'pure': - region_train = region_dat.loc[~region_dat['year'].isin([2021-fold]), :] - else: - region_train = preprocessing(pd.read_csv(train_path)) - region_val = region_dat.loc[region_dat['year'].isin([2021-fold]), :] - region_test = preprocessing(pd.read_csv(test_path)) - - # 컬럼 정렬 (일관성 유지) - common_columns = region_train.columns.to_list() - train_data = region_train[common_columns] - val_data = region_val[common_columns] - test_data = region_test[common_columns] - - # 설명변수 & 타겟 분리 - X_train = train_data.drop(columns=drop_col) - y_train = train_data[target_col] - X_val = val_data.drop(columns=drop_col) - y_val = val_data[target_col] - X_test = test_data.drop(columns=drop_col) - y_test = test_data[target_col] - - # 범주형 & 연속형 변수 분리 - categorical_cols = X_train.select_dtypes(include=['object', 'category', 'int64']).columns - numerical_cols = X_train.select_dtypes(include=['float64']).columns - - # 범주형 변수 Label Encoding - label_encoders = {} - for col in categorical_cols: - le = LabelEncoder() - le.fit(X_train[col]) # Train 데이터 기준으로 학습 - label_encoders[col] = le - - # 변환 적용 - for col in categorical_cols: - X_train[col] = label_encoders[col].transform(X_train[col]) - X_val[col] = label_encoders[col].transform(X_val[col]) - X_test[col] = label_encoders[col].transform(X_test[col]) - - # 연속형 변수 Quantile Transformation - scaler = QuantileTransformer(output_distribution='normal') - scaler.fit(X_train[numerical_cols]) # Train 데이터 기준으로 학습 - - # 변환 적용 - X_train[numerical_cols] = scaler.transform(X_train[numerical_cols]) - X_val[numerical_cols] = scaler.transform(X_val[numerical_cols]) - X_test[numerical_cols] = scaler.transform(X_test[numerical_cols]) - - # 연속형 변수와 범주형 변수 분리 - X_train_num = torch.tensor(X_train[numerical_cols].values, dtype=torch.float32) - X_train_cat = torch.tensor(X_train[categorical_cols].values, dtype=torch.long) - - X_val_num = torch.tensor(X_val[numerical_cols].values, dtype=torch.float32) - X_val_cat = torch.tensor(X_val[categorical_cols].values, dtype=torch.long) - - X_test_num = torch.tensor(X_test[numerical_cols].values, dtype=torch.float32) - X_test_cat = torch.tensor(X_test[categorical_cols].values, dtype=torch.long) - - # 레이블 변환 - if target == "binary": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.float32) # 이진 분류 → float32 - y_val_tensor = torch.tensor(y_val.values, dtype=torch.float32) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.float32) - elif target == "multi": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.long) # 다중 분류 → long - y_val_tensor = torch.tensor(y_val.values, dtype=torch.long) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.long) - else: - raise ValueError("target must be 'binary' or 'multi'") - - # TensorDataset 생성 - train_dataset = TensorDataset(X_train_num, X_train_cat, y_train_tensor) - val_dataset = TensorDataset(X_val_num, X_val_cat, y_val_tensor) - test_dataset = TensorDataset(X_test_num, X_test_cat, y_test_tensor) - - # DataLoader 생성 (batch_size 파라미터 사용) - if random_state == None: - train_loader = DataLoader(train_dataset, batch_size=batch_size, shuffle=True) - else: - train_loader = DataLoader(train_dataset, batch_size=batch_size, shuffle=True, generator=torch.Generator().manual_seed(random_state)) - val_loader = DataLoader(val_dataset, batch_size=batch_size, shuffle=False) - test_loader = DataLoader(test_dataset, batch_size=batch_size, shuffle=False) - - return X_train, categorical_cols, numerical_cols, train_loader, val_loader, test_loader, y_train, scaler - - -def calculate_csi(y_true, pred): - - cm = confusion_matrix(y_true, pred) # 변수 이름을 cm으로 변경 - # 혼동 행렬에서 H, F, M 추출 - H = (cm[0, 0] + cm[1, 1]) - - F = (cm[1, 0] + cm[2, 0] + - cm[0, 1] + cm[2, 1]) - - M = (cm[0, 2] + cm[1, 2]) - - # CSI 계산 - CSI = H / (H + F + M + 1e-10) - return CSI - -def sample_weight(y_train): - class_weights = compute_class_weight( - class_weight='balanced', - classes=np.unique(y_train), # 고유 클래스 - y=y_train # 학습 데이터 레이블 - ) - sample_weights = np.array([class_weights[label] for label in y_train]) - - return sample_weights - -# 하이퍼파라미터 최적화 함수 정의 -def objective(trial, model_choose, region, data_sample='pure', target='multi', n_folds=3, random_state=42): - # GPU 사용 가능 여부 확인 및 device 설정 - device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') - val_scores = [] - - # --- 1. 하이퍼파라미터 탐색 범위 정의 (수정됨) --- - if model_choose == "ft_transformer": - d_token = trial.suggest_int("d_token", 64, 256, step=32) - n_blocks = trial.suggest_int("n_blocks", 2, 6) # 깊이 축소로 과적합 방지 - n_heads = trial.suggest_categorical("n_heads", [4, 8]) - # d_token은 n_heads의 배수여야 함 (FT-Transformer의 구조적 제약 대응) - if d_token % n_heads != 0: - d_token = (d_token // n_heads) * n_heads - - attention_dropout = trial.suggest_float("attention_dropout", 0.1, 0.4) - ffn_dropout = trial.suggest_float("ffn_dropout", 0.1, 0.4) - lr = trial.suggest_float("lr", 1e-5, 1e-2, log=True) # 범위 확대 - weight_decay = trial.suggest_float("weight_decay", 1e-4, 1e-1, log=True) # 더 공격적인 범위로 확장 - batch_size = trial.suggest_categorical("batch_size", [32, 64, 128, 256]) # Batch Size 추가 - - elif model_choose == 'resnet_like': - d_main = trial.suggest_int("d_main", 64, 256, step=32) - d_hidden = trial.suggest_int("d_hidden", 64, 512, step=64) - n_blocks = trial.suggest_int("n_blocks", 2, 5) # 너무 깊지 않게 조절 - dropout_first = trial.suggest_float("dropout_first", 0.1, 0.4) - dropout_second = trial.suggest_float("dropout_second", 0.0, 0.2) - lr = trial.suggest_float("lr", 1e-5, 1e-2, log=True) - weight_decay = trial.suggest_float("weight_decay", 1e-4, 1e-1, log=True) # 더 공격적인 범위로 확장 - batch_size = trial.suggest_categorical("batch_size", [32, 64, 128, 256]) # Batch Size 추가 - - elif model_choose == 'deepgbm': - # DeepGBM의 경우 모델 특성에 맞춰 ResNet 블록 및 임베딩 차원 조절 - d_main = trial.suggest_int("d_main", 64, 256, step=32) - d_hidden = trial.suggest_int("d_hidden", 64, 256, step=64) - n_blocks = trial.suggest_int("n_blocks", 2, 6) - dropout = trial.suggest_float("dropout", 0.1, 0.4) - lr = trial.suggest_float("lr", 1e-5, 1e-2, log=True) - weight_decay = trial.suggest_float("weight_decay", 1e-4, 1e-1, log=True) # 더 공격적인 범위로 확장 - batch_size = trial.suggest_categorical("batch_size", [32, 64, 128, 256]) # Batch Size 추가 - - # --- 2. Fold별 학습 및 교차 검증 --- - for fold in range(1, n_folds + 1): - X_train_df, categorical_cols, numerical_cols, train_loader, val_loader, _, y_train, _ = prepare_dataloader_with_batchsize( - region, data_sample=data_sample, target=target, fold=fold, random_state=random_state, batch_size=batch_size - ) - - # 모델 초기화 - if model_choose == "ft_transformer": - model = FTTransformer( - num_features=len(numerical_cols), - cat_cardinalities=[len(X_train_df[col].unique()) for col in categorical_cols], - d_token=d_token, - n_blocks=n_blocks, - n_heads=n_heads, - attention_dropout=attention_dropout, - ffn_dropout=ffn_dropout, - num_classes=3 - ).to(device) - elif model_choose == 'resnet_like': - input_dim = len(numerical_cols) + len(categorical_cols) - model = ResNetLike( - input_dim=input_dim, - d_main=d_main, - d_hidden=d_hidden, - n_blocks=n_blocks, - dropout_first=dropout_first, - dropout_second=dropout_second, - num_classes=3 - ).to(device) - elif model_choose == 'deepgbm': - model = DeepGBM( - num_features=len(numerical_cols), - cat_features=[len(X_train_df[col].unique()) for col in categorical_cols], - d_main=d_main, - d_hidden=d_hidden, - n_blocks=n_blocks, - dropout=dropout, - num_classes=3 - ).to(device) - - # 클래스 가중치 계산 및 손실 함수 설정 (Label Smoothing 적용) - if target == 'multi': - class_weights = compute_class_weight( - class_weight='balanced', - classes=np.unique(y_train), - y=y_train - ) - # 클래스별 가중치 로그 출력 - unique_classes = np.unique(y_train) - class_counts = {cls: np.sum(y_train == cls) for cls in unique_classes} - print(f" Fold {fold} - 클래스별 가중치: {dict(zip(unique_classes, class_weights))} (클래스별 샘플 수: {class_counts})") - class_weights_tensor = torch.tensor(class_weights, dtype=torch.float32).to(device) - criterion = nn.CrossEntropyLoss(weight=class_weights_tensor, label_smoothing=0.0) # Label Smoothing 추가 - else: - criterion = nn.BCEWithLogitsLoss() - optimizer = optim.AdamW(model.parameters(), lr=lr, weight_decay=weight_decay) - - # 학습률 스케줄러 추가: 성능 정체 시 LR을 0.5배 감소 (검증 CSI 기준) - scheduler = optim.lr_scheduler.ReduceLROnPlateau(optimizer, mode='max', factor=0.5, patience=3) - - # 학습 설정 (에폭 및 페이션스 상향) - epochs = 200 - patience = 12 # 딥러닝의 정체 구간을 고려하여 소폭 상향 - best_fold_csi = 0 - counter = 0 - - for epoch in range(epochs): - model.train() - for x_num_batch, x_cat_batch, y_batch in train_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - - optimizer.zero_grad() - y_pred = model(x_num_batch, x_cat_batch) - loss = criterion(y_pred, y_batch if target == 'multi' else y_batch.float()) - loss.backward() - optimizer.step() - - # Validation 평가 - model.eval() - y_pred_val, y_true_val = [], [] - with torch.no_grad(): - for x_num_batch, x_cat_batch, y_batch in val_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - output = model(x_num_batch, x_cat_batch) - pred = output.argmax(dim=1) if target == 'multi' else (torch.sigmoid(output) >= 0.5).long() - - y_pred_val.extend(pred.cpu().numpy()) - y_true_val.extend(y_batch.cpu().numpy()) - - # CSI 계산 및 스케줄러 업데이트 - val_csi = calculate_csi(y_true_val, y_pred_val) - scheduler.step(val_csi) - - # Optuna Pruning 적용 (첫 번째 Fold에서 조기 종료 판단 강화) - trial.report(val_csi, epoch) - if trial.should_prune(): - raise optuna.exceptions.TrialPruned() - - # Early Stopping 체크 - if val_csi > best_fold_csi: - best_fold_csi = val_csi - counter = 0 - else: - counter += 1 - - if counter >= patience: - break - - val_scores.append(best_fold_csi) - - # 모든 fold의 평균 성능 반환 - return np.mean(val_scores) - - -# 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 함수 -def train_final_model(best_params, model_choose, region, data_sample='pure', target='multi', n_folds=3, random_state=42): - """ - 최적화된 하이퍼파라미터로 최종 모델을 학습하고 저장합니다. - - Args: - best_params: 최적화된 하이퍼파라미터 딕셔너리 - model_choose: 모델 선택 ('ft_transformer', 'resnet_like', 'deepgbm') - region: 지역명 - data_sample: 데이터 샘플 타입 ('pure', 'smote', etc.) - target: 타겟 타입 ('multi', 'binary') - n_folds: 교차 검증 fold 수 - random_state: 랜덤 시드 - - Returns: - 저장된 모델 경로 리스트 - """ - # GPU 사용 가능 여부 확인 및 device 설정 - device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') - - models = [] - scalers = [] # scaler 리스트 추가 - - print("최종 모델 학습 시작...") - - for fold in range(1, n_folds + 1): - print(f"Fold {fold} 학습 중...") - - # 최적화된 batch_size 사용 - batch_size = best_params.get("batch_size", 64) - X_train_df, categorical_cols, numerical_cols, train_loader, val_loader, _, y_train, scaler = prepare_dataloader_with_batchsize( - region, data_sample=data_sample, target=target, fold=fold, random_state=random_state, batch_size=batch_size - ) - - # 모델 초기화 - if model_choose == "ft_transformer": - d_token = best_params["d_token"] - n_heads = best_params.get("n_heads", 8) - # d_token은 n_heads의 배수여야 함 (FT-Transformer의 구조적 제약 대응) - if d_token % n_heads != 0: - d_token = (d_token // n_heads) * n_heads - - model = FTTransformer( - num_features=len(numerical_cols), - cat_cardinalities=[len(X_train_df[col].unique()) for col in categorical_cols], - d_token=d_token, - n_blocks=best_params["n_blocks"], - n_heads=n_heads, - attention_dropout=best_params["attention_dropout"], - ffn_dropout=best_params["ffn_dropout"], - num_classes=3 - ).to(device) - elif model_choose == 'resnet_like': - input_dim = len(numerical_cols) + len(categorical_cols) - model = ResNetLike( - input_dim=input_dim, - d_main=best_params["d_main"], - d_hidden=best_params["d_hidden"], - n_blocks=best_params["n_blocks"], - dropout_first=best_params["dropout_first"], - dropout_second=best_params["dropout_second"], - num_classes=3 - ).to(device) - elif model_choose == 'deepgbm': - model = DeepGBM( - num_features=len(numerical_cols), - cat_features=[len(X_train_df[col].unique()) for col in categorical_cols], - d_main=best_params["d_main"], - d_hidden=best_params["d_hidden"], - n_blocks=best_params["n_blocks"], - dropout=best_params["dropout"], - num_classes=3 - ).to(device) - else: - raise ValueError(f"Unknown model_choose: {model_choose}") - - # 클래스 가중치 계산 및 손실 함수 설정 (Label Smoothing 적용) - if target == 'multi': - class_weights = compute_class_weight( - class_weight='balanced', - classes=np.unique(y_train), - y=y_train - ) - class_weights_tensor = torch.tensor(class_weights, dtype=torch.float32).to(device) - criterion = nn.CrossEntropyLoss(weight=class_weights_tensor, label_smoothing=0.0) # Label Smoothing 추가 - else: - criterion = nn.BCEWithLogitsLoss() - optimizer = optim.AdamW(model.parameters(), lr=best_params["lr"], weight_decay=best_params["weight_decay"]) - - # 학습률 스케줄러 - scheduler = optim.lr_scheduler.ReduceLROnPlateau(optimizer, mode='max', factor=0.5, patience=3) - - # 학습 설정 - epochs = 200 - patience = 12 - best_fold_csi = 0 - counter = 0 - best_model = None - - for epoch in range(epochs): - model.train() - for x_num_batch, x_cat_batch, y_batch in train_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - - optimizer.zero_grad() - y_pred = model(x_num_batch, x_cat_batch) - loss = criterion(y_pred, y_batch if target == 'multi' else y_batch.float()) - loss.backward() - optimizer.step() - - # Validation 평가 - model.eval() - y_pred_val, y_true_val = [], [] - with torch.no_grad(): - for x_num_batch, x_cat_batch, y_batch in val_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - output = model(x_num_batch, x_cat_batch) - pred = output.argmax(dim=1) if target == 'multi' else (torch.sigmoid(output) >= 0.5).long() - - y_pred_val.extend(pred.cpu().numpy()) - y_true_val.extend(y_batch.cpu().numpy()) - - # CSI 계산 및 스케줄러 업데이트 - val_csi = calculate_csi(y_true_val, y_pred_val) - scheduler.step(val_csi) - - # Early Stopping 체크 - if val_csi > best_fold_csi: - best_fold_csi = val_csi - counter = 0 - best_model = copy.deepcopy(model) - else: - counter += 1 - - if counter >= patience: - print(f" Early stopping at epoch {epoch+1}, Best CSI: {best_fold_csi:.4f}") - break - - if best_model is None: - best_model = model - - scalers.append(scaler) # scaler 저장 (fold 순서대로) - models.append(best_model) - print(f" Fold {fold} 학습 완료 (검증 CSI: {best_fold_csi:.4f})") - - # 모델 저장 경로 설정 - save_dir = f'../save_model/{model_choose}_optima' - os.makedirs(save_dir, exist_ok=True) - - # 파일명 생성 - if data_sample == 'pure': - model_filename = f'{model_choose}_pure_{region}.pkl' - else: - model_filename = f'{model_choose}_{data_sample}_{region}.pkl' - - model_path = f'{save_dir}/{model_filename}' - - # 리스트에 담아 한 번에 저장 - joblib.dump(models, model_path) - print(f"\n모든 모델 저장 완료: {model_path} (총 {len(models)}개 fold)") - - # Scaler 별도 저장 - scaler_save_dir = f'../save_model/{model_choose}_optima/scaler' - os.makedirs(scaler_save_dir, exist_ok=True) - - # 파일명 생성 (모델과 동일한 패턴) - if data_sample == 'pure': - scaler_filename = f'{model_choose}_pure_{region}_scaler.pkl' - else: - scaler_filename = f'{model_choose}_{data_sample}_{region}_scaler.pkl' - - scaler_path = f'{scaler_save_dir}/{scaler_filename}' - joblib.dump(scalers, scaler_path) - print(f"Scaler 저장 완료: {scaler_path} (총 {len(scalers)}개 fold)") - - return model_path diff --git a/Analysis_code/5.optima/deepgbm_smotenc_ctgan20000/deepgbm_smotenc_ctgan20000_busan.py b/Analysis_code/5.optima/deepgbm_smotenc_ctgan20000/deepgbm_smotenc_ctgan20000_busan.py deleted file mode 100644 index 640aafcdf78119b9c04799ae3a4c6563b6bb4b33..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/deepgbm_smotenc_ctgan20000/deepgbm_smotenc_ctgan20000_busan.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="deepgbm", region="busan", data_sample='smotenc_ctgan20000'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/deepgbm_smotenc_ctgan20000_busan_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="deepgbm", - region="busan", - data_sample='smotenc_ctgan20000', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/deepgbm_smotenc_ctgan20000/deepgbm_smotenc_ctgan20000_daegu.py b/Analysis_code/5.optima/deepgbm_smotenc_ctgan20000/deepgbm_smotenc_ctgan20000_daegu.py deleted file mode 100644 index 00d24e71bb4c05bc40998662507b952a1d631265..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/deepgbm_smotenc_ctgan20000/deepgbm_smotenc_ctgan20000_daegu.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="deepgbm", region="daegu", data_sample='smotenc_ctgan20000'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/deepgbm_smotenc_ctgan20000_daegu_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="deepgbm", - region="daegu", - data_sample='smotenc_ctgan20000', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/deepgbm_smotenc_ctgan20000/deepgbm_smotenc_ctgan20000_daejeon.py b/Analysis_code/5.optima/deepgbm_smotenc_ctgan20000/deepgbm_smotenc_ctgan20000_daejeon.py deleted file mode 100644 index 4bea203a84e23a05c4f275ac19f0e79c1ec9c96c..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/deepgbm_smotenc_ctgan20000/deepgbm_smotenc_ctgan20000_daejeon.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="deepgbm", region="daejeon", data_sample='smotenc_ctgan20000'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/deepgbm_smotenc_ctgan20000_daejeon_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="deepgbm", - region="daejeon", - data_sample='smotenc_ctgan20000', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/deepgbm_smotenc_ctgan20000/deepgbm_smotenc_ctgan20000_gwangju.py b/Analysis_code/5.optima/deepgbm_smotenc_ctgan20000/deepgbm_smotenc_ctgan20000_gwangju.py deleted file mode 100644 index 59aaa9cb7025eb9f1b040690681c1fb9d99938bf..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/deepgbm_smotenc_ctgan20000/deepgbm_smotenc_ctgan20000_gwangju.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="deepgbm", region="gwangju", data_sample='smotenc_ctgan20000'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/deepgbm_smotenc_ctgan20000_gwangju_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="deepgbm", - region="gwangju", - data_sample='smotenc_ctgan20000', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/deepgbm_smotenc_ctgan20000/deepgbm_smotenc_ctgan20000_incheon.py b/Analysis_code/5.optima/deepgbm_smotenc_ctgan20000/deepgbm_smotenc_ctgan20000_incheon.py deleted file mode 100644 index 4c2025c32e6449675b41c491a4dc273c65f3e404..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/deepgbm_smotenc_ctgan20000/deepgbm_smotenc_ctgan20000_incheon.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="deepgbm", region="incheon", data_sample='smotenc_ctgan20000'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/deepgbm_smotenc_ctgan20000_incheon_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="deepgbm", - region="incheon", - data_sample='smotenc_ctgan20000', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/deepgbm_smotenc_ctgan20000/deepgbm_smotenc_ctgan20000_seoul.py b/Analysis_code/5.optima/deepgbm_smotenc_ctgan20000/deepgbm_smotenc_ctgan20000_seoul.py deleted file mode 100644 index 2d44d9b510bf96604ea636cf2321d9c184eeb570..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/deepgbm_smotenc_ctgan20000/deepgbm_smotenc_ctgan20000_seoul.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="deepgbm", region="seoul", data_sample='smotenc_ctgan20000'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/deepgbm_smotenc_ctgan20000_seoul_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="deepgbm", - region="seoul", - data_sample='smotenc_ctgan20000', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/deepgbm_smotenc_ctgan20000/utils.py b/Analysis_code/5.optima/deepgbm_smotenc_ctgan20000/utils.py deleted file mode 100644 index 43d496ecda4c82ad96e7ed6c5a87409fd31b53cb..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/deepgbm_smotenc_ctgan20000/utils.py +++ /dev/null @@ -1,720 +0,0 @@ -import torch -import torch.nn as nn -import torch.optim as optim -import numpy as np -import random -import os -import copy -from sklearn.preprocessing import QuantileTransformer, LabelEncoder -from torch.utils.data import DataLoader, TensorDataset -from sklearn.metrics import confusion_matrix -from sklearn.utils.class_weight import compute_class_weight -import pandas as pd -import optuna -from sklearn.metrics import accuracy_score, f1_score -import joblib - - -import sys -# 파일 위치 기반으로 models 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -models_path = os.path.abspath(os.path.join(current_file_dir, '../../models')) -sys.path.insert(0, models_path) -from ft_transformer import FTTransformer -from resnet_like import ResNetLike -from deepgbm import DeepGBM -import warnings -warnings.filterwarnings('ignore') - - -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - -# PyTorch 시드 고정 -torch.manual_seed(seed) -torch.cuda.manual_seed(seed) -torch.cuda.manual_seed_all(seed) # Multi-GPU 환경에서 동일한 시드 적용 - -# PyTorch 연산의 결정적 모드 설정 -torch.backends.cudnn.deterministic = True # 실행마다 동일한 결과를 보장 -torch.backends.cudnn.benchmark = True # 성능 최적화를 활성화 (가능한 한 빠른 연산 수행) - - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - - -# 데이터셋 준비 함수 -def prepare_dataset(region, data_sample='pure', target='multi', fold=3): - - # 파일 위치 기반으로 데이터 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) - - # 데이터 경로 지정 - dat_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_train.csv") - if data_sample == 'pure': - train_path = dat_path - else: - train_path = os.path.join(data_base_dir, f'data_oversampled/{data_sample}/{data_sample}_{fold}_{region}.csv') - test_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_test.csv") - drop_col = ['multi_class','year'] - target_col = f'{target}_class' - - # 데이터 로드 - region_dat = preprocessing(pd.read_csv(dat_path, index_col=0)) - if data_sample == 'pure': - region_train = region_dat.loc[~region_dat['year'].isin([2021-fold]), :] - else: - region_train = preprocessing(pd.read_csv(train_path)) - region_val = region_dat.loc[region_dat['year'].isin([2021-fold]), :] - region_test = preprocessing(pd.read_csv(test_path)) - - # 컬럼 정렬 (일관성 유지) - common_columns = region_train.columns.to_list() - train_data = region_train[common_columns] - val_data = region_val[common_columns] - test_data = region_test[common_columns] - - # 설명변수 & 타겟 분리 - X_train = train_data.drop(columns=drop_col) - y_train = train_data[target_col] - X_val = val_data.drop(columns=drop_col) - y_val = val_data[target_col] - X_test = test_data.drop(columns=drop_col) - y_test = test_data[target_col] - - # 범주형 & 연속형 변수 분리 - categorical_cols = X_train.select_dtypes(include=['object', 'category', 'int64']).columns - numerical_cols = X_train.select_dtypes(include=['float64']).columns - - # 범주형 변수 Label Encoding - label_encoders = {} - for col in categorical_cols: - le = LabelEncoder() - le.fit(X_train[col]) # Train 데이터 기준으로 학습 - label_encoders[col] = le - - # 변환 적용 - for col in categorical_cols: - X_train[col] = label_encoders[col].transform(X_train[col]) - X_val[col] = label_encoders[col].transform(X_val[col]) - X_test[col] = label_encoders[col].transform(X_test[col]) - - # 연속형 변수 Quantile Transformation - scaler = QuantileTransformer(output_distribution='normal') - scaler.fit(X_train[numerical_cols]) # Train 데이터 기준으로 학습 - - # 변환 적용 - X_train[numerical_cols] = scaler.transform(X_train[numerical_cols]) - X_val[numerical_cols] = scaler.transform(X_val[numerical_cols]) - X_test[numerical_cols] = scaler.transform(X_test[numerical_cols]) - - return X_train, X_val, X_test, y_train, y_val, y_test, categorical_cols, numerical_cols - - - -# 데이터 변환 및 dataloader 생성 함수 -def prepare_dataloader(region, data_sample='pure', target='multi', fold=3, random_state=None): - - # 파일 위치 기반으로 데이터 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) - - # 데이터 경로 지정 - dat_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_train.csv") - if data_sample == 'pure': - train_path = dat_path - else: - train_path = os.path.join(data_base_dir, f'data_oversampled/{data_sample}/{data_sample}_{fold}_{region}.csv') - test_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_test.csv") - drop_col = ['multi_class','year'] - target_col = f'{target}_class' - - # 데이터 로드 - region_dat = preprocessing(pd.read_csv(dat_path, index_col=0)) - if data_sample == 'pure': - region_train = region_dat.loc[~region_dat['year'].isin([2021-fold]), :] - else: - region_train = preprocessing(pd.read_csv(train_path)) - region_val = region_dat.loc[region_dat['year'].isin([2021-fold]), :] - region_test = preprocessing(pd.read_csv(test_path)) - - # 컬럼 정렬 (일관성 유지) - common_columns = region_train.columns.to_list() - train_data = region_train[common_columns] - val_data = region_val[common_columns] - test_data = region_test[common_columns] - - # 설명변수 & 타겟 분리 - X_train = train_data.drop(columns=drop_col) - y_train = train_data[target_col] - X_val = val_data.drop(columns=drop_col) - y_val = val_data[target_col] - X_test = test_data.drop(columns=drop_col) - y_test = test_data[target_col] - - # 범주형 & 연속형 변수 분리 - categorical_cols = X_train.select_dtypes(include=['object', 'category', 'int64']).columns - numerical_cols = X_train.select_dtypes(include=['float64']).columns - - # 범주형 변수 Label Encoding - label_encoders = {} - for col in categorical_cols: - le = LabelEncoder() - le.fit(X_train[col]) # Train 데이터 기준으로 학습 - label_encoders[col] = le - - # 변환 적용 - for col in categorical_cols: - X_train[col] = label_encoders[col].transform(X_train[col]) - X_val[col] = label_encoders[col].transform(X_val[col]) - X_test[col] = label_encoders[col].transform(X_test[col]) - - # 연속형 변수 Quantile Transformation - scaler = QuantileTransformer(output_distribution='normal') - scaler.fit(X_train[numerical_cols]) # Train 데이터 기준으로 학습 - - # 변환 적용 - X_train[numerical_cols] = scaler.transform(X_train[numerical_cols]) - X_val[numerical_cols] = scaler.transform(X_val[numerical_cols]) - X_test[numerical_cols] = scaler.transform(X_test[numerical_cols]) - - # 연속형 변수와 범주형 변수 분리 - X_train_num = torch.tensor(X_train[numerical_cols].values, dtype=torch.float32) - X_train_cat = torch.tensor(X_train[categorical_cols].values, dtype=torch.long) - - X_val_num = torch.tensor(X_val[numerical_cols].values, dtype=torch.float32) - X_val_cat = torch.tensor(X_val[categorical_cols].values, dtype=torch.long) - - X_test_num = torch.tensor(X_test[numerical_cols].values, dtype=torch.float32) - X_test_cat = torch.tensor(X_test[categorical_cols].values, dtype=torch.long) - - # 레이블 변환 - if target == "binary": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.float32) # 이진 분류 → float32 - y_val_tensor = torch.tensor(y_val.values, dtype=torch.float32) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.float32) - elif target == "multi": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.long) # 다중 분류 → long - y_val_tensor = torch.tensor(y_val.values, dtype=torch.long) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.long) - else: - raise ValueError("target must be 'binary' or 'multi'") - - # TensorDataset 생성 - train_dataset = TensorDataset(X_train_num, X_train_cat, y_train_tensor) - val_dataset = TensorDataset(X_val_num, X_val_cat, y_val_tensor) - test_dataset = TensorDataset(X_test_num, X_test_cat, y_test_tensor) - - # DataLoader 생성 - if random_state == None: - train_loader = DataLoader(train_dataset, batch_size=64, shuffle=True) - else: - train_loader = DataLoader(train_dataset, batch_size=64, shuffle=True, generator=torch.Generator().manual_seed(random_state)) - val_loader = DataLoader(val_dataset, batch_size=64, shuffle=False) - test_loader = DataLoader(test_dataset, batch_size=64, shuffle=False) - - return X_train, categorical_cols, numerical_cols, train_loader, val_loader, test_loader - -# 데이터 변환 및 dataloader 생성 함수 (batch_size 파라미터 추가 버전) -def prepare_dataloader_with_batchsize(region, data_sample='pure', target='multi', fold=3, random_state=None, batch_size=64): - # 파일 위치 기반으로 데이터 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) - - # 데이터 경로 지정 - dat_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_train.csv") - if data_sample == 'pure': - train_path = dat_path - else: - train_path = os.path.join(data_base_dir, f'data_oversampled/{data_sample}/{data_sample}_{fold}_{region}.csv') - test_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_test.csv") - drop_col = ['multi_class','year'] - target_col = f'{target}_class' - - # 데이터 로드 - region_dat = preprocessing(pd.read_csv(dat_path, index_col=0)) - if data_sample == 'pure': - region_train = region_dat.loc[~region_dat['year'].isin([2021-fold]), :] - else: - region_train = preprocessing(pd.read_csv(train_path)) - region_val = region_dat.loc[region_dat['year'].isin([2021-fold]), :] - region_test = preprocessing(pd.read_csv(test_path)) - - # 컬럼 정렬 (일관성 유지) - common_columns = region_train.columns.to_list() - train_data = region_train[common_columns] - val_data = region_val[common_columns] - test_data = region_test[common_columns] - - # 설명변수 & 타겟 분리 - X_train = train_data.drop(columns=drop_col) - y_train = train_data[target_col] - X_val = val_data.drop(columns=drop_col) - y_val = val_data[target_col] - X_test = test_data.drop(columns=drop_col) - y_test = test_data[target_col] - - # 범주형 & 연속형 변수 분리 - categorical_cols = X_train.select_dtypes(include=['object', 'category', 'int64']).columns - numerical_cols = X_train.select_dtypes(include=['float64']).columns - - # 범주형 변수 Label Encoding - label_encoders = {} - for col in categorical_cols: - le = LabelEncoder() - le.fit(X_train[col]) # Train 데이터 기준으로 학습 - label_encoders[col] = le - - # 변환 적용 - for col in categorical_cols: - X_train[col] = label_encoders[col].transform(X_train[col]) - X_val[col] = label_encoders[col].transform(X_val[col]) - X_test[col] = label_encoders[col].transform(X_test[col]) - - # 연속형 변수 Quantile Transformation - scaler = QuantileTransformer(output_distribution='normal') - scaler.fit(X_train[numerical_cols]) # Train 데이터 기준으로 학습 - - # 변환 적용 - X_train[numerical_cols] = scaler.transform(X_train[numerical_cols]) - X_val[numerical_cols] = scaler.transform(X_val[numerical_cols]) - X_test[numerical_cols] = scaler.transform(X_test[numerical_cols]) - - # 연속형 변수와 범주형 변수 분리 - X_train_num = torch.tensor(X_train[numerical_cols].values, dtype=torch.float32) - X_train_cat = torch.tensor(X_train[categorical_cols].values, dtype=torch.long) - - X_val_num = torch.tensor(X_val[numerical_cols].values, dtype=torch.float32) - X_val_cat = torch.tensor(X_val[categorical_cols].values, dtype=torch.long) - - X_test_num = torch.tensor(X_test[numerical_cols].values, dtype=torch.float32) - X_test_cat = torch.tensor(X_test[categorical_cols].values, dtype=torch.long) - - # 레이블 변환 - if target == "binary": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.float32) # 이진 분류 → float32 - y_val_tensor = torch.tensor(y_val.values, dtype=torch.float32) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.float32) - elif target == "multi": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.long) # 다중 분류 → long - y_val_tensor = torch.tensor(y_val.values, dtype=torch.long) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.long) - else: - raise ValueError("target must be 'binary' or 'multi'") - - # TensorDataset 생성 - train_dataset = TensorDataset(X_train_num, X_train_cat, y_train_tensor) - val_dataset = TensorDataset(X_val_num, X_val_cat, y_val_tensor) - test_dataset = TensorDataset(X_test_num, X_test_cat, y_test_tensor) - - # DataLoader 생성 (batch_size 파라미터 사용) - if random_state == None: - train_loader = DataLoader(train_dataset, batch_size=batch_size, shuffle=True) - else: - train_loader = DataLoader(train_dataset, batch_size=batch_size, shuffle=True, generator=torch.Generator().manual_seed(random_state)) - val_loader = DataLoader(val_dataset, batch_size=batch_size, shuffle=False) - test_loader = DataLoader(test_dataset, batch_size=batch_size, shuffle=False) - - return X_train, categorical_cols, numerical_cols, train_loader, val_loader, test_loader, y_train, scaler - - -def calculate_csi(y_true, pred): - - cm = confusion_matrix(y_true, pred) # 변수 이름을 cm으로 변경 - # 혼동 행렬에서 H, F, M 추출 - H = (cm[0, 0] + cm[1, 1]) - - F = (cm[1, 0] + cm[2, 0] + - cm[0, 1] + cm[2, 1]) - - M = (cm[0, 2] + cm[1, 2]) - - # CSI 계산 - CSI = H / (H + F + M + 1e-10) - return CSI - -def sample_weight(y_train): - class_weights = compute_class_weight( - class_weight='balanced', - classes=np.unique(y_train), # 고유 클래스 - y=y_train # 학습 데이터 레이블 - ) - sample_weights = np.array([class_weights[label] for label in y_train]) - - return sample_weights - -# 하이퍼파라미터 최적화 함수 정의 -def objective(trial, model_choose, region, data_sample='pure', target='multi', n_folds=3, random_state=42): - # GPU 사용 가능 여부 확인 및 device 설정 - device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') - val_scores = [] - - # --- 1. 하이퍼파라미터 탐색 범위 정의 (수정됨) --- - if model_choose == "ft_transformer": - d_token = trial.suggest_int("d_token", 64, 256, step=32) - n_blocks = trial.suggest_int("n_blocks", 2, 6) # 깊이 축소로 과적합 방지 - n_heads = trial.suggest_categorical("n_heads", [4, 8]) - # d_token은 n_heads의 배수여야 함 (FT-Transformer의 구조적 제약 대응) - if d_token % n_heads != 0: - d_token = (d_token // n_heads) * n_heads - - attention_dropout = trial.suggest_float("attention_dropout", 0.1, 0.4) - ffn_dropout = trial.suggest_float("ffn_dropout", 0.1, 0.4) - lr = trial.suggest_float("lr", 1e-5, 1e-2, log=True) # 범위 확대 - weight_decay = trial.suggest_float("weight_decay", 1e-4, 1e-1, log=True) # 더 공격적인 범위로 확장 - batch_size = trial.suggest_categorical("batch_size", [32, 64, 128, 256]) # Batch Size 추가 - - elif model_choose == 'resnet_like': - d_main = trial.suggest_int("d_main", 64, 256, step=32) - d_hidden = trial.suggest_int("d_hidden", 64, 512, step=64) - n_blocks = trial.suggest_int("n_blocks", 2, 5) # 너무 깊지 않게 조절 - dropout_first = trial.suggest_float("dropout_first", 0.1, 0.4) - dropout_second = trial.suggest_float("dropout_second", 0.0, 0.2) - lr = trial.suggest_float("lr", 1e-5, 1e-2, log=True) - weight_decay = trial.suggest_float("weight_decay", 1e-4, 1e-1, log=True) # 더 공격적인 범위로 확장 - batch_size = trial.suggest_categorical("batch_size", [32, 64, 128, 256]) # Batch Size 추가 - - elif model_choose == 'deepgbm': - # DeepGBM의 경우 모델 특성에 맞춰 ResNet 블록 및 임베딩 차원 조절 - d_main = trial.suggest_int("d_main", 64, 256, step=32) - d_hidden = trial.suggest_int("d_hidden", 64, 256, step=64) - n_blocks = trial.suggest_int("n_blocks", 2, 6) - dropout = trial.suggest_float("dropout", 0.1, 0.4) - lr = trial.suggest_float("lr", 1e-5, 1e-2, log=True) - weight_decay = trial.suggest_float("weight_decay", 1e-4, 1e-1, log=True) # 더 공격적인 범위로 확장 - batch_size = trial.suggest_categorical("batch_size", [32, 64, 128, 256]) # Batch Size 추가 - - # --- 2. Fold별 학습 및 교차 검증 --- - for fold in range(1, n_folds + 1): - X_train_df, categorical_cols, numerical_cols, train_loader, val_loader, _, y_train, _ = prepare_dataloader_with_batchsize( - region, data_sample=data_sample, target=target, fold=fold, random_state=random_state, batch_size=batch_size - ) - - # 모델 초기화 - if model_choose == "ft_transformer": - model = FTTransformer( - num_features=len(numerical_cols), - cat_cardinalities=[len(X_train_df[col].unique()) for col in categorical_cols], - d_token=d_token, - n_blocks=n_blocks, - n_heads=n_heads, - attention_dropout=attention_dropout, - ffn_dropout=ffn_dropout, - num_classes=3 - ).to(device) - elif model_choose == 'resnet_like': - input_dim = len(numerical_cols) + len(categorical_cols) - model = ResNetLike( - input_dim=input_dim, - d_main=d_main, - d_hidden=d_hidden, - n_blocks=n_blocks, - dropout_first=dropout_first, - dropout_second=dropout_second, - num_classes=3 - ).to(device) - elif model_choose == 'deepgbm': - model = DeepGBM( - num_features=len(numerical_cols), - cat_features=[len(X_train_df[col].unique()) for col in categorical_cols], - d_main=d_main, - d_hidden=d_hidden, - n_blocks=n_blocks, - dropout=dropout, - num_classes=3 - ).to(device) - - # 클래스 가중치 계산 및 손실 함수 설정 (Label Smoothing 적용) - if target == 'multi': - class_weights = compute_class_weight( - class_weight='balanced', - classes=np.unique(y_train), - y=y_train - ) - # 클래스별 가중치 로그 출력 - unique_classes = np.unique(y_train) - class_counts = {cls: np.sum(y_train == cls) for cls in unique_classes} - print(f" Fold {fold} - 클래스별 가중치: {dict(zip(unique_classes, class_weights))} (클래스별 샘플 수: {class_counts})") - class_weights_tensor = torch.tensor(class_weights, dtype=torch.float32).to(device) - criterion = nn.CrossEntropyLoss(weight=class_weights_tensor, label_smoothing=0.0) # Label Smoothing 추가 - else: - criterion = nn.BCEWithLogitsLoss() - optimizer = optim.AdamW(model.parameters(), lr=lr, weight_decay=weight_decay) - - # 학습률 스케줄러 추가: 성능 정체 시 LR을 0.5배 감소 (검증 CSI 기준) - scheduler = optim.lr_scheduler.ReduceLROnPlateau(optimizer, mode='max', factor=0.5, patience=3) - - # 학습 설정 (에폭 및 페이션스 상향) - epochs = 200 - patience = 12 # 딥러닝의 정체 구간을 고려하여 소폭 상향 - best_fold_csi = 0 - counter = 0 - - for epoch in range(epochs): - model.train() - for x_num_batch, x_cat_batch, y_batch in train_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - - optimizer.zero_grad() - y_pred = model(x_num_batch, x_cat_batch) - loss = criterion(y_pred, y_batch if target == 'multi' else y_batch.float()) - loss.backward() - optimizer.step() - - # Validation 평가 - model.eval() - y_pred_val, y_true_val = [], [] - with torch.no_grad(): - for x_num_batch, x_cat_batch, y_batch in val_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - output = model(x_num_batch, x_cat_batch) - pred = output.argmax(dim=1) if target == 'multi' else (torch.sigmoid(output) >= 0.5).long() - - y_pred_val.extend(pred.cpu().numpy()) - y_true_val.extend(y_batch.cpu().numpy()) - - # CSI 계산 및 스케줄러 업데이트 - val_csi = calculate_csi(y_true_val, y_pred_val) - scheduler.step(val_csi) - - # Optuna Pruning 적용 (첫 번째 Fold에서 조기 종료 판단 강화) - trial.report(val_csi, epoch) - if trial.should_prune(): - raise optuna.exceptions.TrialPruned() - - # Early Stopping 체크 - if val_csi > best_fold_csi: - best_fold_csi = val_csi - counter = 0 - else: - counter += 1 - - if counter >= patience: - break - - val_scores.append(best_fold_csi) - - # 모든 fold의 평균 성능 반환 - return np.mean(val_scores) - - -# 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 함수 -def train_final_model(best_params, model_choose, region, data_sample='pure', target='multi', n_folds=3, random_state=42): - """ - 최적화된 하이퍼파라미터로 최종 모델을 학습하고 저장합니다. - - Args: - best_params: 최적화된 하이퍼파라미터 딕셔너리 - model_choose: 모델 선택 ('ft_transformer', 'resnet_like', 'deepgbm') - region: 지역명 - data_sample: 데이터 샘플 타입 ('pure', 'smote', etc.) - target: 타겟 타입 ('multi', 'binary') - n_folds: 교차 검증 fold 수 - random_state: 랜덤 시드 - - Returns: - 저장된 모델 경로 리스트 - """ - # GPU 사용 가능 여부 확인 및 device 설정 - device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') - - models = [] - scalers = [] # scaler 리스트 추가 - - print("최종 모델 학습 시작...") - - for fold in range(1, n_folds + 1): - print(f"Fold {fold} 학습 중...") - - # 최적화된 batch_size 사용 - batch_size = best_params.get("batch_size", 64) - X_train_df, categorical_cols, numerical_cols, train_loader, val_loader, _, y_train, scaler = prepare_dataloader_with_batchsize( - region, data_sample=data_sample, target=target, fold=fold, random_state=random_state, batch_size=batch_size - ) - - # 모델 초기화 - if model_choose == "ft_transformer": - d_token = best_params["d_token"] - n_heads = best_params.get("n_heads", 8) - # d_token은 n_heads의 배수여야 함 (FT-Transformer의 구조적 제약 대응) - if d_token % n_heads != 0: - d_token = (d_token // n_heads) * n_heads - - model = FTTransformer( - num_features=len(numerical_cols), - cat_cardinalities=[len(X_train_df[col].unique()) for col in categorical_cols], - d_token=d_token, - n_blocks=best_params["n_blocks"], - n_heads=n_heads, - attention_dropout=best_params["attention_dropout"], - ffn_dropout=best_params["ffn_dropout"], - num_classes=3 - ).to(device) - elif model_choose == 'resnet_like': - input_dim = len(numerical_cols) + len(categorical_cols) - model = ResNetLike( - input_dim=input_dim, - d_main=best_params["d_main"], - d_hidden=best_params["d_hidden"], - n_blocks=best_params["n_blocks"], - dropout_first=best_params["dropout_first"], - dropout_second=best_params["dropout_second"], - num_classes=3 - ).to(device) - elif model_choose == 'deepgbm': - model = DeepGBM( - num_features=len(numerical_cols), - cat_features=[len(X_train_df[col].unique()) for col in categorical_cols], - d_main=best_params["d_main"], - d_hidden=best_params["d_hidden"], - n_blocks=best_params["n_blocks"], - dropout=best_params["dropout"], - num_classes=3 - ).to(device) - else: - raise ValueError(f"Unknown model_choose: {model_choose}") - - # 클래스 가중치 계산 및 손실 함수 설정 (Label Smoothing 적용) - if target == 'multi': - class_weights = compute_class_weight( - class_weight='balanced', - classes=np.unique(y_train), - y=y_train - ) - class_weights_tensor = torch.tensor(class_weights, dtype=torch.float32).to(device) - criterion = nn.CrossEntropyLoss(weight=class_weights_tensor, label_smoothing=0.0) # Label Smoothing 추가 - else: - criterion = nn.BCEWithLogitsLoss() - optimizer = optim.AdamW(model.parameters(), lr=best_params["lr"], weight_decay=best_params["weight_decay"]) - - # 학습률 스케줄러 - scheduler = optim.lr_scheduler.ReduceLROnPlateau(optimizer, mode='max', factor=0.5, patience=3) - - # 학습 설정 - epochs = 200 - patience = 12 - best_fold_csi = 0 - counter = 0 - best_model = None - - for epoch in range(epochs): - model.train() - for x_num_batch, x_cat_batch, y_batch in train_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - - optimizer.zero_grad() - y_pred = model(x_num_batch, x_cat_batch) - loss = criterion(y_pred, y_batch if target == 'multi' else y_batch.float()) - loss.backward() - optimizer.step() - - # Validation 평가 - model.eval() - y_pred_val, y_true_val = [], [] - with torch.no_grad(): - for x_num_batch, x_cat_batch, y_batch in val_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - output = model(x_num_batch, x_cat_batch) - pred = output.argmax(dim=1) if target == 'multi' else (torch.sigmoid(output) >= 0.5).long() - - y_pred_val.extend(pred.cpu().numpy()) - y_true_val.extend(y_batch.cpu().numpy()) - - # CSI 계산 및 스케줄러 업데이트 - val_csi = calculate_csi(y_true_val, y_pred_val) - scheduler.step(val_csi) - - # Early Stopping 체크 - if val_csi > best_fold_csi: - best_fold_csi = val_csi - counter = 0 - best_model = copy.deepcopy(model) - else: - counter += 1 - - if counter >= patience: - print(f" Early stopping at epoch {epoch+1}, Best CSI: {best_fold_csi:.4f}") - break - - if best_model is None: - best_model = model - - scalers.append(scaler) # scaler 저장 (fold 순서대로) - models.append(best_model) - print(f" Fold {fold} 학습 완료 (검증 CSI: {best_fold_csi:.4f})") - - # 모델 저장 경로 설정 - save_dir = f'../save_model/{model_choose}_optima' - os.makedirs(save_dir, exist_ok=True) - - # 파일명 생성 - if data_sample == 'pure': - model_filename = f'{model_choose}_pure_{region}.pkl' - else: - model_filename = f'{model_choose}_{data_sample}_{region}.pkl' - - model_path = f'{save_dir}/{model_filename}' - - # 리스트에 담아 한 번에 저장 - joblib.dump(models, model_path) - print(f"\n모든 모델 저장 완료: {model_path} (총 {len(models)}개 fold)") - - # Scaler 별도 저장 - scaler_save_dir = f'../save_model/{model_choose}_optima/scaler' - os.makedirs(scaler_save_dir, exist_ok=True) - - # 파일명 생성 (모델과 동일한 패턴) - if data_sample == 'pure': - scaler_filename = f'{model_choose}_pure_{region}_scaler.pkl' - else: - scaler_filename = f'{model_choose}_{data_sample}_{region}_scaler.pkl' - - scaler_path = f'{scaler_save_dir}/{scaler_filename}' - joblib.dump(scalers, scaler_path) - print(f"Scaler 저장 완료: {scaler_path} (총 {len(scalers)}개 fold)") - - return model_path diff --git a/Analysis_code/5.optima/ft_transformer_ctgan10000/ft_transformer_ctgan10000_busan.py b/Analysis_code/5.optima/ft_transformer_ctgan10000/ft_transformer_ctgan10000_busan.py deleted file mode 100644 index 513f66f47e9869609e6d7c5c40892a5a189d72c0..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/ft_transformer_ctgan10000/ft_transformer_ctgan10000_busan.py +++ /dev/null @@ -1,96 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="ft_transformer", region="busan", data_sample='ctgan10000'), - n_trials=100, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/ft_transformer_ctgan10000_busan_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="ft_transformer", - region="busan", - data_sample='ctgan10000', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/ft_transformer_ctgan10000/ft_transformer_ctgan10000_daegu.py b/Analysis_code/5.optima/ft_transformer_ctgan10000/ft_transformer_ctgan10000_daegu.py deleted file mode 100644 index e771cc7f1f435b4832f1284f467ebb8f9fc031a4..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/ft_transformer_ctgan10000/ft_transformer_ctgan10000_daegu.py +++ /dev/null @@ -1,96 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="ft_transformer", region="daegu", data_sample='ctgan10000'), - n_trials=100, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/ft_transformer_ctgan10000_daegu_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="ft_transformer", - region="daegu", - data_sample='ctgan10000', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/ft_transformer_ctgan10000/ft_transformer_ctgan10000_daejeon.py b/Analysis_code/5.optima/ft_transformer_ctgan10000/ft_transformer_ctgan10000_daejeon.py deleted file mode 100644 index e589cd02bb6ace4d63d8998ffc248387f6db4498..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/ft_transformer_ctgan10000/ft_transformer_ctgan10000_daejeon.py +++ /dev/null @@ -1,96 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="ft_transformer", region="daejeon", data_sample='ctgan10000'), - n_trials=100, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/ft_transformer_ctgan10000_daejeon_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="ft_transformer", - region="daejeon", - data_sample='ctgan10000', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/ft_transformer_ctgan10000/ft_transformer_ctgan10000_gwangju.py b/Analysis_code/5.optima/ft_transformer_ctgan10000/ft_transformer_ctgan10000_gwangju.py deleted file mode 100644 index c286b90507bea60f87d6ea4bc884af5ac0b14c82..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/ft_transformer_ctgan10000/ft_transformer_ctgan10000_gwangju.py +++ /dev/null @@ -1,96 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="ft_transformer", region="gwangju", data_sample='ctgan10000'), - n_trials=100, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/ft_transformer_ctgan10000_gwangju_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="ft_transformer", - region="gwangju", - data_sample='ctgan10000', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/ft_transformer_ctgan10000/ft_transformer_ctgan10000_incheon.py b/Analysis_code/5.optima/ft_transformer_ctgan10000/ft_transformer_ctgan10000_incheon.py deleted file mode 100644 index ee055b57e8f9a56011aa47bafc16888a44441204..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/ft_transformer_ctgan10000/ft_transformer_ctgan10000_incheon.py +++ /dev/null @@ -1,96 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="ft_transformer", region="incheon", data_sample='ctgan10000'), - n_trials=100, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/ft_transformer_ctgan10000_incheon_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="ft_transformer", - region="incheon", - data_sample='ctgan10000', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/ft_transformer_ctgan10000/ft_transformer_ctgan10000_seoul.py b/Analysis_code/5.optima/ft_transformer_ctgan10000/ft_transformer_ctgan10000_seoul.py deleted file mode 100644 index 85c3d9ae25fadb185b5d1d82e8a6f3b6e145ad03..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/ft_transformer_ctgan10000/ft_transformer_ctgan10000_seoul.py +++ /dev/null @@ -1,96 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="ft_transformer", region="seoul", data_sample='ctgan10000'), - n_trials=100, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/ft_transformer_ctgan10000_seoul_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="ft_transformer", - region="seoul", - data_sample='ctgan10000', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/ft_transformer_ctgan10000/utils.py b/Analysis_code/5.optima/ft_transformer_ctgan10000/utils.py deleted file mode 100644 index ed3ba502d2669af274cc5f990de41c8b37d7776f..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/ft_transformer_ctgan10000/utils.py +++ /dev/null @@ -1,720 +0,0 @@ -import torch -import torch.nn as nn -import torch.optim as optim -import numpy as np -import random -import os -import copy -from sklearn.preprocessing import QuantileTransformer, LabelEncoder -from torch.utils.data import DataLoader, TensorDataset -from sklearn.metrics import confusion_matrix -from sklearn.utils.class_weight import compute_class_weight -import pandas as pd -import optuna -from sklearn.metrics import accuracy_score, f1_score -import joblib - - -import sys -# 파일 위치 기반으로 models 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -models_path = os.path.abspath(os.path.join(current_file_dir, '../../models')) -sys.path.insert(0, models_path) -from ft_transformer import FTTransformer -from resnet_like import ResNetLike -from deepgbm import DeepGBM -import warnings -warnings.filterwarnings('ignore') - -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - -# PyTorch 시드 고정 -torch.manual_seed(seed) -torch.cuda.manual_seed(seed) -torch.cuda.manual_seed_all(seed) # Multi-GPU 환경에서 동일한 시드 적용 - -# PyTorch 연산의 결정적 모드 설정 -torch.backends.cudnn.deterministic = True # 실행마다 동일한 결과를 보장 -torch.backends.cudnn.benchmark = True # 성능 최적화를 활성화 (가능한 한 빠른 연산 수행) - - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - - -# 데이터셋 준비 함수 -def prepare_dataset(region, data_sample='pure', target='multi', fold=3): - - # 파일 위치 기반으로 데이터 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) - - # 데이터 경로 지정 - dat_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_train.csv") - if data_sample == 'pure': - train_path = dat_path - else: - train_path = os.path.join(data_base_dir, f'data_oversampled/{data_sample}/{data_sample}_{fold}_{region}.csv') - test_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_test.csv") - drop_col = ['multi_class','year'] - target_col = f'{target}_class' - - # 데이터 로드 - region_dat = preprocessing(pd.read_csv(dat_path, index_col=0)) - if data_sample == 'pure': - region_train = region_dat.loc[~region_dat['year'].isin([2021-fold]), :] - else: - region_train = preprocessing(pd.read_csv(train_path)) - region_val = region_dat.loc[region_dat['year'].isin([2021-fold]), :] - region_test = preprocessing(pd.read_csv(test_path)) - - # 컬럼 정렬 (일관성 유지) - common_columns = region_train.columns.to_list() - train_data = region_train[common_columns] - val_data = region_val[common_columns] - test_data = region_test[common_columns] - - # 설명변수 & 타겟 분리 - X_train = train_data.drop(columns=drop_col) - y_train = train_data[target_col] - X_val = val_data.drop(columns=drop_col) - y_val = val_data[target_col] - X_test = test_data.drop(columns=drop_col) - y_test = test_data[target_col] - - # 범주형 & 연속형 변수 분리 - categorical_cols = X_train.select_dtypes(include=['object', 'category', 'int64']).columns - numerical_cols = X_train.select_dtypes(include=['float64']).columns - - # 범주형 변수 Label Encoding - label_encoders = {} - for col in categorical_cols: - le = LabelEncoder() - le.fit(X_train[col]) # Train 데이터 기준으로 학습 - label_encoders[col] = le - - # 변환 적용 - for col in categorical_cols: - X_train[col] = label_encoders[col].transform(X_train[col]) - X_val[col] = label_encoders[col].transform(X_val[col]) - X_test[col] = label_encoders[col].transform(X_test[col]) - - # 연속형 변수 Quantile Transformation - scaler = QuantileTransformer(output_distribution='normal') - scaler.fit(X_train[numerical_cols]) # Train 데이터 기준으로 학습 - - # 변환 적용 - X_train[numerical_cols] = scaler.transform(X_train[numerical_cols]) - X_val[numerical_cols] = scaler.transform(X_val[numerical_cols]) - X_test[numerical_cols] = scaler.transform(X_test[numerical_cols]) - - return X_train, X_val, X_test, y_train, y_val, y_test, categorical_cols, numerical_cols - - - -# 데이터 변환 및 dataloader 생성 함수 -def prepare_dataloader(region, data_sample='pure', target='multi', fold=3, random_state=None): - - # 파일 위치 기반으로 데이터 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) - - # 데이터 경로 지정 - dat_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_train.csv") - if data_sample == 'pure': - train_path = dat_path - else: - train_path = os.path.join(data_base_dir, f'data_oversampled/{data_sample}/{data_sample}_{fold}_{region}.csv') - test_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_test.csv") - drop_col = ['multi_class','year'] - target_col = f'{target}_class' - - # 데이터 로드 - region_dat = preprocessing(pd.read_csv(dat_path, index_col=0)) - if data_sample == 'pure': - region_train = region_dat.loc[~region_dat['year'].isin([2021-fold]), :] - else: - region_train = preprocessing(pd.read_csv(train_path)) - region_val = region_dat.loc[region_dat['year'].isin([2021-fold]), :] - region_test = preprocessing(pd.read_csv(test_path)) - - # 컬럼 정렬 (일관성 유지) - common_columns = region_train.columns.to_list() - train_data = region_train[common_columns] - val_data = region_val[common_columns] - test_data = region_test[common_columns] - - # 설명변수 & 타겟 분리 - X_train = train_data.drop(columns=drop_col) - y_train = train_data[target_col] - X_val = val_data.drop(columns=drop_col) - y_val = val_data[target_col] - X_test = test_data.drop(columns=drop_col) - y_test = test_data[target_col] - - # 범주형 & 연속형 변수 분리 - categorical_cols = X_train.select_dtypes(include=['object', 'category', 'int64']).columns - numerical_cols = X_train.select_dtypes(include=['float64']).columns - - # 범주형 변수 Label Encoding - label_encoders = {} - for col in categorical_cols: - le = LabelEncoder() - le.fit(X_train[col]) # Train 데이터 기준으로 학습 - label_encoders[col] = le - - # 변환 적용 - for col in categorical_cols: - X_train[col] = label_encoders[col].transform(X_train[col]) - X_val[col] = label_encoders[col].transform(X_val[col]) - X_test[col] = label_encoders[col].transform(X_test[col]) - - # 연속형 변수 Quantile Transformation - scaler = QuantileTransformer(output_distribution='normal') - scaler.fit(X_train[numerical_cols]) # Train 데이터 기준으로 학습 - - # 변환 적용 - X_train[numerical_cols] = scaler.transform(X_train[numerical_cols]) - X_val[numerical_cols] = scaler.transform(X_val[numerical_cols]) - X_test[numerical_cols] = scaler.transform(X_test[numerical_cols]) - - # 연속형 변수와 범주형 변수 분리 - X_train_num = torch.tensor(X_train[numerical_cols].values, dtype=torch.float32) - X_train_cat = torch.tensor(X_train[categorical_cols].values, dtype=torch.long) - - X_val_num = torch.tensor(X_val[numerical_cols].values, dtype=torch.float32) - X_val_cat = torch.tensor(X_val[categorical_cols].values, dtype=torch.long) - - X_test_num = torch.tensor(X_test[numerical_cols].values, dtype=torch.float32) - X_test_cat = torch.tensor(X_test[categorical_cols].values, dtype=torch.long) - - # 레이블 변환 - if target == "binary": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.float32) # 이진 분류 → float32 - y_val_tensor = torch.tensor(y_val.values, dtype=torch.float32) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.float32) - elif target == "multi": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.long) # 다중 분류 → long - y_val_tensor = torch.tensor(y_val.values, dtype=torch.long) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.long) - else: - raise ValueError("target must be 'binary' or 'multi'") - - # TensorDataset 생성 - train_dataset = TensorDataset(X_train_num, X_train_cat, y_train_tensor) - val_dataset = TensorDataset(X_val_num, X_val_cat, y_val_tensor) - test_dataset = TensorDataset(X_test_num, X_test_cat, y_test_tensor) - - # DataLoader 생성 - if random_state == None: - train_loader = DataLoader(train_dataset, batch_size=64, shuffle=True) - else: - train_loader = DataLoader(train_dataset, batch_size=64, shuffle=True, generator=torch.Generator().manual_seed(random_state)) - val_loader = DataLoader(val_dataset, batch_size=64, shuffle=False) - test_loader = DataLoader(test_dataset, batch_size=64, shuffle=False) - - return X_train, categorical_cols, numerical_cols, train_loader, val_loader, test_loader - -# 데이터 변환 및 dataloader 생성 함수 (batch_size 파라미터 추가 버전) -def prepare_dataloader_with_batchsize(region, data_sample='pure', target='multi', fold=3, random_state=None, batch_size=64): - # 파일 위치 기반으로 데이터 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) - - # 데이터 경로 지정 - dat_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_train.csv") - if data_sample == 'pure': - train_path = dat_path - else: - train_path = os.path.join(data_base_dir, f'data_oversampled/{data_sample}/{data_sample}_{fold}_{region}.csv') - test_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_test.csv") - drop_col = ['multi_class','year'] - target_col = f'{target}_class' - - # 데이터 로드 - region_dat = preprocessing(pd.read_csv(dat_path, index_col=0)) - if data_sample == 'pure': - region_train = region_dat.loc[~region_dat['year'].isin([2021-fold]), :] - else: - region_train = preprocessing(pd.read_csv(train_path)) - region_val = region_dat.loc[region_dat['year'].isin([2021-fold]), :] - region_test = preprocessing(pd.read_csv(test_path)) - - # 컬럼 정렬 (일관성 유지) - common_columns = region_train.columns.to_list() - train_data = region_train[common_columns] - val_data = region_val[common_columns] - test_data = region_test[common_columns] - - # 설명변수 & 타겟 분리 - X_train = train_data.drop(columns=drop_col) - y_train = train_data[target_col] - X_val = val_data.drop(columns=drop_col) - y_val = val_data[target_col] - X_test = test_data.drop(columns=drop_col) - y_test = test_data[target_col] - - # 범주형 & 연속형 변수 분리 - categorical_cols = X_train.select_dtypes(include=['object', 'category', 'int64']).columns - numerical_cols = X_train.select_dtypes(include=['float64']).columns - - # 범주형 변수 Label Encoding - label_encoders = {} - for col in categorical_cols: - le = LabelEncoder() - le.fit(X_train[col]) # Train 데이터 기준으로 학습 - label_encoders[col] = le - - # 변환 적용 - for col in categorical_cols: - X_train[col] = label_encoders[col].transform(X_train[col]) - X_val[col] = label_encoders[col].transform(X_val[col]) - X_test[col] = label_encoders[col].transform(X_test[col]) - - # 연속형 변수 Quantile Transformation - scaler = QuantileTransformer(output_distribution='normal') - scaler.fit(X_train[numerical_cols]) # Train 데이터 기준으로 학습 - - # 변환 적용 - X_train[numerical_cols] = scaler.transform(X_train[numerical_cols]) - X_val[numerical_cols] = scaler.transform(X_val[numerical_cols]) - X_test[numerical_cols] = scaler.transform(X_test[numerical_cols]) - - # 연속형 변수와 범주형 변수 분리 - X_train_num = torch.tensor(X_train[numerical_cols].values, dtype=torch.float32) - X_train_cat = torch.tensor(X_train[categorical_cols].values, dtype=torch.long) - - X_val_num = torch.tensor(X_val[numerical_cols].values, dtype=torch.float32) - X_val_cat = torch.tensor(X_val[categorical_cols].values, dtype=torch.long) - - X_test_num = torch.tensor(X_test[numerical_cols].values, dtype=torch.float32) - X_test_cat = torch.tensor(X_test[categorical_cols].values, dtype=torch.long) - - # 레이블 변환 - if target == "binary": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.float32) # 이진 분류 → float32 - y_val_tensor = torch.tensor(y_val.values, dtype=torch.float32) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.float32) - elif target == "multi": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.long) # 다중 분류 → long - y_val_tensor = torch.tensor(y_val.values, dtype=torch.long) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.long) - else: - raise ValueError("target must be 'binary' or 'multi'") - - # TensorDataset 생성 - train_dataset = TensorDataset(X_train_num, X_train_cat, y_train_tensor) - val_dataset = TensorDataset(X_val_num, X_val_cat, y_val_tensor) - test_dataset = TensorDataset(X_test_num, X_test_cat, y_test_tensor) - - # DataLoader 생성 (batch_size 파라미터 사용) - if random_state == None: - train_loader = DataLoader(train_dataset, batch_size=batch_size, shuffle=True) - else: - train_loader = DataLoader(train_dataset, batch_size=batch_size, shuffle=True, generator=torch.Generator().manual_seed(random_state)) - val_loader = DataLoader(val_dataset, batch_size=batch_size, shuffle=False) - test_loader = DataLoader(test_dataset, batch_size=batch_size, shuffle=False) - - return X_train, categorical_cols, numerical_cols, train_loader, val_loader, test_loader, y_train, scaler - - -def calculate_csi(y_true, pred): - - cm = confusion_matrix(y_true, pred) # 변수 이름을 cm으로 변경 - # 혼동 행렬에서 H, F, M 추출 - H = (cm[0, 0] + cm[1, 1]) - - F = (cm[1, 0] + cm[2, 0] + - cm[0, 1] + cm[2, 1]) - - M = (cm[0, 2] + cm[1, 2]) - - # CSI 계산 - CSI = H / (H + F + M + 1e-10) - return CSI - -def sample_weight(y_train): - class_weights = compute_class_weight( - class_weight='balanced', - classes=np.unique(y_train), # 고유 클래스 - y=y_train # 학습 데이터 레이블 - ) - sample_weights = np.array([class_weights[label] for label in y_train]) - - return sample_weights - -# 하이퍼파라미터 최적화 함수 정의 -def objective(trial, model_choose, region, data_sample='pure', target='multi', n_folds=3, random_state=42): - # GPU 사용 가능 여부 확인 및 device 설정 - device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') - val_scores = [] - - # --- 1. 하이퍼파라미터 탐색 범위 정의 (수정됨) --- - if model_choose == "ft_transformer": - d_token = trial.suggest_int("d_token", 64, 256, step=32) - n_blocks = trial.suggest_int("n_blocks", 2, 6) # 깊이 축소로 과적합 방지 - n_heads = trial.suggest_categorical("n_heads", [4, 8]) - # d_token은 n_heads의 배수여야 함 (FT-Transformer의 구조적 제약 대응) - if d_token % n_heads != 0: - d_token = (d_token // n_heads) * n_heads - - attention_dropout = trial.suggest_float("attention_dropout", 0.1, 0.4) - ffn_dropout = trial.suggest_float("ffn_dropout", 0.1, 0.4) - lr = trial.suggest_float("lr", 1e-5, 1e-2, log=True) # 범위 확대 - weight_decay = trial.suggest_float("weight_decay", 1e-4, 1e-1, log=True) # 더 공격적인 범위로 확장 - batch_size = trial.suggest_categorical("batch_size", [32, 64, 128, 256]) # Batch Size 추가 - - elif model_choose == 'resnet_like': - d_main = trial.suggest_int("d_main", 64, 256, step=32) - d_hidden = trial.suggest_int("d_hidden", 64, 512, step=64) - n_blocks = trial.suggest_int("n_blocks", 2, 5) # 너무 깊지 않게 조절 - dropout_first = trial.suggest_float("dropout_first", 0.1, 0.4) - dropout_second = trial.suggest_float("dropout_second", 0.0, 0.2) - lr = trial.suggest_float("lr", 1e-5, 1e-2, log=True) - weight_decay = trial.suggest_float("weight_decay", 1e-4, 1e-1, log=True) # 더 공격적인 범위로 확장 - batch_size = trial.suggest_categorical("batch_size", [32, 64, 128, 256]) # Batch Size 추가 - - elif model_choose == 'deepgbm': - # DeepGBM의 경우 모델 특성에 맞춰 ResNet 블록 및 임베딩 차원 조절 - d_main = trial.suggest_int("d_main", 64, 256, step=32) - d_hidden = trial.suggest_int("d_hidden", 64, 256, step=64) - n_blocks = trial.suggest_int("n_blocks", 2, 6) - dropout = trial.suggest_float("dropout", 0.1, 0.4) - lr = trial.suggest_float("lr", 1e-5, 1e-2, log=True) - weight_decay = trial.suggest_float("weight_decay", 1e-4, 1e-1, log=True) # 더 공격적인 범위로 확장 - batch_size = trial.suggest_categorical("batch_size", [32, 64, 128, 256]) # Batch Size 추가 - - # --- 2. Fold별 학습 및 교차 검증 --- - for fold in range(1, n_folds + 1): - X_train_df, categorical_cols, numerical_cols, train_loader, val_loader, _, y_train, _ = prepare_dataloader_with_batchsize( - region, data_sample=data_sample, target=target, fold=fold, random_state=random_state, batch_size=batch_size - ) - - # 모델 초기화 - if model_choose == "ft_transformer": - model = FTTransformer( - num_features=len(numerical_cols), - cat_cardinalities=[len(X_train_df[col].unique()) for col in categorical_cols], - d_token=d_token, - n_blocks=n_blocks, - n_heads=n_heads, - attention_dropout=attention_dropout, - ffn_dropout=ffn_dropout, - num_classes=3 - ).to(device) - elif model_choose == 'resnet_like': - input_dim = len(numerical_cols) + len(categorical_cols) - model = ResNetLike( - input_dim=input_dim, - d_main=d_main, - d_hidden=d_hidden, - n_blocks=n_blocks, - dropout_first=dropout_first, - dropout_second=dropout_second, - num_classes=3 - ).to(device) - elif model_choose == 'deepgbm': - model = DeepGBM( - num_features=len(numerical_cols), - cat_features=[len(X_train_df[col].unique()) for col in categorical_cols], - d_main=d_main, - d_hidden=d_hidden, - n_blocks=n_blocks, - dropout=dropout, - num_classes=3 - ).to(device) - - # 클래스 가중치 계산 및 손실 함수 설정 (Label Smoothing 적용) - if target == 'multi': - class_weights = compute_class_weight( - class_weight='balanced', - classes=np.unique(y_train), - y=y_train - ) - # 클래스별 가중치 로그 출력 - unique_classes = np.unique(y_train) - class_counts = {cls: np.sum(y_train == cls) for cls in unique_classes} - print(f" Fold {fold} - 클래스별 가중치: {dict(zip(unique_classes, class_weights))} (클래스별 샘플 수: {class_counts})") - class_weights_tensor = torch.tensor(class_weights, dtype=torch.float32).to(device) - criterion = nn.CrossEntropyLoss(weight=class_weights_tensor, label_smoothing=0.0) # Label Smoothing 추가 - else: - criterion = nn.BCEWithLogitsLoss() - optimizer = optim.AdamW(model.parameters(), lr=lr, weight_decay=weight_decay) - - # 학습률 스케줄러 추가: 성능 정체 시 LR을 0.5배 감소 (검증 CSI 기준) - scheduler = optim.lr_scheduler.ReduceLROnPlateau(optimizer, mode='max', factor=0.5, patience=3) - - # 학습 설정 (에폭 및 페이션스 상향) - epochs = 200 - patience = 12 # 딥러닝의 정체 구간을 고려하여 소폭 상향 - best_fold_csi = 0 - counter = 0 - - for epoch in range(epochs): - model.train() - for x_num_batch, x_cat_batch, y_batch in train_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - - optimizer.zero_grad() - y_pred = model(x_num_batch, x_cat_batch) - loss = criterion(y_pred, y_batch if target == 'multi' else y_batch.float()) - loss.backward() - optimizer.step() - - # Validation 평가 - model.eval() - y_pred_val, y_true_val = [], [] - with torch.no_grad(): - for x_num_batch, x_cat_batch, y_batch in val_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - output = model(x_num_batch, x_cat_batch) - pred = output.argmax(dim=1) if target == 'multi' else (torch.sigmoid(output) >= 0.5).long() - - y_pred_val.extend(pred.cpu().numpy()) - y_true_val.extend(y_batch.cpu().numpy()) - - # CSI 계산 및 스케줄러 업데이트 - val_csi = calculate_csi(y_true_val, y_pred_val) - scheduler.step(val_csi) - - # Optuna Pruning 적용 (첫 번째 Fold에서 조기 종료 판단 강화) - trial.report(val_csi, epoch) - if trial.should_prune(): - raise optuna.exceptions.TrialPruned() - - # Early Stopping 체크 - if val_csi > best_fold_csi: - best_fold_csi = val_csi - counter = 0 - else: - counter += 1 - - if counter >= patience: - break - - val_scores.append(best_fold_csi) - - # 모든 fold의 평균 성능 반환 - return np.mean(val_scores) - - -# 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 함수 -def train_final_model(best_params, model_choose, region, data_sample='pure', target='multi', n_folds=3, random_state=42): - """ - 최적화된 하이퍼파라미터로 최종 모델을 학습하고 저장합니다. - - Args: - best_params: 최적화된 하이퍼파라미터 딕셔너리 - model_choose: 모델 선택 ('ft_transformer', 'resnet_like', 'deepgbm') - region: 지역명 - data_sample: 데이터 샘플 타입 ('pure', 'smote', etc.) - target: 타겟 타입 ('multi', 'binary') - n_folds: 교차 검증 fold 수 - random_state: 랜덤 시드 - - Returns: - 저장된 모델 경로 리스트 - """ - # GPU 사용 가능 여부 확인 및 device 설정 - device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') - - models = [] - scalers = [] # scaler 리스트 추가 - - print("최종 모델 학습 시작...") - - for fold in range(1, n_folds + 1): - print(f"Fold {fold} 학습 중...") - - # 최적화된 batch_size 사용 - batch_size = best_params.get("batch_size", 64) - X_train_df, categorical_cols, numerical_cols, train_loader, val_loader, _, y_train, scaler = prepare_dataloader_with_batchsize( - region, data_sample=data_sample, target=target, fold=fold, random_state=random_state, batch_size=batch_size - ) - - # 모델 초기화 - if model_choose == "ft_transformer": - d_token = best_params["d_token"] - n_heads = best_params.get("n_heads", 8) - # d_token은 n_heads의 배수여야 함 (FT-Transformer의 구조적 제약 대응) - if d_token % n_heads != 0: - d_token = (d_token // n_heads) * n_heads - - model = FTTransformer( - num_features=len(numerical_cols), - cat_cardinalities=[len(X_train_df[col].unique()) for col in categorical_cols], - d_token=d_token, - n_blocks=best_params["n_blocks"], - n_heads=n_heads, - attention_dropout=best_params["attention_dropout"], - ffn_dropout=best_params["ffn_dropout"], - num_classes=3 - ).to(device) - elif model_choose == 'resnet_like': - input_dim = len(numerical_cols) + len(categorical_cols) - model = ResNetLike( - input_dim=input_dim, - d_main=best_params["d_main"], - d_hidden=best_params["d_hidden"], - n_blocks=best_params["n_blocks"], - dropout_first=best_params["dropout_first"], - dropout_second=best_params["dropout_second"], - num_classes=3 - ).to(device) - elif model_choose == 'deepgbm': - model = DeepGBM( - num_features=len(numerical_cols), - cat_features=[len(X_train_df[col].unique()) for col in categorical_cols], - d_main=best_params["d_main"], - d_hidden=best_params["d_hidden"], - n_blocks=best_params["n_blocks"], - dropout=best_params["dropout"], - num_classes=3 - ).to(device) - else: - raise ValueError(f"Unknown model_choose: {model_choose}") - - # 클래스 가중치 계산 및 손실 함수 설정 (Label Smoothing 적용) - if target == 'multi': - class_weights = compute_class_weight( - class_weight='balanced', - classes=np.unique(y_train), - y=y_train - ) - class_weights_tensor = torch.tensor(class_weights, dtype=torch.float32).to(device) - criterion = nn.CrossEntropyLoss(weight=class_weights_tensor, label_smoothing=0.0) # Label Smoothing 추가 - else: - criterion = nn.BCEWithLogitsLoss() - optimizer = optim.AdamW(model.parameters(), lr=best_params["lr"], weight_decay=best_params["weight_decay"]) - - # 학습률 스케줄러 - scheduler = optim.lr_scheduler.ReduceLROnPlateau(optimizer, mode='max', factor=0.5, patience=3) - - # 학습 설정 - epochs = 200 - patience = 12 - best_fold_csi = 0 - counter = 0 - best_model = None - - for epoch in range(epochs): - model.train() - for x_num_batch, x_cat_batch, y_batch in train_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - - optimizer.zero_grad() - y_pred = model(x_num_batch, x_cat_batch) - loss = criterion(y_pred, y_batch if target == 'multi' else y_batch.float()) - loss.backward() - optimizer.step() - - # Validation 평가 - model.eval() - y_pred_val, y_true_val = [], [] - with torch.no_grad(): - for x_num_batch, x_cat_batch, y_batch in val_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - output = model(x_num_batch, x_cat_batch) - pred = output.argmax(dim=1) if target == 'multi' else (torch.sigmoid(output) >= 0.5).long() - - y_pred_val.extend(pred.cpu().numpy()) - y_true_val.extend(y_batch.cpu().numpy()) - - # CSI 계산 및 스케줄러 업데이트 - val_csi = calculate_csi(y_true_val, y_pred_val) - scheduler.step(val_csi) - - # Early Stopping 체크 - if val_csi > best_fold_csi: - best_fold_csi = val_csi - counter = 0 - best_model = copy.deepcopy(model) - else: - counter += 1 - - if counter >= patience: - print(f" Early stopping at epoch {epoch+1}, Best CSI: {best_fold_csi:.4f}") - break - - if best_model is None: - best_model = model - - scalers.append(scaler) # scaler 저장 (fold 순서대로) - models.append(best_model) - print(f" Fold {fold} 학습 완료 (검증 CSI: {best_fold_csi:.4f})") - - # 모델 저장 경로 설정 - save_dir = f'../save_model/{model_choose}_optima' - os.makedirs(save_dir, exist_ok=True) - - # 파일명 생성 - if data_sample == 'pure': - model_filename = f'{model_choose}_pure_{region}.pkl' - else: - model_filename = f'{model_choose}_{data_sample}_{region}.pkl' - - model_path = f'{save_dir}/{model_filename}' - - # 리스트에 담아 한 번에 저장 - joblib.dump(models, model_path) - print(f"\n모든 모델 저장 완료: {model_path} (총 {len(models)}개 fold)") - - # Scaler 별도 저장 - scaler_save_dir = f'../save_model/{model_choose}_optima/scaler' - os.makedirs(scaler_save_dir, exist_ok=True) - - # 파일명 생성 (모델과 동일한 패턴) - if data_sample == 'pure': - scaler_filename = f'{model_choose}_pure_{region}_scaler.pkl' - else: - scaler_filename = f'{model_choose}_{data_sample}_{region}_scaler.pkl' - - scaler_path = f'{scaler_save_dir}/{scaler_filename}' - joblib.dump(scalers, scaler_path) - print(f"Scaler 저장 완료: {scaler_path} (총 {len(scalers)}개 fold)") - - return model_path - diff --git a/Analysis_code/5.optima/ft_transformer_pure/ft_transforemer_pure_busan.py b/Analysis_code/5.optima/ft_transformer_pure/ft_transforemer_pure_busan.py deleted file mode 100644 index 4553ed82192d3d57fec55b5875dd506b9710d12c..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/ft_transformer_pure/ft_transforemer_pure_busan.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="ft_transformer", region="busan"), - n_trials=100, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/ft_transformer_pure_busan_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_paths = train_final_model( - best_params=best_params, - model_choose="ft_transformer", - region="busan", - data_sample='pure', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로:") - for path in model_paths: - print(f" - {path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) \ No newline at end of file diff --git a/Analysis_code/5.optima/ft_transformer_pure/ft_transforemer_pure_daegu.py b/Analysis_code/5.optima/ft_transformer_pure/ft_transforemer_pure_daegu.py deleted file mode 100644 index 414e2d3073cb96f541452f71c6f3fb747e2dc8c8..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/ft_transformer_pure/ft_transforemer_pure_daegu.py +++ /dev/null @@ -1,99 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="ft_transformer", region="daegu"), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/ft_transformer_pure_daegu_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_paths = train_final_model( - best_params=best_params, - model_choose="ft_transformer", - region="daegu", - data_sample='pure', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로:") - for path in model_paths: - print(f" - {path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/ft_transformer_pure/ft_transforemer_pure_daejeon.py b/Analysis_code/5.optima/ft_transformer_pure/ft_transforemer_pure_daejeon.py deleted file mode 100644 index e3aef1c3fe9b16de324b798ff54e15116dcc84b8..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/ft_transformer_pure/ft_transforemer_pure_daejeon.py +++ /dev/null @@ -1,99 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="ft_transformer", region="daejeon"), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/ft_transformer_pure_daejeon_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_paths = train_final_model( - best_params=best_params, - model_choose="ft_transformer", - region="daejeon", - data_sample='pure', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로:") - for path in model_paths: - print(f" - {path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/ft_transformer_pure/ft_transforemer_pure_gwangju.py b/Analysis_code/5.optima/ft_transformer_pure/ft_transforemer_pure_gwangju.py deleted file mode 100644 index 5da9a6af927bebfb5ff5ae85830e04adabbf20f3..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/ft_transformer_pure/ft_transforemer_pure_gwangju.py +++ /dev/null @@ -1,99 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="ft_transformer", region="gwangju"), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/ft_transformer_pure_gwangju_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_paths = train_final_model( - best_params=best_params, - model_choose="ft_transformer", - region="gwangju", - data_sample='pure', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로:") - for path in model_paths: - print(f" - {path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/ft_transformer_pure/ft_transforemer_pure_incheon.py b/Analysis_code/5.optima/ft_transformer_pure/ft_transforemer_pure_incheon.py deleted file mode 100644 index 7137c1d413d0ae851eb9a7f7756a224d6571ed71..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/ft_transformer_pure/ft_transforemer_pure_incheon.py +++ /dev/null @@ -1,99 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="ft_transformer", region="incheon"), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/ft_transformer_pure_incheon_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_paths = train_final_model( - best_params=best_params, - model_choose="ft_transformer", - region="incheon", - data_sample='pure', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로:") - for path in model_paths: - print(f" - {path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/ft_transformer_pure/ft_transforemer_pure_seoul.py b/Analysis_code/5.optima/ft_transformer_pure/ft_transforemer_pure_seoul.py deleted file mode 100644 index 7ae0e86fcd579dfb52dbc963cdb35bf901c92396..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/ft_transformer_pure/ft_transforemer_pure_seoul.py +++ /dev/null @@ -1,98 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="ft_transformer", region="seoul"), - n_trials=100, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/ft_transformer_pure_seoul_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_paths = train_final_model( - best_params=best_params, - model_choose="ft_transformer", - region="seoul", - data_sample='pure', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로:") - for path in model_paths: - print(f" - {path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/ft_transformer_pure/utils.py b/Analysis_code/5.optima/ft_transformer_pure/utils.py deleted file mode 100644 index 43d496ecda4c82ad96e7ed6c5a87409fd31b53cb..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/ft_transformer_pure/utils.py +++ /dev/null @@ -1,720 +0,0 @@ -import torch -import torch.nn as nn -import torch.optim as optim -import numpy as np -import random -import os -import copy -from sklearn.preprocessing import QuantileTransformer, LabelEncoder -from torch.utils.data import DataLoader, TensorDataset -from sklearn.metrics import confusion_matrix -from sklearn.utils.class_weight import compute_class_weight -import pandas as pd -import optuna -from sklearn.metrics import accuracy_score, f1_score -import joblib - - -import sys -# 파일 위치 기반으로 models 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -models_path = os.path.abspath(os.path.join(current_file_dir, '../../models')) -sys.path.insert(0, models_path) -from ft_transformer import FTTransformer -from resnet_like import ResNetLike -from deepgbm import DeepGBM -import warnings -warnings.filterwarnings('ignore') - - -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - -# PyTorch 시드 고정 -torch.manual_seed(seed) -torch.cuda.manual_seed(seed) -torch.cuda.manual_seed_all(seed) # Multi-GPU 환경에서 동일한 시드 적용 - -# PyTorch 연산의 결정적 모드 설정 -torch.backends.cudnn.deterministic = True # 실행마다 동일한 결과를 보장 -torch.backends.cudnn.benchmark = True # 성능 최적화를 활성화 (가능한 한 빠른 연산 수행) - - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - - -# 데이터셋 준비 함수 -def prepare_dataset(region, data_sample='pure', target='multi', fold=3): - - # 파일 위치 기반으로 데이터 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) - - # 데이터 경로 지정 - dat_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_train.csv") - if data_sample == 'pure': - train_path = dat_path - else: - train_path = os.path.join(data_base_dir, f'data_oversampled/{data_sample}/{data_sample}_{fold}_{region}.csv') - test_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_test.csv") - drop_col = ['multi_class','year'] - target_col = f'{target}_class' - - # 데이터 로드 - region_dat = preprocessing(pd.read_csv(dat_path, index_col=0)) - if data_sample == 'pure': - region_train = region_dat.loc[~region_dat['year'].isin([2021-fold]), :] - else: - region_train = preprocessing(pd.read_csv(train_path)) - region_val = region_dat.loc[region_dat['year'].isin([2021-fold]), :] - region_test = preprocessing(pd.read_csv(test_path)) - - # 컬럼 정렬 (일관성 유지) - common_columns = region_train.columns.to_list() - train_data = region_train[common_columns] - val_data = region_val[common_columns] - test_data = region_test[common_columns] - - # 설명변수 & 타겟 분리 - X_train = train_data.drop(columns=drop_col) - y_train = train_data[target_col] - X_val = val_data.drop(columns=drop_col) - y_val = val_data[target_col] - X_test = test_data.drop(columns=drop_col) - y_test = test_data[target_col] - - # 범주형 & 연속형 변수 분리 - categorical_cols = X_train.select_dtypes(include=['object', 'category', 'int64']).columns - numerical_cols = X_train.select_dtypes(include=['float64']).columns - - # 범주형 변수 Label Encoding - label_encoders = {} - for col in categorical_cols: - le = LabelEncoder() - le.fit(X_train[col]) # Train 데이터 기준으로 학습 - label_encoders[col] = le - - # 변환 적용 - for col in categorical_cols: - X_train[col] = label_encoders[col].transform(X_train[col]) - X_val[col] = label_encoders[col].transform(X_val[col]) - X_test[col] = label_encoders[col].transform(X_test[col]) - - # 연속형 변수 Quantile Transformation - scaler = QuantileTransformer(output_distribution='normal') - scaler.fit(X_train[numerical_cols]) # Train 데이터 기준으로 학습 - - # 변환 적용 - X_train[numerical_cols] = scaler.transform(X_train[numerical_cols]) - X_val[numerical_cols] = scaler.transform(X_val[numerical_cols]) - X_test[numerical_cols] = scaler.transform(X_test[numerical_cols]) - - return X_train, X_val, X_test, y_train, y_val, y_test, categorical_cols, numerical_cols - - - -# 데이터 변환 및 dataloader 생성 함수 -def prepare_dataloader(region, data_sample='pure', target='multi', fold=3, random_state=None): - - # 파일 위치 기반으로 데이터 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) - - # 데이터 경로 지정 - dat_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_train.csv") - if data_sample == 'pure': - train_path = dat_path - else: - train_path = os.path.join(data_base_dir, f'data_oversampled/{data_sample}/{data_sample}_{fold}_{region}.csv') - test_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_test.csv") - drop_col = ['multi_class','year'] - target_col = f'{target}_class' - - # 데이터 로드 - region_dat = preprocessing(pd.read_csv(dat_path, index_col=0)) - if data_sample == 'pure': - region_train = region_dat.loc[~region_dat['year'].isin([2021-fold]), :] - else: - region_train = preprocessing(pd.read_csv(train_path)) - region_val = region_dat.loc[region_dat['year'].isin([2021-fold]), :] - region_test = preprocessing(pd.read_csv(test_path)) - - # 컬럼 정렬 (일관성 유지) - common_columns = region_train.columns.to_list() - train_data = region_train[common_columns] - val_data = region_val[common_columns] - test_data = region_test[common_columns] - - # 설명변수 & 타겟 분리 - X_train = train_data.drop(columns=drop_col) - y_train = train_data[target_col] - X_val = val_data.drop(columns=drop_col) - y_val = val_data[target_col] - X_test = test_data.drop(columns=drop_col) - y_test = test_data[target_col] - - # 범주형 & 연속형 변수 분리 - categorical_cols = X_train.select_dtypes(include=['object', 'category', 'int64']).columns - numerical_cols = X_train.select_dtypes(include=['float64']).columns - - # 범주형 변수 Label Encoding - label_encoders = {} - for col in categorical_cols: - le = LabelEncoder() - le.fit(X_train[col]) # Train 데이터 기준으로 학습 - label_encoders[col] = le - - # 변환 적용 - for col in categorical_cols: - X_train[col] = label_encoders[col].transform(X_train[col]) - X_val[col] = label_encoders[col].transform(X_val[col]) - X_test[col] = label_encoders[col].transform(X_test[col]) - - # 연속형 변수 Quantile Transformation - scaler = QuantileTransformer(output_distribution='normal') - scaler.fit(X_train[numerical_cols]) # Train 데이터 기준으로 학습 - - # 변환 적용 - X_train[numerical_cols] = scaler.transform(X_train[numerical_cols]) - X_val[numerical_cols] = scaler.transform(X_val[numerical_cols]) - X_test[numerical_cols] = scaler.transform(X_test[numerical_cols]) - - # 연속형 변수와 범주형 변수 분리 - X_train_num = torch.tensor(X_train[numerical_cols].values, dtype=torch.float32) - X_train_cat = torch.tensor(X_train[categorical_cols].values, dtype=torch.long) - - X_val_num = torch.tensor(X_val[numerical_cols].values, dtype=torch.float32) - X_val_cat = torch.tensor(X_val[categorical_cols].values, dtype=torch.long) - - X_test_num = torch.tensor(X_test[numerical_cols].values, dtype=torch.float32) - X_test_cat = torch.tensor(X_test[categorical_cols].values, dtype=torch.long) - - # 레이블 변환 - if target == "binary": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.float32) # 이진 분류 → float32 - y_val_tensor = torch.tensor(y_val.values, dtype=torch.float32) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.float32) - elif target == "multi": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.long) # 다중 분류 → long - y_val_tensor = torch.tensor(y_val.values, dtype=torch.long) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.long) - else: - raise ValueError("target must be 'binary' or 'multi'") - - # TensorDataset 생성 - train_dataset = TensorDataset(X_train_num, X_train_cat, y_train_tensor) - val_dataset = TensorDataset(X_val_num, X_val_cat, y_val_tensor) - test_dataset = TensorDataset(X_test_num, X_test_cat, y_test_tensor) - - # DataLoader 생성 - if random_state == None: - train_loader = DataLoader(train_dataset, batch_size=64, shuffle=True) - else: - train_loader = DataLoader(train_dataset, batch_size=64, shuffle=True, generator=torch.Generator().manual_seed(random_state)) - val_loader = DataLoader(val_dataset, batch_size=64, shuffle=False) - test_loader = DataLoader(test_dataset, batch_size=64, shuffle=False) - - return X_train, categorical_cols, numerical_cols, train_loader, val_loader, test_loader - -# 데이터 변환 및 dataloader 생성 함수 (batch_size 파라미터 추가 버전) -def prepare_dataloader_with_batchsize(region, data_sample='pure', target='multi', fold=3, random_state=None, batch_size=64): - # 파일 위치 기반으로 데이터 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) - - # 데이터 경로 지정 - dat_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_train.csv") - if data_sample == 'pure': - train_path = dat_path - else: - train_path = os.path.join(data_base_dir, f'data_oversampled/{data_sample}/{data_sample}_{fold}_{region}.csv') - test_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_test.csv") - drop_col = ['multi_class','year'] - target_col = f'{target}_class' - - # 데이터 로드 - region_dat = preprocessing(pd.read_csv(dat_path, index_col=0)) - if data_sample == 'pure': - region_train = region_dat.loc[~region_dat['year'].isin([2021-fold]), :] - else: - region_train = preprocessing(pd.read_csv(train_path)) - region_val = region_dat.loc[region_dat['year'].isin([2021-fold]), :] - region_test = preprocessing(pd.read_csv(test_path)) - - # 컬럼 정렬 (일관성 유지) - common_columns = region_train.columns.to_list() - train_data = region_train[common_columns] - val_data = region_val[common_columns] - test_data = region_test[common_columns] - - # 설명변수 & 타겟 분리 - X_train = train_data.drop(columns=drop_col) - y_train = train_data[target_col] - X_val = val_data.drop(columns=drop_col) - y_val = val_data[target_col] - X_test = test_data.drop(columns=drop_col) - y_test = test_data[target_col] - - # 범주형 & 연속형 변수 분리 - categorical_cols = X_train.select_dtypes(include=['object', 'category', 'int64']).columns - numerical_cols = X_train.select_dtypes(include=['float64']).columns - - # 범주형 변수 Label Encoding - label_encoders = {} - for col in categorical_cols: - le = LabelEncoder() - le.fit(X_train[col]) # Train 데이터 기준으로 학습 - label_encoders[col] = le - - # 변환 적용 - for col in categorical_cols: - X_train[col] = label_encoders[col].transform(X_train[col]) - X_val[col] = label_encoders[col].transform(X_val[col]) - X_test[col] = label_encoders[col].transform(X_test[col]) - - # 연속형 변수 Quantile Transformation - scaler = QuantileTransformer(output_distribution='normal') - scaler.fit(X_train[numerical_cols]) # Train 데이터 기준으로 학습 - - # 변환 적용 - X_train[numerical_cols] = scaler.transform(X_train[numerical_cols]) - X_val[numerical_cols] = scaler.transform(X_val[numerical_cols]) - X_test[numerical_cols] = scaler.transform(X_test[numerical_cols]) - - # 연속형 변수와 범주형 변수 분리 - X_train_num = torch.tensor(X_train[numerical_cols].values, dtype=torch.float32) - X_train_cat = torch.tensor(X_train[categorical_cols].values, dtype=torch.long) - - X_val_num = torch.tensor(X_val[numerical_cols].values, dtype=torch.float32) - X_val_cat = torch.tensor(X_val[categorical_cols].values, dtype=torch.long) - - X_test_num = torch.tensor(X_test[numerical_cols].values, dtype=torch.float32) - X_test_cat = torch.tensor(X_test[categorical_cols].values, dtype=torch.long) - - # 레이블 변환 - if target == "binary": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.float32) # 이진 분류 → float32 - y_val_tensor = torch.tensor(y_val.values, dtype=torch.float32) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.float32) - elif target == "multi": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.long) # 다중 분류 → long - y_val_tensor = torch.tensor(y_val.values, dtype=torch.long) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.long) - else: - raise ValueError("target must be 'binary' or 'multi'") - - # TensorDataset 생성 - train_dataset = TensorDataset(X_train_num, X_train_cat, y_train_tensor) - val_dataset = TensorDataset(X_val_num, X_val_cat, y_val_tensor) - test_dataset = TensorDataset(X_test_num, X_test_cat, y_test_tensor) - - # DataLoader 생성 (batch_size 파라미터 사용) - if random_state == None: - train_loader = DataLoader(train_dataset, batch_size=batch_size, shuffle=True) - else: - train_loader = DataLoader(train_dataset, batch_size=batch_size, shuffle=True, generator=torch.Generator().manual_seed(random_state)) - val_loader = DataLoader(val_dataset, batch_size=batch_size, shuffle=False) - test_loader = DataLoader(test_dataset, batch_size=batch_size, shuffle=False) - - return X_train, categorical_cols, numerical_cols, train_loader, val_loader, test_loader, y_train, scaler - - -def calculate_csi(y_true, pred): - - cm = confusion_matrix(y_true, pred) # 변수 이름을 cm으로 변경 - # 혼동 행렬에서 H, F, M 추출 - H = (cm[0, 0] + cm[1, 1]) - - F = (cm[1, 0] + cm[2, 0] + - cm[0, 1] + cm[2, 1]) - - M = (cm[0, 2] + cm[1, 2]) - - # CSI 계산 - CSI = H / (H + F + M + 1e-10) - return CSI - -def sample_weight(y_train): - class_weights = compute_class_weight( - class_weight='balanced', - classes=np.unique(y_train), # 고유 클래스 - y=y_train # 학습 데이터 레이블 - ) - sample_weights = np.array([class_weights[label] for label in y_train]) - - return sample_weights - -# 하이퍼파라미터 최적화 함수 정의 -def objective(trial, model_choose, region, data_sample='pure', target='multi', n_folds=3, random_state=42): - # GPU 사용 가능 여부 확인 및 device 설정 - device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') - val_scores = [] - - # --- 1. 하이퍼파라미터 탐색 범위 정의 (수정됨) --- - if model_choose == "ft_transformer": - d_token = trial.suggest_int("d_token", 64, 256, step=32) - n_blocks = trial.suggest_int("n_blocks", 2, 6) # 깊이 축소로 과적합 방지 - n_heads = trial.suggest_categorical("n_heads", [4, 8]) - # d_token은 n_heads의 배수여야 함 (FT-Transformer의 구조적 제약 대응) - if d_token % n_heads != 0: - d_token = (d_token // n_heads) * n_heads - - attention_dropout = trial.suggest_float("attention_dropout", 0.1, 0.4) - ffn_dropout = trial.suggest_float("ffn_dropout", 0.1, 0.4) - lr = trial.suggest_float("lr", 1e-5, 1e-2, log=True) # 범위 확대 - weight_decay = trial.suggest_float("weight_decay", 1e-4, 1e-1, log=True) # 더 공격적인 범위로 확장 - batch_size = trial.suggest_categorical("batch_size", [32, 64, 128, 256]) # Batch Size 추가 - - elif model_choose == 'resnet_like': - d_main = trial.suggest_int("d_main", 64, 256, step=32) - d_hidden = trial.suggest_int("d_hidden", 64, 512, step=64) - n_blocks = trial.suggest_int("n_blocks", 2, 5) # 너무 깊지 않게 조절 - dropout_first = trial.suggest_float("dropout_first", 0.1, 0.4) - dropout_second = trial.suggest_float("dropout_second", 0.0, 0.2) - lr = trial.suggest_float("lr", 1e-5, 1e-2, log=True) - weight_decay = trial.suggest_float("weight_decay", 1e-4, 1e-1, log=True) # 더 공격적인 범위로 확장 - batch_size = trial.suggest_categorical("batch_size", [32, 64, 128, 256]) # Batch Size 추가 - - elif model_choose == 'deepgbm': - # DeepGBM의 경우 모델 특성에 맞춰 ResNet 블록 및 임베딩 차원 조절 - d_main = trial.suggest_int("d_main", 64, 256, step=32) - d_hidden = trial.suggest_int("d_hidden", 64, 256, step=64) - n_blocks = trial.suggest_int("n_blocks", 2, 6) - dropout = trial.suggest_float("dropout", 0.1, 0.4) - lr = trial.suggest_float("lr", 1e-5, 1e-2, log=True) - weight_decay = trial.suggest_float("weight_decay", 1e-4, 1e-1, log=True) # 더 공격적인 범위로 확장 - batch_size = trial.suggest_categorical("batch_size", [32, 64, 128, 256]) # Batch Size 추가 - - # --- 2. Fold별 학습 및 교차 검증 --- - for fold in range(1, n_folds + 1): - X_train_df, categorical_cols, numerical_cols, train_loader, val_loader, _, y_train, _ = prepare_dataloader_with_batchsize( - region, data_sample=data_sample, target=target, fold=fold, random_state=random_state, batch_size=batch_size - ) - - # 모델 초기화 - if model_choose == "ft_transformer": - model = FTTransformer( - num_features=len(numerical_cols), - cat_cardinalities=[len(X_train_df[col].unique()) for col in categorical_cols], - d_token=d_token, - n_blocks=n_blocks, - n_heads=n_heads, - attention_dropout=attention_dropout, - ffn_dropout=ffn_dropout, - num_classes=3 - ).to(device) - elif model_choose == 'resnet_like': - input_dim = len(numerical_cols) + len(categorical_cols) - model = ResNetLike( - input_dim=input_dim, - d_main=d_main, - d_hidden=d_hidden, - n_blocks=n_blocks, - dropout_first=dropout_first, - dropout_second=dropout_second, - num_classes=3 - ).to(device) - elif model_choose == 'deepgbm': - model = DeepGBM( - num_features=len(numerical_cols), - cat_features=[len(X_train_df[col].unique()) for col in categorical_cols], - d_main=d_main, - d_hidden=d_hidden, - n_blocks=n_blocks, - dropout=dropout, - num_classes=3 - ).to(device) - - # 클래스 가중치 계산 및 손실 함수 설정 (Label Smoothing 적용) - if target == 'multi': - class_weights = compute_class_weight( - class_weight='balanced', - classes=np.unique(y_train), - y=y_train - ) - # 클래스별 가중치 로그 출력 - unique_classes = np.unique(y_train) - class_counts = {cls: np.sum(y_train == cls) for cls in unique_classes} - print(f" Fold {fold} - 클래스별 가중치: {dict(zip(unique_classes, class_weights))} (클래스별 샘플 수: {class_counts})") - class_weights_tensor = torch.tensor(class_weights, dtype=torch.float32).to(device) - criterion = nn.CrossEntropyLoss(weight=class_weights_tensor, label_smoothing=0.0) # Label Smoothing 추가 - else: - criterion = nn.BCEWithLogitsLoss() - optimizer = optim.AdamW(model.parameters(), lr=lr, weight_decay=weight_decay) - - # 학습률 스케줄러 추가: 성능 정체 시 LR을 0.5배 감소 (검증 CSI 기준) - scheduler = optim.lr_scheduler.ReduceLROnPlateau(optimizer, mode='max', factor=0.5, patience=3) - - # 학습 설정 (에폭 및 페이션스 상향) - epochs = 200 - patience = 12 # 딥러닝의 정체 구간을 고려하여 소폭 상향 - best_fold_csi = 0 - counter = 0 - - for epoch in range(epochs): - model.train() - for x_num_batch, x_cat_batch, y_batch in train_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - - optimizer.zero_grad() - y_pred = model(x_num_batch, x_cat_batch) - loss = criterion(y_pred, y_batch if target == 'multi' else y_batch.float()) - loss.backward() - optimizer.step() - - # Validation 평가 - model.eval() - y_pred_val, y_true_val = [], [] - with torch.no_grad(): - for x_num_batch, x_cat_batch, y_batch in val_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - output = model(x_num_batch, x_cat_batch) - pred = output.argmax(dim=1) if target == 'multi' else (torch.sigmoid(output) >= 0.5).long() - - y_pred_val.extend(pred.cpu().numpy()) - y_true_val.extend(y_batch.cpu().numpy()) - - # CSI 계산 및 스케줄러 업데이트 - val_csi = calculate_csi(y_true_val, y_pred_val) - scheduler.step(val_csi) - - # Optuna Pruning 적용 (첫 번째 Fold에서 조기 종료 판단 강화) - trial.report(val_csi, epoch) - if trial.should_prune(): - raise optuna.exceptions.TrialPruned() - - # Early Stopping 체크 - if val_csi > best_fold_csi: - best_fold_csi = val_csi - counter = 0 - else: - counter += 1 - - if counter >= patience: - break - - val_scores.append(best_fold_csi) - - # 모든 fold의 평균 성능 반환 - return np.mean(val_scores) - - -# 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 함수 -def train_final_model(best_params, model_choose, region, data_sample='pure', target='multi', n_folds=3, random_state=42): - """ - 최적화된 하이퍼파라미터로 최종 모델을 학습하고 저장합니다. - - Args: - best_params: 최적화된 하이퍼파라미터 딕셔너리 - model_choose: 모델 선택 ('ft_transformer', 'resnet_like', 'deepgbm') - region: 지역명 - data_sample: 데이터 샘플 타입 ('pure', 'smote', etc.) - target: 타겟 타입 ('multi', 'binary') - n_folds: 교차 검증 fold 수 - random_state: 랜덤 시드 - - Returns: - 저장된 모델 경로 리스트 - """ - # GPU 사용 가능 여부 확인 및 device 설정 - device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') - - models = [] - scalers = [] # scaler 리스트 추가 - - print("최종 모델 학습 시작...") - - for fold in range(1, n_folds + 1): - print(f"Fold {fold} 학습 중...") - - # 최적화된 batch_size 사용 - batch_size = best_params.get("batch_size", 64) - X_train_df, categorical_cols, numerical_cols, train_loader, val_loader, _, y_train, scaler = prepare_dataloader_with_batchsize( - region, data_sample=data_sample, target=target, fold=fold, random_state=random_state, batch_size=batch_size - ) - - # 모델 초기화 - if model_choose == "ft_transformer": - d_token = best_params["d_token"] - n_heads = best_params.get("n_heads", 8) - # d_token은 n_heads의 배수여야 함 (FT-Transformer의 구조적 제약 대응) - if d_token % n_heads != 0: - d_token = (d_token // n_heads) * n_heads - - model = FTTransformer( - num_features=len(numerical_cols), - cat_cardinalities=[len(X_train_df[col].unique()) for col in categorical_cols], - d_token=d_token, - n_blocks=best_params["n_blocks"], - n_heads=n_heads, - attention_dropout=best_params["attention_dropout"], - ffn_dropout=best_params["ffn_dropout"], - num_classes=3 - ).to(device) - elif model_choose == 'resnet_like': - input_dim = len(numerical_cols) + len(categorical_cols) - model = ResNetLike( - input_dim=input_dim, - d_main=best_params["d_main"], - d_hidden=best_params["d_hidden"], - n_blocks=best_params["n_blocks"], - dropout_first=best_params["dropout_first"], - dropout_second=best_params["dropout_second"], - num_classes=3 - ).to(device) - elif model_choose == 'deepgbm': - model = DeepGBM( - num_features=len(numerical_cols), - cat_features=[len(X_train_df[col].unique()) for col in categorical_cols], - d_main=best_params["d_main"], - d_hidden=best_params["d_hidden"], - n_blocks=best_params["n_blocks"], - dropout=best_params["dropout"], - num_classes=3 - ).to(device) - else: - raise ValueError(f"Unknown model_choose: {model_choose}") - - # 클래스 가중치 계산 및 손실 함수 설정 (Label Smoothing 적용) - if target == 'multi': - class_weights = compute_class_weight( - class_weight='balanced', - classes=np.unique(y_train), - y=y_train - ) - class_weights_tensor = torch.tensor(class_weights, dtype=torch.float32).to(device) - criterion = nn.CrossEntropyLoss(weight=class_weights_tensor, label_smoothing=0.0) # Label Smoothing 추가 - else: - criterion = nn.BCEWithLogitsLoss() - optimizer = optim.AdamW(model.parameters(), lr=best_params["lr"], weight_decay=best_params["weight_decay"]) - - # 학습률 스케줄러 - scheduler = optim.lr_scheduler.ReduceLROnPlateau(optimizer, mode='max', factor=0.5, patience=3) - - # 학습 설정 - epochs = 200 - patience = 12 - best_fold_csi = 0 - counter = 0 - best_model = None - - for epoch in range(epochs): - model.train() - for x_num_batch, x_cat_batch, y_batch in train_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - - optimizer.zero_grad() - y_pred = model(x_num_batch, x_cat_batch) - loss = criterion(y_pred, y_batch if target == 'multi' else y_batch.float()) - loss.backward() - optimizer.step() - - # Validation 평가 - model.eval() - y_pred_val, y_true_val = [], [] - with torch.no_grad(): - for x_num_batch, x_cat_batch, y_batch in val_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - output = model(x_num_batch, x_cat_batch) - pred = output.argmax(dim=1) if target == 'multi' else (torch.sigmoid(output) >= 0.5).long() - - y_pred_val.extend(pred.cpu().numpy()) - y_true_val.extend(y_batch.cpu().numpy()) - - # CSI 계산 및 스케줄러 업데이트 - val_csi = calculate_csi(y_true_val, y_pred_val) - scheduler.step(val_csi) - - # Early Stopping 체크 - if val_csi > best_fold_csi: - best_fold_csi = val_csi - counter = 0 - best_model = copy.deepcopy(model) - else: - counter += 1 - - if counter >= patience: - print(f" Early stopping at epoch {epoch+1}, Best CSI: {best_fold_csi:.4f}") - break - - if best_model is None: - best_model = model - - scalers.append(scaler) # scaler 저장 (fold 순서대로) - models.append(best_model) - print(f" Fold {fold} 학습 완료 (검증 CSI: {best_fold_csi:.4f})") - - # 모델 저장 경로 설정 - save_dir = f'../save_model/{model_choose}_optima' - os.makedirs(save_dir, exist_ok=True) - - # 파일명 생성 - if data_sample == 'pure': - model_filename = f'{model_choose}_pure_{region}.pkl' - else: - model_filename = f'{model_choose}_{data_sample}_{region}.pkl' - - model_path = f'{save_dir}/{model_filename}' - - # 리스트에 담아 한 번에 저장 - joblib.dump(models, model_path) - print(f"\n모든 모델 저장 완료: {model_path} (총 {len(models)}개 fold)") - - # Scaler 별도 저장 - scaler_save_dir = f'../save_model/{model_choose}_optima/scaler' - os.makedirs(scaler_save_dir, exist_ok=True) - - # 파일명 생성 (모델과 동일한 패턴) - if data_sample == 'pure': - scaler_filename = f'{model_choose}_pure_{region}_scaler.pkl' - else: - scaler_filename = f'{model_choose}_{data_sample}_{region}_scaler.pkl' - - scaler_path = f'{scaler_save_dir}/{scaler_filename}' - joblib.dump(scalers, scaler_path) - print(f"Scaler 저장 완료: {scaler_path} (총 {len(scalers)}개 fold)") - - return model_path diff --git a/Analysis_code/5.optima/ft_transformer_smote/ft_transformer_smote_busan.py b/Analysis_code/5.optima/ft_transformer_smote/ft_transformer_smote_busan.py deleted file mode 100644 index f26b4feb5e029a551a8acb39c54e1d458816f3e6..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/ft_transformer_smote/ft_transformer_smote_busan.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="ft_transformer", region="busan", data_sample='smote'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/ft_transformer_smote_busan_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="ft_transformer", - region="busan", - data_sample='smote', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/ft_transformer_smote/ft_transformer_smote_daegu.py b/Analysis_code/5.optima/ft_transformer_smote/ft_transformer_smote_daegu.py deleted file mode 100644 index 808de3e542291050e32240703a84a3be867ff475..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/ft_transformer_smote/ft_transformer_smote_daegu.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="ft_transformer", region="daegu", data_sample='smote'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/ft_transformer_smote_daegu_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="ft_transformer", - region="daegu", - data_sample='smote', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/ft_transformer_smote/ft_transformer_smote_daejeon.py b/Analysis_code/5.optima/ft_transformer_smote/ft_transformer_smote_daejeon.py deleted file mode 100644 index 90b547efe981778dfd3293401bbf5d2253ab01b3..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/ft_transformer_smote/ft_transformer_smote_daejeon.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="ft_transformer", region="daejeon", data_sample='smote'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/ft_transformer_smote_daejeon_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="ft_transformer", - region="daejeon", - data_sample='smote', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/ft_transformer_smote/ft_transformer_smote_gwangju.py b/Analysis_code/5.optima/ft_transformer_smote/ft_transformer_smote_gwangju.py deleted file mode 100644 index cc894d8ba961502c120c42ff404b27925901b3b3..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/ft_transformer_smote/ft_transformer_smote_gwangju.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="ft_transformer", region="gwangju", data_sample='smote'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/ft_transformer_smote_gwangju_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="ft_transformer", - region="gwangju", - data_sample='smote', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/ft_transformer_smote/ft_transformer_smote_incheon.py b/Analysis_code/5.optima/ft_transformer_smote/ft_transformer_smote_incheon.py deleted file mode 100644 index 839b1aa6ff7b2eca606bf7719e1f795e3e4d2151..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/ft_transformer_smote/ft_transformer_smote_incheon.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="ft_transformer", region="incheon", data_sample='smote'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/ft_transformer_smote_incheon_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="ft_transformer", - region="incheon", - data_sample='smote', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/ft_transformer_smote/ft_transformer_smote_seoul.py b/Analysis_code/5.optima/ft_transformer_smote/ft_transformer_smote_seoul.py deleted file mode 100644 index 29075b44a948ec3916438d2e3b9621bfb3911494..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/ft_transformer_smote/ft_transformer_smote_seoul.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="ft_transformer", region="seoul", data_sample='smote'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/ft_transformer_smote_seoul_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="ft_transformer", - region="seoul", - data_sample='smote', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/ft_transformer_smote/utils.py b/Analysis_code/5.optima/ft_transformer_smote/utils.py deleted file mode 100644 index 3f4f4d793d54387f8f7ea639fbad36de0622fb51..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/ft_transformer_smote/utils.py +++ /dev/null @@ -1,719 +0,0 @@ -import torch -import torch.nn as nn -import torch.optim as optim -import numpy as np -import random -import os -import copy -from sklearn.preprocessing import QuantileTransformer, LabelEncoder -from torch.utils.data import DataLoader, TensorDataset -from sklearn.metrics import confusion_matrix -from sklearn.utils.class_weight import compute_class_weight -import pandas as pd -import optuna -from sklearn.metrics import accuracy_score, f1_score -import joblib - - -import sys -# 파일 위치 기반으로 models 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -models_path = os.path.abspath(os.path.join(current_file_dir, '../../models')) -sys.path.insert(0, models_path) -from ft_transformer import FTTransformer -from resnet_like import ResNetLike -from deepgbm import DeepGBM -import warnings -warnings.filterwarnings('ignore') - -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - -# PyTorch 시드 고정 -torch.manual_seed(seed) -torch.cuda.manual_seed(seed) -torch.cuda.manual_seed_all(seed) # Multi-GPU 환경에서 동일한 시드 적용 - -# PyTorch 연산의 결정적 모드 설정 -torch.backends.cudnn.deterministic = True # 실행마다 동일한 결과를 보장 -torch.backends.cudnn.benchmark = True # 성능 최적화를 활성화 (가능한 한 빠른 연산 수행) - - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - - -# 데이터셋 준비 함수 -def prepare_dataset(region, data_sample='pure', target='multi', fold=3): - - # 파일 위치 기반으로 데이터 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) - - # 데이터 경로 지정 - dat_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_train.csv") - if data_sample == 'pure': - train_path = dat_path - else: - train_path = os.path.join(data_base_dir, f'data_oversampled/{data_sample}/{data_sample}_{fold}_{region}.csv') - test_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_test.csv") - drop_col = ['multi_class','year'] - target_col = f'{target}_class' - - # 데이터 로드 - region_dat = preprocessing(pd.read_csv(dat_path, index_col=0)) - if data_sample == 'pure': - region_train = region_dat.loc[~region_dat['year'].isin([2021-fold]), :] - else: - region_train = preprocessing(pd.read_csv(train_path)) - region_val = region_dat.loc[region_dat['year'].isin([2021-fold]), :] - region_test = preprocessing(pd.read_csv(test_path)) - - # 컬럼 정렬 (일관성 유지) - common_columns = region_train.columns.to_list() - train_data = region_train[common_columns] - val_data = region_val[common_columns] - test_data = region_test[common_columns] - - # 설명변수 & 타겟 분리 - X_train = train_data.drop(columns=drop_col) - y_train = train_data[target_col] - X_val = val_data.drop(columns=drop_col) - y_val = val_data[target_col] - X_test = test_data.drop(columns=drop_col) - y_test = test_data[target_col] - - # 범주형 & 연속형 변수 분리 - categorical_cols = X_train.select_dtypes(include=['object', 'category', 'int64']).columns - numerical_cols = X_train.select_dtypes(include=['float64']).columns - - # 범주형 변수 Label Encoding - label_encoders = {} - for col in categorical_cols: - le = LabelEncoder() - le.fit(X_train[col]) # Train 데이터 기준으로 학습 - label_encoders[col] = le - - # 변환 적용 - for col in categorical_cols: - X_train[col] = label_encoders[col].transform(X_train[col]) - X_val[col] = label_encoders[col].transform(X_val[col]) - X_test[col] = label_encoders[col].transform(X_test[col]) - - # 연속형 변수 Quantile Transformation - scaler = QuantileTransformer(output_distribution='normal') - scaler.fit(X_train[numerical_cols]) # Train 데이터 기준으로 학습 - - # 변환 적용 - X_train[numerical_cols] = scaler.transform(X_train[numerical_cols]) - X_val[numerical_cols] = scaler.transform(X_val[numerical_cols]) - X_test[numerical_cols] = scaler.transform(X_test[numerical_cols]) - - return X_train, X_val, X_test, y_train, y_val, y_test, categorical_cols, numerical_cols - - - -# 데이터 변환 및 dataloader 생성 함수 -def prepare_dataloader(region, data_sample='pure', target='multi', fold=3, random_state=None): - - # 파일 위치 기반으로 데이터 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) - - # 데이터 경로 지정 - dat_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_train.csv") - if data_sample == 'pure': - train_path = dat_path - else: - train_path = os.path.join(data_base_dir, f'data_oversampled/{data_sample}/{data_sample}_{fold}_{region}.csv') - test_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_test.csv") - drop_col = ['multi_class','year'] - target_col = f'{target}_class' - - # 데이터 로드 - region_dat = preprocessing(pd.read_csv(dat_path, index_col=0)) - if data_sample == 'pure': - region_train = region_dat.loc[~region_dat['year'].isin([2021-fold]), :] - else: - region_train = preprocessing(pd.read_csv(train_path)) - region_val = region_dat.loc[region_dat['year'].isin([2021-fold]), :] - region_test = preprocessing(pd.read_csv(test_path)) - - # 컬럼 정렬 (일관성 유지) - common_columns = region_train.columns.to_list() - train_data = region_train[common_columns] - val_data = region_val[common_columns] - test_data = region_test[common_columns] - - # 설명변수 & 타겟 분리 - X_train = train_data.drop(columns=drop_col) - y_train = train_data[target_col] - X_val = val_data.drop(columns=drop_col) - y_val = val_data[target_col] - X_test = test_data.drop(columns=drop_col) - y_test = test_data[target_col] - - # 범주형 & 연속형 변수 분리 - categorical_cols = X_train.select_dtypes(include=['object', 'category', 'int64']).columns - numerical_cols = X_train.select_dtypes(include=['float64']).columns - - # 범주형 변수 Label Encoding - label_encoders = {} - for col in categorical_cols: - le = LabelEncoder() - le.fit(X_train[col]) # Train 데이터 기준으로 학습 - label_encoders[col] = le - - # 변환 적용 - for col in categorical_cols: - X_train[col] = label_encoders[col].transform(X_train[col]) - X_val[col] = label_encoders[col].transform(X_val[col]) - X_test[col] = label_encoders[col].transform(X_test[col]) - - # 연속형 변수 Quantile Transformation - scaler = QuantileTransformer(output_distribution='normal') - scaler.fit(X_train[numerical_cols]) # Train 데이터 기준으로 학습 - - # 변환 적용 - X_train[numerical_cols] = scaler.transform(X_train[numerical_cols]) - X_val[numerical_cols] = scaler.transform(X_val[numerical_cols]) - X_test[numerical_cols] = scaler.transform(X_test[numerical_cols]) - - # 연속형 변수와 범주형 변수 분리 - X_train_num = torch.tensor(X_train[numerical_cols].values, dtype=torch.float32) - X_train_cat = torch.tensor(X_train[categorical_cols].values, dtype=torch.long) - - X_val_num = torch.tensor(X_val[numerical_cols].values, dtype=torch.float32) - X_val_cat = torch.tensor(X_val[categorical_cols].values, dtype=torch.long) - - X_test_num = torch.tensor(X_test[numerical_cols].values, dtype=torch.float32) - X_test_cat = torch.tensor(X_test[categorical_cols].values, dtype=torch.long) - - # 레이블 변환 - if target == "binary": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.float32) # 이진 분류 → float32 - y_val_tensor = torch.tensor(y_val.values, dtype=torch.float32) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.float32) - elif target == "multi": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.long) # 다중 분류 → long - y_val_tensor = torch.tensor(y_val.values, dtype=torch.long) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.long) - else: - raise ValueError("target must be 'binary' or 'multi'") - - # TensorDataset 생성 - train_dataset = TensorDataset(X_train_num, X_train_cat, y_train_tensor) - val_dataset = TensorDataset(X_val_num, X_val_cat, y_val_tensor) - test_dataset = TensorDataset(X_test_num, X_test_cat, y_test_tensor) - - # DataLoader 생성 - if random_state == None: - train_loader = DataLoader(train_dataset, batch_size=64, shuffle=True) - else: - train_loader = DataLoader(train_dataset, batch_size=64, shuffle=True, generator=torch.Generator().manual_seed(random_state)) - val_loader = DataLoader(val_dataset, batch_size=64, shuffle=False) - test_loader = DataLoader(test_dataset, batch_size=64, shuffle=False) - - return X_train, categorical_cols, numerical_cols, train_loader, val_loader, test_loader - -# 데이터 변환 및 dataloader 생성 함수 (batch_size 파라미터 추가 버전) -def prepare_dataloader_with_batchsize(region, data_sample='pure', target='multi', fold=3, random_state=None, batch_size=64): - # 파일 위치 기반으로 데이터 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) - - # 데이터 경로 지정 - dat_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_train.csv") - if data_sample == 'pure': - train_path = dat_path - else: - train_path = os.path.join(data_base_dir, f'data_oversampled/{data_sample}/{data_sample}_{fold}_{region}.csv') - test_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_test.csv") - drop_col = ['multi_class','year'] - target_col = f'{target}_class' - - # 데이터 로드 - region_dat = preprocessing(pd.read_csv(dat_path, index_col=0)) - if data_sample == 'pure': - region_train = region_dat.loc[~region_dat['year'].isin([2021-fold]), :] - else: - region_train = preprocessing(pd.read_csv(train_path)) - region_val = region_dat.loc[region_dat['year'].isin([2021-fold]), :] - region_test = preprocessing(pd.read_csv(test_path)) - - # 컬럼 정렬 (일관성 유지) - common_columns = region_train.columns.to_list() - train_data = region_train[common_columns] - val_data = region_val[common_columns] - test_data = region_test[common_columns] - - # 설명변수 & 타겟 분리 - X_train = train_data.drop(columns=drop_col) - y_train = train_data[target_col] - X_val = val_data.drop(columns=drop_col) - y_val = val_data[target_col] - X_test = test_data.drop(columns=drop_col) - y_test = test_data[target_col] - - # 범주형 & 연속형 변수 분리 - categorical_cols = X_train.select_dtypes(include=['object', 'category', 'int64']).columns - numerical_cols = X_train.select_dtypes(include=['float64']).columns - - # 범주형 변수 Label Encoding - label_encoders = {} - for col in categorical_cols: - le = LabelEncoder() - le.fit(X_train[col]) # Train 데이터 기준으로 학습 - label_encoders[col] = le - - # 변환 적용 - for col in categorical_cols: - X_train[col] = label_encoders[col].transform(X_train[col]) - X_val[col] = label_encoders[col].transform(X_val[col]) - X_test[col] = label_encoders[col].transform(X_test[col]) - - # 연속형 변수 Quantile Transformation - scaler = QuantileTransformer(output_distribution='normal') - scaler.fit(X_train[numerical_cols]) # Train 데이터 기준으로 학습 - - # 변환 적용 - X_train[numerical_cols] = scaler.transform(X_train[numerical_cols]) - X_val[numerical_cols] = scaler.transform(X_val[numerical_cols]) - X_test[numerical_cols] = scaler.transform(X_test[numerical_cols]) - - # 연속형 변수와 범주형 변수 분리 - X_train_num = torch.tensor(X_train[numerical_cols].values, dtype=torch.float32) - X_train_cat = torch.tensor(X_train[categorical_cols].values, dtype=torch.long) - - X_val_num = torch.tensor(X_val[numerical_cols].values, dtype=torch.float32) - X_val_cat = torch.tensor(X_val[categorical_cols].values, dtype=torch.long) - - X_test_num = torch.tensor(X_test[numerical_cols].values, dtype=torch.float32) - X_test_cat = torch.tensor(X_test[categorical_cols].values, dtype=torch.long) - - # 레이블 변환 - if target == "binary": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.float32) # 이진 분류 → float32 - y_val_tensor = torch.tensor(y_val.values, dtype=torch.float32) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.float32) - elif target == "multi": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.long) # 다중 분류 → long - y_val_tensor = torch.tensor(y_val.values, dtype=torch.long) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.long) - else: - raise ValueError("target must be 'binary' or 'multi'") - - # TensorDataset 생성 - train_dataset = TensorDataset(X_train_num, X_train_cat, y_train_tensor) - val_dataset = TensorDataset(X_val_num, X_val_cat, y_val_tensor) - test_dataset = TensorDataset(X_test_num, X_test_cat, y_test_tensor) - - # DataLoader 생성 (batch_size 파라미터 사용) - if random_state == None: - train_loader = DataLoader(train_dataset, batch_size=batch_size, shuffle=True) - else: - train_loader = DataLoader(train_dataset, batch_size=batch_size, shuffle=True, generator=torch.Generator().manual_seed(random_state)) - val_loader = DataLoader(val_dataset, batch_size=batch_size, shuffle=False) - test_loader = DataLoader(test_dataset, batch_size=batch_size, shuffle=False) - - return X_train, categorical_cols, numerical_cols, train_loader, val_loader, test_loader, y_train, scaler - - -def calculate_csi(y_true, pred): - - cm = confusion_matrix(y_true, pred) # 변수 이름을 cm으로 변경 - # 혼동 행렬에서 H, F, M 추출 - H = (cm[0, 0] + cm[1, 1]) - - F = (cm[1, 0] + cm[2, 0] + - cm[0, 1] + cm[2, 1]) - - M = (cm[0, 2] + cm[1, 2]) - - # CSI 계산 - CSI = H / (H + F + M + 1e-10) - return CSI - -def sample_weight(y_train): - class_weights = compute_class_weight( - class_weight='balanced', - classes=np.unique(y_train), # 고유 클래스 - y=y_train # 학습 데이터 레이블 - ) - sample_weights = np.array([class_weights[label] for label in y_train]) - - return sample_weights - -# 하이퍼파라미터 최적화 함수 정의 -def objective(trial, model_choose, region, data_sample='pure', target='multi', n_folds=3, random_state=42): - # GPU 사용 가능 여부 확인 및 device 설정 - device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') - val_scores = [] - - # --- 1. 하이퍼파라미터 탐색 범위 정의 (수정됨) --- - if model_choose == "ft_transformer": - d_token = trial.suggest_int("d_token", 64, 256, step=32) - n_blocks = trial.suggest_int("n_blocks", 2, 6) # 깊이 축소로 과적합 방지 - n_heads = trial.suggest_categorical("n_heads", [4, 8]) - # d_token은 n_heads의 배수여야 함 (FT-Transformer의 구조적 제약 대응) - if d_token % n_heads != 0: - d_token = (d_token // n_heads) * n_heads - - attention_dropout = trial.suggest_float("attention_dropout", 0.1, 0.4) - ffn_dropout = trial.suggest_float("ffn_dropout", 0.1, 0.4) - lr = trial.suggest_float("lr", 1e-5, 1e-2, log=True) # 범위 확대 - weight_decay = trial.suggest_float("weight_decay", 1e-4, 1e-1, log=True) # 더 공격적인 범위로 확장 - batch_size = trial.suggest_categorical("batch_size", [32, 64, 128, 256]) # Batch Size 추가 - - elif model_choose == 'resnet_like': - d_main = trial.suggest_int("d_main", 64, 256, step=32) - d_hidden = trial.suggest_int("d_hidden", 64, 512, step=64) - n_blocks = trial.suggest_int("n_blocks", 2, 5) # 너무 깊지 않게 조절 - dropout_first = trial.suggest_float("dropout_first", 0.1, 0.4) - dropout_second = trial.suggest_float("dropout_second", 0.0, 0.2) - lr = trial.suggest_float("lr", 1e-5, 1e-2, log=True) - weight_decay = trial.suggest_float("weight_decay", 1e-4, 1e-1, log=True) # 더 공격적인 범위로 확장 - batch_size = trial.suggest_categorical("batch_size", [32, 64, 128, 256]) # Batch Size 추가 - - elif model_choose == 'deepgbm': - # DeepGBM의 경우 모델 특성에 맞춰 ResNet 블록 및 임베딩 차원 조절 - d_main = trial.suggest_int("d_main", 64, 256, step=32) - d_hidden = trial.suggest_int("d_hidden", 64, 256, step=64) - n_blocks = trial.suggest_int("n_blocks", 2, 6) - dropout = trial.suggest_float("dropout", 0.1, 0.4) - lr = trial.suggest_float("lr", 1e-5, 1e-2, log=True) - weight_decay = trial.suggest_float("weight_decay", 1e-4, 1e-1, log=True) # 더 공격적인 범위로 확장 - batch_size = trial.suggest_categorical("batch_size", [32, 64, 128, 256]) # Batch Size 추가 - - # --- 2. Fold별 학습 및 교차 검증 --- - for fold in range(1, n_folds + 1): - X_train_df, categorical_cols, numerical_cols, train_loader, val_loader, _, y_train, _ = prepare_dataloader_with_batchsize( - region, data_sample=data_sample, target=target, fold=fold, random_state=random_state, batch_size=batch_size - ) - - # 모델 초기화 - if model_choose == "ft_transformer": - model = FTTransformer( - num_features=len(numerical_cols), - cat_cardinalities=[len(X_train_df[col].unique()) for col in categorical_cols], - d_token=d_token, - n_blocks=n_blocks, - n_heads=n_heads, - attention_dropout=attention_dropout, - ffn_dropout=ffn_dropout, - num_classes=3 - ).to(device) - elif model_choose == 'resnet_like': - input_dim = len(numerical_cols) + len(categorical_cols) - model = ResNetLike( - input_dim=input_dim, - d_main=d_main, - d_hidden=d_hidden, - n_blocks=n_blocks, - dropout_first=dropout_first, - dropout_second=dropout_second, - num_classes=3 - ).to(device) - elif model_choose == 'deepgbm': - model = DeepGBM( - num_features=len(numerical_cols), - cat_features=[len(X_train_df[col].unique()) for col in categorical_cols], - d_main=d_main, - d_hidden=d_hidden, - n_blocks=n_blocks, - dropout=dropout, - num_classes=3 - ).to(device) - - # 클래스 가중치 계산 및 손실 함수 설정 (Label Smoothing 적용) - if target == 'multi': - class_weights = compute_class_weight( - class_weight='balanced', - classes=np.unique(y_train), - y=y_train - ) - # 클래스별 가중치 로그 출력 - unique_classes = np.unique(y_train) - class_counts = {cls: np.sum(y_train == cls) for cls in unique_classes} - print(f" Fold {fold} - 클래스별 가중치: {dict(zip(unique_classes, class_weights))} (클래스별 샘플 수: {class_counts})") - class_weights_tensor = torch.tensor(class_weights, dtype=torch.float32).to(device) - criterion = nn.CrossEntropyLoss(weight=class_weights_tensor, label_smoothing=0.0) # Label Smoothing 추가 - else: - criterion = nn.BCEWithLogitsLoss() - optimizer = optim.AdamW(model.parameters(), lr=lr, weight_decay=weight_decay) - - # 학습률 스케줄러 추가: 성능 정체 시 LR을 0.5배 감소 (검증 CSI 기준) - scheduler = optim.lr_scheduler.ReduceLROnPlateau(optimizer, mode='max', factor=0.5, patience=3) - - # 학습 설정 (에폭 및 페이션스 상향) - epochs = 200 - patience = 12 # 딥러닝의 정체 구간을 고려하여 소폭 상향 - best_fold_csi = 0 - counter = 0 - - for epoch in range(epochs): - model.train() - for x_num_batch, x_cat_batch, y_batch in train_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - - optimizer.zero_grad() - y_pred = model(x_num_batch, x_cat_batch) - loss = criterion(y_pred, y_batch if target == 'multi' else y_batch.float()) - loss.backward() - optimizer.step() - - # Validation 평가 - model.eval() - y_pred_val, y_true_val = [], [] - with torch.no_grad(): - for x_num_batch, x_cat_batch, y_batch in val_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - output = model(x_num_batch, x_cat_batch) - pred = output.argmax(dim=1) if target == 'multi' else (torch.sigmoid(output) >= 0.5).long() - - y_pred_val.extend(pred.cpu().numpy()) - y_true_val.extend(y_batch.cpu().numpy()) - - # CSI 계산 및 스케줄러 업데이트 - val_csi = calculate_csi(y_true_val, y_pred_val) - scheduler.step(val_csi) - - # Optuna Pruning 적용 (첫 번째 Fold에서 조기 종료 판단 강화) - trial.report(val_csi, epoch) - if trial.should_prune(): - raise optuna.exceptions.TrialPruned() - - # Early Stopping 체크 - if val_csi > best_fold_csi: - best_fold_csi = val_csi - counter = 0 - else: - counter += 1 - - if counter >= patience: - break - - val_scores.append(best_fold_csi) - - # 모든 fold의 평균 성능 반환 - return np.mean(val_scores) - - -# 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 함수 -def train_final_model(best_params, model_choose, region, data_sample='pure', target='multi', n_folds=3, random_state=42): - """ - 최적화된 하이퍼파라미터로 최종 모델을 학습하고 저장합니다. - - Args: - best_params: 최적화된 하이퍼파라미터 딕셔너리 - model_choose: 모델 선택 ('ft_transformer', 'resnet_like', 'deepgbm') - region: 지역명 - data_sample: 데이터 샘플 타입 ('pure', 'smote', etc.) - target: 타겟 타입 ('multi', 'binary') - n_folds: 교차 검증 fold 수 - random_state: 랜덤 시드 - - Returns: - 저장된 모델 경로 리스트 - """ - # GPU 사용 가능 여부 확인 및 device 설정 - device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') - - models = [] - scalers = [] # scaler 리스트 추가 - - print("최종 모델 학습 시작...") - - for fold in range(1, n_folds + 1): - print(f"Fold {fold} 학습 중...") - - # 최적화된 batch_size 사용 - batch_size = best_params.get("batch_size", 64) - X_train_df, categorical_cols, numerical_cols, train_loader, val_loader, _, y_train, scaler = prepare_dataloader_with_batchsize( - region, data_sample=data_sample, target=target, fold=fold, random_state=random_state, batch_size=batch_size - ) - - # 모델 초기화 - if model_choose == "ft_transformer": - d_token = best_params["d_token"] - n_heads = best_params.get("n_heads", 8) - # d_token은 n_heads의 배수여야 함 (FT-Transformer의 구조적 제약 대응) - if d_token % n_heads != 0: - d_token = (d_token // n_heads) * n_heads - - model = FTTransformer( - num_features=len(numerical_cols), - cat_cardinalities=[len(X_train_df[col].unique()) for col in categorical_cols], - d_token=d_token, - n_blocks=best_params["n_blocks"], - n_heads=n_heads, - attention_dropout=best_params["attention_dropout"], - ffn_dropout=best_params["ffn_dropout"], - num_classes=3 - ).to(device) - elif model_choose == 'resnet_like': - input_dim = len(numerical_cols) + len(categorical_cols) - model = ResNetLike( - input_dim=input_dim, - d_main=best_params["d_main"], - d_hidden=best_params["d_hidden"], - n_blocks=best_params["n_blocks"], - dropout_first=best_params["dropout_first"], - dropout_second=best_params["dropout_second"], - num_classes=3 - ).to(device) - elif model_choose == 'deepgbm': - model = DeepGBM( - num_features=len(numerical_cols), - cat_features=[len(X_train_df[col].unique()) for col in categorical_cols], - d_main=best_params["d_main"], - d_hidden=best_params["d_hidden"], - n_blocks=best_params["n_blocks"], - dropout=best_params["dropout"], - num_classes=3 - ).to(device) - else: - raise ValueError(f"Unknown model_choose: {model_choose}") - - # 클래스 가중치 계산 및 손실 함수 설정 (Label Smoothing 적용) - if target == 'multi': - class_weights = compute_class_weight( - class_weight='balanced', - classes=np.unique(y_train), - y=y_train - ) - class_weights_tensor = torch.tensor(class_weights, dtype=torch.float32).to(device) - criterion = nn.CrossEntropyLoss(weight=class_weights_tensor, label_smoothing=0.0) # Label Smoothing 추가 - else: - criterion = nn.BCEWithLogitsLoss() - optimizer = optim.AdamW(model.parameters(), lr=best_params["lr"], weight_decay=best_params["weight_decay"]) - - # 학습률 스케줄러 - scheduler = optim.lr_scheduler.ReduceLROnPlateau(optimizer, mode='max', factor=0.5, patience=3) - - # 학습 설정 - epochs = 200 - patience = 12 - best_fold_csi = 0 - counter = 0 - best_model = None - - for epoch in range(epochs): - model.train() - for x_num_batch, x_cat_batch, y_batch in train_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - - optimizer.zero_grad() - y_pred = model(x_num_batch, x_cat_batch) - loss = criterion(y_pred, y_batch if target == 'multi' else y_batch.float()) - loss.backward() - optimizer.step() - - # Validation 평가 - model.eval() - y_pred_val, y_true_val = [], [] - with torch.no_grad(): - for x_num_batch, x_cat_batch, y_batch in val_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - output = model(x_num_batch, x_cat_batch) - pred = output.argmax(dim=1) if target == 'multi' else (torch.sigmoid(output) >= 0.5).long() - - y_pred_val.extend(pred.cpu().numpy()) - y_true_val.extend(y_batch.cpu().numpy()) - - # CSI 계산 및 스케줄러 업데이트 - val_csi = calculate_csi(y_true_val, y_pred_val) - scheduler.step(val_csi) - - # Early Stopping 체크 - if val_csi > best_fold_csi: - best_fold_csi = val_csi - counter = 0 - best_model = copy.deepcopy(model) - else: - counter += 1 - - if counter >= patience: - print(f" Early stopping at epoch {epoch+1}, Best CSI: {best_fold_csi:.4f}") - break - - if best_model is None: - best_model = model - - scalers.append(scaler) # scaler 저장 (fold 순서대로) - models.append(best_model) - print(f" Fold {fold} 학습 완료 (검증 CSI: {best_fold_csi:.4f})") - - # 모델 저장 경로 설정 - save_dir = f'../save_model/{model_choose}_optima' - os.makedirs(save_dir, exist_ok=True) - - # 파일명 생성 - if data_sample == 'pure': - model_filename = f'{model_choose}_pure_{region}.pkl' - else: - model_filename = f'{model_choose}_{data_sample}_{region}.pkl' - - model_path = f'{save_dir}/{model_filename}' - - # 리스트에 담아 한 번에 저장 - joblib.dump(models, model_path) - print(f"\n모든 모델 저장 완료: {model_path} (총 {len(models)}개 fold)") - - # Scaler 별도 저장 - scaler_save_dir = f'../save_model/{model_choose}_optima/scaler' - os.makedirs(scaler_save_dir, exist_ok=True) - - # 파일명 생성 (모델과 동일한 패턴) - if data_sample == 'pure': - scaler_filename = f'{model_choose}_pure_{region}_scaler.pkl' - else: - scaler_filename = f'{model_choose}_{data_sample}_{region}_scaler.pkl' - - scaler_path = f'{scaler_save_dir}/{scaler_filename}' - joblib.dump(scalers, scaler_path) - print(f"Scaler 저장 완료: {scaler_path} (총 {len(scalers)}개 fold)") - - return model_path diff --git a/Analysis_code/5.optima/ft_transformer_smotenc_ctgan20000/ft_transformer_smotenc_ctgan20000_busan.py b/Analysis_code/5.optima/ft_transformer_smotenc_ctgan20000/ft_transformer_smotenc_ctgan20000_busan.py deleted file mode 100644 index 313029939803c0ca4ade0e8a6cdfb4a148d3f532..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/ft_transformer_smotenc_ctgan20000/ft_transformer_smotenc_ctgan20000_busan.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="ft_transformer", region="busan", data_sample='smotenc_ctgan20000'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/ft_transformer_smotenc_ctgan20000_busan_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="ft_transformer", - region="busan", - data_sample='smotenc_ctgan20000', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/ft_transformer_smotenc_ctgan20000/ft_transformer_smotenc_ctgan20000_daegu.py b/Analysis_code/5.optima/ft_transformer_smotenc_ctgan20000/ft_transformer_smotenc_ctgan20000_daegu.py deleted file mode 100644 index 0cf613aa2d2a210467fc6aeeca6cb1d09bf96304..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/ft_transformer_smotenc_ctgan20000/ft_transformer_smotenc_ctgan20000_daegu.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="ft_transformer", region="daegu", data_sample='smotenc_ctgan20000'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/ft_transformer_smotenc_ctgan20000_daegu_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="ft_transformer", - region="daegu", - data_sample='smotenc_ctgan20000', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/ft_transformer_smotenc_ctgan20000/ft_transformer_smotenc_ctgan20000_daejeon.py b/Analysis_code/5.optima/ft_transformer_smotenc_ctgan20000/ft_transformer_smotenc_ctgan20000_daejeon.py deleted file mode 100644 index 79a542533ff136265031773eb8f83fc015361f50..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/ft_transformer_smotenc_ctgan20000/ft_transformer_smotenc_ctgan20000_daejeon.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="ft_transformer", region="daejeon", data_sample='smotenc_ctgan20000'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/ft_transformer_smotenc_ctgan20000_daejeon_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="ft_transformer", - region="daejeon", - data_sample='smotenc_ctgan20000', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/ft_transformer_smotenc_ctgan20000/ft_transformer_smotenc_ctgan20000_gwangju.py b/Analysis_code/5.optima/ft_transformer_smotenc_ctgan20000/ft_transformer_smotenc_ctgan20000_gwangju.py deleted file mode 100644 index 44836964afa35e1c9781bca01fd9dd0a34ed2ac9..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/ft_transformer_smotenc_ctgan20000/ft_transformer_smotenc_ctgan20000_gwangju.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="ft_transformer", region="gwangju", data_sample='smotenc_ctgan20000'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/ft_transformer_smotenc_ctgan20000_gwangju_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="ft_transformer", - region="gwangju", - data_sample='smotenc_ctgan20000', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/ft_transformer_smotenc_ctgan20000/ft_transformer_smotenc_ctgan20000_incheon.py b/Analysis_code/5.optima/ft_transformer_smotenc_ctgan20000/ft_transformer_smotenc_ctgan20000_incheon.py deleted file mode 100644 index ba7183d189aee81011734f08615983b0f47de953..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/ft_transformer_smotenc_ctgan20000/ft_transformer_smotenc_ctgan20000_incheon.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="ft_transformer", region="incheon", data_sample='smotenc_ctgan20000'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/ft_transformer_smotenc_ctgan20000_incheon_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="ft_transformer", - region="incheon", - data_sample='smotenc_ctgan20000', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/ft_transformer_smotenc_ctgan20000/ft_transformer_smotenc_ctgan20000_seoul.py b/Analysis_code/5.optima/ft_transformer_smotenc_ctgan20000/ft_transformer_smotenc_ctgan20000_seoul.py deleted file mode 100644 index c07bf7922bb0f2fe701cb2ecd0fd8007f23a6350..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/ft_transformer_smotenc_ctgan20000/ft_transformer_smotenc_ctgan20000_seoul.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="ft_transformer", region="seoul", data_sample='smotenc_ctgan20000'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/ft_transformer_smotenc_ctgan20000_seoul_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="ft_transformer", - region="seoul", - data_sample='smotenc_ctgan20000', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/ft_transformer_smotenc_ctgan20000/utils.py b/Analysis_code/5.optima/ft_transformer_smotenc_ctgan20000/utils.py deleted file mode 100644 index 3f4f4d793d54387f8f7ea639fbad36de0622fb51..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/ft_transformer_smotenc_ctgan20000/utils.py +++ /dev/null @@ -1,719 +0,0 @@ -import torch -import torch.nn as nn -import torch.optim as optim -import numpy as np -import random -import os -import copy -from sklearn.preprocessing import QuantileTransformer, LabelEncoder -from torch.utils.data import DataLoader, TensorDataset -from sklearn.metrics import confusion_matrix -from sklearn.utils.class_weight import compute_class_weight -import pandas as pd -import optuna -from sklearn.metrics import accuracy_score, f1_score -import joblib - - -import sys -# 파일 위치 기반으로 models 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -models_path = os.path.abspath(os.path.join(current_file_dir, '../../models')) -sys.path.insert(0, models_path) -from ft_transformer import FTTransformer -from resnet_like import ResNetLike -from deepgbm import DeepGBM -import warnings -warnings.filterwarnings('ignore') - -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - -# PyTorch 시드 고정 -torch.manual_seed(seed) -torch.cuda.manual_seed(seed) -torch.cuda.manual_seed_all(seed) # Multi-GPU 환경에서 동일한 시드 적용 - -# PyTorch 연산의 결정적 모드 설정 -torch.backends.cudnn.deterministic = True # 실행마다 동일한 결과를 보장 -torch.backends.cudnn.benchmark = True # 성능 최적화를 활성화 (가능한 한 빠른 연산 수행) - - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - - -# 데이터셋 준비 함수 -def prepare_dataset(region, data_sample='pure', target='multi', fold=3): - - # 파일 위치 기반으로 데이터 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) - - # 데이터 경로 지정 - dat_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_train.csv") - if data_sample == 'pure': - train_path = dat_path - else: - train_path = os.path.join(data_base_dir, f'data_oversampled/{data_sample}/{data_sample}_{fold}_{region}.csv') - test_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_test.csv") - drop_col = ['multi_class','year'] - target_col = f'{target}_class' - - # 데이터 로드 - region_dat = preprocessing(pd.read_csv(dat_path, index_col=0)) - if data_sample == 'pure': - region_train = region_dat.loc[~region_dat['year'].isin([2021-fold]), :] - else: - region_train = preprocessing(pd.read_csv(train_path)) - region_val = region_dat.loc[region_dat['year'].isin([2021-fold]), :] - region_test = preprocessing(pd.read_csv(test_path)) - - # 컬럼 정렬 (일관성 유지) - common_columns = region_train.columns.to_list() - train_data = region_train[common_columns] - val_data = region_val[common_columns] - test_data = region_test[common_columns] - - # 설명변수 & 타겟 분리 - X_train = train_data.drop(columns=drop_col) - y_train = train_data[target_col] - X_val = val_data.drop(columns=drop_col) - y_val = val_data[target_col] - X_test = test_data.drop(columns=drop_col) - y_test = test_data[target_col] - - # 범주형 & 연속형 변수 분리 - categorical_cols = X_train.select_dtypes(include=['object', 'category', 'int64']).columns - numerical_cols = X_train.select_dtypes(include=['float64']).columns - - # 범주형 변수 Label Encoding - label_encoders = {} - for col in categorical_cols: - le = LabelEncoder() - le.fit(X_train[col]) # Train 데이터 기준으로 학습 - label_encoders[col] = le - - # 변환 적용 - for col in categorical_cols: - X_train[col] = label_encoders[col].transform(X_train[col]) - X_val[col] = label_encoders[col].transform(X_val[col]) - X_test[col] = label_encoders[col].transform(X_test[col]) - - # 연속형 변수 Quantile Transformation - scaler = QuantileTransformer(output_distribution='normal') - scaler.fit(X_train[numerical_cols]) # Train 데이터 기준으로 학습 - - # 변환 적용 - X_train[numerical_cols] = scaler.transform(X_train[numerical_cols]) - X_val[numerical_cols] = scaler.transform(X_val[numerical_cols]) - X_test[numerical_cols] = scaler.transform(X_test[numerical_cols]) - - return X_train, X_val, X_test, y_train, y_val, y_test, categorical_cols, numerical_cols - - - -# 데이터 변환 및 dataloader 생성 함수 -def prepare_dataloader(region, data_sample='pure', target='multi', fold=3, random_state=None): - - # 파일 위치 기반으로 데이터 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) - - # 데이터 경로 지정 - dat_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_train.csv") - if data_sample == 'pure': - train_path = dat_path - else: - train_path = os.path.join(data_base_dir, f'data_oversampled/{data_sample}/{data_sample}_{fold}_{region}.csv') - test_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_test.csv") - drop_col = ['multi_class','year'] - target_col = f'{target}_class' - - # 데이터 로드 - region_dat = preprocessing(pd.read_csv(dat_path, index_col=0)) - if data_sample == 'pure': - region_train = region_dat.loc[~region_dat['year'].isin([2021-fold]), :] - else: - region_train = preprocessing(pd.read_csv(train_path)) - region_val = region_dat.loc[region_dat['year'].isin([2021-fold]), :] - region_test = preprocessing(pd.read_csv(test_path)) - - # 컬럼 정렬 (일관성 유지) - common_columns = region_train.columns.to_list() - train_data = region_train[common_columns] - val_data = region_val[common_columns] - test_data = region_test[common_columns] - - # 설명변수 & 타겟 분리 - X_train = train_data.drop(columns=drop_col) - y_train = train_data[target_col] - X_val = val_data.drop(columns=drop_col) - y_val = val_data[target_col] - X_test = test_data.drop(columns=drop_col) - y_test = test_data[target_col] - - # 범주형 & 연속형 변수 분리 - categorical_cols = X_train.select_dtypes(include=['object', 'category', 'int64']).columns - numerical_cols = X_train.select_dtypes(include=['float64']).columns - - # 범주형 변수 Label Encoding - label_encoders = {} - for col in categorical_cols: - le = LabelEncoder() - le.fit(X_train[col]) # Train 데이터 기준으로 학습 - label_encoders[col] = le - - # 변환 적용 - for col in categorical_cols: - X_train[col] = label_encoders[col].transform(X_train[col]) - X_val[col] = label_encoders[col].transform(X_val[col]) - X_test[col] = label_encoders[col].transform(X_test[col]) - - # 연속형 변수 Quantile Transformation - scaler = QuantileTransformer(output_distribution='normal') - scaler.fit(X_train[numerical_cols]) # Train 데이터 기준으로 학습 - - # 변환 적용 - X_train[numerical_cols] = scaler.transform(X_train[numerical_cols]) - X_val[numerical_cols] = scaler.transform(X_val[numerical_cols]) - X_test[numerical_cols] = scaler.transform(X_test[numerical_cols]) - - # 연속형 변수와 범주형 변수 분리 - X_train_num = torch.tensor(X_train[numerical_cols].values, dtype=torch.float32) - X_train_cat = torch.tensor(X_train[categorical_cols].values, dtype=torch.long) - - X_val_num = torch.tensor(X_val[numerical_cols].values, dtype=torch.float32) - X_val_cat = torch.tensor(X_val[categorical_cols].values, dtype=torch.long) - - X_test_num = torch.tensor(X_test[numerical_cols].values, dtype=torch.float32) - X_test_cat = torch.tensor(X_test[categorical_cols].values, dtype=torch.long) - - # 레이블 변환 - if target == "binary": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.float32) # 이진 분류 → float32 - y_val_tensor = torch.tensor(y_val.values, dtype=torch.float32) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.float32) - elif target == "multi": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.long) # 다중 분류 → long - y_val_tensor = torch.tensor(y_val.values, dtype=torch.long) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.long) - else: - raise ValueError("target must be 'binary' or 'multi'") - - # TensorDataset 생성 - train_dataset = TensorDataset(X_train_num, X_train_cat, y_train_tensor) - val_dataset = TensorDataset(X_val_num, X_val_cat, y_val_tensor) - test_dataset = TensorDataset(X_test_num, X_test_cat, y_test_tensor) - - # DataLoader 생성 - if random_state == None: - train_loader = DataLoader(train_dataset, batch_size=64, shuffle=True) - else: - train_loader = DataLoader(train_dataset, batch_size=64, shuffle=True, generator=torch.Generator().manual_seed(random_state)) - val_loader = DataLoader(val_dataset, batch_size=64, shuffle=False) - test_loader = DataLoader(test_dataset, batch_size=64, shuffle=False) - - return X_train, categorical_cols, numerical_cols, train_loader, val_loader, test_loader - -# 데이터 변환 및 dataloader 생성 함수 (batch_size 파라미터 추가 버전) -def prepare_dataloader_with_batchsize(region, data_sample='pure', target='multi', fold=3, random_state=None, batch_size=64): - # 파일 위치 기반으로 데이터 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) - - # 데이터 경로 지정 - dat_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_train.csv") - if data_sample == 'pure': - train_path = dat_path - else: - train_path = os.path.join(data_base_dir, f'data_oversampled/{data_sample}/{data_sample}_{fold}_{region}.csv') - test_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_test.csv") - drop_col = ['multi_class','year'] - target_col = f'{target}_class' - - # 데이터 로드 - region_dat = preprocessing(pd.read_csv(dat_path, index_col=0)) - if data_sample == 'pure': - region_train = region_dat.loc[~region_dat['year'].isin([2021-fold]), :] - else: - region_train = preprocessing(pd.read_csv(train_path)) - region_val = region_dat.loc[region_dat['year'].isin([2021-fold]), :] - region_test = preprocessing(pd.read_csv(test_path)) - - # 컬럼 정렬 (일관성 유지) - common_columns = region_train.columns.to_list() - train_data = region_train[common_columns] - val_data = region_val[common_columns] - test_data = region_test[common_columns] - - # 설명변수 & 타겟 분리 - X_train = train_data.drop(columns=drop_col) - y_train = train_data[target_col] - X_val = val_data.drop(columns=drop_col) - y_val = val_data[target_col] - X_test = test_data.drop(columns=drop_col) - y_test = test_data[target_col] - - # 범주형 & 연속형 변수 분리 - categorical_cols = X_train.select_dtypes(include=['object', 'category', 'int64']).columns - numerical_cols = X_train.select_dtypes(include=['float64']).columns - - # 범주형 변수 Label Encoding - label_encoders = {} - for col in categorical_cols: - le = LabelEncoder() - le.fit(X_train[col]) # Train 데이터 기준으로 학습 - label_encoders[col] = le - - # 변환 적용 - for col in categorical_cols: - X_train[col] = label_encoders[col].transform(X_train[col]) - X_val[col] = label_encoders[col].transform(X_val[col]) - X_test[col] = label_encoders[col].transform(X_test[col]) - - # 연속형 변수 Quantile Transformation - scaler = QuantileTransformer(output_distribution='normal') - scaler.fit(X_train[numerical_cols]) # Train 데이터 기준으로 학습 - - # 변환 적용 - X_train[numerical_cols] = scaler.transform(X_train[numerical_cols]) - X_val[numerical_cols] = scaler.transform(X_val[numerical_cols]) - X_test[numerical_cols] = scaler.transform(X_test[numerical_cols]) - - # 연속형 변수와 범주형 변수 분리 - X_train_num = torch.tensor(X_train[numerical_cols].values, dtype=torch.float32) - X_train_cat = torch.tensor(X_train[categorical_cols].values, dtype=torch.long) - - X_val_num = torch.tensor(X_val[numerical_cols].values, dtype=torch.float32) - X_val_cat = torch.tensor(X_val[categorical_cols].values, dtype=torch.long) - - X_test_num = torch.tensor(X_test[numerical_cols].values, dtype=torch.float32) - X_test_cat = torch.tensor(X_test[categorical_cols].values, dtype=torch.long) - - # 레이블 변환 - if target == "binary": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.float32) # 이진 분류 → float32 - y_val_tensor = torch.tensor(y_val.values, dtype=torch.float32) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.float32) - elif target == "multi": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.long) # 다중 분류 → long - y_val_tensor = torch.tensor(y_val.values, dtype=torch.long) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.long) - else: - raise ValueError("target must be 'binary' or 'multi'") - - # TensorDataset 생성 - train_dataset = TensorDataset(X_train_num, X_train_cat, y_train_tensor) - val_dataset = TensorDataset(X_val_num, X_val_cat, y_val_tensor) - test_dataset = TensorDataset(X_test_num, X_test_cat, y_test_tensor) - - # DataLoader 생성 (batch_size 파라미터 사용) - if random_state == None: - train_loader = DataLoader(train_dataset, batch_size=batch_size, shuffle=True) - else: - train_loader = DataLoader(train_dataset, batch_size=batch_size, shuffle=True, generator=torch.Generator().manual_seed(random_state)) - val_loader = DataLoader(val_dataset, batch_size=batch_size, shuffle=False) - test_loader = DataLoader(test_dataset, batch_size=batch_size, shuffle=False) - - return X_train, categorical_cols, numerical_cols, train_loader, val_loader, test_loader, y_train, scaler - - -def calculate_csi(y_true, pred): - - cm = confusion_matrix(y_true, pred) # 변수 이름을 cm으로 변경 - # 혼동 행렬에서 H, F, M 추출 - H = (cm[0, 0] + cm[1, 1]) - - F = (cm[1, 0] + cm[2, 0] + - cm[0, 1] + cm[2, 1]) - - M = (cm[0, 2] + cm[1, 2]) - - # CSI 계산 - CSI = H / (H + F + M + 1e-10) - return CSI - -def sample_weight(y_train): - class_weights = compute_class_weight( - class_weight='balanced', - classes=np.unique(y_train), # 고유 클래스 - y=y_train # 학습 데이터 레이블 - ) - sample_weights = np.array([class_weights[label] for label in y_train]) - - return sample_weights - -# 하이퍼파라미터 최적화 함수 정의 -def objective(trial, model_choose, region, data_sample='pure', target='multi', n_folds=3, random_state=42): - # GPU 사용 가능 여부 확인 및 device 설정 - device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') - val_scores = [] - - # --- 1. 하이퍼파라미터 탐색 범위 정의 (수정됨) --- - if model_choose == "ft_transformer": - d_token = trial.suggest_int("d_token", 64, 256, step=32) - n_blocks = trial.suggest_int("n_blocks", 2, 6) # 깊이 축소로 과적합 방지 - n_heads = trial.suggest_categorical("n_heads", [4, 8]) - # d_token은 n_heads의 배수여야 함 (FT-Transformer의 구조적 제약 대응) - if d_token % n_heads != 0: - d_token = (d_token // n_heads) * n_heads - - attention_dropout = trial.suggest_float("attention_dropout", 0.1, 0.4) - ffn_dropout = trial.suggest_float("ffn_dropout", 0.1, 0.4) - lr = trial.suggest_float("lr", 1e-5, 1e-2, log=True) # 범위 확대 - weight_decay = trial.suggest_float("weight_decay", 1e-4, 1e-1, log=True) # 더 공격적인 범위로 확장 - batch_size = trial.suggest_categorical("batch_size", [32, 64, 128, 256]) # Batch Size 추가 - - elif model_choose == 'resnet_like': - d_main = trial.suggest_int("d_main", 64, 256, step=32) - d_hidden = trial.suggest_int("d_hidden", 64, 512, step=64) - n_blocks = trial.suggest_int("n_blocks", 2, 5) # 너무 깊지 않게 조절 - dropout_first = trial.suggest_float("dropout_first", 0.1, 0.4) - dropout_second = trial.suggest_float("dropout_second", 0.0, 0.2) - lr = trial.suggest_float("lr", 1e-5, 1e-2, log=True) - weight_decay = trial.suggest_float("weight_decay", 1e-4, 1e-1, log=True) # 더 공격적인 범위로 확장 - batch_size = trial.suggest_categorical("batch_size", [32, 64, 128, 256]) # Batch Size 추가 - - elif model_choose == 'deepgbm': - # DeepGBM의 경우 모델 특성에 맞춰 ResNet 블록 및 임베딩 차원 조절 - d_main = trial.suggest_int("d_main", 64, 256, step=32) - d_hidden = trial.suggest_int("d_hidden", 64, 256, step=64) - n_blocks = trial.suggest_int("n_blocks", 2, 6) - dropout = trial.suggest_float("dropout", 0.1, 0.4) - lr = trial.suggest_float("lr", 1e-5, 1e-2, log=True) - weight_decay = trial.suggest_float("weight_decay", 1e-4, 1e-1, log=True) # 더 공격적인 범위로 확장 - batch_size = trial.suggest_categorical("batch_size", [32, 64, 128, 256]) # Batch Size 추가 - - # --- 2. Fold별 학습 및 교차 검증 --- - for fold in range(1, n_folds + 1): - X_train_df, categorical_cols, numerical_cols, train_loader, val_loader, _, y_train, _ = prepare_dataloader_with_batchsize( - region, data_sample=data_sample, target=target, fold=fold, random_state=random_state, batch_size=batch_size - ) - - # 모델 초기화 - if model_choose == "ft_transformer": - model = FTTransformer( - num_features=len(numerical_cols), - cat_cardinalities=[len(X_train_df[col].unique()) for col in categorical_cols], - d_token=d_token, - n_blocks=n_blocks, - n_heads=n_heads, - attention_dropout=attention_dropout, - ffn_dropout=ffn_dropout, - num_classes=3 - ).to(device) - elif model_choose == 'resnet_like': - input_dim = len(numerical_cols) + len(categorical_cols) - model = ResNetLike( - input_dim=input_dim, - d_main=d_main, - d_hidden=d_hidden, - n_blocks=n_blocks, - dropout_first=dropout_first, - dropout_second=dropout_second, - num_classes=3 - ).to(device) - elif model_choose == 'deepgbm': - model = DeepGBM( - num_features=len(numerical_cols), - cat_features=[len(X_train_df[col].unique()) for col in categorical_cols], - d_main=d_main, - d_hidden=d_hidden, - n_blocks=n_blocks, - dropout=dropout, - num_classes=3 - ).to(device) - - # 클래스 가중치 계산 및 손실 함수 설정 (Label Smoothing 적용) - if target == 'multi': - class_weights = compute_class_weight( - class_weight='balanced', - classes=np.unique(y_train), - y=y_train - ) - # 클래스별 가중치 로그 출력 - unique_classes = np.unique(y_train) - class_counts = {cls: np.sum(y_train == cls) for cls in unique_classes} - print(f" Fold {fold} - 클래스별 가중치: {dict(zip(unique_classes, class_weights))} (클래스별 샘플 수: {class_counts})") - class_weights_tensor = torch.tensor(class_weights, dtype=torch.float32).to(device) - criterion = nn.CrossEntropyLoss(weight=class_weights_tensor, label_smoothing=0.0) # Label Smoothing 추가 - else: - criterion = nn.BCEWithLogitsLoss() - optimizer = optim.AdamW(model.parameters(), lr=lr, weight_decay=weight_decay) - - # 학습률 스케줄러 추가: 성능 정체 시 LR을 0.5배 감소 (검증 CSI 기준) - scheduler = optim.lr_scheduler.ReduceLROnPlateau(optimizer, mode='max', factor=0.5, patience=3) - - # 학습 설정 (에폭 및 페이션스 상향) - epochs = 200 - patience = 12 # 딥러닝의 정체 구간을 고려하여 소폭 상향 - best_fold_csi = 0 - counter = 0 - - for epoch in range(epochs): - model.train() - for x_num_batch, x_cat_batch, y_batch in train_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - - optimizer.zero_grad() - y_pred = model(x_num_batch, x_cat_batch) - loss = criterion(y_pred, y_batch if target == 'multi' else y_batch.float()) - loss.backward() - optimizer.step() - - # Validation 평가 - model.eval() - y_pred_val, y_true_val = [], [] - with torch.no_grad(): - for x_num_batch, x_cat_batch, y_batch in val_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - output = model(x_num_batch, x_cat_batch) - pred = output.argmax(dim=1) if target == 'multi' else (torch.sigmoid(output) >= 0.5).long() - - y_pred_val.extend(pred.cpu().numpy()) - y_true_val.extend(y_batch.cpu().numpy()) - - # CSI 계산 및 스케줄러 업데이트 - val_csi = calculate_csi(y_true_val, y_pred_val) - scheduler.step(val_csi) - - # Optuna Pruning 적용 (첫 번째 Fold에서 조기 종료 판단 강화) - trial.report(val_csi, epoch) - if trial.should_prune(): - raise optuna.exceptions.TrialPruned() - - # Early Stopping 체크 - if val_csi > best_fold_csi: - best_fold_csi = val_csi - counter = 0 - else: - counter += 1 - - if counter >= patience: - break - - val_scores.append(best_fold_csi) - - # 모든 fold의 평균 성능 반환 - return np.mean(val_scores) - - -# 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 함수 -def train_final_model(best_params, model_choose, region, data_sample='pure', target='multi', n_folds=3, random_state=42): - """ - 최적화된 하이퍼파라미터로 최종 모델을 학습하고 저장합니다. - - Args: - best_params: 최적화된 하이퍼파라미터 딕셔너리 - model_choose: 모델 선택 ('ft_transformer', 'resnet_like', 'deepgbm') - region: 지역명 - data_sample: 데이터 샘플 타입 ('pure', 'smote', etc.) - target: 타겟 타입 ('multi', 'binary') - n_folds: 교차 검증 fold 수 - random_state: 랜덤 시드 - - Returns: - 저장된 모델 경로 리스트 - """ - # GPU 사용 가능 여부 확인 및 device 설정 - device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') - - models = [] - scalers = [] # scaler 리스트 추가 - - print("최종 모델 학습 시작...") - - for fold in range(1, n_folds + 1): - print(f"Fold {fold} 학습 중...") - - # 최적화된 batch_size 사용 - batch_size = best_params.get("batch_size", 64) - X_train_df, categorical_cols, numerical_cols, train_loader, val_loader, _, y_train, scaler = prepare_dataloader_with_batchsize( - region, data_sample=data_sample, target=target, fold=fold, random_state=random_state, batch_size=batch_size - ) - - # 모델 초기화 - if model_choose == "ft_transformer": - d_token = best_params["d_token"] - n_heads = best_params.get("n_heads", 8) - # d_token은 n_heads의 배수여야 함 (FT-Transformer의 구조적 제약 대응) - if d_token % n_heads != 0: - d_token = (d_token // n_heads) * n_heads - - model = FTTransformer( - num_features=len(numerical_cols), - cat_cardinalities=[len(X_train_df[col].unique()) for col in categorical_cols], - d_token=d_token, - n_blocks=best_params["n_blocks"], - n_heads=n_heads, - attention_dropout=best_params["attention_dropout"], - ffn_dropout=best_params["ffn_dropout"], - num_classes=3 - ).to(device) - elif model_choose == 'resnet_like': - input_dim = len(numerical_cols) + len(categorical_cols) - model = ResNetLike( - input_dim=input_dim, - d_main=best_params["d_main"], - d_hidden=best_params["d_hidden"], - n_blocks=best_params["n_blocks"], - dropout_first=best_params["dropout_first"], - dropout_second=best_params["dropout_second"], - num_classes=3 - ).to(device) - elif model_choose == 'deepgbm': - model = DeepGBM( - num_features=len(numerical_cols), - cat_features=[len(X_train_df[col].unique()) for col in categorical_cols], - d_main=best_params["d_main"], - d_hidden=best_params["d_hidden"], - n_blocks=best_params["n_blocks"], - dropout=best_params["dropout"], - num_classes=3 - ).to(device) - else: - raise ValueError(f"Unknown model_choose: {model_choose}") - - # 클래스 가중치 계산 및 손실 함수 설정 (Label Smoothing 적용) - if target == 'multi': - class_weights = compute_class_weight( - class_weight='balanced', - classes=np.unique(y_train), - y=y_train - ) - class_weights_tensor = torch.tensor(class_weights, dtype=torch.float32).to(device) - criterion = nn.CrossEntropyLoss(weight=class_weights_tensor, label_smoothing=0.0) # Label Smoothing 추가 - else: - criterion = nn.BCEWithLogitsLoss() - optimizer = optim.AdamW(model.parameters(), lr=best_params["lr"], weight_decay=best_params["weight_decay"]) - - # 학습률 스케줄러 - scheduler = optim.lr_scheduler.ReduceLROnPlateau(optimizer, mode='max', factor=0.5, patience=3) - - # 학습 설정 - epochs = 200 - patience = 12 - best_fold_csi = 0 - counter = 0 - best_model = None - - for epoch in range(epochs): - model.train() - for x_num_batch, x_cat_batch, y_batch in train_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - - optimizer.zero_grad() - y_pred = model(x_num_batch, x_cat_batch) - loss = criterion(y_pred, y_batch if target == 'multi' else y_batch.float()) - loss.backward() - optimizer.step() - - # Validation 평가 - model.eval() - y_pred_val, y_true_val = [], [] - with torch.no_grad(): - for x_num_batch, x_cat_batch, y_batch in val_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - output = model(x_num_batch, x_cat_batch) - pred = output.argmax(dim=1) if target == 'multi' else (torch.sigmoid(output) >= 0.5).long() - - y_pred_val.extend(pred.cpu().numpy()) - y_true_val.extend(y_batch.cpu().numpy()) - - # CSI 계산 및 스케줄러 업데이트 - val_csi = calculate_csi(y_true_val, y_pred_val) - scheduler.step(val_csi) - - # Early Stopping 체크 - if val_csi > best_fold_csi: - best_fold_csi = val_csi - counter = 0 - best_model = copy.deepcopy(model) - else: - counter += 1 - - if counter >= patience: - print(f" Early stopping at epoch {epoch+1}, Best CSI: {best_fold_csi:.4f}") - break - - if best_model is None: - best_model = model - - scalers.append(scaler) # scaler 저장 (fold 순서대로) - models.append(best_model) - print(f" Fold {fold} 학습 완료 (검증 CSI: {best_fold_csi:.4f})") - - # 모델 저장 경로 설정 - save_dir = f'../save_model/{model_choose}_optima' - os.makedirs(save_dir, exist_ok=True) - - # 파일명 생성 - if data_sample == 'pure': - model_filename = f'{model_choose}_pure_{region}.pkl' - else: - model_filename = f'{model_choose}_{data_sample}_{region}.pkl' - - model_path = f'{save_dir}/{model_filename}' - - # 리스트에 담아 한 번에 저장 - joblib.dump(models, model_path) - print(f"\n모든 모델 저장 완료: {model_path} (총 {len(models)}개 fold)") - - # Scaler 별도 저장 - scaler_save_dir = f'../save_model/{model_choose}_optima/scaler' - os.makedirs(scaler_save_dir, exist_ok=True) - - # 파일명 생성 (모델과 동일한 패턴) - if data_sample == 'pure': - scaler_filename = f'{model_choose}_pure_{region}_scaler.pkl' - else: - scaler_filename = f'{model_choose}_{data_sample}_{region}_scaler.pkl' - - scaler_path = f'{scaler_save_dir}/{scaler_filename}' - joblib.dump(scalers, scaler_path) - print(f"Scaler 저장 완료: {scaler_path} (총 {len(scalers)}개 fold)") - - return model_path diff --git a/Analysis_code/5.optima/lgb_ctgan10000/LGB_ctgan10000_busan.py b/Analysis_code/5.optima/lgb_ctgan10000/LGB_ctgan10000_busan.py deleted file mode 100644 index af4a616acfe854c9456096523f2e2cefbfe6b025..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/lgb_ctgan10000/LGB_ctgan10000_busan.py +++ /dev/null @@ -1,317 +0,0 @@ -import pandas as pd -import numpy as np -import joblib -import os -from warnings import filterwarnings -from sklearn.metrics import confusion_matrix -from lightgbm import LGBMClassifier -from hyperopt import fmin, tpe, Trials, hp - -filterwarnings('ignore') - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 -DEVICE = 'gpu' -OBJECTIVE = 'multiclassova' - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(y_true, y_pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - y_true: 실제 레이블 - y_pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(y_true, y_pred) - - # 혼동 행렬에서 H(Hit), F(False alarm), M(Miss) 추출 - H = cm[0, 0] + cm[1, 1] - F = cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1] - M = cm[0, 2] + cm[1, 2] - - # CSI 계산 - csi = H / (H + F + M + 1e-10) - return csi - - -def csi_metric(y_true, pred_prob): - """LightGBM용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 (shape: [n_samples, n_classes]) - - Returns: - ('CSI', score, higher_better) 튜플 - """ - y_pred_binary = np.argmax(pred_prob, axis=1) - score = calculate_csi(y_true, y_pred_binary) - return 'CSI', score, True - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - - -def split_data(df_sampled, df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_sampled: 샘플링된 데이터프레임 - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: 샘플링된 데이터에서 train_years에 해당하는 데이터 - train_mask = df_sampled['year'].isin(train_years) - X_train = df_sampled.loc[train_mask, df_sampled.columns != 'multi_class'].copy() - y_train = df_sampled.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - # 'year' 컬럼 제거 - X_train = X_train.drop(columns=['year']) - X_val = X_val.drop(columns=['year']) - - return X_train, X_val, y_train, y_val - - -def create_lgb_model(search_space=None, best_params=None): - """LightGBM 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - LGBMClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'device': DEVICE, - 'objective': OBJECTIVE, - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - 'verbose': -1, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'num_leaves': int(search_space['num_leaves']), - 'min_child_weight': int(search_space['min_child_weight']), - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'num_leaves': int(best_params['num_leaves']), - 'min_child_weight': int(best_params['min_child_weight']), - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return LGBMClassifier(**params) - -# 데이터 로딩 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_busan = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/busan_train.csv")) -df_ctgan_busan_1 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/ctgan10000/ctgan10000_1_busan.csv")) -df_ctgan_busan_2 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/ctgan10000/ctgan10000_2_busan.csv")) -df_ctgan_busan_3 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/ctgan10000/ctgan10000_3_busan.csv")) - -# 데이터 전처리 -print("데이터 전처리 중...") -df_ctgan_busan_1 = preprocessing(df_ctgan_busan_1) -df_ctgan_busan_2 = preprocessing(df_ctgan_busan_2) -df_ctgan_busan_3 = preprocessing(df_ctgan_busan_3) -df_busan = preprocessing(df_busan) - -# CTGAN 데이터 리스트 (fold 순서와 일치) -df_ctgan_list = [df_ctgan_busan_1, df_ctgan_busan_2, df_ctgan_busan_3] - -# 하이퍼파라미터 검색 공간 정의 -lgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 15, 1), - 'num_leaves': hp.quniform('num_leaves', 20, 150, 1), # 2^max_depth 보다는 작게 - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - lgb_model = create_lgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for df_ctgan, (train_years, val_year) in zip(df_ctgan_list, FOLD_CONFIGS): - X_train, X_val, y_train, y_val = split_data( - df_ctgan, df_busan, train_years, val_year - ) - - lgb_model.fit( - X_train, y_train, - eval_set=[(X_val, y_val)], - eval_metric=csi_metric - ) - - csi = calculate_csi(y_val, lgb_model.predict(X_val)) - csi_scores.append(csi) - - # 평균 CSI의 음수값 반환 (hyperopt는 최소화를 수행) - return -1 * round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -lgb_best = fmin( - fn=objective_func, - space=lgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) - -# 최적화 결과 분석 및 출력 -print(f"\n최적화 완료. 최적 파라미터: {lgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -import os -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/lgb_ctgan10000_busan_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (df_ctgan, (train_years, val_year)) in enumerate( - zip(df_ctgan_list, FOLD_CONFIGS), start=1 -): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_ctgan, df_busan, train_years, val_year - ) - - lgb_model = create_lgb_model(best_params=lgb_best) - lgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)]) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, lgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(lgb_model) - -# 모델 저장 -print("모델 저장 중...") -model_save_path = os.path.join(base_dir, "save_model/lgb_optima/lgb_ctgan10000_busan.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") - diff --git a/Analysis_code/5.optima/lgb_ctgan10000/LGB_ctgan10000_daegu.py b/Analysis_code/5.optima/lgb_ctgan10000/LGB_ctgan10000_daegu.py deleted file mode 100644 index 185e5f534a94e794a98c52c851c2746372c48dca..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/lgb_ctgan10000/LGB_ctgan10000_daegu.py +++ /dev/null @@ -1,317 +0,0 @@ -import pandas as pd -import numpy as np -import joblib -import os -from warnings import filterwarnings -from sklearn.metrics import confusion_matrix -from lightgbm import LGBMClassifier -from hyperopt import fmin, tpe, Trials, hp - -filterwarnings('ignore') - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 -DEVICE = 'gpu' -OBJECTIVE = 'multiclassova' - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(y_true, y_pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - y_true: 실제 레이블 - y_pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(y_true, y_pred) - - # 혼동 행렬에서 H(Hit), F(False alarm), M(Miss) 추출 - H = cm[0, 0] + cm[1, 1] - F = cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1] - M = cm[0, 2] + cm[1, 2] - - # CSI 계산 - csi = H / (H + F + M + 1e-10) - return csi - - -def csi_metric(y_true, pred_prob): - """LightGBM용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 (shape: [n_samples, n_classes]) - - Returns: - ('CSI', score, higher_better) 튜플 - """ - y_pred_binary = np.argmax(pred_prob, axis=1) - score = calculate_csi(y_true, y_pred_binary) - return 'CSI', score, True - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - - -def split_data(df_sampled, df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_sampled: 샘플링된 데이터프레임 - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: 샘플링된 데이터에서 train_years에 해당하는 데이터 - train_mask = df_sampled['year'].isin(train_years) - X_train = df_sampled.loc[train_mask, df_sampled.columns != 'multi_class'].copy() - y_train = df_sampled.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - # 'year' 컬럼 제거 - X_train = X_train.drop(columns=['year']) - X_val = X_val.drop(columns=['year']) - - return X_train, X_val, y_train, y_val - - -def create_lgb_model(search_space=None, best_params=None): - """LightGBM 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - LGBMClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'device': DEVICE, - 'objective': OBJECTIVE, - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - 'verbose': -1, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'num_leaves': int(search_space['num_leaves']), - 'min_child_weight': int(search_space['min_child_weight']), - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'num_leaves': int(best_params['num_leaves']), - 'min_child_weight': int(best_params['min_child_weight']), - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return LGBMClassifier(**params) - -# 데이터 로딩 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_daegu = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/daegu_train.csv")) -df_ctgan_daegu_1 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/ctgan10000/ctgan10000_1_daegu.csv")) -df_ctgan_daegu_2 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/ctgan10000/ctgan10000_2_daegu.csv")) -df_ctgan_daegu_3 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/ctgan10000/ctgan10000_3_daegu.csv")) - -# 데이터 전처리 -print("데이터 전처리 중...") -df_ctgan_daegu_1 = preprocessing(df_ctgan_daegu_1) -df_ctgan_daegu_2 = preprocessing(df_ctgan_daegu_2) -df_ctgan_daegu_3 = preprocessing(df_ctgan_daegu_3) -df_daegu = preprocessing(df_daegu) - -# CTGAN 데이터 리스트 (fold 순서와 일치) -df_ctgan_list = [df_ctgan_daegu_1, df_ctgan_daegu_2, df_ctgan_daegu_3] - -# 하이퍼파라미터 검색 공간 정의 -lgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 15, 1), - 'num_leaves': hp.quniform('num_leaves', 20, 150, 1), # 2^max_depth 보다는 작게 - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - lgb_model = create_lgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for df_ctgan, (train_years, val_year) in zip(df_ctgan_list, FOLD_CONFIGS): - X_train, X_val, y_train, y_val = split_data( - df_ctgan, df_daegu, train_years, val_year - ) - - lgb_model.fit( - X_train, y_train, - eval_set=[(X_val, y_val)], - eval_metric=csi_metric - ) - - csi = calculate_csi(y_val, lgb_model.predict(X_val)) - csi_scores.append(csi) - - # 평균 CSI의 음수값 반환 (hyperopt는 최소화를 수행) - return -1 * round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -lgb_best = fmin( - fn=objective_func, - space=lgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) - -# 최적화 결과 분석 및 출력 -print(f"\n최적화 완료. 최적 파라미터: {lgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -import os -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/lgb_ctgan10000_daegu_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (df_ctgan, (train_years, val_year)) in enumerate( - zip(df_ctgan_list, FOLD_CONFIGS), start=1 -): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_ctgan, df_daegu, train_years, val_year - ) - - lgb_model = create_lgb_model(best_params=lgb_best) - lgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)]) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, lgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(lgb_model) - -# 모델 저장 -print("모델 저장 중...") -model_save_path = os.path.join(base_dir, "save_model/lgb_optima/lgb_ctgan10000_daegu.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") - diff --git a/Analysis_code/5.optima/lgb_ctgan10000/LGB_ctgan10000_daejeon.py b/Analysis_code/5.optima/lgb_ctgan10000/LGB_ctgan10000_daejeon.py deleted file mode 100644 index b0cbd62d4751c94d7d1268109c55fd63381ac0c5..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/lgb_ctgan10000/LGB_ctgan10000_daejeon.py +++ /dev/null @@ -1,317 +0,0 @@ -import pandas as pd -import numpy as np -import joblib -import os -from warnings import filterwarnings -from sklearn.metrics import confusion_matrix -from lightgbm import LGBMClassifier -from hyperopt import fmin, tpe, Trials, hp - -filterwarnings('ignore') - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 -DEVICE = 'gpu' -OBJECTIVE = 'multiclassova' - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(y_true, y_pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - y_true: 실제 레이블 - y_pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(y_true, y_pred) - - # 혼동 행렬에서 H(Hit), F(False alarm), M(Miss) 추출 - H = cm[0, 0] + cm[1, 1] - F = cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1] - M = cm[0, 2] + cm[1, 2] - - # CSI 계산 - csi = H / (H + F + M + 1e-10) - return csi - - -def csi_metric(y_true, pred_prob): - """LightGBM용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 (shape: [n_samples, n_classes]) - - Returns: - ('CSI', score, higher_better) 튜플 - """ - y_pred_binary = np.argmax(pred_prob, axis=1) - score = calculate_csi(y_true, y_pred_binary) - return 'CSI', score, True - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - - -def split_data(df_sampled, df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_sampled: 샘플링된 데이터프레임 - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: 샘플링된 데이터에서 train_years에 해당하는 데이터 - train_mask = df_sampled['year'].isin(train_years) - X_train = df_sampled.loc[train_mask, df_sampled.columns != 'multi_class'].copy() - y_train = df_sampled.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - # 'year' 컬럼 제거 - X_train = X_train.drop(columns=['year']) - X_val = X_val.drop(columns=['year']) - - return X_train, X_val, y_train, y_val - - -def create_lgb_model(search_space=None, best_params=None): - """LightGBM 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - LGBMClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'device': DEVICE, - 'objective': OBJECTIVE, - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - 'verbose': -1, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'num_leaves': int(search_space['num_leaves']), - 'min_child_weight': int(search_space['min_child_weight']), - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'num_leaves': int(best_params['num_leaves']), - 'min_child_weight': int(best_params['min_child_weight']), - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return LGBMClassifier(**params) - -# 데이터 로딩 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_daejeon = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/daejeon_train.csv")) -df_ctgan_daejeon_1 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/ctgan10000/ctgan10000_1_daejeon.csv")) -df_ctgan_daejeon_2 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/ctgan10000/ctgan10000_2_daejeon.csv")) -df_ctgan_daejeon_3 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/ctgan10000/ctgan10000_3_daejeon.csv")) - -# 데이터 전처리 -print("데이터 전처리 중...") -df_ctgan_daejeon_1 = preprocessing(df_ctgan_daejeon_1) -df_ctgan_daejeon_2 = preprocessing(df_ctgan_daejeon_2) -df_ctgan_daejeon_3 = preprocessing(df_ctgan_daejeon_3) -df_daejeon = preprocessing(df_daejeon) - -# CTGAN 데이터 리스트 (fold 순서와 일치) -df_ctgan_list = [df_ctgan_daejeon_1, df_ctgan_daejeon_2, df_ctgan_daejeon_3] - -# 하이퍼파라미터 검색 공간 정의 -lgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 15, 1), - 'num_leaves': hp.quniform('num_leaves', 20, 150, 1), # 2^max_depth 보다는 작게 - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - lgb_model = create_lgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for df_ctgan, (train_years, val_year) in zip(df_ctgan_list, FOLD_CONFIGS): - X_train, X_val, y_train, y_val = split_data( - df_ctgan, df_daejeon, train_years, val_year - ) - - lgb_model.fit( - X_train, y_train, - eval_set=[(X_val, y_val)], - eval_metric=csi_metric - ) - - csi = calculate_csi(y_val, lgb_model.predict(X_val)) - csi_scores.append(csi) - - # 평균 CSI의 음수값 반환 (hyperopt는 최소화를 수행) - return -1 * round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -lgb_best = fmin( - fn=objective_func, - space=lgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) - -# 최적화 결과 분석 및 출력 -print(f"\n최적화 완료. 최적 파라미터: {lgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -import os -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/lgb_ctgan10000_daejeon_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (df_ctgan, (train_years, val_year)) in enumerate( - zip(df_ctgan_list, FOLD_CONFIGS), start=1 -): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_ctgan, df_daejeon, train_years, val_year - ) - - lgb_model = create_lgb_model(best_params=lgb_best) - lgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)]) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, lgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(lgb_model) - -# 모델 저장 -print("모델 저장 중...") -model_save_path = os.path.join(base_dir, "save_model/lgb_optima/lgb_ctgan10000_daejeon.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") - diff --git a/Analysis_code/5.optima/lgb_ctgan10000/LGB_ctgan10000_gwangju.py b/Analysis_code/5.optima/lgb_ctgan10000/LGB_ctgan10000_gwangju.py deleted file mode 100644 index 650e3f23f52129e13d34e8a46bc1f2a3b00465ab..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/lgb_ctgan10000/LGB_ctgan10000_gwangju.py +++ /dev/null @@ -1,317 +0,0 @@ -import pandas as pd -import numpy as np -import joblib -import os -from warnings import filterwarnings -from sklearn.metrics import confusion_matrix -from lightgbm import LGBMClassifier -from hyperopt import fmin, tpe, Trials, hp - -filterwarnings('ignore') - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 -DEVICE = 'gpu' -OBJECTIVE = 'multiclassova' - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(y_true, y_pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - y_true: 실제 레이블 - y_pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(y_true, y_pred) - - # 혼동 행렬에서 H(Hit), F(False alarm), M(Miss) 추출 - H = cm[0, 0] + cm[1, 1] - F = cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1] - M = cm[0, 2] + cm[1, 2] - - # CSI 계산 - csi = H / (H + F + M + 1e-10) - return csi - - -def csi_metric(y_true, pred_prob): - """LightGBM용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 (shape: [n_samples, n_classes]) - - Returns: - ('CSI', score, higher_better) 튜플 - """ - y_pred_binary = np.argmax(pred_prob, axis=1) - score = calculate_csi(y_true, y_pred_binary) - return 'CSI', score, True - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - - -def split_data(df_sampled, df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_sampled: 샘플링된 데이터프레임 - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: 샘플링된 데이터에서 train_years에 해당하는 데이터 - train_mask = df_sampled['year'].isin(train_years) - X_train = df_sampled.loc[train_mask, df_sampled.columns != 'multi_class'].copy() - y_train = df_sampled.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - # 'year' 컬럼 제거 - X_train = X_train.drop(columns=['year']) - X_val = X_val.drop(columns=['year']) - - return X_train, X_val, y_train, y_val - - -def create_lgb_model(search_space=None, best_params=None): - """LightGBM 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - LGBMClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'device': DEVICE, - 'objective': OBJECTIVE, - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - 'verbose': -1, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'num_leaves': int(search_space['num_leaves']), - 'min_child_weight': int(search_space['min_child_weight']), - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'num_leaves': int(best_params['num_leaves']), - 'min_child_weight': int(best_params['min_child_weight']), - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return LGBMClassifier(**params) - -# 데이터 로딩 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_gwangju = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/gwangju_train.csv")) -df_ctgan_gwangju_1 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/ctgan10000/ctgan10000_1_gwangju.csv")) -df_ctgan_gwangju_2 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/ctgan10000/ctgan10000_2_gwangju.csv")) -df_ctgan_gwangju_3 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/ctgan10000/ctgan10000_3_gwangju.csv")) - -# 데이터 전처리 -print("데이터 전처리 중...") -df_ctgan_gwangju_1 = preprocessing(df_ctgan_gwangju_1) -df_ctgan_gwangju_2 = preprocessing(df_ctgan_gwangju_2) -df_ctgan_gwangju_3 = preprocessing(df_ctgan_gwangju_3) -df_gwangju = preprocessing(df_gwangju) - -# CTGAN 데이터 리스트 (fold 순서와 일치) -df_ctgan_list = [df_ctgan_gwangju_1, df_ctgan_gwangju_2, df_ctgan_gwangju_3] - -# 하이퍼파라미터 검색 공간 정의 -lgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 15, 1), - 'num_leaves': hp.quniform('num_leaves', 20, 150, 1), # 2^max_depth 보다는 작게 - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - lgb_model = create_lgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for df_ctgan, (train_years, val_year) in zip(df_ctgan_list, FOLD_CONFIGS): - X_train, X_val, y_train, y_val = split_data( - df_ctgan, df_gwangju, train_years, val_year - ) - - lgb_model.fit( - X_train, y_train, - eval_set=[(X_val, y_val)], - eval_metric=csi_metric - ) - - csi = calculate_csi(y_val, lgb_model.predict(X_val)) - csi_scores.append(csi) - - # 평균 CSI의 음수값 반환 (hyperopt는 최소화를 수행) - return -1 * round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -lgb_best = fmin( - fn=objective_func, - space=lgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) - -# 최적화 결과 분석 및 출력 -print(f"\n최적화 완료. 최적 파라미터: {lgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -import os -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/lgb_ctgan10000_gwangju_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (df_ctgan, (train_years, val_year)) in enumerate( - zip(df_ctgan_list, FOLD_CONFIGS), start=1 -): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_ctgan, df_gwangju, train_years, val_year - ) - - lgb_model = create_lgb_model(best_params=lgb_best) - lgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)]) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, lgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(lgb_model) - -# 모델 저장 -print("모델 저장 중...") -model_save_path = os.path.join(base_dir, "save_model/lgb_optima/lgb_ctgan10000_gwangju.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") - diff --git a/Analysis_code/5.optima/lgb_ctgan10000/LGB_ctgan10000_incheon.py b/Analysis_code/5.optima/lgb_ctgan10000/LGB_ctgan10000_incheon.py deleted file mode 100644 index fcc0450aece8e03959f6980b4bd3ff82510d3cfc..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/lgb_ctgan10000/LGB_ctgan10000_incheon.py +++ /dev/null @@ -1,317 +0,0 @@ -import pandas as pd -import numpy as np -import joblib -import os -from warnings import filterwarnings -from sklearn.metrics import confusion_matrix -from lightgbm import LGBMClassifier -from hyperopt import fmin, tpe, Trials, hp - -filterwarnings('ignore') - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 -DEVICE = 'gpu' -OBJECTIVE = 'multiclassova' - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(y_true, y_pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - y_true: 실제 레이블 - y_pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(y_true, y_pred) - - # 혼동 행렬에서 H(Hit), F(False alarm), M(Miss) 추출 - H = cm[0, 0] + cm[1, 1] - F = cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1] - M = cm[0, 2] + cm[1, 2] - - # CSI 계산 - csi = H / (H + F + M + 1e-10) - return csi - - -def csi_metric(y_true, pred_prob): - """LightGBM용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 (shape: [n_samples, n_classes]) - - Returns: - ('CSI', score, higher_better) 튜플 - """ - y_pred_binary = np.argmax(pred_prob, axis=1) - score = calculate_csi(y_true, y_pred_binary) - return 'CSI', score, True - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - - -def split_data(df_sampled, df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_sampled: 샘플링된 데이터프레임 - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: 샘플링된 데이터에서 train_years에 해당하는 데이터 - train_mask = df_sampled['year'].isin(train_years) - X_train = df_sampled.loc[train_mask, df_sampled.columns != 'multi_class'].copy() - y_train = df_sampled.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - # 'year' 컬럼 제거 - X_train = X_train.drop(columns=['year']) - X_val = X_val.drop(columns=['year']) - - return X_train, X_val, y_train, y_val - - -def create_lgb_model(search_space=None, best_params=None): - """LightGBM 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - LGBMClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'device': DEVICE, - 'objective': OBJECTIVE, - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - 'verbose': -1, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'num_leaves': int(search_space['num_leaves']), - 'min_child_weight': int(search_space['min_child_weight']), - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'num_leaves': int(best_params['num_leaves']), - 'min_child_weight': int(best_params['min_child_weight']), - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return LGBMClassifier(**params) - -# 데이터 로딩 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_incheon = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/incheon_train.csv")) -df_ctgan_incheon_1 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/ctgan10000/ctgan10000_1_incheon.csv")) -df_ctgan_incheon_2 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/ctgan10000/ctgan10000_2_incheon.csv")) -df_ctgan_incheon_3 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/ctgan10000/ctgan10000_3_incheon.csv")) - -# 데이터 전처리 -print("데이터 전처리 중...") -df_ctgan_incheon_1 = preprocessing(df_ctgan_incheon_1) -df_ctgan_incheon_2 = preprocessing(df_ctgan_incheon_2) -df_ctgan_incheon_3 = preprocessing(df_ctgan_incheon_3) -df_incheon = preprocessing(df_incheon) - -# CTGAN 데이터 리스트 (fold 순서와 일치) -df_ctgan_list = [df_ctgan_incheon_1, df_ctgan_incheon_2, df_ctgan_incheon_3] - -# 하이퍼파라미터 검색 공간 정의 -lgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 15, 1), - 'num_leaves': hp.quniform('num_leaves', 20, 150, 1), # 2^max_depth 보다는 작게 - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - lgb_model = create_lgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for df_ctgan, (train_years, val_year) in zip(df_ctgan_list, FOLD_CONFIGS): - X_train, X_val, y_train, y_val = split_data( - df_ctgan, df_incheon, train_years, val_year - ) - - lgb_model.fit( - X_train, y_train, - eval_set=[(X_val, y_val)], - eval_metric=csi_metric - ) - - csi = calculate_csi(y_val, lgb_model.predict(X_val)) - csi_scores.append(csi) - - # 평균 CSI의 음수값 반환 (hyperopt는 최소화를 수행) - return -1 * round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -lgb_best = fmin( - fn=objective_func, - space=lgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) - -# 최적화 결과 분석 및 출력 -print(f"\n최적화 완료. 최적 파라미터: {lgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -import os -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/lgb_ctgan10000_incheon_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (df_ctgan, (train_years, val_year)) in enumerate( - zip(df_ctgan_list, FOLD_CONFIGS), start=1 -): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_ctgan, df_incheon, train_years, val_year - ) - - lgb_model = create_lgb_model(best_params=lgb_best) - lgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)]) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, lgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(lgb_model) - -# 모델 저장 -print("모델 저장 중...") -model_save_path = os.path.join(base_dir, "save_model/lgb_optima/lgb_ctgan10000_incheon.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") - diff --git a/Analysis_code/5.optima/lgb_ctgan10000/LGB_ctgan10000_seoul.py b/Analysis_code/5.optima/lgb_ctgan10000/LGB_ctgan10000_seoul.py deleted file mode 100644 index 2af44f1c108b052821920b226c8772a9ef792f93..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/lgb_ctgan10000/LGB_ctgan10000_seoul.py +++ /dev/null @@ -1,317 +0,0 @@ -import pandas as pd -import numpy as np -import joblib -import os -from warnings import filterwarnings -from sklearn.metrics import confusion_matrix -from lightgbm import LGBMClassifier -from hyperopt import fmin, tpe, Trials, hp - -filterwarnings('ignore') - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 -DEVICE = 'gpu' -OBJECTIVE = 'multiclassova' - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(y_true, y_pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - y_true: 실제 레이블 - y_pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(y_true, y_pred) - - # 혼동 행렬에서 H(Hit), F(False alarm), M(Miss) 추출 - H = cm[0, 0] + cm[1, 1] - F = cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1] - M = cm[0, 2] + cm[1, 2] - - # CSI 계산 - csi = H / (H + F + M + 1e-10) - return csi - - -def csi_metric(y_true, pred_prob): - """LightGBM용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 (shape: [n_samples, n_classes]) - - Returns: - ('CSI', score, higher_better) 튜플 - """ - y_pred_binary = np.argmax(pred_prob, axis=1) - score = calculate_csi(y_true, y_pred_binary) - return 'CSI', score, True - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - - -def split_data(df_sampled, df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_sampled: 샘플링된 데이터프레임 - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: 샘플링된 데이터에서 train_years에 해당하는 데이터 - train_mask = df_sampled['year'].isin(train_years) - X_train = df_sampled.loc[train_mask, df_sampled.columns != 'multi_class'].copy() - y_train = df_sampled.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - # 'year' 컬럼 제거 - X_train = X_train.drop(columns=['year']) - X_val = X_val.drop(columns=['year']) - - return X_train, X_val, y_train, y_val - - -def create_lgb_model(search_space=None, best_params=None): - """LightGBM 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - LGBMClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'device': DEVICE, - 'objective': OBJECTIVE, - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - 'verbose': -1, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'num_leaves': int(search_space['num_leaves']), - 'min_child_weight': int(search_space['min_child_weight']), - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'num_leaves': int(best_params['num_leaves']), - 'min_child_weight': int(best_params['min_child_weight']), - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return LGBMClassifier(**params) - -# 데이터 로딩 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_seoul = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/seoul_train.csv")) -df_ctgan_seoul_1 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/ctgan10000/ctgan10000_1_seoul.csv")) -df_ctgan_seoul_2 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/ctgan10000/ctgan10000_2_seoul.csv")) -df_ctgan_seoul_3 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/ctgan10000/ctgan10000_3_seoul.csv")) - -# 데이터 전처리 -print("데이터 전처리 중...") -df_ctgan_seoul_1 = preprocessing(df_ctgan_seoul_1) -df_ctgan_seoul_2 = preprocessing(df_ctgan_seoul_2) -df_ctgan_seoul_3 = preprocessing(df_ctgan_seoul_3) -df_seoul = preprocessing(df_seoul) - -# CTGAN 데이터 리스트 (fold 순서와 일치) -df_ctgan_list = [df_ctgan_seoul_1, df_ctgan_seoul_2, df_ctgan_seoul_3] - -# 하이퍼파라미터 검색 공간 정의 -lgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 15, 1), - 'num_leaves': hp.quniform('num_leaves', 20, 150, 1), # 2^max_depth 보다는 작게 - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - lgb_model = create_lgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for df_ctgan, (train_years, val_year) in zip(df_ctgan_list, FOLD_CONFIGS): - X_train, X_val, y_train, y_val = split_data( - df_ctgan, df_seoul, train_years, val_year - ) - - lgb_model.fit( - X_train, y_train, - eval_set=[(X_val, y_val)], - eval_metric=csi_metric - ) - - csi = calculate_csi(y_val, lgb_model.predict(X_val)) - csi_scores.append(csi) - - # 평균 CSI의 음수값 반환 (hyperopt는 최소화를 수행) - return -1 * round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -lgb_best = fmin( - fn=objective_func, - space=lgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) - -# 최적화 결과 분석 및 출력 -print(f"\n최적화 완료. 최적 파라미터: {lgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -import os -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/lgb_ctgan10000_seoul_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (df_ctgan, (train_years, val_year)) in enumerate( - zip(df_ctgan_list, FOLD_CONFIGS), start=1 -): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_ctgan, df_seoul, train_years, val_year - ) - - lgb_model = create_lgb_model(best_params=lgb_best) - lgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)]) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, lgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(lgb_model) - -# 모델 저장 -print("모델 저장 중...") -model_save_path = os.path.join(base_dir, "save_model/lgb_optima/lgb_ctgan10000_seoul.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") - diff --git a/Analysis_code/5.optima/lgb_pure/LGB_pure_busan.py b/Analysis_code/5.optima/lgb_pure/LGB_pure_busan.py deleted file mode 100644 index 0867072990c60cfc605569f0840f5f4a35f70a59..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/lgb_pure/LGB_pure_busan.py +++ /dev/null @@ -1,359 +0,0 @@ - -import pandas as pd -import numpy as np -import joblib -import os -from warnings import filterwarnings -from sklearn.metrics import confusion_matrix -from lightgbm import LGBMClassifier -from hyperopt import fmin, tpe, Trials, hp - -filterwarnings('ignore') - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 -DEVICE = 'gpu' -OBJECTIVE = 'multiclassova' - -# GPU 사용 가능 여부 캐시 (한 번만 확인) -_GPU_AVAILABLE = None - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(y_true, y_pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - y_true: 실제 레이블 - y_pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(y_true, y_pred) - - # 혼동 행렬에서 H(Hit), F(False alarm), M(Miss) 추출 - H = cm[0, 0] + cm[1, 1] - F = cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1] - M = cm[0, 2] + cm[1, 2] - - # CSI 계산 - csi = H / (H + F + M + 1e-10) - return csi - - -def csi_metric(y_true, pred_prob): - """LightGBM용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 (shape: [n_samples, n_classes]) - - Returns: - ('CSI', score, higher_better) 튜플 - """ - y_pred_binary = np.argmax(pred_prob, axis=1) - score = calculate_csi(y_true, y_pred_binary) - return 'CSI', score, True - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - - -def split_data_pure(df_original, train_years, val_year): - """Pure 데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: 원본 데이터에서 train_years에 해당하는 데이터 - train_mask = df_original['year'].isin(train_years) - X_train = df_original.loc[train_mask, df_original.columns != 'multi_class'].copy() - y_train = df_original.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - # 'year' 컬럼 제거 - X_train = X_train.drop(columns=['year']) - X_val = X_val.drop(columns=['year']) - - return X_train, X_val, y_train, y_val - - -def check_gpu_available(): - """OpenCL GPU 디바이스가 사용 가능한지 확인합니다 (캐시된 결과 사용). - - Returns: - bool: GPU 사용 가능 여부 - """ - global _GPU_AVAILABLE - - # 캐시된 결과가 있으면 재사용 - if _GPU_AVAILABLE is not None: - return _GPU_AVAILABLE - - if DEVICE != 'gpu': - _GPU_AVAILABLE = False - return False - - # LightGBM이 GPU를 사용할 수 있는지 테스트 - try: - import lightgbm as lgb - import numpy as np - # 작은 테스트 데이터셋으로 GPU 사용 가능 여부 확인 - test_X = np.random.rand(10, 5) - test_y = np.random.randint(0, 3, 10) - test_model = lgb.LGBMClassifier(device='gpu', n_estimators=1, verbose=-1) - test_model.fit(test_X, test_y) - _GPU_AVAILABLE = True - return True - except Exception as e: - _GPU_AVAILABLE = False - return False - -def create_lgb_model(search_space=None, best_params=None): - """LightGBM 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - LGBMClassifier 인스턴스 - """ - # GPU 사용 가능 여부 확인 및 자동 폴백 - actual_device = DEVICE - if DEVICE == 'gpu': - if not check_gpu_available(): - actual_device = 'cpu' - print(f"⚠️ GPU 디바이스를 찾을 수 없습니다. CPU 모드로 전환합니다.") - - base_params = { - 'n_estimators': N_ESTIMATORS, - 'device': actual_device, - 'objective': OBJECTIVE, - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - 'verbose': -1, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'num_leaves': int(search_space['num_leaves']), - 'min_child_weight': int(search_space['min_child_weight']), - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'num_leaves': int(best_params['num_leaves']), - 'min_child_weight': int(best_params['min_child_weight']), - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - model = LGBMClassifier(**params) - return model - -# 데이터 로딩 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_busan = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/busan_train.csv")) - -# 데이터 전처리 -print("데이터 전처리 중...") -df_busan = preprocessing(df_busan) - -# 하이퍼파라미터 검색 공간 정의 -lgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 15, 1), - 'num_leaves': hp.quniform('num_leaves', 20, 150, 1), # 2^max_depth 보다는 작게 - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - lgb_model = create_lgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for fold_idx, (train_years, val_year) in enumerate(FOLD_CONFIGS): - X_train, X_val, y_train, y_val = split_data_pure( - df_busan, train_years, val_year - ) - - lgb_model.fit( - X_train, y_train, - eval_set=[(X_val, y_val)], - eval_metric=csi_metric - ) - - csi = calculate_csi(y_val, lgb_model.predict(X_val)) - csi_scores.append(csi) - - result = -1 * round(np.mean(csi_scores), 4) - return result - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -lgb_best = fmin( - fn=objective_func, - space=lgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) - -# 최적화 결과 분석 및 출력 -print(f"\n최적화 완료. 최적 파라미터: {lgb_best}") - -try: - # Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) - best_loss = trials.best_trial['result']['loss'] - best_csi = -best_loss - print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - - # 모든 trial의 loss 값 추출 - losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] - csi_scores = [-loss for loss in losses] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(trials.trials)}") - print(f" - 성공한 시도: {len(losses)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Trials 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - trials_path = os.path.join(base_dir, "optimization_history/lgb_pure_busan_trials.pkl") - joblib.dump(trials, trials_path) - print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (train_years, val_year) in enumerate(FOLD_CONFIGS, start=1): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data_pure( - df_busan, train_years, val_year - ) - - lgb_model = create_lgb_model(best_params=lgb_best) - lgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)]) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, lgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(lgb_model) - -# 모델 저장 -print("모델 저장 중...") -model_save_path = os.path.join(base_dir, "save_model/lgb_optima/lgb_pure_busan.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/lgb_pure/LGB_pure_daegu.py b/Analysis_code/5.optima/lgb_pure/LGB_pure_daegu.py deleted file mode 100644 index 85f7c24d7c94c5cd46bde577772b5884c64b3b0c..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/lgb_pure/LGB_pure_daegu.py +++ /dev/null @@ -1,307 +0,0 @@ - -import pandas as pd -import os -import numpy as np -import joblib -from warnings import filterwarnings -from sklearn.metrics import confusion_matrix -from lightgbm import LGBMClassifier -from hyperopt import fmin, tpe, Trials, hp - -filterwarnings('ignore') - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 -DEVICE = 'gpu' -OBJECTIVE = 'multiclassova' - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(y_true, y_pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - y_true: 실제 레이블 - y_pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(y_true, y_pred) - - # 혼동 행렬에서 H(Hit), F(False alarm), M(Miss) 추출 - H = cm[0, 0] + cm[1, 1] - F = cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1] - M = cm[0, 2] + cm[1, 2] - - # CSI 계산 - csi = H / (H + F + M + 1e-10) - return csi - - -def csi_metric(y_true, pred_prob): - """LightGBM용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 (shape: [n_samples, n_classes]) - - Returns: - ('CSI', score, higher_better) 튜플 - """ - y_pred_binary = np.argmax(pred_prob, axis=1) - score = calculate_csi(y_true, y_pred_binary) - return 'CSI', score, True - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - - -def split_data_pure(df_original, train_years, val_year): - """Pure 데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: 원본 데이터에서 train_years에 해당하는 데이터 - train_mask = df_original['year'].isin(train_years) - X_train = df_original.loc[train_mask, df_original.columns != 'multi_class'].copy() - y_train = df_original.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - # 'year' 컬럼 제거 - X_train = X_train.drop(columns=['year']) - X_val = X_val.drop(columns=['year']) - - return X_train, X_val, y_train, y_val - - -def create_lgb_model(search_space=None, best_params=None): - """LightGBM 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - LGBMClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'device': DEVICE, - 'objective': OBJECTIVE, - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - 'verbose': -1, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'num_leaves': int(search_space['num_leaves']), - 'min_child_weight': int(search_space['min_child_weight']), - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'num_leaves': int(best_params['num_leaves']), - 'min_child_weight': int(best_params['min_child_weight']), - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return LGBMClassifier(**params) - -# 데이터 로딩 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_daegu = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/daegu_train.csv")) - -# 데이터 전처리 -print("데이터 전처리 중...") -df_daegu = preprocessing(df_daegu) - -# 하이퍼파라미터 검색 공간 정의 -lgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 15, 1), - 'num_leaves': hp.quniform('num_leaves', 20, 150, 1), # 2^max_depth 보다는 작게 - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - lgb_model = create_lgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for train_years, val_year in FOLD_CONFIGS: - X_train, X_val, y_train, y_val = split_data_pure( - df_daegu, train_years, val_year - ) - - lgb_model.fit( - X_train, y_train, - eval_set=[(X_val, y_val)], - eval_metric=csi_metric - ) - - csi = calculate_csi(y_val, lgb_model.predict(X_val)) - csi_scores.append(csi) - - # 평균 CSI의 음수값 반환 (hyperopt는 최소화를 수행) - return -1 * round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -lgb_best = fmin( - fn=objective_func, - space=lgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) - -# 최적화 결과 분석 및 출력 -print(f"\n최적화 완료. 최적 파라미터: {lgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/lgb_pure_daegu_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (train_years, val_year) in enumerate(FOLD_CONFIGS, start=1): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data_pure( - df_daegu, train_years, val_year - ) - - lgb_model = create_lgb_model(best_params=lgb_best) - lgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)]) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, lgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(lgb_model) - -# 모델 저장 -print("모델 저장 중...") -model_save_path = os.path.join(base_dir, "save_model/lgb_optima/lgb_pure_daegu.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") - -import sys -sys.exit(0) diff --git a/Analysis_code/5.optima/lgb_pure/LGB_pure_daejeon.py b/Analysis_code/5.optima/lgb_pure/LGB_pure_daejeon.py deleted file mode 100644 index 495f7f47cc99b9256e47d222bd6eeb0e535bc63a..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/lgb_pure/LGB_pure_daejeon.py +++ /dev/null @@ -1,307 +0,0 @@ - -import pandas as pd -import os -import numpy as np -import joblib -from warnings import filterwarnings -from sklearn.metrics import confusion_matrix -from lightgbm import LGBMClassifier -from hyperopt import fmin, tpe, Trials, hp - -filterwarnings('ignore') - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 -DEVICE = 'gpu' -OBJECTIVE = 'multiclassova' - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(y_true, y_pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - y_true: 실제 레이블 - y_pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(y_true, y_pred) - - # 혼동 행렬에서 H(Hit), F(False alarm), M(Miss) 추출 - H = cm[0, 0] + cm[1, 1] - F = cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1] - M = cm[0, 2] + cm[1, 2] - - # CSI 계산 - csi = H / (H + F + M + 1e-10) - return csi - - -def csi_metric(y_true, pred_prob): - """LightGBM용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 (shape: [n_samples, n_classes]) - - Returns: - ('CSI', score, higher_better) 튜플 - """ - y_pred_binary = np.argmax(pred_prob, axis=1) - score = calculate_csi(y_true, y_pred_binary) - return 'CSI', score, True - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - - -def split_data_pure(df_original, train_years, val_year): - """Pure 데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: 원본 데이터에서 train_years에 해당하는 데이터 - train_mask = df_original['year'].isin(train_years) - X_train = df_original.loc[train_mask, df_original.columns != 'multi_class'].copy() - y_train = df_original.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - # 'year' 컬럼 제거 - X_train = X_train.drop(columns=['year']) - X_val = X_val.drop(columns=['year']) - - return X_train, X_val, y_train, y_val - - -def create_lgb_model(search_space=None, best_params=None): - """LightGBM 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - LGBMClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'device': DEVICE, - 'objective': OBJECTIVE, - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - 'verbose': -1, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'num_leaves': int(search_space['num_leaves']), - 'min_child_weight': int(search_space['min_child_weight']), - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'num_leaves': int(best_params['num_leaves']), - 'min_child_weight': int(best_params['min_child_weight']), - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return LGBMClassifier(**params) - -# 데이터 로딩 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_daejeon = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/daejeon_train.csv")) - -# 데이터 전처리 -print("데이터 전처리 중...") -df_daejeon = preprocessing(df_daejeon) - -# 하이퍼파라미터 검색 공간 정의 -lgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 15, 1), - 'num_leaves': hp.quniform('num_leaves', 20, 150, 1), # 2^max_depth 보다는 작게 - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - lgb_model = create_lgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for train_years, val_year in FOLD_CONFIGS: - X_train, X_val, y_train, y_val = split_data_pure( - df_daejeon, train_years, val_year - ) - - lgb_model.fit( - X_train, y_train, - eval_set=[(X_val, y_val)], - eval_metric=csi_metric - ) - - csi = calculate_csi(y_val, lgb_model.predict(X_val)) - csi_scores.append(csi) - - # 평균 CSI의 음수값 반환 (hyperopt는 최소화를 수행) - return -1 * round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -lgb_best = fmin( - fn=objective_func, - space=lgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) - -# 최적화 결과 분석 및 출력 -print(f"\n최적화 완료. 최적 파라미터: {lgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/lgb_pure_daejeon_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (train_years, val_year) in enumerate(FOLD_CONFIGS, start=1): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data_pure( - df_daejeon, train_years, val_year - ) - - lgb_model = create_lgb_model(best_params=lgb_best) - lgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)]) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, lgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(lgb_model) - -# 모델 저장 -print("모델 저장 중...") -model_save_path = os.path.join(base_dir, "save_model/lgb_optima/lgb_pure_daejeon.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") - -import sys -sys.exit(0) diff --git a/Analysis_code/5.optima/lgb_pure/LGB_pure_gwangju.py b/Analysis_code/5.optima/lgb_pure/LGB_pure_gwangju.py deleted file mode 100644 index 6827f82cba339bf23d71d1eacbc01dd01bfd1fd4..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/lgb_pure/LGB_pure_gwangju.py +++ /dev/null @@ -1,307 +0,0 @@ - -import pandas as pd -import os -import numpy as np -import joblib -from warnings import filterwarnings -from sklearn.metrics import confusion_matrix -from lightgbm import LGBMClassifier -from hyperopt import fmin, tpe, Trials, hp - -filterwarnings('ignore') - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 -DEVICE = 'gpu' -OBJECTIVE = 'multiclassova' - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(y_true, y_pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - y_true: 실제 레이블 - y_pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(y_true, y_pred) - - # 혼동 행렬에서 H(Hit), F(False alarm), M(Miss) 추출 - H = cm[0, 0] + cm[1, 1] - F = cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1] - M = cm[0, 2] + cm[1, 2] - - # CSI 계산 - csi = H / (H + F + M + 1e-10) - return csi - - -def csi_metric(y_true, pred_prob): - """LightGBM용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 (shape: [n_samples, n_classes]) - - Returns: - ('CSI', score, higher_better) 튜플 - """ - y_pred_binary = np.argmax(pred_prob, axis=1) - score = calculate_csi(y_true, y_pred_binary) - return 'CSI', score, True - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - - -def split_data_pure(df_original, train_years, val_year): - """Pure 데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: 원본 데이터에서 train_years에 해당하는 데이터 - train_mask = df_original['year'].isin(train_years) - X_train = df_original.loc[train_mask, df_original.columns != 'multi_class'].copy() - y_train = df_original.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - # 'year' 컬럼 제거 - X_train = X_train.drop(columns=['year']) - X_val = X_val.drop(columns=['year']) - - return X_train, X_val, y_train, y_val - - -def create_lgb_model(search_space=None, best_params=None): - """LightGBM 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - LGBMClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'device': DEVICE, - 'objective': OBJECTIVE, - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - 'verbose': -1, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'num_leaves': int(search_space['num_leaves']), - 'min_child_weight': int(search_space['min_child_weight']), - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'num_leaves': int(best_params['num_leaves']), - 'min_child_weight': int(best_params['min_child_weight']), - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return LGBMClassifier(**params) - -# 데이터 로딩 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_gwangju = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/gwangju_train.csv")) - -# 데이터 전처리 -print("데이터 전처리 중...") -df_gwangju = preprocessing(df_gwangju) - -# 하이퍼파라미터 검색 공간 정의 -lgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 15, 1), - 'num_leaves': hp.quniform('num_leaves', 20, 150, 1), # 2^max_depth 보다는 작게 - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - lgb_model = create_lgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for train_years, val_year in FOLD_CONFIGS: - X_train, X_val, y_train, y_val = split_data_pure( - df_gwangju, train_years, val_year - ) - - lgb_model.fit( - X_train, y_train, - eval_set=[(X_val, y_val)], - eval_metric=csi_metric - ) - - csi = calculate_csi(y_val, lgb_model.predict(X_val)) - csi_scores.append(csi) - - # 평균 CSI의 음수값 반환 (hyperopt는 최소화를 수행) - return -1 * round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -lgb_best = fmin( - fn=objective_func, - space=lgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) - -# 최적화 결과 분석 및 출력 -print(f"\n최적화 완료. 최적 파라미터: {lgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/lgb_pure_gwangju_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (train_years, val_year) in enumerate(FOLD_CONFIGS, start=1): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data_pure( - df_gwangju, train_years, val_year - ) - - lgb_model = create_lgb_model(best_params=lgb_best) - lgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)]) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, lgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(lgb_model) - -# 모델 저장 -print("모델 저장 중...") -model_save_path = os.path.join(base_dir, "save_model/lgb_optima/lgb_pure_gwangju.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") - -import sys -sys.exit(0) diff --git a/Analysis_code/5.optima/lgb_pure/LGB_pure_incheon.py b/Analysis_code/5.optima/lgb_pure/LGB_pure_incheon.py deleted file mode 100644 index 80972fdf2126daedce421aaef7dc513bbd569f26..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/lgb_pure/LGB_pure_incheon.py +++ /dev/null @@ -1,307 +0,0 @@ - -import pandas as pd -import os -import numpy as np -import joblib -from warnings import filterwarnings -from sklearn.metrics import confusion_matrix -from lightgbm import LGBMClassifier -from hyperopt import fmin, tpe, Trials, hp - -filterwarnings('ignore') - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 -DEVICE = 'gpu' -OBJECTIVE = 'multiclassova' - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(y_true, y_pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - y_true: 실제 레이블 - y_pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(y_true, y_pred) - - # 혼동 행렬에서 H(Hit), F(False alarm), M(Miss) 추출 - H = cm[0, 0] + cm[1, 1] - F = cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1] - M = cm[0, 2] + cm[1, 2] - - # CSI 계산 - csi = H / (H + F + M + 1e-10) - return csi - - -def csi_metric(y_true, pred_prob): - """LightGBM용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 (shape: [n_samples, n_classes]) - - Returns: - ('CSI', score, higher_better) 튜플 - """ - y_pred_binary = np.argmax(pred_prob, axis=1) - score = calculate_csi(y_true, y_pred_binary) - return 'CSI', score, True - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - - -def split_data_pure(df_original, train_years, val_year): - """Pure 데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: 원본 데이터에서 train_years에 해당하는 데이터 - train_mask = df_original['year'].isin(train_years) - X_train = df_original.loc[train_mask, df_original.columns != 'multi_class'].copy() - y_train = df_original.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - # 'year' 컬럼 제거 - X_train = X_train.drop(columns=['year']) - X_val = X_val.drop(columns=['year']) - - return X_train, X_val, y_train, y_val - - -def create_lgb_model(search_space=None, best_params=None): - """LightGBM 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - LGBMClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'device': DEVICE, - 'objective': OBJECTIVE, - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - 'verbose': -1, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'num_leaves': int(search_space['num_leaves']), - 'min_child_weight': int(search_space['min_child_weight']), - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'num_leaves': int(best_params['num_leaves']), - 'min_child_weight': int(best_params['min_child_weight']), - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return LGBMClassifier(**params) - -# 데이터 로딩 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_incheon = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/incheon_train.csv")) - -# 데이터 전처리 -print("데이터 전처리 중...") -df_incheon = preprocessing(df_incheon) - -# 하이퍼파라미터 검색 공간 정의 -lgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 15, 1), - 'num_leaves': hp.quniform('num_leaves', 20, 150, 1), # 2^max_depth 보다는 작게 - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - lgb_model = create_lgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for train_years, val_year in FOLD_CONFIGS: - X_train, X_val, y_train, y_val = split_data_pure( - df_incheon, train_years, val_year - ) - - lgb_model.fit( - X_train, y_train, - eval_set=[(X_val, y_val)], - eval_metric=csi_metric - ) - - csi = calculate_csi(y_val, lgb_model.predict(X_val)) - csi_scores.append(csi) - - # 평균 CSI의 음수값 반환 (hyperopt는 최소화를 수행) - return -1 * round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -lgb_best = fmin( - fn=objective_func, - space=lgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) - -# 최적화 결과 분석 및 출력 -print(f"\n최적화 완료. 최적 파라미터: {lgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/lgb_pure_incheon_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (train_years, val_year) in enumerate(FOLD_CONFIGS, start=1): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data_pure( - df_incheon, train_years, val_year - ) - - lgb_model = create_lgb_model(best_params=lgb_best) - lgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)]) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, lgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(lgb_model) - -# 모델 저장 -print("모델 저장 중...") -model_save_path = os.path.join(base_dir, "save_model/lgb_optima/lgb_pure_incheon.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") - -import sys -sys.exit(0) diff --git a/Analysis_code/5.optima/lgb_pure/LGB_pure_seoul.py b/Analysis_code/5.optima/lgb_pure/LGB_pure_seoul.py deleted file mode 100644 index e5dbc2bd887f77170c6c4a205d204f52b6469967..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/lgb_pure/LGB_pure_seoul.py +++ /dev/null @@ -1,307 +0,0 @@ - -import pandas as pd -import os -import numpy as np -import joblib -from warnings import filterwarnings -from sklearn.metrics import confusion_matrix -from lightgbm import LGBMClassifier -from hyperopt import fmin, tpe, Trials, hp - -filterwarnings('ignore') - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 -DEVICE = 'gpu' -OBJECTIVE = 'multiclassova' - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(y_true, y_pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - y_true: 실제 레이블 - y_pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(y_true, y_pred) - - # 혼동 행렬에서 H(Hit), F(False alarm), M(Miss) 추출 - H = cm[0, 0] + cm[1, 1] - F = cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1] - M = cm[0, 2] + cm[1, 2] - - # CSI 계산 - csi = H / (H + F + M + 1e-10) - return csi - - -def csi_metric(y_true, pred_prob): - """LightGBM용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 (shape: [n_samples, n_classes]) - - Returns: - ('CSI', score, higher_better) 튜플 - """ - y_pred_binary = np.argmax(pred_prob, axis=1) - score = calculate_csi(y_true, y_pred_binary) - return 'CSI', score, True - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - - -def split_data_pure(df_original, train_years, val_year): - """Pure 데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: 원본 데이터에서 train_years에 해당하는 데이터 - train_mask = df_original['year'].isin(train_years) - X_train = df_original.loc[train_mask, df_original.columns != 'multi_class'].copy() - y_train = df_original.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - # 'year' 컬럼 제거 - X_train = X_train.drop(columns=['year']) - X_val = X_val.drop(columns=['year']) - - return X_train, X_val, y_train, y_val - - -def create_lgb_model(search_space=None, best_params=None): - """LightGBM 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - LGBMClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'device': DEVICE, - 'objective': OBJECTIVE, - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - 'verbose': -1, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'num_leaves': int(search_space['num_leaves']), - 'min_child_weight': int(search_space['min_child_weight']), - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'num_leaves': int(best_params['num_leaves']), - 'min_child_weight': int(best_params['min_child_weight']), - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return LGBMClassifier(**params) - -# 데이터 로딩 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_seoul = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/seoul_train.csv")) - -# 데이터 전처리 -print("데이터 전처리 중...") -df_seoul = preprocessing(df_seoul) - -# 하이퍼파라미터 검색 공간 정의 -lgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 15, 1), - 'num_leaves': hp.quniform('num_leaves', 20, 150, 1), # 2^max_depth 보다는 작게 - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - lgb_model = create_lgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for train_years, val_year in FOLD_CONFIGS: - X_train, X_val, y_train, y_val = split_data_pure( - df_seoul, train_years, val_year - ) - - lgb_model.fit( - X_train, y_train, - eval_set=[(X_val, y_val)], - eval_metric=csi_metric - ) - - csi = calculate_csi(y_val, lgb_model.predict(X_val)) - csi_scores.append(csi) - - # 평균 CSI의 음수값 반환 (hyperopt는 최소화를 수행) - return -1 * round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -lgb_best = fmin( - fn=objective_func, - space=lgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) - -# 최적화 결과 분석 및 출력 -print(f"\n최적화 완료. 최적 파라미터: {lgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/lgb_pure_seoul_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (train_years, val_year) in enumerate(FOLD_CONFIGS, start=1): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data_pure( - df_seoul, train_years, val_year - ) - - lgb_model = create_lgb_model(best_params=lgb_best) - lgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)]) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, lgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(lgb_model) - -# 모델 저장 -print("모델 저장 중...") -model_save_path = os.path.join(base_dir, "save_model/lgb_optima/lgb_pure_seoul.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") - -import sys -sys.exit(0) diff --git a/Analysis_code/5.optima/lgb_smote/LGB_smote_busan.py b/Analysis_code/5.optima/lgb_smote/LGB_smote_busan.py deleted file mode 100644 index 03afa0878d9f251f0d6a7e9f698a276d73576a7d..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/lgb_smote/LGB_smote_busan.py +++ /dev/null @@ -1,314 +0,0 @@ -import joblib -import pandas as pd -import os -import numpy as np -from warnings import filterwarnings -from sklearn.metrics import confusion_matrix -from lightgbm import LGBMClassifier -from hyperopt import fmin, tpe, Trials, hp - -filterwarnings('ignore') - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 -DEVICE = 'gpu' -OBJECTIVE = 'multiclassova' - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(y_true, y_pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - y_true: 실제 레이블 - y_pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(y_true, y_pred) - - # 혼동 행렬에서 H(Hit), F(False alarm), M(Miss) 추출 - H = cm[0, 0] + cm[1, 1] - F = cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1] - M = cm[0, 2] + cm[1, 2] - - # CSI 계산 - csi = H / (H + F + M + 1e-10) - return csi - - -def csi_metric(y_true, pred_prob): - """LightGBM용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 (shape: [n_samples, n_classes]) - - Returns: - ('CSI', score, higher_better) 튜플 - """ - y_pred_binary = np.argmax(pred_prob, axis=1) - score = calculate_csi(y_true, y_pred_binary) - return 'CSI', score, True - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - - -def split_data(df_smote, df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_smote: SMOTE로 오버샘플링된 데이터프레임 - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: SMOTE 데이터에서 train_years에 해당하는 데이터 - train_mask = df_smote['year'].isin(train_years) - X_train = df_smote.loc[train_mask, df_smote.columns != 'multi_class'].copy() - y_train = df_smote.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - # 'year' 컬럼 제거 - X_train = X_train.drop(columns=['year']) - X_val = X_val.drop(columns=['year']) - - return X_train, X_val, y_train, y_val - - -def create_lgb_model(search_space=None, best_params=None): - """LightGBM 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - LGBMClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'device': DEVICE, - 'objective': OBJECTIVE, - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - 'verbose': -1, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'num_leaves': int(search_space['num_leaves']), - 'min_child_weight': int(search_space['min_child_weight']), - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'num_leaves': int(best_params['num_leaves']), - 'min_child_weight': int(best_params['min_child_weight']), - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return LGBMClassifier(**params) - -# 데이터 로딩 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_busan = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/busan_train.csv")) -df_smote_busan_1 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smote/smote_1_busan.csv")) -df_smote_busan_2 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smote/smote_2_busan.csv")) -df_smote_busan_3 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smote/smote_3_busan.csv")) - -# 데이터 전처리 -print("데이터 전처리 중...") -df_smote_busan_1 = preprocessing(df_smote_busan_1) -df_smote_busan_2 = preprocessing(df_smote_busan_2) -df_smote_busan_3 = preprocessing(df_smote_busan_3) -df_busan = preprocessing(df_busan) - -# SMOTE 데이터 리스트 (fold 순서와 일치) -df_smote_list = [df_smote_busan_1, df_smote_busan_2, df_smote_busan_3] - -# 하이퍼파라미터 검색 공간 정의 -lgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 15, 1), - 'num_leaves': hp.quniform('num_leaves', 20, 150, 1), # 2^max_depth 보다는 작게 - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - lgb_model = create_lgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for df_smote, (train_years, val_year) in zip(df_smote_list, FOLD_CONFIGS): - X_train, X_val, y_train, y_val = split_data( - df_smote, df_busan, train_years, val_year - ) - - lgb_model.fit( - X_train, y_train, - eval_set=[(X_val, y_val)], - eval_metric=csi_metric - ) - - csi = calculate_csi(y_val, lgb_model.predict(X_val)) - csi_scores.append(csi) - - # 평균 CSI의 음수값 반환 (hyperopt는 최소화를 수행) - return -1 * round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -lgb_best = fmin( - fn=objective_func, - space=lgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) -print(f"최적화 완료. 최적 파라미터: {lgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/lgb_smote_busan_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (df_smote, (train_years, val_year)) in enumerate( - zip(df_smote_list, FOLD_CONFIGS), start=1 -): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_smote, df_busan, train_years, val_year - ) - - lgb_model = create_lgb_model(best_params=lgb_best) - lgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)]) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, lgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(lgb_model) - -# 모델 저장 -print("모델 저장 중...") -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -model_save_path = os.path.join(base_dir, "save_model/lgb_optima/lgb_smote_busan.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") \ No newline at end of file diff --git a/Analysis_code/5.optima/lgb_smote/LGB_smote_daegu.py b/Analysis_code/5.optima/lgb_smote/LGB_smote_daegu.py deleted file mode 100644 index d632305cb3f92fff7382a25adfb7ddaa1b79a5f4..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/lgb_smote/LGB_smote_daegu.py +++ /dev/null @@ -1,316 +0,0 @@ - -import pandas as pd -import os -import numpy as np -import joblib -from warnings import filterwarnings -from sklearn.metrics import confusion_matrix -from lightgbm import LGBMClassifier -from hyperopt import fmin, tpe, Trials, hp - -filterwarnings('ignore') - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 -DEVICE = 'gpu' -OBJECTIVE = 'multiclassova' - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(y_true, y_pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - y_true: 실제 레이블 - y_pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(y_true, y_pred) - - # 혼동 행렬에서 H(Hit), F(False alarm), M(Miss) 추출 - H = cm[0, 0] + cm[1, 1] - F = cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1] - M = cm[0, 2] + cm[1, 2] - - # CSI 계산 - csi = H / (H + F + M + 1e-10) - return csi - - -def csi_metric(y_true, pred_prob): - """LightGBM용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 (shape: [n_samples, n_classes]) - - Returns: - ('CSI', score, higher_better) 튜플 - """ - y_pred_binary = np.argmax(pred_prob, axis=1) - score = calculate_csi(y_true, y_pred_binary) - return 'CSI', score, True - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - - -def split_data(df_smote, df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_smote: SMOTE로 오버샘플링된 데이터프레임 - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: SMOTE 데이터에서 train_years에 해당하는 데이터 - train_mask = df_smote['year'].isin(train_years) - X_train = df_smote.loc[train_mask, df_smote.columns != 'multi_class'].copy() - y_train = df_smote.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - # 'year' 컬럼 제거 - X_train = X_train.drop(columns=['year']) - X_val = X_val.drop(columns=['year']) - - return X_train, X_val, y_train, y_val - - -def create_lgb_model(search_space=None, best_params=None): - """LightGBM 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - LGBMClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'device': DEVICE, - 'objective': OBJECTIVE, - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - 'verbose': -1, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'num_leaves': int(search_space['num_leaves']), - 'min_child_weight': int(search_space['min_child_weight']), - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'num_leaves': int(best_params['num_leaves']), - 'min_child_weight': int(best_params['min_child_weight']), - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return LGBMClassifier(**params) - -# 데이터 로딩 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_daegu = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/daegu_train.csv")) -df_smote_daegu_1 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smote/smote_1_daegu.csv")) -df_smote_daegu_2 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smote/smote_2_daegu.csv")) -df_smote_daegu_3 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smote/smote_3_daegu.csv")) - -# 데이터 전처리 -print("데이터 전처리 중...") -df_smote_daegu_1 = preprocessing(df_smote_daegu_1) -df_smote_daegu_2 = preprocessing(df_smote_daegu_2) -df_smote_daegu_3 = preprocessing(df_smote_daegu_3) -df_daegu = preprocessing(df_daegu) - -# SMOTE 데이터 리스트 (fold 순서와 일치) -df_smote_list = [df_smote_daegu_1, df_smote_daegu_2, df_smote_daegu_3] - -# 하이퍼파라미터 검색 공간 정의 -lgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 15, 1), - 'num_leaves': hp.quniform('num_leaves', 20, 150, 1), # 2^max_depth 보다는 작게 - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - lgb_model = create_lgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for df_smote, (train_years, val_year) in zip(df_smote_list, FOLD_CONFIGS): - X_train, X_val, y_train, y_val = split_data( - df_smote, df_daegu, train_years, val_year - ) - - lgb_model.fit( - X_train, y_train, - eval_set=[(X_val, y_val)], - eval_metric=csi_metric - ) - - csi = calculate_csi(y_val, lgb_model.predict(X_val)) - csi_scores.append(csi) - - # 평균 CSI의 음수값 반환 (hyperopt는 최소화를 수행) - return -1 * round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -lgb_best = fmin( - fn=objective_func, - space=lgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) -print(f"최적화 완료. 최적 파라미터: {lgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/lgb_smote_daegu_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (df_smote, (train_years, val_year)) in enumerate( - zip(df_smote_list, FOLD_CONFIGS), start=1 -): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_smote, df_daegu, train_years, val_year - ) - - lgb_model = create_lgb_model(best_params=lgb_best) - lgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)]) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, lgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(lgb_model) - -# 모델 저장 -print("모델 저장 중...") -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -model_save_path = os.path.join(base_dir, "save_model/lgb_optima/lgb_smote_daegu.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") - diff --git a/Analysis_code/5.optima/lgb_smote/LGB_smote_daejeon.py b/Analysis_code/5.optima/lgb_smote/LGB_smote_daejeon.py deleted file mode 100644 index f180e86f63057eb924b08b72f6d36ab2d86557d7..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/lgb_smote/LGB_smote_daejeon.py +++ /dev/null @@ -1,316 +0,0 @@ - -import pandas as pd -import os -import numpy as np -import joblib -from warnings import filterwarnings -from sklearn.metrics import confusion_matrix -from lightgbm import LGBMClassifier -from hyperopt import fmin, tpe, Trials, hp - -filterwarnings('ignore') - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 -DEVICE = 'gpu' -OBJECTIVE = 'multiclassova' - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(y_true, y_pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - y_true: 실제 레이블 - y_pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(y_true, y_pred) - - # 혼동 행렬에서 H(Hit), F(False alarm), M(Miss) 추출 - H = cm[0, 0] + cm[1, 1] - F = cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1] - M = cm[0, 2] + cm[1, 2] - - # CSI 계산 - csi = H / (H + F + M + 1e-10) - return csi - - -def csi_metric(y_true, pred_prob): - """LightGBM용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 (shape: [n_samples, n_classes]) - - Returns: - ('CSI', score, higher_better) 튜플 - """ - y_pred_binary = np.argmax(pred_prob, axis=1) - score = calculate_csi(y_true, y_pred_binary) - return 'CSI', score, True - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - - -def split_data(df_smote, df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_smote: SMOTE로 오버샘플링된 데이터프레임 - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: SMOTE 데이터에서 train_years에 해당하는 데이터 - train_mask = df_smote['year'].isin(train_years) - X_train = df_smote.loc[train_mask, df_smote.columns != 'multi_class'].copy() - y_train = df_smote.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - # 'year' 컬럼 제거 - X_train = X_train.drop(columns=['year']) - X_val = X_val.drop(columns=['year']) - - return X_train, X_val, y_train, y_val - - -def create_lgb_model(search_space=None, best_params=None): - """LightGBM 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - LGBMClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'device': DEVICE, - 'objective': OBJECTIVE, - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - 'verbose': -1, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'num_leaves': int(search_space['num_leaves']), - 'min_child_weight': int(search_space['min_child_weight']), - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'num_leaves': int(best_params['num_leaves']), - 'min_child_weight': int(best_params['min_child_weight']), - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return LGBMClassifier(**params) - -# 데이터 로딩 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_daejeon = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/daejeon_train.csv")) -df_smote_daejeon_1 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smote/smote_1_daejeon.csv")) -df_smote_daejeon_2 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smote/smote_2_daejeon.csv")) -df_smote_daejeon_3 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smote/smote_3_daejeon.csv")) - -# 데이터 전처리 -print("데이터 전처리 중...") -df_smote_daejeon_1 = preprocessing(df_smote_daejeon_1) -df_smote_daejeon_2 = preprocessing(df_smote_daejeon_2) -df_smote_daejeon_3 = preprocessing(df_smote_daejeon_3) -df_daejeon = preprocessing(df_daejeon) - -# SMOTE 데이터 리스트 (fold 순서와 일치) -df_smote_list = [df_smote_daejeon_1, df_smote_daejeon_2, df_smote_daejeon_3] - -# 하이퍼파라미터 검색 공간 정의 -lgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 15, 1), - 'num_leaves': hp.quniform('num_leaves', 20, 150, 1), # 2^max_depth 보다는 작게 - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - lgb_model = create_lgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for df_smote, (train_years, val_year) in zip(df_smote_list, FOLD_CONFIGS): - X_train, X_val, y_train, y_val = split_data( - df_smote, df_daejeon, train_years, val_year - ) - - lgb_model.fit( - X_train, y_train, - eval_set=[(X_val, y_val)], - eval_metric=csi_metric - ) - - csi = calculate_csi(y_val, lgb_model.predict(X_val)) - csi_scores.append(csi) - - # 평균 CSI의 음수값 반환 (hyperopt는 최소화를 수행) - return -1 * round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -lgb_best = fmin( - fn=objective_func, - space=lgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) -print(f"최적화 완료. 최적 파라미터: {lgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/lgb_smote_daejeon_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (df_smote, (train_years, val_year)) in enumerate( - zip(df_smote_list, FOLD_CONFIGS), start=1 -): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_smote, df_daejeon, train_years, val_year - ) - - lgb_model = create_lgb_model(best_params=lgb_best) - lgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)]) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, lgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(lgb_model) - -# 모델 저장 -print("모델 저장 중...") -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -model_save_path = os.path.join(base_dir, "save_model/lgb_optima/lgb_smote_daejeon.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") - diff --git a/Analysis_code/5.optima/lgb_smote/LGB_smote_gwangju.py b/Analysis_code/5.optima/lgb_smote/LGB_smote_gwangju.py deleted file mode 100644 index 638df8a22652e5f95db7db4b06a924872464c739..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/lgb_smote/LGB_smote_gwangju.py +++ /dev/null @@ -1,316 +0,0 @@ - -import pandas as pd -import os -import numpy as np -import joblib -from warnings import filterwarnings -from sklearn.metrics import confusion_matrix -from lightgbm import LGBMClassifier -from hyperopt import fmin, tpe, Trials, hp - -filterwarnings('ignore') - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 -DEVICE = 'gpu' -OBJECTIVE = 'multiclassova' - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(y_true, y_pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - y_true: 실제 레이블 - y_pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(y_true, y_pred) - - # 혼동 행렬에서 H(Hit), F(False alarm), M(Miss) 추출 - H = cm[0, 0] + cm[1, 1] - F = cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1] - M = cm[0, 2] + cm[1, 2] - - # CSI 계산 - csi = H / (H + F + M + 1e-10) - return csi - - -def csi_metric(y_true, pred_prob): - """LightGBM용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 (shape: [n_samples, n_classes]) - - Returns: - ('CSI', score, higher_better) 튜플 - """ - y_pred_binary = np.argmax(pred_prob, axis=1) - score = calculate_csi(y_true, y_pred_binary) - return 'CSI', score, True - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - - -def split_data(df_smote, df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_smote: SMOTE로 오버샘플링된 데이터프레임 - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: SMOTE 데이터에서 train_years에 해당하는 데이터 - train_mask = df_smote['year'].isin(train_years) - X_train = df_smote.loc[train_mask, df_smote.columns != 'multi_class'].copy() - y_train = df_smote.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - # 'year' 컬럼 제거 - X_train = X_train.drop(columns=['year']) - X_val = X_val.drop(columns=['year']) - - return X_train, X_val, y_train, y_val - - -def create_lgb_model(search_space=None, best_params=None): - """LightGBM 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - LGBMClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'device': DEVICE, - 'objective': OBJECTIVE, - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - 'verbose': -1, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'num_leaves': int(search_space['num_leaves']), - 'min_child_weight': int(search_space['min_child_weight']), - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'num_leaves': int(best_params['num_leaves']), - 'min_child_weight': int(best_params['min_child_weight']), - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return LGBMClassifier(**params) - -# 데이터 로딩 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_gwangju = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/gwangju_train.csv")) -df_smote_gwangju_1 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smote/smote_1_gwangju.csv")) -df_smote_gwangju_2 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smote/smote_2_gwangju.csv")) -df_smote_gwangju_3 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smote/smote_3_gwangju.csv")) - -# 데이터 전처리 -print("데이터 전처리 중...") -df_smote_gwangju_1 = preprocessing(df_smote_gwangju_1) -df_smote_gwangju_2 = preprocessing(df_smote_gwangju_2) -df_smote_gwangju_3 = preprocessing(df_smote_gwangju_3) -df_gwangju = preprocessing(df_gwangju) - -# SMOTE 데이터 리스트 (fold 순서와 일치) -df_smote_list = [df_smote_gwangju_1, df_smote_gwangju_2, df_smote_gwangju_3] - -# 하이퍼파라미터 검색 공간 정의 -lgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 15, 1), - 'num_leaves': hp.quniform('num_leaves', 20, 150, 1), # 2^max_depth 보다는 작게 - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - lgb_model = create_lgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for df_smote, (train_years, val_year) in zip(df_smote_list, FOLD_CONFIGS): - X_train, X_val, y_train, y_val = split_data( - df_smote, df_gwangju, train_years, val_year - ) - - lgb_model.fit( - X_train, y_train, - eval_set=[(X_val, y_val)], - eval_metric=csi_metric - ) - - csi = calculate_csi(y_val, lgb_model.predict(X_val)) - csi_scores.append(csi) - - # 평균 CSI의 음수값 반환 (hyperopt는 최소화를 수행) - return -1 * round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -lgb_best = fmin( - fn=objective_func, - space=lgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) -print(f"최적화 완료. 최적 파라미터: {lgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/lgb_smote_gwangju_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (df_smote, (train_years, val_year)) in enumerate( - zip(df_smote_list, FOLD_CONFIGS), start=1 -): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_smote, df_gwangju, train_years, val_year - ) - - lgb_model = create_lgb_model(best_params=lgb_best) - lgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)]) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, lgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(lgb_model) - -# 모델 저장 -print("모델 저장 중...") -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -model_save_path = os.path.join(base_dir, "save_model/lgb_optima/lgb_smote_gwangju.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") - diff --git a/Analysis_code/5.optima/lgb_smote/LGB_smote_incheon.py b/Analysis_code/5.optima/lgb_smote/LGB_smote_incheon.py deleted file mode 100644 index 0be32d2805b845718335afa74062b003e33ad4a7..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/lgb_smote/LGB_smote_incheon.py +++ /dev/null @@ -1,316 +0,0 @@ - -import pandas as pd -import os -import numpy as np -import joblib -from warnings import filterwarnings -from sklearn.metrics import confusion_matrix -from lightgbm import LGBMClassifier -from hyperopt import fmin, tpe, Trials, hp - -filterwarnings('ignore') - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 -DEVICE = 'gpu' -OBJECTIVE = 'multiclassova' - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(y_true, y_pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - y_true: 실제 레이블 - y_pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(y_true, y_pred) - - # 혼동 행렬에서 H(Hit), F(False alarm), M(Miss) 추출 - H = cm[0, 0] + cm[1, 1] - F = cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1] - M = cm[0, 2] + cm[1, 2] - - # CSI 계산 - csi = H / (H + F + M + 1e-10) - return csi - - -def csi_metric(y_true, pred_prob): - """LightGBM용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 (shape: [n_samples, n_classes]) - - Returns: - ('CSI', score, higher_better) 튜플 - """ - y_pred_binary = np.argmax(pred_prob, axis=1) - score = calculate_csi(y_true, y_pred_binary) - return 'CSI', score, True - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - - -def split_data(df_smote, df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_smote: SMOTE로 오버샘플링된 데이터프레임 - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: SMOTE 데이터에서 train_years에 해당하는 데이터 - train_mask = df_smote['year'].isin(train_years) - X_train = df_smote.loc[train_mask, df_smote.columns != 'multi_class'].copy() - y_train = df_smote.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - # 'year' 컬럼 제거 - X_train = X_train.drop(columns=['year']) - X_val = X_val.drop(columns=['year']) - - return X_train, X_val, y_train, y_val - - -def create_lgb_model(search_space=None, best_params=None): - """LightGBM 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - LGBMClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'device': DEVICE, - 'objective': OBJECTIVE, - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - 'verbose': -1, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'num_leaves': int(search_space['num_leaves']), - 'min_child_weight': int(search_space['min_child_weight']), - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'num_leaves': int(best_params['num_leaves']), - 'min_child_weight': int(best_params['min_child_weight']), - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return LGBMClassifier(**params) - -# 데이터 로딩 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_incheon = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/incheon_train.csv")) -df_smote_incheon_1 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smote/smote_1_incheon.csv")) -df_smote_incheon_2 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smote/smote_2_incheon.csv")) -df_smote_incheon_3 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smote/smote_3_incheon.csv")) - -# 데이터 전처리 -print("데이터 전처리 중...") -df_smote_incheon_1 = preprocessing(df_smote_incheon_1) -df_smote_incheon_2 = preprocessing(df_smote_incheon_2) -df_smote_incheon_3 = preprocessing(df_smote_incheon_3) -df_incheon = preprocessing(df_incheon) - -# SMOTE 데이터 리스트 (fold 순서와 일치) -df_smote_list = [df_smote_incheon_1, df_smote_incheon_2, df_smote_incheon_3] - -# 하이퍼파라미터 검색 공간 정의 -lgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 15, 1), - 'num_leaves': hp.quniform('num_leaves', 20, 150, 1), # 2^max_depth 보다는 작게 - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - lgb_model = create_lgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for df_smote, (train_years, val_year) in zip(df_smote_list, FOLD_CONFIGS): - X_train, X_val, y_train, y_val = split_data( - df_smote, df_incheon, train_years, val_year - ) - - lgb_model.fit( - X_train, y_train, - eval_set=[(X_val, y_val)], - eval_metric=csi_metric - ) - - csi = calculate_csi(y_val, lgb_model.predict(X_val)) - csi_scores.append(csi) - - # 평균 CSI의 음수값 반환 (hyperopt는 최소화를 수행) - return -1 * round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -lgb_best = fmin( - fn=objective_func, - space=lgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) -print(f"최적화 완료. 최적 파라미터: {lgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/lgb_smote_incheon_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (df_smote, (train_years, val_year)) in enumerate( - zip(df_smote_list, FOLD_CONFIGS), start=1 -): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_smote, df_incheon, train_years, val_year - ) - - lgb_model = create_lgb_model(best_params=lgb_best) - lgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)]) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, lgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(lgb_model) - -# 모델 저장 -print("모델 저장 중...") -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -model_save_path = os.path.join(base_dir, "save_model/lgb_optima/lgb_smote_incheon.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") - diff --git a/Analysis_code/5.optima/lgb_smote/LGB_smote_seoul.py b/Analysis_code/5.optima/lgb_smote/LGB_smote_seoul.py deleted file mode 100644 index b2f4293cf0df3b591d67ea6740da8b4c1f9c8ee2..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/lgb_smote/LGB_smote_seoul.py +++ /dev/null @@ -1,316 +0,0 @@ - -import pandas as pd -import os -import numpy as np -import joblib -from warnings import filterwarnings -from sklearn.metrics import confusion_matrix -from lightgbm import LGBMClassifier -from hyperopt import fmin, tpe, Trials, hp - -filterwarnings('ignore') - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 -DEVICE = 'gpu' -OBJECTIVE = 'multiclassova' - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(y_true, y_pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - y_true: 실제 레이블 - y_pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(y_true, y_pred) - - # 혼동 행렬에서 H(Hit), F(False alarm), M(Miss) 추출 - H = cm[0, 0] + cm[1, 1] - F = cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1] - M = cm[0, 2] + cm[1, 2] - - # CSI 계산 - csi = H / (H + F + M + 1e-10) - return csi - - -def csi_metric(y_true, pred_prob): - """LightGBM용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 (shape: [n_samples, n_classes]) - - Returns: - ('CSI', score, higher_better) 튜플 - """ - y_pred_binary = np.argmax(pred_prob, axis=1) - score = calculate_csi(y_true, y_pred_binary) - return 'CSI', score, True - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - - -def split_data(df_smote, df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_smote: SMOTE로 오버샘플링된 데이터프레임 - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: SMOTE 데이터에서 train_years에 해당하는 데이터 - train_mask = df_smote['year'].isin(train_years) - X_train = df_smote.loc[train_mask, df_smote.columns != 'multi_class'].copy() - y_train = df_smote.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - # 'year' 컬럼 제거 - X_train = X_train.drop(columns=['year']) - X_val = X_val.drop(columns=['year']) - - return X_train, X_val, y_train, y_val - - -def create_lgb_model(search_space=None, best_params=None): - """LightGBM 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - LGBMClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'device': DEVICE, - 'objective': OBJECTIVE, - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - 'verbose': -1, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'num_leaves': int(search_space['num_leaves']), - 'min_child_weight': int(search_space['min_child_weight']), - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'num_leaves': int(best_params['num_leaves']), - 'min_child_weight': int(best_params['min_child_weight']), - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return LGBMClassifier(**params) - -# 데이터 로딩 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_seoul = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/seoul_train.csv")) -df_smote_seoul_1 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smote/smote_1_seoul.csv")) -df_smote_seoul_2 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smote/smote_2_seoul.csv")) -df_smote_seoul_3 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smote/smote_3_seoul.csv")) - -# 데이터 전처리 -print("데이터 전처리 중...") -df_smote_seoul_1 = preprocessing(df_smote_seoul_1) -df_smote_seoul_2 = preprocessing(df_smote_seoul_2) -df_smote_seoul_3 = preprocessing(df_smote_seoul_3) -df_seoul = preprocessing(df_seoul) - -# SMOTE 데이터 리스트 (fold 순서와 일치) -df_smote_list = [df_smote_seoul_1, df_smote_seoul_2, df_smote_seoul_3] - -# 하이퍼파라미터 검색 공간 정의 -lgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 15, 1), - 'num_leaves': hp.quniform('num_leaves', 20, 150, 1), # 2^max_depth 보다는 작게 - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - lgb_model = create_lgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for df_smote, (train_years, val_year) in zip(df_smote_list, FOLD_CONFIGS): - X_train, X_val, y_train, y_val = split_data( - df_smote, df_seoul, train_years, val_year - ) - - lgb_model.fit( - X_train, y_train, - eval_set=[(X_val, y_val)], - eval_metric=csi_metric - ) - - csi = calculate_csi(y_val, lgb_model.predict(X_val)) - csi_scores.append(csi) - - # 평균 CSI의 음수값 반환 (hyperopt는 최소화를 수행) - return -1 * round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -lgb_best = fmin( - fn=objective_func, - space=lgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) -print(f"최적화 완료. 최적 파라미터: {lgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/lgb_smote_seoul_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (df_smote, (train_years, val_year)) in enumerate( - zip(df_smote_list, FOLD_CONFIGS), start=1 -): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_smote, df_seoul, train_years, val_year - ) - - lgb_model = create_lgb_model(best_params=lgb_best) - lgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)]) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, lgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(lgb_model) - -# 모델 저장 -print("모델 저장 중...") -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -model_save_path = os.path.join(base_dir, "save_model/lgb_optima/lgb_smote_seoul.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") - diff --git a/Analysis_code/5.optima/lgb_smotenc_ctgan20000/LGB_smotenc_ctgan20000_busan.py b/Analysis_code/5.optima/lgb_smotenc_ctgan20000/LGB_smotenc_ctgan20000_busan.py deleted file mode 100644 index 51bcb9bff7576cb7f970c24d6538052ec6a9b05e..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/lgb_smotenc_ctgan20000/LGB_smotenc_ctgan20000_busan.py +++ /dev/null @@ -1,319 +0,0 @@ - -import pandas as pd -import os -import numpy as np -import joblib -from warnings import filterwarnings -from sklearn.metrics import confusion_matrix -from lightgbm import LGBMClassifier -from hyperopt import fmin, tpe, Trials, hp - -filterwarnings('ignore') - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 -DEVICE = 'gpu' -OBJECTIVE = 'multiclassova' - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(y_true, y_pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - y_true: 실제 레이블 - y_pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(y_true, y_pred) - - # 혼동 행렬에서 H(Hit), F(False alarm), M(Miss) 추출 - H = cm[0, 0] + cm[1, 1] - F = cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1] - M = cm[0, 2] + cm[1, 2] - - # CSI 계산 - csi = H / (H + F + M + 1e-10) - return csi - - -def csi_metric(y_true, pred_prob): - """LightGBM용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 (shape: [n_samples, n_classes]) - - Returns: - ('CSI', score, higher_better) 튜플 - """ - y_pred_binary = np.argmax(pred_prob, axis=1) - score = calculate_csi(y_true, y_pred_binary) - return 'CSI', score, True - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - - -def split_data(df_sampled, df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_sampled: 샘플링된 데이터프레임 - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: 샘플링된 데이터에서 train_years에 해당하는 데이터 - train_mask = df_sampled['year'].isin(train_years) - X_train = df_sampled.loc[train_mask, df_sampled.columns != 'multi_class'].copy() - y_train = df_sampled.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - # 'year' 컬럼 제거 - X_train = X_train.drop(columns=['year']) - X_val = X_val.drop(columns=['year']) - - return X_train, X_val, y_train, y_val - - -def create_lgb_model(search_space=None, best_params=None): - """LightGBM 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - LGBMClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'device': DEVICE, - 'objective': OBJECTIVE, - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - 'verbose': -1, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'num_leaves': int(search_space['num_leaves']), - 'min_child_weight': int(search_space['min_child_weight']), - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'num_leaves': int(best_params['num_leaves']), - 'min_child_weight': int(best_params['min_child_weight']), - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return LGBMClassifier(**params) - -# 데이터 로딩 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_busan = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/busan_train.csv")) -df_smotenc_ctgan_busan_1 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smotenc_ctgan20000/smotenc_ctgan20000_1_busan.csv")) -df_smotenc_ctgan_busan_2 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smotenc_ctgan20000/smotenc_ctgan20000_2_busan.csv")) -df_smotenc_ctgan_busan_3 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smotenc_ctgan20000/smotenc_ctgan20000_3_busan.csv")) - -# 데이터 전처리 -print("데이터 전처리 중...") -df_smotenc_ctgan_busan_1 = preprocessing(df_smotenc_ctgan_busan_1) -df_smotenc_ctgan_busan_2 = preprocessing(df_smotenc_ctgan_busan_2) -df_smotenc_ctgan_busan_3 = preprocessing(df_smotenc_ctgan_busan_3) -df_busan = preprocessing(df_busan) - -# SMOTENC+CTGAN 데이터 리스트 (fold 순서와 일치) -df_smotenc_ctgan_list = [df_smotenc_ctgan_busan_1, df_smotenc_ctgan_busan_2, df_smotenc_ctgan_busan_3] - -# 하이퍼파라미터 검색 공간 정의 -lgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 15, 1), - 'num_leaves': hp.quniform('num_leaves', 20, 150, 1), # 2^max_depth 보다는 작게 - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - lgb_model = create_lgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for df_smotenc_ctgan, (train_years, val_year) in zip(df_smotenc_ctgan_list, FOLD_CONFIGS): - X_train, X_val, y_train, y_val = split_data( - df_smotenc_ctgan, df_busan, train_years, val_year - ) - - lgb_model.fit( - X_train, y_train, - eval_set=[(X_val, y_val)], - eval_metric=csi_metric - ) - - csi = calculate_csi(y_val, lgb_model.predict(X_val)) - csi_scores.append(csi) - - # 평균 CSI의 음수값 반환 (hyperopt는 최소화를 수행) - return -1 * round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -lgb_best = fmin( - fn=objective_func, - space=lgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) -print(f"최적화 완료. 최적 파라미터: {lgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/lgb_smotenc_ctgan20000_busan_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (df_smotenc_ctgan, (train_years, val_year)) in enumerate( - zip(df_smotenc_ctgan_list, FOLD_CONFIGS), start=1 -): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_smotenc_ctgan, df_busan, train_years, val_year - ) - - lgb_model = create_lgb_model(best_params=lgb_best) - lgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)]) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, lgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(lgb_model) - -# 모델 저장 -print("모델 저장 중...") -# 파일 위치 기반으로 base 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "save_model/lgb_optima"), exist_ok=True) -model_save_path = os.path.join(base_dir, "save_model/lgb_optima/lgb_smotenc_ctgan20000_busan.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") - diff --git a/Analysis_code/5.optima/lgb_smotenc_ctgan20000/LGB_smotenc_ctgan20000_daegu.py b/Analysis_code/5.optima/lgb_smotenc_ctgan20000/LGB_smotenc_ctgan20000_daegu.py deleted file mode 100644 index c8e165396022647ae12adfe34e418ebfecd68a9c..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/lgb_smotenc_ctgan20000/LGB_smotenc_ctgan20000_daegu.py +++ /dev/null @@ -1,319 +0,0 @@ - -import pandas as pd -import os -import numpy as np -import joblib -from warnings import filterwarnings -from sklearn.metrics import confusion_matrix -from lightgbm import LGBMClassifier -from hyperopt import fmin, tpe, Trials, hp - -filterwarnings('ignore') - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 -DEVICE = 'gpu' -OBJECTIVE = 'multiclassova' - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(y_true, y_pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - y_true: 실제 레이블 - y_pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(y_true, y_pred) - - # 혼동 행렬에서 H(Hit), F(False alarm), M(Miss) 추출 - H = cm[0, 0] + cm[1, 1] - F = cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1] - M = cm[0, 2] + cm[1, 2] - - # CSI 계산 - csi = H / (H + F + M + 1e-10) - return csi - - -def csi_metric(y_true, pred_prob): - """LightGBM용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 (shape: [n_samples, n_classes]) - - Returns: - ('CSI', score, higher_better) 튜플 - """ - y_pred_binary = np.argmax(pred_prob, axis=1) - score = calculate_csi(y_true, y_pred_binary) - return 'CSI', score, True - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - - -def split_data(df_sampled, df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_sampled: 샘플링된 데이터프레임 - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: 샘플링된 데이터에서 train_years에 해당하는 데이터 - train_mask = df_sampled['year'].isin(train_years) - X_train = df_sampled.loc[train_mask, df_sampled.columns != 'multi_class'].copy() - y_train = df_sampled.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - # 'year' 컬럼 제거 - X_train = X_train.drop(columns=['year']) - X_val = X_val.drop(columns=['year']) - - return X_train, X_val, y_train, y_val - - -def create_lgb_model(search_space=None, best_params=None): - """LightGBM 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - LGBMClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'device': DEVICE, - 'objective': OBJECTIVE, - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - 'verbose': -1, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'num_leaves': int(search_space['num_leaves']), - 'min_child_weight': int(search_space['min_child_weight']), - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'num_leaves': int(best_params['num_leaves']), - 'min_child_weight': int(best_params['min_child_weight']), - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return LGBMClassifier(**params) - -# 데이터 로딩 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_daegu = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/daegu_train.csv")) -df_smotenc_ctgan_daegu_1 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smotenc_ctgan20000/smotenc_ctgan20000_1_daegu.csv")) -df_smotenc_ctgan_daegu_2 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smotenc_ctgan20000/smotenc_ctgan20000_2_daegu.csv")) -df_smotenc_ctgan_daegu_3 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smotenc_ctgan20000/smotenc_ctgan20000_3_daegu.csv")) - -# 데이터 전처리 -print("데이터 전처리 중...") -df_smotenc_ctgan_daegu_1 = preprocessing(df_smotenc_ctgan_daegu_1) -df_smotenc_ctgan_daegu_2 = preprocessing(df_smotenc_ctgan_daegu_2) -df_smotenc_ctgan_daegu_3 = preprocessing(df_smotenc_ctgan_daegu_3) -df_daegu = preprocessing(df_daegu) - -# SMOTENC+CTGAN 데이터 리스트 (fold 순서와 일치) -df_smotenc_ctgan_list = [df_smotenc_ctgan_daegu_1, df_smotenc_ctgan_daegu_2, df_smotenc_ctgan_daegu_3] - -# 하이퍼파라미터 검색 공간 정의 -lgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 15, 1), - 'num_leaves': hp.quniform('num_leaves', 20, 150, 1), # 2^max_depth 보다는 작게 - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - lgb_model = create_lgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for df_smotenc_ctgan, (train_years, val_year) in zip(df_smotenc_ctgan_list, FOLD_CONFIGS): - X_train, X_val, y_train, y_val = split_data( - df_smotenc_ctgan, df_daegu, train_years, val_year - ) - - lgb_model.fit( - X_train, y_train, - eval_set=[(X_val, y_val)], - eval_metric=csi_metric - ) - - csi = calculate_csi(y_val, lgb_model.predict(X_val)) - csi_scores.append(csi) - - # 평균 CSI의 음수값 반환 (hyperopt는 최소화를 수행) - return -1 * round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -lgb_best = fmin( - fn=objective_func, - space=lgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) -print(f"최적화 완료. 최적 파라미터: {lgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/lgb_smotenc_ctgan20000_daegu_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (df_smotenc_ctgan, (train_years, val_year)) in enumerate( - zip(df_smotenc_ctgan_list, FOLD_CONFIGS), start=1 -): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_smotenc_ctgan, df_daegu, train_years, val_year - ) - - lgb_model = create_lgb_model(best_params=lgb_best) - lgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)]) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, lgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(lgb_model) - -# 모델 저장 -print("모델 저장 중...") -# 파일 위치 기반으로 base 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "save_model/lgb_optima"), exist_ok=True) -model_save_path = os.path.join(base_dir, "save_model/lgb_optima/lgb_smotenc_ctgan20000_daegu.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") - diff --git a/Analysis_code/5.optima/lgb_smotenc_ctgan20000/LGB_smotenc_ctgan20000_daejeon.py b/Analysis_code/5.optima/lgb_smotenc_ctgan20000/LGB_smotenc_ctgan20000_daejeon.py deleted file mode 100644 index f022cfd63e9f7f4efe4b320b0490b596d311aab2..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/lgb_smotenc_ctgan20000/LGB_smotenc_ctgan20000_daejeon.py +++ /dev/null @@ -1,319 +0,0 @@ - -import pandas as pd -import os -import numpy as np -import joblib -from warnings import filterwarnings -from sklearn.metrics import confusion_matrix -from lightgbm import LGBMClassifier -from hyperopt import fmin, tpe, Trials, hp - -filterwarnings('ignore') - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 -DEVICE = 'gpu' -OBJECTIVE = 'multiclassova' - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(y_true, y_pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - y_true: 실제 레이블 - y_pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(y_true, y_pred) - - # 혼동 행렬에서 H(Hit), F(False alarm), M(Miss) 추출 - H = cm[0, 0] + cm[1, 1] - F = cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1] - M = cm[0, 2] + cm[1, 2] - - # CSI 계산 - csi = H / (H + F + M + 1e-10) - return csi - - -def csi_metric(y_true, pred_prob): - """LightGBM용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 (shape: [n_samples, n_classes]) - - Returns: - ('CSI', score, higher_better) 튜플 - """ - y_pred_binary = np.argmax(pred_prob, axis=1) - score = calculate_csi(y_true, y_pred_binary) - return 'CSI', score, True - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - - -def split_data(df_sampled, df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_sampled: 샘플링된 데이터프레임 - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: 샘플링된 데이터에서 train_years에 해당하는 데이터 - train_mask = df_sampled['year'].isin(train_years) - X_train = df_sampled.loc[train_mask, df_sampled.columns != 'multi_class'].copy() - y_train = df_sampled.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - # 'year' 컬럼 제거 - X_train = X_train.drop(columns=['year']) - X_val = X_val.drop(columns=['year']) - - return X_train, X_val, y_train, y_val - - -def create_lgb_model(search_space=None, best_params=None): - """LightGBM 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - LGBMClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'device': DEVICE, - 'objective': OBJECTIVE, - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - 'verbose': -1, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'num_leaves': int(search_space['num_leaves']), - 'min_child_weight': int(search_space['min_child_weight']), - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'num_leaves': int(best_params['num_leaves']), - 'min_child_weight': int(best_params['min_child_weight']), - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return LGBMClassifier(**params) - -# 데이터 로딩 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_daejeon = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/daejeon_train.csv")) -df_smotenc_ctgan_daejeon_1 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smotenc_ctgan20000/smotenc_ctgan20000_1_daejeon.csv")) -df_smotenc_ctgan_daejeon_2 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smotenc_ctgan20000/smotenc_ctgan20000_2_daejeon.csv")) -df_smotenc_ctgan_daejeon_3 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smotenc_ctgan20000/smotenc_ctgan20000_3_daejeon.csv")) - -# 데이터 전처리 -print("데이터 전처리 중...") -df_smotenc_ctgan_daejeon_1 = preprocessing(df_smotenc_ctgan_daejeon_1) -df_smotenc_ctgan_daejeon_2 = preprocessing(df_smotenc_ctgan_daejeon_2) -df_smotenc_ctgan_daejeon_3 = preprocessing(df_smotenc_ctgan_daejeon_3) -df_daejeon = preprocessing(df_daejeon) - -# SMOTENC+CTGAN 데이터 리스트 (fold 순서와 일치) -df_smotenc_ctgan_list = [df_smotenc_ctgan_daejeon_1, df_smotenc_ctgan_daejeon_2, df_smotenc_ctgan_daejeon_3] - -# 하이퍼파라미터 검색 공간 정의 -lgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 15, 1), - 'num_leaves': hp.quniform('num_leaves', 20, 150, 1), # 2^max_depth 보다는 작게 - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - lgb_model = create_lgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for df_smotenc_ctgan, (train_years, val_year) in zip(df_smotenc_ctgan_list, FOLD_CONFIGS): - X_train, X_val, y_train, y_val = split_data( - df_smotenc_ctgan, df_daejeon, train_years, val_year - ) - - lgb_model.fit( - X_train, y_train, - eval_set=[(X_val, y_val)], - eval_metric=csi_metric - ) - - csi = calculate_csi(y_val, lgb_model.predict(X_val)) - csi_scores.append(csi) - - # 평균 CSI의 음수값 반환 (hyperopt는 최소화를 수행) - return -1 * round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -lgb_best = fmin( - fn=objective_func, - space=lgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) -print(f"최적화 완료. 최적 파라미터: {lgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/lgb_smotenc_ctgan20000_daejeon_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (df_smotenc_ctgan, (train_years, val_year)) in enumerate( - zip(df_smotenc_ctgan_list, FOLD_CONFIGS), start=1 -): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_smotenc_ctgan, df_daejeon, train_years, val_year - ) - - lgb_model = create_lgb_model(best_params=lgb_best) - lgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)]) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, lgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(lgb_model) - -# 모델 저장 -print("모델 저장 중...") -# 파일 위치 기반으로 base 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "save_model/lgb_optima"), exist_ok=True) -model_save_path = os.path.join(base_dir, "save_model/lgb_optima/lgb_smotenc_ctgan20000_daejeon.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") - diff --git a/Analysis_code/5.optima/lgb_smotenc_ctgan20000/LGB_smotenc_ctgan20000_gwangju.py b/Analysis_code/5.optima/lgb_smotenc_ctgan20000/LGB_smotenc_ctgan20000_gwangju.py deleted file mode 100644 index a33d9707ef8ef85f5b32e6de6ffa7a7db23f3da9..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/lgb_smotenc_ctgan20000/LGB_smotenc_ctgan20000_gwangju.py +++ /dev/null @@ -1,319 +0,0 @@ - -import pandas as pd -import os -import numpy as np -import joblib -from warnings import filterwarnings -from sklearn.metrics import confusion_matrix -from lightgbm import LGBMClassifier -from hyperopt import fmin, tpe, Trials, hp - -filterwarnings('ignore') - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 -DEVICE = 'gpu' -OBJECTIVE = 'multiclassova' - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(y_true, y_pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - y_true: 실제 레이블 - y_pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(y_true, y_pred) - - # 혼동 행렬에서 H(Hit), F(False alarm), M(Miss) 추출 - H = cm[0, 0] + cm[1, 1] - F = cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1] - M = cm[0, 2] + cm[1, 2] - - # CSI 계산 - csi = H / (H + F + M + 1e-10) - return csi - - -def csi_metric(y_true, pred_prob): - """LightGBM용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 (shape: [n_samples, n_classes]) - - Returns: - ('CSI', score, higher_better) 튜플 - """ - y_pred_binary = np.argmax(pred_prob, axis=1) - score = calculate_csi(y_true, y_pred_binary) - return 'CSI', score, True - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - - -def split_data(df_sampled, df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_sampled: 샘플링된 데이터프레임 - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: 샘플링된 데이터에서 train_years에 해당하는 데이터 - train_mask = df_sampled['year'].isin(train_years) - X_train = df_sampled.loc[train_mask, df_sampled.columns != 'multi_class'].copy() - y_train = df_sampled.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - # 'year' 컬럼 제거 - X_train = X_train.drop(columns=['year']) - X_val = X_val.drop(columns=['year']) - - return X_train, X_val, y_train, y_val - - -def create_lgb_model(search_space=None, best_params=None): - """LightGBM 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - LGBMClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'device': DEVICE, - 'objective': OBJECTIVE, - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - 'verbose': -1, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'num_leaves': int(search_space['num_leaves']), - 'min_child_weight': int(search_space['min_child_weight']), - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'num_leaves': int(best_params['num_leaves']), - 'min_child_weight': int(best_params['min_child_weight']), - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return LGBMClassifier(**params) - -# 데이터 로딩 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_gwangju = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/gwangju_train.csv")) -df_smotenc_ctgan_gwangju_1 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smotenc_ctgan20000/smotenc_ctgan20000_1_gwangju.csv")) -df_smotenc_ctgan_gwangju_2 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smotenc_ctgan20000/smotenc_ctgan20000_2_gwangju.csv")) -df_smotenc_ctgan_gwangju_3 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smotenc_ctgan20000/smotenc_ctgan20000_3_gwangju.csv")) - -# 데이터 전처리 -print("데이터 전처리 중...") -df_smotenc_ctgan_gwangju_1 = preprocessing(df_smotenc_ctgan_gwangju_1) -df_smotenc_ctgan_gwangju_2 = preprocessing(df_smotenc_ctgan_gwangju_2) -df_smotenc_ctgan_gwangju_3 = preprocessing(df_smotenc_ctgan_gwangju_3) -df_gwangju = preprocessing(df_gwangju) - -# SMOTENC+CTGAN 데이터 리스트 (fold 순서와 일치) -df_smotenc_ctgan_list = [df_smotenc_ctgan_gwangju_1, df_smotenc_ctgan_gwangju_2, df_smotenc_ctgan_gwangju_3] - -# 하이퍼파라미터 검색 공간 정의 -lgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 15, 1), - 'num_leaves': hp.quniform('num_leaves', 20, 150, 1), # 2^max_depth 보다는 작게 - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - lgb_model = create_lgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for df_smotenc_ctgan, (train_years, val_year) in zip(df_smotenc_ctgan_list, FOLD_CONFIGS): - X_train, X_val, y_train, y_val = split_data( - df_smotenc_ctgan, df_gwangju, train_years, val_year - ) - - lgb_model.fit( - X_train, y_train, - eval_set=[(X_val, y_val)], - eval_metric=csi_metric - ) - - csi = calculate_csi(y_val, lgb_model.predict(X_val)) - csi_scores.append(csi) - - # 평균 CSI의 음수값 반환 (hyperopt는 최소화를 수행) - return -1 * round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -lgb_best = fmin( - fn=objective_func, - space=lgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) -print(f"최적화 완료. 최적 파라미터: {lgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/lgb_smotenc_ctgan20000_gwangju_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (df_smotenc_ctgan, (train_years, val_year)) in enumerate( - zip(df_smotenc_ctgan_list, FOLD_CONFIGS), start=1 -): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_smotenc_ctgan, df_gwangju, train_years, val_year - ) - - lgb_model = create_lgb_model(best_params=lgb_best) - lgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)]) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, lgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(lgb_model) - -# 모델 저장 -print("모델 저장 중...") -# 파일 위치 기반으로 base 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "save_model/lgb_optima"), exist_ok=True) -model_save_path = os.path.join(base_dir, "save_model/lgb_optima/lgb_smotenc_ctgan20000_gwangju.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") - diff --git a/Analysis_code/5.optima/lgb_smotenc_ctgan20000/LGB_smotenc_ctgan20000_incheon.py b/Analysis_code/5.optima/lgb_smotenc_ctgan20000/LGB_smotenc_ctgan20000_incheon.py deleted file mode 100644 index 26d1d612d61cb2923a92870d94a3473486180991..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/lgb_smotenc_ctgan20000/LGB_smotenc_ctgan20000_incheon.py +++ /dev/null @@ -1,319 +0,0 @@ - -import pandas as pd -import os -import numpy as np -import joblib -from warnings import filterwarnings -from sklearn.metrics import confusion_matrix -from lightgbm import LGBMClassifier -from hyperopt import fmin, tpe, Trials, hp - -filterwarnings('ignore') - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 -DEVICE = 'gpu' -OBJECTIVE = 'multiclassova' - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(y_true, y_pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - y_true: 실제 레이블 - y_pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(y_true, y_pred) - - # 혼동 행렬에서 H(Hit), F(False alarm), M(Miss) 추출 - H = cm[0, 0] + cm[1, 1] - F = cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1] - M = cm[0, 2] + cm[1, 2] - - # CSI 계산 - csi = H / (H + F + M + 1e-10) - return csi - - -def csi_metric(y_true, pred_prob): - """LightGBM용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 (shape: [n_samples, n_classes]) - - Returns: - ('CSI', score, higher_better) 튜플 - """ - y_pred_binary = np.argmax(pred_prob, axis=1) - score = calculate_csi(y_true, y_pred_binary) - return 'CSI', score, True - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - - -def split_data(df_sampled, df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_sampled: 샘플링된 데이터프레임 - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: 샘플링된 데이터에서 train_years에 해당하는 데이터 - train_mask = df_sampled['year'].isin(train_years) - X_train = df_sampled.loc[train_mask, df_sampled.columns != 'multi_class'].copy() - y_train = df_sampled.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - # 'year' 컬럼 제거 - X_train = X_train.drop(columns=['year']) - X_val = X_val.drop(columns=['year']) - - return X_train, X_val, y_train, y_val - - -def create_lgb_model(search_space=None, best_params=None): - """LightGBM 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - LGBMClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'device': DEVICE, - 'objective': OBJECTIVE, - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - 'verbose': -1, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'num_leaves': int(search_space['num_leaves']), - 'min_child_weight': int(search_space['min_child_weight']), - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'num_leaves': int(best_params['num_leaves']), - 'min_child_weight': int(best_params['min_child_weight']), - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return LGBMClassifier(**params) - -# 데이터 로딩 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_incheon = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/incheon_train.csv")) -df_smotenc_ctgan_incheon_1 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smotenc_ctgan20000/smotenc_ctgan20000_1_incheon.csv")) -df_smotenc_ctgan_incheon_2 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smotenc_ctgan20000/smotenc_ctgan20000_2_incheon.csv")) -df_smotenc_ctgan_incheon_3 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smotenc_ctgan20000/smotenc_ctgan20000_3_incheon.csv")) - -# 데이터 전처리 -print("데이터 전처리 중...") -df_smotenc_ctgan_incheon_1 = preprocessing(df_smotenc_ctgan_incheon_1) -df_smotenc_ctgan_incheon_2 = preprocessing(df_smotenc_ctgan_incheon_2) -df_smotenc_ctgan_incheon_3 = preprocessing(df_smotenc_ctgan_incheon_3) -df_incheon = preprocessing(df_incheon) - -# SMOTENC+CTGAN 데이터 리스트 (fold 순서와 일치) -df_smotenc_ctgan_list = [df_smotenc_ctgan_incheon_1, df_smotenc_ctgan_incheon_2, df_smotenc_ctgan_incheon_3] - -# 하이퍼파라미터 검색 공간 정의 -lgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 15, 1), - 'num_leaves': hp.quniform('num_leaves', 20, 150, 1), # 2^max_depth 보다는 작게 - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - lgb_model = create_lgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for df_smotenc_ctgan, (train_years, val_year) in zip(df_smotenc_ctgan_list, FOLD_CONFIGS): - X_train, X_val, y_train, y_val = split_data( - df_smotenc_ctgan, df_incheon, train_years, val_year - ) - - lgb_model.fit( - X_train, y_train, - eval_set=[(X_val, y_val)], - eval_metric=csi_metric - ) - - csi = calculate_csi(y_val, lgb_model.predict(X_val)) - csi_scores.append(csi) - - # 평균 CSI의 음수값 반환 (hyperopt는 최소화를 수행) - return -1 * round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -lgb_best = fmin( - fn=objective_func, - space=lgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) -print(f"최적화 완료. 최적 파라미터: {lgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/lgb_smotenc_ctgan20000_incheon_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (df_smotenc_ctgan, (train_years, val_year)) in enumerate( - zip(df_smotenc_ctgan_list, FOLD_CONFIGS), start=1 -): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_smotenc_ctgan, df_incheon, train_years, val_year - ) - - lgb_model = create_lgb_model(best_params=lgb_best) - lgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)]) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, lgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(lgb_model) - -# 모델 저장 -print("모델 저장 중...") -# 파일 위치 기반으로 base 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "save_model/lgb_optima"), exist_ok=True) -model_save_path = os.path.join(base_dir, "save_model/lgb_optima/lgb_smotenc_ctgan20000_incheon.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") - diff --git a/Analysis_code/5.optima/lgb_smotenc_ctgan20000/LGB_smotenc_ctgan20000_seoul.py b/Analysis_code/5.optima/lgb_smotenc_ctgan20000/LGB_smotenc_ctgan20000_seoul.py deleted file mode 100644 index 5ad162a92df74000c2f71f46ab3d8c15742da55e..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/lgb_smotenc_ctgan20000/LGB_smotenc_ctgan20000_seoul.py +++ /dev/null @@ -1,319 +0,0 @@ - -import pandas as pd -import os -import numpy as np -import joblib -from warnings import filterwarnings -from sklearn.metrics import confusion_matrix -from lightgbm import LGBMClassifier -from hyperopt import fmin, tpe, Trials, hp - -filterwarnings('ignore') - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 -DEVICE = 'gpu' -OBJECTIVE = 'multiclassova' - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(y_true, y_pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - y_true: 실제 레이블 - y_pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(y_true, y_pred) - - # 혼동 행렬에서 H(Hit), F(False alarm), M(Miss) 추출 - H = cm[0, 0] + cm[1, 1] - F = cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1] - M = cm[0, 2] + cm[1, 2] - - # CSI 계산 - csi = H / (H + F + M + 1e-10) - return csi - - -def csi_metric(y_true, pred_prob): - """LightGBM용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 (shape: [n_samples, n_classes]) - - Returns: - ('CSI', score, higher_better) 튜플 - """ - y_pred_binary = np.argmax(pred_prob, axis=1) - score = calculate_csi(y_true, y_pred_binary) - return 'CSI', score, True - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - - -def split_data(df_sampled, df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_sampled: 샘플링된 데이터프레임 - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: 샘플링된 데이터에서 train_years에 해당하는 데이터 - train_mask = df_sampled['year'].isin(train_years) - X_train = df_sampled.loc[train_mask, df_sampled.columns != 'multi_class'].copy() - y_train = df_sampled.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - # 'year' 컬럼 제거 - X_train = X_train.drop(columns=['year']) - X_val = X_val.drop(columns=['year']) - - return X_train, X_val, y_train, y_val - - -def create_lgb_model(search_space=None, best_params=None): - """LightGBM 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - LGBMClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'device': DEVICE, - 'objective': OBJECTIVE, - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - 'verbose': -1, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'num_leaves': int(search_space['num_leaves']), - 'min_child_weight': int(search_space['min_child_weight']), - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'num_leaves': int(best_params['num_leaves']), - 'min_child_weight': int(best_params['min_child_weight']), - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return LGBMClassifier(**params) - -# 데이터 로딩 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_seoul = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/seoul_train.csv")) -df_smotenc_ctgan_seoul_1 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smotenc_ctgan20000/smotenc_ctgan20000_1_seoul.csv")) -df_smotenc_ctgan_seoul_2 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smotenc_ctgan20000/smotenc_ctgan20000_2_seoul.csv")) -df_smotenc_ctgan_seoul_3 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smotenc_ctgan20000/smotenc_ctgan20000_3_seoul.csv")) - -# 데이터 전처리 -print("데이터 전처리 중...") -df_smotenc_ctgan_seoul_1 = preprocessing(df_smotenc_ctgan_seoul_1) -df_smotenc_ctgan_seoul_2 = preprocessing(df_smotenc_ctgan_seoul_2) -df_smotenc_ctgan_seoul_3 = preprocessing(df_smotenc_ctgan_seoul_3) -df_seoul = preprocessing(df_seoul) - -# SMOTENC+CTGAN 데이터 리스트 (fold 순서와 일치) -df_smotenc_ctgan_list = [df_smotenc_ctgan_seoul_1, df_smotenc_ctgan_seoul_2, df_smotenc_ctgan_seoul_3] - -# 하이퍼파라미터 검색 공간 정의 -lgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 15, 1), - 'num_leaves': hp.quniform('num_leaves', 20, 150, 1), # 2^max_depth 보다는 작게 - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - lgb_model = create_lgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for df_smotenc_ctgan, (train_years, val_year) in zip(df_smotenc_ctgan_list, FOLD_CONFIGS): - X_train, X_val, y_train, y_val = split_data( - df_smotenc_ctgan, df_seoul, train_years, val_year - ) - - lgb_model.fit( - X_train, y_train, - eval_set=[(X_val, y_val)], - eval_metric=csi_metric - ) - - csi = calculate_csi(y_val, lgb_model.predict(X_val)) - csi_scores.append(csi) - - # 평균 CSI의 음수값 반환 (hyperopt는 최소화를 수행) - return -1 * round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -lgb_best = fmin( - fn=objective_func, - space=lgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) -print(f"최적화 완료. 최적 파라미터: {lgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/lgb_smotenc_ctgan20000_seoul_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (df_smotenc_ctgan, (train_years, val_year)) in enumerate( - zip(df_smotenc_ctgan_list, FOLD_CONFIGS), start=1 -): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_smotenc_ctgan, df_seoul, train_years, val_year - ) - - lgb_model = create_lgb_model(best_params=lgb_best) - lgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)]) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, lgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(lgb_model) - -# 모델 저장 -print("모델 저장 중...") -# 파일 위치 기반으로 base 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "save_model/lgb_optima"), exist_ok=True) -model_save_path = os.path.join(base_dir, "save_model/lgb_optima/lgb_smotenc_ctgan20000_seoul.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") - diff --git a/Analysis_code/5.optima/resnet_like_ctgan10000/resnet_like_ctgan10000_busan.py b/Analysis_code/5.optima/resnet_like_ctgan10000/resnet_like_ctgan10000_busan.py deleted file mode 100644 index c080bb900d9b5609b29892d816e569ca953a1c9d..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/resnet_like_ctgan10000/resnet_like_ctgan10000_busan.py +++ /dev/null @@ -1,98 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="resnet_like", region="busan", data_sample='ctgan10000'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/resnet_like_ctgan10000_busan_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="resnet_like", - region="busan", - data_sample='ctgan10000', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - - diff --git a/Analysis_code/5.optima/resnet_like_ctgan10000/resnet_like_ctgan10000_daegu.py b/Analysis_code/5.optima/resnet_like_ctgan10000/resnet_like_ctgan10000_daegu.py deleted file mode 100644 index 32634ab2b1674291ce9b138d2dac53576401a5d3..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/resnet_like_ctgan10000/resnet_like_ctgan10000_daegu.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="resnet_like", region="daegu", data_sample='ctgan10000'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/resnet_like_ctgan10000_daegu_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="resnet_like", - region="daegu", - data_sample='ctgan10000', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/resnet_like_ctgan10000/resnet_like_ctgan10000_daejeon.py b/Analysis_code/5.optima/resnet_like_ctgan10000/resnet_like_ctgan10000_daejeon.py deleted file mode 100644 index 6f6ae18683f6aa105a98c2faa287a3dbc01bc430..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/resnet_like_ctgan10000/resnet_like_ctgan10000_daejeon.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="resnet_like", region="daejeon", data_sample='ctgan10000'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/resnet_like_ctgan10000_daejeon_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="resnet_like", - region="daejeon", - data_sample='ctgan10000', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/resnet_like_ctgan10000/resnet_like_ctgan10000_gwangju.py b/Analysis_code/5.optima/resnet_like_ctgan10000/resnet_like_ctgan10000_gwangju.py deleted file mode 100644 index 92706176c6357eb0aa2fb3fd0c14cefa6d48815e..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/resnet_like_ctgan10000/resnet_like_ctgan10000_gwangju.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="resnet_like", region="gwangju", data_sample='ctgan10000'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/resnet_like_ctgan10000_gwangju_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="resnet_like", - region="gwangju", - data_sample='ctgan10000', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/resnet_like_ctgan10000/resnet_like_ctgan10000_incheon.py b/Analysis_code/5.optima/resnet_like_ctgan10000/resnet_like_ctgan10000_incheon.py deleted file mode 100644 index 196d54c4e4c7b6ea8e7b38606cf6c461f8672389..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/resnet_like_ctgan10000/resnet_like_ctgan10000_incheon.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="resnet_like", region="incheon", data_sample='ctgan10000'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/resnet_like_ctgan10000_incheon_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="resnet_like", - region="incheon", - data_sample='ctgan10000', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/resnet_like_ctgan10000/resnet_like_ctgan10000_seoul.py b/Analysis_code/5.optima/resnet_like_ctgan10000/resnet_like_ctgan10000_seoul.py deleted file mode 100644 index dd6f3c96a204dfc3cc910c65dc6dd0022b987fbc..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/resnet_like_ctgan10000/resnet_like_ctgan10000_seoul.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="resnet_like", region="seoul", data_sample='ctgan10000'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/resnet_like_ctgan10000_seoul_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="resnet_like", - region="seoul", - data_sample='ctgan10000', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/resnet_like_ctgan10000/utils.py b/Analysis_code/5.optima/resnet_like_ctgan10000/utils.py deleted file mode 100644 index 9ea18bdc4d08eadee87e7cba3d725e9e7a32d5e8..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/resnet_like_ctgan10000/utils.py +++ /dev/null @@ -1,719 +0,0 @@ -import torch -import torch.nn as nn -import torch.optim as optim -import numpy as np -import random -import os -import copy -from sklearn.preprocessing import QuantileTransformer, LabelEncoder -from torch.utils.data import DataLoader, TensorDataset -from sklearn.metrics import confusion_matrix -from sklearn.utils.class_weight import compute_class_weight -import pandas as pd -import optuna -from sklearn.metrics import accuracy_score, f1_score -import joblib - - -import sys -# 파일 위치 기반으로 models 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -models_path = os.path.abspath(os.path.join(current_file_dir, '../../models')) -sys.path.insert(0, models_path) -from ft_transformer import FTTransformer -from resnet_like import ResNetLike -from deepgbm import DeepGBM -import warnings -warnings.filterwarnings('ignore') - - -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - -# PyTorch 시드 고정 -torch.manual_seed(seed) -torch.cuda.manual_seed(seed) -torch.cuda.manual_seed_all(seed) # Multi-GPU 환경에서 동일한 시드 적용 - -# PyTorch 연산의 결정적 모드 설정 -torch.backends.cudnn.deterministic = True # 실행마다 동일한 결과를 보장 -torch.backends.cudnn.benchmark = True # 성능 최적화를 활성화 (가능한 한 빠른 연산 수행) - - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - - -# 데이터셋 준비 함수 -def prepare_dataset(region, data_sample='pure', target='multi', fold=3): - # 파일 위치 기반으로 데이터 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) - - # 데이터 경로 지정 - dat_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_train.csv") - if data_sample == 'pure': - train_path = dat_path - else: - train_path = os.path.join(data_base_dir, f'data_oversampled/{data_sample}/{data_sample}_{fold}_{region}.csv') - test_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_test.csv") - drop_col = ['multi_class','year'] - target_col = f'{target}_class' - - # 데이터 로드 - region_dat = preprocessing(pd.read_csv(dat_path, index_col=0)) - if data_sample == 'pure': - region_train = region_dat.loc[~region_dat['year'].isin([2021-fold]), :] - else: - region_train = preprocessing(pd.read_csv(train_path)) - region_val = region_dat.loc[region_dat['year'].isin([2021-fold]), :] - region_test = preprocessing(pd.read_csv(test_path)) - - # 컬럼 정렬 (일관성 유지) - common_columns = region_train.columns.to_list() - train_data = region_train[common_columns] - val_data = region_val[common_columns] - test_data = region_test[common_columns] - - # 설명변수 & 타겟 분리 - X_train = train_data.drop(columns=drop_col) - y_train = train_data[target_col] - X_val = val_data.drop(columns=drop_col) - y_val = val_data[target_col] - X_test = test_data.drop(columns=drop_col) - y_test = test_data[target_col] - - # 범주형 & 연속형 변수 분리 - categorical_cols = X_train.select_dtypes(include=['object', 'category', 'int64']).columns - numerical_cols = X_train.select_dtypes(include=['float64']).columns - - # 범주형 변수 Label Encoding - label_encoders = {} - for col in categorical_cols: - le = LabelEncoder() - le.fit(X_train[col]) # Train 데이터 기준으로 학습 - label_encoders[col] = le - - # 변환 적용 - for col in categorical_cols: - X_train[col] = label_encoders[col].transform(X_train[col]) - X_val[col] = label_encoders[col].transform(X_val[col]) - X_test[col] = label_encoders[col].transform(X_test[col]) - - # 연속형 변수 Quantile Transformation - scaler = QuantileTransformer(output_distribution='normal') - scaler.fit(X_train[numerical_cols]) # Train 데이터 기준으로 학습 - - # 변환 적용 - X_train[numerical_cols] = scaler.transform(X_train[numerical_cols]) - X_val[numerical_cols] = scaler.transform(X_val[numerical_cols]) - X_test[numerical_cols] = scaler.transform(X_test[numerical_cols]) - - return X_train, X_val, X_test, y_train, y_val, y_test, categorical_cols, numerical_cols - - - -# 데이터 변환 및 dataloader 생성 함수 -def prepare_dataloader(region, data_sample='pure', target='multi', fold=3, random_state=None): - # 파일 위치 기반으로 데이터 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) - - # 데이터 경로 지정 - dat_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_train.csv") - if data_sample == 'pure': - train_path = dat_path - else: - train_path = os.path.join(data_base_dir, f'data_oversampled/{data_sample}/{data_sample}_{fold}_{region}.csv') - test_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_test.csv") - drop_col = ['multi_class','year'] - target_col = f'{target}_class' - - # 데이터 로드 - region_dat = preprocessing(pd.read_csv(dat_path, index_col=0)) - if data_sample == 'pure': - region_train = region_dat.loc[~region_dat['year'].isin([2021-fold]), :] - else: - region_train = preprocessing(pd.read_csv(train_path)) - region_val = region_dat.loc[region_dat['year'].isin([2021-fold]), :] - region_test = preprocessing(pd.read_csv(test_path)) - - # 컬럼 정렬 (일관성 유지) - common_columns = region_train.columns.to_list() - train_data = region_train[common_columns] - val_data = region_val[common_columns] - test_data = region_test[common_columns] - - # 설명변수 & 타겟 분리 - X_train = train_data.drop(columns=drop_col) - y_train = train_data[target_col] - X_val = val_data.drop(columns=drop_col) - y_val = val_data[target_col] - X_test = test_data.drop(columns=drop_col) - y_test = test_data[target_col] - - # 범주형 & 연속형 변수 분리 - categorical_cols = X_train.select_dtypes(include=['object', 'category', 'int64']).columns - numerical_cols = X_train.select_dtypes(include=['float64']).columns - - # 범주형 변수 Label Encoding - label_encoders = {} - for col in categorical_cols: - le = LabelEncoder() - le.fit(X_train[col]) # Train 데이터 기준으로 학습 - label_encoders[col] = le - - # 변환 적용 - for col in categorical_cols: - X_train[col] = label_encoders[col].transform(X_train[col]) - X_val[col] = label_encoders[col].transform(X_val[col]) - X_test[col] = label_encoders[col].transform(X_test[col]) - - # 연속형 변수 Quantile Transformation - scaler = QuantileTransformer(output_distribution='normal') - scaler.fit(X_train[numerical_cols]) # Train 데이터 기준으로 학습 - - # 변환 적용 - X_train[numerical_cols] = scaler.transform(X_train[numerical_cols]) - X_val[numerical_cols] = scaler.transform(X_val[numerical_cols]) - X_test[numerical_cols] = scaler.transform(X_test[numerical_cols]) - - # 연속형 변수와 범주형 변수 분리 - X_train_num = torch.tensor(X_train[numerical_cols].values, dtype=torch.float32) - X_train_cat = torch.tensor(X_train[categorical_cols].values, dtype=torch.long) - - X_val_num = torch.tensor(X_val[numerical_cols].values, dtype=torch.float32) - X_val_cat = torch.tensor(X_val[categorical_cols].values, dtype=torch.long) - - X_test_num = torch.tensor(X_test[numerical_cols].values, dtype=torch.float32) - X_test_cat = torch.tensor(X_test[categorical_cols].values, dtype=torch.long) - - # 레이블 변환 - if target == "binary": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.float32) # 이진 분류 → float32 - y_val_tensor = torch.tensor(y_val.values, dtype=torch.float32) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.float32) - elif target == "multi": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.long) # 다중 분류 → long - y_val_tensor = torch.tensor(y_val.values, dtype=torch.long) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.long) - else: - raise ValueError("target must be 'binary' or 'multi'") - - # TensorDataset 생성 - train_dataset = TensorDataset(X_train_num, X_train_cat, y_train_tensor) - val_dataset = TensorDataset(X_val_num, X_val_cat, y_val_tensor) - test_dataset = TensorDataset(X_test_num, X_test_cat, y_test_tensor) - - # DataLoader 생성 - if random_state == None: - train_loader = DataLoader(train_dataset, batch_size=64, shuffle=True) - else: - train_loader = DataLoader(train_dataset, batch_size=64, shuffle=True, generator=torch.Generator().manual_seed(random_state)) - val_loader = DataLoader(val_dataset, batch_size=64, shuffle=False) - test_loader = DataLoader(test_dataset, batch_size=64, shuffle=False) - - return X_train, categorical_cols, numerical_cols, train_loader, val_loader, test_loader - -# 데이터 변환 및 dataloader 생성 함수 (batch_size 파라미터 추가 버전) -def prepare_dataloader_with_batchsize(region, data_sample='pure', target='multi', fold=3, random_state=None, batch_size=64): - # 파일 위치 기반으로 데이터 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) - - # 데이터 경로 지정 - dat_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_train.csv") - if data_sample == 'pure': - train_path = dat_path - else: - train_path = os.path.join(data_base_dir, f'data_oversampled/{data_sample}/{data_sample}_{fold}_{region}.csv') - test_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_test.csv") - drop_col = ['multi_class','year'] - target_col = f'{target}_class' - - # 데이터 로드 - region_dat = preprocessing(pd.read_csv(dat_path, index_col=0)) - if data_sample == 'pure': - region_train = region_dat.loc[~region_dat['year'].isin([2021-fold]), :] - else: - region_train = preprocessing(pd.read_csv(train_path)) - region_val = region_dat.loc[region_dat['year'].isin([2021-fold]), :] - region_test = preprocessing(pd.read_csv(test_path)) - - # 컬럼 정렬 (일관성 유지) - common_columns = region_train.columns.to_list() - train_data = region_train[common_columns] - val_data = region_val[common_columns] - test_data = region_test[common_columns] - - # 설명변수 & 타겟 분리 - X_train = train_data.drop(columns=drop_col) - y_train = train_data[target_col] - X_val = val_data.drop(columns=drop_col) - y_val = val_data[target_col] - X_test = test_data.drop(columns=drop_col) - y_test = test_data[target_col] - - # 범주형 & 연속형 변수 분리 - categorical_cols = X_train.select_dtypes(include=['object', 'category', 'int64']).columns - numerical_cols = X_train.select_dtypes(include=['float64']).columns - - # 범주형 변수 Label Encoding - label_encoders = {} - for col in categorical_cols: - le = LabelEncoder() - le.fit(X_train[col]) # Train 데이터 기준으로 학습 - label_encoders[col] = le - - # 변환 적용 - for col in categorical_cols: - X_train[col] = label_encoders[col].transform(X_train[col]) - X_val[col] = label_encoders[col].transform(X_val[col]) - X_test[col] = label_encoders[col].transform(X_test[col]) - - # 연속형 변수 Quantile Transformation - scaler = QuantileTransformer(output_distribution='normal') - scaler.fit(X_train[numerical_cols]) # Train 데이터 기준으로 학습 - - # 변환 적용 - X_train[numerical_cols] = scaler.transform(X_train[numerical_cols]) - X_val[numerical_cols] = scaler.transform(X_val[numerical_cols]) - X_test[numerical_cols] = scaler.transform(X_test[numerical_cols]) - - # 연속형 변수와 범주형 변수 분리 - X_train_num = torch.tensor(X_train[numerical_cols].values, dtype=torch.float32) - X_train_cat = torch.tensor(X_train[categorical_cols].values, dtype=torch.long) - - X_val_num = torch.tensor(X_val[numerical_cols].values, dtype=torch.float32) - X_val_cat = torch.tensor(X_val[categorical_cols].values, dtype=torch.long) - - X_test_num = torch.tensor(X_test[numerical_cols].values, dtype=torch.float32) - X_test_cat = torch.tensor(X_test[categorical_cols].values, dtype=torch.long) - - # 레이블 변환 - if target == "binary": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.float32) # 이진 분류 → float32 - y_val_tensor = torch.tensor(y_val.values, dtype=torch.float32) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.float32) - elif target == "multi": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.long) # 다중 분류 → long - y_val_tensor = torch.tensor(y_val.values, dtype=torch.long) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.long) - else: - raise ValueError("target must be 'binary' or 'multi'") - - # TensorDataset 생성 - train_dataset = TensorDataset(X_train_num, X_train_cat, y_train_tensor) - val_dataset = TensorDataset(X_val_num, X_val_cat, y_val_tensor) - test_dataset = TensorDataset(X_test_num, X_test_cat, y_test_tensor) - - # DataLoader 생성 (batch_size 파라미터 사용) - if random_state == None: - train_loader = DataLoader(train_dataset, batch_size=batch_size, shuffle=True) - else: - train_loader = DataLoader(train_dataset, batch_size=batch_size, shuffle=True, generator=torch.Generator().manual_seed(random_state)) - val_loader = DataLoader(val_dataset, batch_size=batch_size, shuffle=False) - test_loader = DataLoader(test_dataset, batch_size=batch_size, shuffle=False) - - return X_train, categorical_cols, numerical_cols, train_loader, val_loader, test_loader, y_train, scaler - - -def calculate_csi(y_true, pred): - - cm = confusion_matrix(y_true, pred) # 변수 이름을 cm으로 변경 - # 혼동 행렬에서 H, F, M 추출 - H = (cm[0, 0] + cm[1, 1]) - - F = (cm[1, 0] + cm[2, 0] + - cm[0, 1] + cm[2, 1]) - - M = (cm[0, 2] + cm[1, 2]) - - # CSI 계산 - CSI = H / (H + F + M + 1e-10) - return CSI - -def sample_weight(y_train): - class_weights = compute_class_weight( - class_weight='balanced', - classes=np.unique(y_train), # 고유 클래스 - y=y_train # 학습 데이터 레이블 - ) - sample_weights = np.array([class_weights[label] for label in y_train]) - - return sample_weights - -# 하이퍼파라미터 최적화 함수 정의 -def objective(trial, model_choose, region, data_sample='pure', target='multi', n_folds=3, random_state=42): - # GPU 사용 가능 여부 확인 및 device 설정 - device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') - val_scores = [] - - # --- 1. 하이퍼파라미터 탐색 범위 정의 (수정됨) --- - if model_choose == "ft_transformer": - d_token = trial.suggest_int("d_token", 64, 256, step=32) - n_blocks = trial.suggest_int("n_blocks", 2, 6) # 깊이 축소로 과적합 방지 - n_heads = trial.suggest_categorical("n_heads", [4, 8]) - # d_token은 n_heads의 배수여야 함 (FT-Transformer의 구조적 제약 대응) - if d_token % n_heads != 0: - d_token = (d_token // n_heads) * n_heads - - attention_dropout = trial.suggest_float("attention_dropout", 0.1, 0.4) - ffn_dropout = trial.suggest_float("ffn_dropout", 0.1, 0.4) - lr = trial.suggest_float("lr", 1e-5, 1e-2, log=True) # 범위 확대 - weight_decay = trial.suggest_float("weight_decay", 1e-4, 1e-1, log=True) # 더 공격적인 범위로 확장 - batch_size = trial.suggest_categorical("batch_size", [32, 64, 128, 256]) # Batch Size 추가 - - elif model_choose == 'resnet_like': - d_main = trial.suggest_int("d_main", 64, 256, step=32) - d_hidden = trial.suggest_int("d_hidden", 64, 512, step=64) - n_blocks = trial.suggest_int("n_blocks", 2, 5) # 너무 깊지 않게 조절 - dropout_first = trial.suggest_float("dropout_first", 0.1, 0.4) - dropout_second = trial.suggest_float("dropout_second", 0.0, 0.2) - lr = trial.suggest_float("lr", 1e-5, 1e-2, log=True) - weight_decay = trial.suggest_float("weight_decay", 1e-4, 1e-1, log=True) # 더 공격적인 범위로 확장 - batch_size = trial.suggest_categorical("batch_size", [32, 64, 128, 256]) # Batch Size 추가 - - elif model_choose == 'deepgbm': - # DeepGBM의 경우 모델 특성에 맞춰 ResNet 블록 및 임베딩 차원 조절 - d_main = trial.suggest_int("d_main", 64, 256, step=32) - d_hidden = trial.suggest_int("d_hidden", 64, 256, step=64) - n_blocks = trial.suggest_int("n_blocks", 2, 6) - dropout = trial.suggest_float("dropout", 0.1, 0.4) - lr = trial.suggest_float("lr", 1e-5, 1e-2, log=True) - weight_decay = trial.suggest_float("weight_decay", 1e-4, 1e-1, log=True) # 더 공격적인 범위로 확장 - batch_size = trial.suggest_categorical("batch_size", [32, 64, 128, 256]) # Batch Size 추가 - - # --- 2. Fold별 학습 및 교차 검증 --- - for fold in range(1, n_folds + 1): - X_train_df, categorical_cols, numerical_cols, train_loader, val_loader, _, y_train, _ = prepare_dataloader_with_batchsize( - region, data_sample=data_sample, target=target, fold=fold, random_state=random_state, batch_size=batch_size - ) - - # 모델 초기화 - if model_choose == "ft_transformer": - model = FTTransformer( - num_features=len(numerical_cols), - cat_cardinalities=[len(X_train_df[col].unique()) for col in categorical_cols], - d_token=d_token, - n_blocks=n_blocks, - n_heads=n_heads, - attention_dropout=attention_dropout, - ffn_dropout=ffn_dropout, - num_classes=3 - ).to(device) - elif model_choose == 'resnet_like': - input_dim = len(numerical_cols) + len(categorical_cols) - model = ResNetLike( - input_dim=input_dim, - d_main=d_main, - d_hidden=d_hidden, - n_blocks=n_blocks, - dropout_first=dropout_first, - dropout_second=dropout_second, - num_classes=3 - ).to(device) - elif model_choose == 'deepgbm': - model = DeepGBM( - num_features=len(numerical_cols), - cat_features=[len(X_train_df[col].unique()) for col in categorical_cols], - d_main=d_main, - d_hidden=d_hidden, - n_blocks=n_blocks, - dropout=dropout, - num_classes=3 - ).to(device) - - # 클래스 가중치 계산 및 손실 함수 설정 (Label Smoothing 적용) - if target == 'multi': - class_weights = compute_class_weight( - class_weight='balanced', - classes=np.unique(y_train), - y=y_train - ) - # 클래스별 가중치 로그 출력 - unique_classes = np.unique(y_train) - class_counts = {cls: np.sum(y_train == cls) for cls in unique_classes} - print(f" Fold {fold} - 클래스별 가중치: {dict(zip(unique_classes, class_weights))} (클래스별 샘플 수: {class_counts})") - class_weights_tensor = torch.tensor(class_weights, dtype=torch.float32).to(device) - criterion = nn.CrossEntropyLoss(weight=class_weights_tensor, label_smoothing=0.0) # Label Smoothing 추가 - else: - criterion = nn.BCEWithLogitsLoss() - optimizer = optim.AdamW(model.parameters(), lr=lr, weight_decay=weight_decay) - - # 학습률 스케줄러 추가: 성능 정체 시 LR을 0.5배 감소 (검증 CSI 기준) - scheduler = optim.lr_scheduler.ReduceLROnPlateau(optimizer, mode='max', factor=0.5, patience=3) - - # 학습 설정 (에폭 및 페이션스 상향) - epochs = 200 - patience = 12 # 딥러닝의 정체 구간을 고려하여 소폭 상향 - best_fold_csi = 0 - counter = 0 - - for epoch in range(epochs): - model.train() - for x_num_batch, x_cat_batch, y_batch in train_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - - optimizer.zero_grad() - y_pred = model(x_num_batch, x_cat_batch) - loss = criterion(y_pred, y_batch if target == 'multi' else y_batch.float()) - loss.backward() - optimizer.step() - - # Validation 평가 - model.eval() - y_pred_val, y_true_val = [], [] - with torch.no_grad(): - for x_num_batch, x_cat_batch, y_batch in val_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - output = model(x_num_batch, x_cat_batch) - pred = output.argmax(dim=1) if target == 'multi' else (torch.sigmoid(output) >= 0.5).long() - - y_pred_val.extend(pred.cpu().numpy()) - y_true_val.extend(y_batch.cpu().numpy()) - - # CSI 계산 및 스케줄러 업데이트 - val_csi = calculate_csi(y_true_val, y_pred_val) - scheduler.step(val_csi) - - # Optuna Pruning 적용 (첫 번째 Fold에서 조기 종료 판단 강화) - trial.report(val_csi, epoch) - if trial.should_prune(): - raise optuna.exceptions.TrialPruned() - - # Early Stopping 체크 - if val_csi > best_fold_csi: - best_fold_csi = val_csi - counter = 0 - else: - counter += 1 - - if counter >= patience: - break - - val_scores.append(best_fold_csi) - - # 모든 fold의 평균 성능 반환 - return np.mean(val_scores) - - -# 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 함수 -def train_final_model(best_params, model_choose, region, data_sample='pure', target='multi', n_folds=3, random_state=42): - """ - 최적화된 하이퍼파라미터로 최종 모델을 학습하고 저장합니다. - - Args: - best_params: 최적화된 하이퍼파라미터 딕셔너리 - model_choose: 모델 선택 ('ft_transformer', 'resnet_like', 'deepgbm') - region: 지역명 - data_sample: 데이터 샘플 타입 ('pure', 'smote', etc.) - target: 타겟 타입 ('multi', 'binary') - n_folds: 교차 검증 fold 수 - random_state: 랜덤 시드 - - Returns: - 저장된 모델 경로 리스트 - """ - # GPU 사용 가능 여부 확인 및 device 설정 - device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') - - models = [] - scalers = [] # scaler 리스트 추가 - - print("최종 모델 학습 시작...") - - for fold in range(1, n_folds + 1): - print(f"Fold {fold} 학습 중...") - - # 최적화된 batch_size 사용 - batch_size = best_params.get("batch_size", 64) - X_train_df, categorical_cols, numerical_cols, train_loader, val_loader, _, y_train, scaler = prepare_dataloader_with_batchsize( - region, data_sample=data_sample, target=target, fold=fold, random_state=random_state, batch_size=batch_size - ) - - # 모델 초기화 - if model_choose == "ft_transformer": - d_token = best_params["d_token"] - n_heads = best_params.get("n_heads", 8) - # d_token은 n_heads의 배수여야 함 (FT-Transformer의 구조적 제약 대응) - if d_token % n_heads != 0: - d_token = (d_token // n_heads) * n_heads - - model = FTTransformer( - num_features=len(numerical_cols), - cat_cardinalities=[len(X_train_df[col].unique()) for col in categorical_cols], - d_token=d_token, - n_blocks=best_params["n_blocks"], - n_heads=n_heads, - attention_dropout=best_params["attention_dropout"], - ffn_dropout=best_params["ffn_dropout"], - num_classes=3 - ).to(device) - elif model_choose == 'resnet_like': - input_dim = len(numerical_cols) + len(categorical_cols) - model = ResNetLike( - input_dim=input_dim, - d_main=best_params["d_main"], - d_hidden=best_params["d_hidden"], - n_blocks=best_params["n_blocks"], - dropout_first=best_params["dropout_first"], - dropout_second=best_params["dropout_second"], - num_classes=3 - ).to(device) - elif model_choose == 'deepgbm': - model = DeepGBM( - num_features=len(numerical_cols), - cat_features=[len(X_train_df[col].unique()) for col in categorical_cols], - d_main=best_params["d_main"], - d_hidden=best_params["d_hidden"], - n_blocks=best_params["n_blocks"], - dropout=best_params["dropout"], - num_classes=3 - ).to(device) - else: - raise ValueError(f"Unknown model_choose: {model_choose}") - - # 클래스 가중치 계산 및 손실 함수 설정 (Label Smoothing 적용) - if target == 'multi': - class_weights = compute_class_weight( - class_weight='balanced', - classes=np.unique(y_train), - y=y_train - ) - class_weights_tensor = torch.tensor(class_weights, dtype=torch.float32).to(device) - criterion = nn.CrossEntropyLoss(weight=class_weights_tensor, label_smoothing=0.0) # Label Smoothing 추가 - else: - criterion = nn.BCEWithLogitsLoss() - optimizer = optim.AdamW(model.parameters(), lr=best_params["lr"], weight_decay=best_params["weight_decay"]) - - # 학습률 스케줄러 - scheduler = optim.lr_scheduler.ReduceLROnPlateau(optimizer, mode='max', factor=0.5, patience=3) - - # 학습 설정 - epochs = 200 - patience = 12 - best_fold_csi = 0 - counter = 0 - best_model = None - - for epoch in range(epochs): - model.train() - for x_num_batch, x_cat_batch, y_batch in train_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - - optimizer.zero_grad() - y_pred = model(x_num_batch, x_cat_batch) - loss = criterion(y_pred, y_batch if target == 'multi' else y_batch.float()) - loss.backward() - optimizer.step() - - # Validation 평가 - model.eval() - y_pred_val, y_true_val = [], [] - with torch.no_grad(): - for x_num_batch, x_cat_batch, y_batch in val_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - output = model(x_num_batch, x_cat_batch) - pred = output.argmax(dim=1) if target == 'multi' else (torch.sigmoid(output) >= 0.5).long() - - y_pred_val.extend(pred.cpu().numpy()) - y_true_val.extend(y_batch.cpu().numpy()) - - # CSI 계산 및 스케줄러 업데이트 - val_csi = calculate_csi(y_true_val, y_pred_val) - scheduler.step(val_csi) - - # Early Stopping 체크 - if val_csi > best_fold_csi: - best_fold_csi = val_csi - counter = 0 - best_model = copy.deepcopy(model) - else: - counter += 1 - - if counter >= patience: - print(f" Early stopping at epoch {epoch+1}, Best CSI: {best_fold_csi:.4f}") - break - - if best_model is None: - best_model = model - - scalers.append(scaler) # scaler 저장 (fold 순서대로) - models.append(best_model) - print(f" Fold {fold} 학습 완료 (검증 CSI: {best_fold_csi:.4f})") - - # 모델 저장 경로 설정 - save_dir = f'../save_model/{model_choose}_optima' - os.makedirs(save_dir, exist_ok=True) - - # 파일명 생성 - if data_sample == 'pure': - model_filename = f'{model_choose}_pure_{region}.pkl' - else: - model_filename = f'{model_choose}_{data_sample}_{region}.pkl' - - model_path = f'{save_dir}/{model_filename}' - - # 리스트에 담아 한 번에 저장 - joblib.dump(models, model_path) - print(f"\n모든 모델 저장 완료: {model_path} (총 {len(models)}개 fold)") - - # Scaler 별도 저장 - scaler_save_dir = f'../save_model/{model_choose}_optima/scaler' - os.makedirs(scaler_save_dir, exist_ok=True) - - # 파일명 생성 (모델과 동일한 패턴) - if data_sample == 'pure': - scaler_filename = f'{model_choose}_pure_{region}_scaler.pkl' - else: - scaler_filename = f'{model_choose}_{data_sample}_{region}_scaler.pkl' - - scaler_path = f'{scaler_save_dir}/{scaler_filename}' - joblib.dump(scalers, scaler_path) - print(f"Scaler 저장 완료: {scaler_path} (총 {len(scalers)}개 fold)") - - return model_path - diff --git a/Analysis_code/5.optima/resnet_like_pure/resnet_like_pure_busan.py b/Analysis_code/5.optima/resnet_like_pure/resnet_like_pure_busan.py deleted file mode 100644 index 481cd02910a2487202a5e034819023ed6995051e..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/resnet_like_pure/resnet_like_pure_busan.py +++ /dev/null @@ -1,99 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="resnet_like", region="busan"), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/resnet_like_pure_busan_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_paths = train_final_model( - best_params=best_params, - model_choose="resnet_like", - region="busan", - data_sample='pure', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로:") - for path in model_paths: - print(f" - {path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/resnet_like_pure/resnet_like_pure_daegu.py b/Analysis_code/5.optima/resnet_like_pure/resnet_like_pure_daegu.py deleted file mode 100644 index ea88a6edce2f7118f6ebc8de786dc0bfdcbc87c0..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/resnet_like_pure/resnet_like_pure_daegu.py +++ /dev/null @@ -1,99 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="resnet_like", region="daegu"), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/resnet_like_pure_daegu_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_paths = train_final_model( - best_params=best_params, - model_choose="resnet_like", - region="daegu", - data_sample='pure', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로:") - for path in model_paths: - print(f" - {path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/resnet_like_pure/resnet_like_pure_daejeon.py b/Analysis_code/5.optima/resnet_like_pure/resnet_like_pure_daejeon.py deleted file mode 100644 index a15ec6db142f103e39058f412aa0dfcb371e2a54..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/resnet_like_pure/resnet_like_pure_daejeon.py +++ /dev/null @@ -1,99 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="resnet_like", region="daejeon"), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/resnet_like_pure_daejeon_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_paths = train_final_model( - best_params=best_params, - model_choose="resnet_like", - region="daejeon", - data_sample='pure', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로:") - for path in model_paths: - print(f" - {path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/resnet_like_pure/resnet_like_pure_gwangju.py b/Analysis_code/5.optima/resnet_like_pure/resnet_like_pure_gwangju.py deleted file mode 100644 index 0e93a405a945521ae156acbe93a334c88b81519f..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/resnet_like_pure/resnet_like_pure_gwangju.py +++ /dev/null @@ -1,99 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="resnet_like", region="gwangju"), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/resnet_like_pure_gwangju_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_paths = train_final_model( - best_params=best_params, - model_choose="resnet_like", - region="gwangju", - data_sample='pure', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로:") - for path in model_paths: - print(f" - {path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/resnet_like_pure/resnet_like_pure_incheon.py b/Analysis_code/5.optima/resnet_like_pure/resnet_like_pure_incheon.py deleted file mode 100644 index 2c7f6d961bc5221ebc6fb65cb3bd6970f3709f91..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/resnet_like_pure/resnet_like_pure_incheon.py +++ /dev/null @@ -1,99 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="resnet_like", region="incheon"), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/resnet_like_pure_incheon_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_paths = train_final_model( - best_params=best_params, - model_choose="resnet_like", - region="incheon", - data_sample='pure', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로:") - for path in model_paths: - print(f" - {path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/resnet_like_pure/resnet_like_pure_seoul.py b/Analysis_code/5.optima/resnet_like_pure/resnet_like_pure_seoul.py deleted file mode 100644 index c376a97254699475da5c0fd52ed3df9fe5916ded..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/resnet_like_pure/resnet_like_pure_seoul.py +++ /dev/null @@ -1,99 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="resnet_like", region="seoul"), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/resnet_like_pure_seoul_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_paths = train_final_model( - best_params=best_params, - model_choose="resnet_like", - region="seoul", - data_sample='pure', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로:") - for path in model_paths: - print(f" - {path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/resnet_like_pure/utils.py b/Analysis_code/5.optima/resnet_like_pure/utils.py deleted file mode 100644 index 269c884ba87b91694f8a425070862e038f59125e..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/resnet_like_pure/utils.py +++ /dev/null @@ -1,790 +0,0 @@ -import torch -import torch.nn as nn -import torch.optim as optim -import numpy as np -import random -import os -import copy -from sklearn.preprocessing import QuantileTransformer, LabelEncoder, OneHotEncoder -from torch.utils.data import DataLoader, TensorDataset -from sklearn.metrics import confusion_matrix -from sklearn.utils.class_weight import compute_class_weight -import pandas as pd -import optuna -from sklearn.metrics import accuracy_score, f1_score -import joblib - - -import sys -# 파일 위치 기반으로 models 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -models_path = os.path.abspath(os.path.join(current_file_dir, '../../models')) -sys.path.insert(0, models_path) -from ft_transformer import FTTransformer -from resnet_like import ResNetLike -from deepgbm import DeepGBM -import warnings -warnings.filterwarnings('ignore') - - -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - -# PyTorch 시드 고정 -torch.manual_seed(seed) -torch.cuda.manual_seed(seed) -torch.cuda.manual_seed_all(seed) # Multi-GPU 환경에서 동일한 시드 적용 - -# PyTorch 연산의 결정적 모드 설정 -torch.backends.cudnn.deterministic = True # 실행마다 동일한 결과를 보장 -torch.backends.cudnn.benchmark = True # 성능 최적화를 활성화 (가능한 한 빠른 연산 수행) - - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - - -# 데이터셋 준비 함수 -def prepare_dataset(region, data_sample='pure', target='multi', fold=3): - - # 파일 위치 기반으로 데이터 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) - - # 데이터 경로 지정 - dat_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_train.csv") - if data_sample == 'pure': - train_path = dat_path - else: - train_path = os.path.join(data_base_dir, f'data_oversampled/{data_sample}/{data_sample}_{fold}_{region}.csv') - test_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_test.csv") - drop_col = ['multi_class','year'] - target_col = f'{target}_class' - - # 데이터 로드 - region_dat = preprocessing(pd.read_csv(dat_path, index_col=0)) - if data_sample == 'pure': - region_train = region_dat.loc[~region_dat['year'].isin([2021-fold]), :] - else: - region_train = preprocessing(pd.read_csv(train_path)) - region_val = region_dat.loc[region_dat['year'].isin([2021-fold]), :] - region_test = preprocessing(pd.read_csv(test_path)) - - # 컬럼 정렬 (일관성 유지) - common_columns = region_train.columns.to_list() - train_data = region_train[common_columns] - val_data = region_val[common_columns] - test_data = region_test[common_columns] - - # 설명변수 & 타겟 분리 - X_train = train_data.drop(columns=drop_col) - y_train = train_data[target_col] - X_val = val_data.drop(columns=drop_col) - y_val = val_data[target_col] - X_test = test_data.drop(columns=drop_col) - y_test = test_data[target_col] - - # 범주형 & 연속형 변수 분리 - original_categorical_cols = X_train.select_dtypes(include=['object', 'category', 'int64']).columns - numerical_cols = X_train.select_dtypes(include=['float64']).columns - - # 범주형 변수 One-Hot Encoding (ResNetLike는 임베딩 레이어가 없으므로) - if len(original_categorical_cols) > 0: - ohe = OneHotEncoder(sparse_output=False, handle_unknown='ignore', drop=None) - ohe.fit(X_train[original_categorical_cols]) - - # One-Hot 인코딩 적용 - X_train_cat_encoded = pd.DataFrame( - ohe.transform(X_train[original_categorical_cols]), - columns=ohe.get_feature_names_out(original_categorical_cols), - index=X_train.index - ) - X_val_cat_encoded = pd.DataFrame( - ohe.transform(X_val[original_categorical_cols]), - columns=ohe.get_feature_names_out(original_categorical_cols), - index=X_val.index - ) - X_test_cat_encoded = pd.DataFrame( - ohe.transform(X_test[original_categorical_cols]), - columns=ohe.get_feature_names_out(original_categorical_cols), - index=X_test.index - ) - - # 원래 범주형 컬럼 제거 후 One-Hot 인코딩된 컬럼 추가 - X_train = X_train.drop(columns=original_categorical_cols) - X_val = X_val.drop(columns=original_categorical_cols) - X_test = X_test.drop(columns=original_categorical_cols) - - X_train = pd.concat([X_train, X_train_cat_encoded], axis=1) - X_val = pd.concat([X_val, X_val_cat_encoded], axis=1) - X_test = pd.concat([X_test, X_test_cat_encoded], axis=1) - - # One-Hot 인코딩된 컬럼명으로 업데이트 - categorical_cols = ohe.get_feature_names_out(original_categorical_cols) - else: - categorical_cols = [] - - # 연속형 변수 Quantile Transformation - scaler = QuantileTransformer(output_distribution='normal') - scaler.fit(X_train[numerical_cols]) # Train 데이터 기준으로 학습 - - # 변환 적용 - X_train[numerical_cols] = scaler.transform(X_train[numerical_cols]) - X_val[numerical_cols] = scaler.transform(X_val[numerical_cols]) - X_test[numerical_cols] = scaler.transform(X_test[numerical_cols]) - - return X_train, X_val, X_test, y_train, y_val, y_test, categorical_cols, numerical_cols - - - -# 데이터 변환 및 dataloader 생성 함수 -def prepare_dataloader(region, data_sample='pure', target='multi', fold=3, random_state=None): - - # 파일 위치 기반으로 데이터 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) - - # 데이터 경로 지정 - dat_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_train.csv") - if data_sample == 'pure': - train_path = dat_path - else: - train_path = os.path.join(data_base_dir, f'data_oversampled/{data_sample}/{data_sample}_{fold}_{region}.csv') - test_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_test.csv") - drop_col = ['multi_class','year'] - target_col = f'{target}_class' - - # 데이터 로드 - region_dat = preprocessing(pd.read_csv(dat_path, index_col=0)) - if data_sample == 'pure': - region_train = region_dat.loc[~region_dat['year'].isin([2021-fold]), :] - else: - region_train = preprocessing(pd.read_csv(train_path)) - region_val = region_dat.loc[region_dat['year'].isin([2021-fold]), :] - region_test = preprocessing(pd.read_csv(test_path)) - - # 컬럼 정렬 (일관성 유지) - common_columns = region_train.columns.to_list() - train_data = region_train[common_columns] - val_data = region_val[common_columns] - test_data = region_test[common_columns] - - # 설명변수 & 타겟 분리 - X_train = train_data.drop(columns=drop_col) - y_train = train_data[target_col] - X_val = val_data.drop(columns=drop_col) - y_val = val_data[target_col] - X_test = test_data.drop(columns=drop_col) - y_test = test_data[target_col] - - # 범주형 & 연속형 변수 분리 - original_categorical_cols = X_train.select_dtypes(include=['object', 'category', 'int64']).columns - numerical_cols = X_train.select_dtypes(include=['float64']).columns - - # 범주형 변수 One-Hot Encoding (ResNetLike는 임베딩 레이어가 없으므로) - if len(original_categorical_cols) > 0: - ohe = OneHotEncoder(sparse_output=False, handle_unknown='ignore', drop=None) - ohe.fit(X_train[original_categorical_cols]) - - # One-Hot 인코딩 적용 - X_train_cat_encoded = pd.DataFrame( - ohe.transform(X_train[original_categorical_cols]), - columns=ohe.get_feature_names_out(original_categorical_cols), - index=X_train.index - ) - X_val_cat_encoded = pd.DataFrame( - ohe.transform(X_val[original_categorical_cols]), - columns=ohe.get_feature_names_out(original_categorical_cols), - index=X_val.index - ) - X_test_cat_encoded = pd.DataFrame( - ohe.transform(X_test[original_categorical_cols]), - columns=ohe.get_feature_names_out(original_categorical_cols), - index=X_test.index - ) - - # 원래 범주형 컬럼 제거 후 One-Hot 인코딩된 컬럼 추가 - X_train = X_train.drop(columns=original_categorical_cols) - X_val = X_val.drop(columns=original_categorical_cols) - X_test = X_test.drop(columns=original_categorical_cols) - - X_train = pd.concat([X_train, X_train_cat_encoded], axis=1) - X_val = pd.concat([X_val, X_val_cat_encoded], axis=1) - X_test = pd.concat([X_test, X_test_cat_encoded], axis=1) - - # One-Hot 인코딩된 컬럼명으로 업데이트 - categorical_cols = ohe.get_feature_names_out(original_categorical_cols) - else: - categorical_cols = [] - - # 연속형 변수 Quantile Transformation - scaler = QuantileTransformer(output_distribution='normal') - scaler.fit(X_train[numerical_cols]) # Train 데이터 기준으로 학습 - - # 변환 적용 - X_train[numerical_cols] = scaler.transform(X_train[numerical_cols]) - X_val[numerical_cols] = scaler.transform(X_val[numerical_cols]) - X_test[numerical_cols] = scaler.transform(X_test[numerical_cols]) - - # 연속형 변수와 범주형 변수 분리 - X_train_num = torch.tensor(X_train[numerical_cols].values, dtype=torch.float32) - X_train_cat = torch.tensor(X_train[categorical_cols].values, dtype=torch.float32) # One-Hot은 float32 - - X_val_num = torch.tensor(X_val[numerical_cols].values, dtype=torch.float32) - X_val_cat = torch.tensor(X_val[categorical_cols].values, dtype=torch.float32) # One-Hot은 float32 - - X_test_num = torch.tensor(X_test[numerical_cols].values, dtype=torch.float32) - X_test_cat = torch.tensor(X_test[categorical_cols].values, dtype=torch.float32) # One-Hot은 float32 - - # 레이블 변환 - if target == "binary": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.float32) # 이진 분류 → float32 - y_val_tensor = torch.tensor(y_val.values, dtype=torch.float32) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.float32) - elif target == "multi": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.long) # 다중 분류 → long - y_val_tensor = torch.tensor(y_val.values, dtype=torch.long) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.long) - else: - raise ValueError("target must be 'binary' or 'multi'") - - # TensorDataset 생성 - train_dataset = TensorDataset(X_train_num, X_train_cat, y_train_tensor) - val_dataset = TensorDataset(X_val_num, X_val_cat, y_val_tensor) - test_dataset = TensorDataset(X_test_num, X_test_cat, y_test_tensor) - - # DataLoader 생성 - # batch_size는 함수 파라미터로 받아서 사용 - if random_state == None: - train_loader = DataLoader(train_dataset, batch_size=64, shuffle=True) - else: - train_loader = DataLoader(train_dataset, batch_size=64, shuffle=True, generator=torch.Generator().manual_seed(random_state)) - val_loader = DataLoader(val_dataset, batch_size=64, shuffle=False) - test_loader = DataLoader(test_dataset, batch_size=64, shuffle=False) - - return X_train, categorical_cols, numerical_cols, train_loader, val_loader, test_loader, y_train, scaler - -# 데이터 변환 및 dataloader 생성 함수 (batch_size 파라미터 추가 버전) -def prepare_dataloader_with_batchsize(region, data_sample='pure', target='multi', fold=3, random_state=None, batch_size=64): - # 파일 위치 기반으로 데이터 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) - - # 데이터 경로 지정 - dat_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_train.csv") - if data_sample == 'pure': - train_path = dat_path - else: - train_path = os.path.join(data_base_dir, f'data_oversampled/{data_sample}/{data_sample}_{fold}_{region}.csv') - test_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_test.csv") - drop_col = ['multi_class','year'] - target_col = f'{target}_class' - - # 데이터 로드 - region_dat = preprocessing(pd.read_csv(dat_path, index_col=0)) - if data_sample == 'pure': - region_train = region_dat.loc[~region_dat['year'].isin([2021-fold]), :] - else: - region_train = preprocessing(pd.read_csv(train_path)) - region_val = region_dat.loc[region_dat['year'].isin([2021-fold]), :] - region_test = preprocessing(pd.read_csv(test_path)) - - # 컬럼 정렬 (일관성 유지) - common_columns = region_train.columns.to_list() - train_data = region_train[common_columns] - val_data = region_val[common_columns] - test_data = region_test[common_columns] - - # 설명변수 & 타겟 분리 - X_train = train_data.drop(columns=drop_col) - y_train = train_data[target_col] - X_val = val_data.drop(columns=drop_col) - y_val = val_data[target_col] - X_test = test_data.drop(columns=drop_col) - y_test = test_data[target_col] - - # 범주형 & 연속형 변수 분리 - original_categorical_cols = X_train.select_dtypes(include=['object', 'category', 'int64']).columns - numerical_cols = X_train.select_dtypes(include=['float64']).columns - - # 범주형 변수 One-Hot Encoding (ResNetLike는 임베딩 레이어가 없으므로) - if len(original_categorical_cols) > 0: - ohe = OneHotEncoder(sparse_output=False, handle_unknown='ignore', drop=None) - ohe.fit(X_train[original_categorical_cols]) - - # One-Hot 인코딩 적용 - X_train_cat_encoded = pd.DataFrame( - ohe.transform(X_train[original_categorical_cols]), - columns=ohe.get_feature_names_out(original_categorical_cols), - index=X_train.index - ) - X_val_cat_encoded = pd.DataFrame( - ohe.transform(X_val[original_categorical_cols]), - columns=ohe.get_feature_names_out(original_categorical_cols), - index=X_val.index - ) - X_test_cat_encoded = pd.DataFrame( - ohe.transform(X_test[original_categorical_cols]), - columns=ohe.get_feature_names_out(original_categorical_cols), - index=X_test.index - ) - - # 원래 범주형 컬럼 제거 후 One-Hot 인코딩된 컬럼 추가 - X_train = X_train.drop(columns=original_categorical_cols) - X_val = X_val.drop(columns=original_categorical_cols) - X_test = X_test.drop(columns=original_categorical_cols) - - X_train = pd.concat([X_train, X_train_cat_encoded], axis=1) - X_val = pd.concat([X_val, X_val_cat_encoded], axis=1) - X_test = pd.concat([X_test, X_test_cat_encoded], axis=1) - - # One-Hot 인코딩된 컬럼명으로 업데이트 - categorical_cols = ohe.get_feature_names_out(original_categorical_cols) - else: - categorical_cols = [] - - # 연속형 변수 Quantile Transformation - scaler = QuantileTransformer(output_distribution='normal') - scaler.fit(X_train[numerical_cols]) # Train 데이터 기준으로 학습 - - # 변환 적용 - X_train[numerical_cols] = scaler.transform(X_train[numerical_cols]) - X_val[numerical_cols] = scaler.transform(X_val[numerical_cols]) - X_test[numerical_cols] = scaler.transform(X_test[numerical_cols]) - - # 연속형 변수와 범주형 변수 분리 - X_train_num = torch.tensor(X_train[numerical_cols].values, dtype=torch.float32) - X_train_cat = torch.tensor(X_train[categorical_cols].values, dtype=torch.float32) # One-Hot은 float32 - - X_val_num = torch.tensor(X_val[numerical_cols].values, dtype=torch.float32) - X_val_cat = torch.tensor(X_val[categorical_cols].values, dtype=torch.float32) # One-Hot은 float32 - - X_test_num = torch.tensor(X_test[numerical_cols].values, dtype=torch.float32) - X_test_cat = torch.tensor(X_test[categorical_cols].values, dtype=torch.float32) # One-Hot은 float32 - - # 레이블 변환 - if target == "binary": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.float32) # 이진 분류 → float32 - y_val_tensor = torch.tensor(y_val.values, dtype=torch.float32) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.float32) - elif target == "multi": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.long) # 다중 분류 → long - y_val_tensor = torch.tensor(y_val.values, dtype=torch.long) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.long) - else: - raise ValueError("target must be 'binary' or 'multi'") - - # TensorDataset 생성 - train_dataset = TensorDataset(X_train_num, X_train_cat, y_train_tensor) - val_dataset = TensorDataset(X_val_num, X_val_cat, y_val_tensor) - test_dataset = TensorDataset(X_test_num, X_test_cat, y_test_tensor) - - # DataLoader 생성 (batch_size 파라미터 사용) - if random_state == None: - train_loader = DataLoader(train_dataset, batch_size=batch_size, shuffle=True) - else: - train_loader = DataLoader(train_dataset, batch_size=batch_size, shuffle=True, generator=torch.Generator().manual_seed(random_state)) - val_loader = DataLoader(val_dataset, batch_size=batch_size, shuffle=False) - test_loader = DataLoader(test_dataset, batch_size=batch_size, shuffle=False) - - return X_train, categorical_cols, numerical_cols, train_loader, val_loader, test_loader, y_train, scaler - - -def calculate_csi(y_true, pred): - - cm = confusion_matrix(y_true, pred) # 변수 이름을 cm으로 변경 - # 혼동 행렬에서 H, F, M 추출 - H = (cm[0, 0] + cm[1, 1]) - - F = (cm[1, 0] + cm[2, 0] + - cm[0, 1] + cm[2, 1]) - - M = (cm[0, 2] + cm[1, 2]) - - # CSI 계산 - CSI = H / (H + F + M + 1e-10) - return CSI - -def sample_weight(y_train): - class_weights = compute_class_weight( - class_weight='balanced', - classes=np.unique(y_train), # 고유 클래스 - y=y_train # 학습 데이터 레이블 - ) - sample_weights = np.array([class_weights[label] for label in y_train]) - - return sample_weights - -# 하이퍼파라미터 최적화 함수 정의 -def objective(trial, model_choose, region, data_sample='pure', target='multi', n_folds=3, random_state=42): - # GPU 사용 가능 여부 확인 및 device 설정 - device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') - val_scores = [] - - # --- 1. 하이퍼파라미터 탐색 범위 정의 (수정됨) --- - if model_choose == "ft_transformer": - d_token = trial.suggest_int("d_token", 64, 256, step=32) - n_blocks = trial.suggest_int("n_blocks", 2, 6) # 깊이 축소로 과적합 방지 - n_heads = trial.suggest_categorical("n_heads", [4, 8]) - # d_token은 n_heads의 배수여야 함 (FT-Transformer의 구조적 제약 대응) - if d_token % n_heads != 0: - d_token = (d_token // n_heads) * n_heads - - attention_dropout = trial.suggest_float("attention_dropout", 0.1, 0.4) - ffn_dropout = trial.suggest_float("ffn_dropout", 0.1, 0.4) - lr = trial.suggest_float("lr", 1e-5, 1e-2, log=True) # 범위 확대 - weight_decay = trial.suggest_float("weight_decay", 1e-4, 1e-1, log=True) # 더 공격적인 범위로 확장 - batch_size = trial.suggest_categorical("batch_size", [32, 64, 128, 256]) # Batch Size 추가 - - elif model_choose == 'resnet_like': - d_main = trial.suggest_int("d_main", 64, 256, step=32) - d_hidden = trial.suggest_int("d_hidden", 64, 512, step=64) - n_blocks = trial.suggest_int("n_blocks", 2, 5) # 너무 깊지 않게 조절 - dropout_first = trial.suggest_float("dropout_first", 0.1, 0.4) - dropout_second = trial.suggest_float("dropout_second", 0.0, 0.2) - lr = trial.suggest_float("lr", 1e-5, 1e-2, log=True) - weight_decay = trial.suggest_float("weight_decay", 1e-4, 1e-1, log=True) # 더 공격적인 범위로 확장 - batch_size = trial.suggest_categorical("batch_size", [32, 64, 128, 256]) # Batch Size 추가 - - elif model_choose == 'deepgbm': - # DeepGBM의 경우 모델 특성에 맞춰 ResNet 블록 및 임베딩 차원 조절 - d_main = trial.suggest_int("d_main", 64, 256, step=32) - d_hidden = trial.suggest_int("d_hidden", 64, 256, step=64) - n_blocks = trial.suggest_int("n_blocks", 2, 6) - dropout = trial.suggest_float("dropout", 0.1, 0.4) - lr = trial.suggest_float("lr", 1e-5, 1e-2, log=True) - weight_decay = trial.suggest_float("weight_decay", 1e-4, 1e-1, log=True) # 더 공격적인 범위로 확장 - batch_size = trial.suggest_categorical("batch_size", [32, 64, 128, 256]) # Batch Size 추가 - - # --- 2. Fold별 학습 및 교차 검증 --- - for fold in range(1, n_folds + 1): - X_train_df, categorical_cols, numerical_cols, train_loader, val_loader, _, y_train, _ = prepare_dataloader_with_batchsize( - region, data_sample=data_sample, target=target, fold=fold, random_state=random_state, batch_size=batch_size - ) - - # 모델 초기화 - if model_choose == "ft_transformer": - model = FTTransformer( - num_features=len(numerical_cols), - cat_cardinalities=[len(X_train_df[col].unique()) for col in categorical_cols], - d_token=d_token, - n_blocks=n_blocks, - n_heads=n_heads, - attention_dropout=attention_dropout, - ffn_dropout=ffn_dropout, - num_classes=3 - ).to(device) - elif model_choose == 'resnet_like': - input_dim = len(numerical_cols) + len(categorical_cols) - model = ResNetLike( - input_dim=input_dim, - d_main=d_main, - d_hidden=d_hidden, - n_blocks=n_blocks, - dropout_first=dropout_first, - dropout_second=dropout_second, - num_classes=3 - ).to(device) - elif model_choose == 'deepgbm': - model = DeepGBM( - num_features=len(numerical_cols), - cat_features=[len(X_train_df[col].unique()) for col in categorical_cols], - d_main=d_main, - d_hidden=d_hidden, - n_blocks=n_blocks, - dropout=dropout, - num_classes=3 - ).to(device) - - # 클래스 가중치 계산 및 손실 함수 설정 (Label Smoothing 적용) - if target == 'multi': - class_weights = compute_class_weight( - class_weight='balanced', - classes=np.unique(y_train), - y=y_train - ) - # 클래스별 가중치 로그 출력 - unique_classes = np.unique(y_train) - class_counts = {cls: np.sum(y_train == cls) for cls in unique_classes} - print(f" Fold {fold} - 클래스별 가중치: {dict(zip(unique_classes, class_weights))} (클래스별 샘플 수: {class_counts})") - class_weights_tensor = torch.tensor(class_weights, dtype=torch.float32).to(device) - criterion = nn.CrossEntropyLoss(weight=class_weights_tensor, label_smoothing=0.0) # Label Smoothing 추가 - else: - criterion = nn.BCEWithLogitsLoss() - optimizer = optim.AdamW(model.parameters(), lr=lr, weight_decay=weight_decay) - - # 학습률 스케줄러 추가: 성능 정체 시 LR을 0.5배 감소 (검증 CSI 기준) - scheduler = optim.lr_scheduler.ReduceLROnPlateau(optimizer, mode='max', factor=0.5, patience=3) - - # 학습 설정 (에폭 및 페이션스 상향) - epochs = 200 - patience = 12 # 딥러닝의 정체 구간을 고려하여 소폭 상향 - best_fold_csi = 0 - counter = 0 - - for epoch in range(epochs): - model.train() - for x_num_batch, x_cat_batch, y_batch in train_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - - optimizer.zero_grad() - y_pred = model(x_num_batch, x_cat_batch) - loss = criterion(y_pred, y_batch if target == 'multi' else y_batch.float()) - loss.backward() - optimizer.step() - - # Validation 평가 - model.eval() - y_pred_val, y_true_val = [], [] - with torch.no_grad(): - for x_num_batch, x_cat_batch, y_batch in val_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - output = model(x_num_batch, x_cat_batch) - pred = output.argmax(dim=1) if target == 'multi' else (torch.sigmoid(output) >= 0.5).long() - - y_pred_val.extend(pred.cpu().numpy()) - y_true_val.extend(y_batch.cpu().numpy()) - - # CSI 계산 및 스케줄러 업데이트 - val_csi = calculate_csi(y_true_val, y_pred_val) - scheduler.step(val_csi) - - # Optuna Pruning 적용 (첫 번째 Fold에서 조기 종료 판단 강화) - trial.report(val_csi, epoch) - if trial.should_prune(): - raise optuna.exceptions.TrialPruned() - - # Early Stopping 체크 - if val_csi > best_fold_csi: - best_fold_csi = val_csi - counter = 0 - else: - counter += 1 - - if counter >= patience: - break - - val_scores.append(best_fold_csi) - - # 모든 fold의 평균 성능 반환 - return np.mean(val_scores) - - -# 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 함수 -def train_final_model(best_params, model_choose, region, data_sample='pure', target='multi', n_folds=3, random_state=42): - """ - 최적화된 하이퍼파라미터로 최종 모델을 학습하고 저장합니다. - - Args: - best_params: 최적화된 하이퍼파라미터 딕셔너리 - model_choose: 모델 선택 ('ft_transformer', 'resnet_like', 'deepgbm') - region: 지역명 - data_sample: 데이터 샘플 타입 ('pure', 'smote', etc.) - target: 타겟 타입 ('multi', 'binary') - n_folds: 교차 검증 fold 수 - random_state: 랜덤 시드 - - Returns: - 저장된 모델 경로 리스트 - """ - # GPU 사용 가능 여부 확인 및 device 설정 - device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') - - models = [] - scalers = [] # scaler 리스트 추가 - - print("최종 모델 학습 시작...") - - for fold in range(1, n_folds + 1): - print(f"Fold {fold} 학습 중...") - - # 최적화된 batch_size 사용 - batch_size = best_params.get("batch_size", 64) - X_train_df, categorical_cols, numerical_cols, train_loader, val_loader, _, y_train, scaler = prepare_dataloader_with_batchsize( - region, data_sample=data_sample, target=target, fold=fold, random_state=random_state, batch_size=batch_size - ) - - # 모델 초기화 - if model_choose == "ft_transformer": - d_token = best_params["d_token"] - n_heads = best_params.get("n_heads", 8) - # d_token은 n_heads의 배수여야 함 (FT-Transformer의 구조적 제약 대응) - if d_token % n_heads != 0: - d_token = (d_token // n_heads) * n_heads - - model = FTTransformer( - num_features=len(numerical_cols), - cat_cardinalities=[len(X_train_df[col].unique()) for col in categorical_cols], - d_token=d_token, - n_blocks=best_params["n_blocks"], - n_heads=n_heads, - attention_dropout=best_params["attention_dropout"], - ffn_dropout=best_params["ffn_dropout"], - num_classes=3 - ).to(device) - elif model_choose == 'resnet_like': - input_dim = len(numerical_cols) + len(categorical_cols) - model = ResNetLike( - input_dim=input_dim, - d_main=best_params["d_main"], - d_hidden=best_params["d_hidden"], - n_blocks=best_params["n_blocks"], - dropout_first=best_params["dropout_first"], - dropout_second=best_params["dropout_second"], - num_classes=3 - ).to(device) - elif model_choose == 'deepgbm': - model = DeepGBM( - num_features=len(numerical_cols), - cat_features=[len(X_train_df[col].unique()) for col in categorical_cols], - d_main=best_params["d_main"], - d_hidden=best_params["d_hidden"], - n_blocks=best_params["n_blocks"], - dropout=best_params["dropout"], - num_classes=3 - ).to(device) - else: - raise ValueError(f"Unknown model_choose: {model_choose}") - - # 클래스 가중치 계산 및 손실 함수 설정 (Label Smoothing 적용) - if target == 'multi': - class_weights = compute_class_weight( - class_weight='balanced', - classes=np.unique(y_train), - y=y_train - ) - class_weights_tensor = torch.tensor(class_weights, dtype=torch.float32).to(device) - criterion = nn.CrossEntropyLoss(weight=class_weights_tensor, label_smoothing=0.0) # Label Smoothing 추가 - else: - criterion = nn.BCEWithLogitsLoss() - optimizer = optim.AdamW(model.parameters(), lr=best_params["lr"], weight_decay=best_params["weight_decay"]) - - # 학습률 스케줄러 - scheduler = optim.lr_scheduler.ReduceLROnPlateau(optimizer, mode='max', factor=0.5, patience=3) - - # 학습 설정 - epochs = 200 - patience = 12 - best_fold_csi = 0 - counter = 0 - best_model = None - - for epoch in range(epochs): - model.train() - for x_num_batch, x_cat_batch, y_batch in train_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - - optimizer.zero_grad() - y_pred = model(x_num_batch, x_cat_batch) - loss = criterion(y_pred, y_batch if target == 'multi' else y_batch.float()) - loss.backward() - optimizer.step() - - # Validation 평가 - model.eval() - y_pred_val, y_true_val = [], [] - with torch.no_grad(): - for x_num_batch, x_cat_batch, y_batch in val_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - output = model(x_num_batch, x_cat_batch) - pred = output.argmax(dim=1) if target == 'multi' else (torch.sigmoid(output) >= 0.5).long() - - y_pred_val.extend(pred.cpu().numpy()) - y_true_val.extend(y_batch.cpu().numpy()) - - # CSI 계산 및 스케줄러 업데이트 - val_csi = calculate_csi(y_true_val, y_pred_val) - scheduler.step(val_csi) - - # Early Stopping 체크 - if val_csi > best_fold_csi: - best_fold_csi = val_csi - counter = 0 - best_model = copy.deepcopy(model) - else: - counter += 1 - - if counter >= patience: - print(f" Early stopping at epoch {epoch+1}, Best CSI: {best_fold_csi:.4f}") - break - - if best_model is None: - best_model = model - - scalers.append(scaler) # scaler 저장 (fold 순서대로) - models.append(best_model) - print(f" Fold {fold} 학습 완료 (검증 CSI: {best_fold_csi:.4f})") - - # 모델 저장 경로 설정 - save_dir = f'../save_model/{model_choose}_optima' - os.makedirs(save_dir, exist_ok=True) - - # 파일명 생성 - if data_sample == 'pure': - model_filename = f'{model_choose}_pure_{region}.pkl' - else: - model_filename = f'{model_choose}_{data_sample}_{region}.pkl' - - model_path = f'{save_dir}/{model_filename}' - - # 리스트에 담아 한 번에 저장 - joblib.dump(models, model_path) - print(f"\n모든 모델 저장 완료: {model_path} (총 {len(models)}개 fold)") - - # Scaler 별도 저장 - scaler_save_dir = f'../save_model/{model_choose}_optima/scaler' - os.makedirs(scaler_save_dir, exist_ok=True) - - # 파일명 생성 (모델과 동일한 패턴) - if data_sample == 'pure': - scaler_filename = f'{model_choose}_pure_{region}_scaler.pkl' - else: - scaler_filename = f'{model_choose}_{data_sample}_{region}_scaler.pkl' - - scaler_path = f'{scaler_save_dir}/{scaler_filename}' - joblib.dump(scalers, scaler_path) - print(f"Scaler 저장 완료: {scaler_path} (총 {len(scalers)}개 fold)") - - return model_path diff --git a/Analysis_code/5.optima/resnet_like_smote/resnet_like_smote_busan.py b/Analysis_code/5.optima/resnet_like_smote/resnet_like_smote_busan.py deleted file mode 100644 index 298c2426fb78657af8e7ce4f93b3ed76c14b9f8e..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/resnet_like_smote/resnet_like_smote_busan.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="resnet_like", region="busan", data_sample='smote'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/resnet_like_smote_busan_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="resnet_like", - region="busan", - data_sample='smote', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/resnet_like_smote/resnet_like_smote_daegu.py b/Analysis_code/5.optima/resnet_like_smote/resnet_like_smote_daegu.py deleted file mode 100644 index 22fd4665849aaaa26b298336e5209874f2f4155c..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/resnet_like_smote/resnet_like_smote_daegu.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="resnet_like", region="daegu", data_sample='smote'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/resnet_like_smote_daegu_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="resnet_like", - region="daegu", - data_sample='smote', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/resnet_like_smote/resnet_like_smote_daejeon.py b/Analysis_code/5.optima/resnet_like_smote/resnet_like_smote_daejeon.py deleted file mode 100644 index 871a94bd7e3b02b2a3d4787dd4787d8f18c72b74..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/resnet_like_smote/resnet_like_smote_daejeon.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="resnet_like", region="daejeon", data_sample='smote'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/resnet_like_smote_daejeon_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="resnet_like", - region="daejeon", - data_sample='smote', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/resnet_like_smote/resnet_like_smote_gwangju.py b/Analysis_code/5.optima/resnet_like_smote/resnet_like_smote_gwangju.py deleted file mode 100644 index f8031fb03128876a496b524c07b559da0ff42dc1..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/resnet_like_smote/resnet_like_smote_gwangju.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="resnet_like", region="gwangju", data_sample='smote'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/resnet_like_smote_gwangju_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="resnet_like", - region="gwangju", - data_sample='smote', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/resnet_like_smote/resnet_like_smote_incheon.py b/Analysis_code/5.optima/resnet_like_smote/resnet_like_smote_incheon.py deleted file mode 100644 index 280efff110198ef0e6169366a654ecdbafe97ed0..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/resnet_like_smote/resnet_like_smote_incheon.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="resnet_like", region="incheon", data_sample='smote'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/resnet_like_smote_incheon_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="resnet_like", - region="incheon", - data_sample='smote', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/resnet_like_smote/resnet_like_smote_seoul.py b/Analysis_code/5.optima/resnet_like_smote/resnet_like_smote_seoul.py deleted file mode 100644 index 48146fee7c12fe60c0f57396f5406fa5dedc408e..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/resnet_like_smote/resnet_like_smote_seoul.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="resnet_like", region="seoul", data_sample='smote'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/resnet_like_smote_seoul_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="resnet_like", - region="seoul", - data_sample='smote', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/resnet_like_smote/utils.py b/Analysis_code/5.optima/resnet_like_smote/utils.py deleted file mode 100644 index 2cebe5700041635baab0fec01daa0ea1b11f7c4e..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/resnet_like_smote/utils.py +++ /dev/null @@ -1,718 +0,0 @@ -import torch -import torch.nn as nn -import torch.optim as optim -import numpy as np -import random -import os -import copy -from sklearn.preprocessing import QuantileTransformer, LabelEncoder -from torch.utils.data import DataLoader, TensorDataset -from sklearn.metrics import confusion_matrix -from sklearn.utils.class_weight import compute_class_weight -import pandas as pd -import optuna -from sklearn.metrics import accuracy_score, f1_score -import joblib - - -import sys -# 파일 위치 기반으로 models 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -models_path = os.path.abspath(os.path.join(current_file_dir, '../../models')) -sys.path.insert(0, models_path) -from ft_transformer import FTTransformer -from resnet_like import ResNetLike -from deepgbm import DeepGBM -import warnings -warnings.filterwarnings('ignore') - - -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - -# PyTorch 시드 고정 -torch.manual_seed(seed) -torch.cuda.manual_seed(seed) -torch.cuda.manual_seed_all(seed) # Multi-GPU 환경에서 동일한 시드 적용 - -# PyTorch 연산의 결정적 모드 설정 -torch.backends.cudnn.deterministic = True # 실행마다 동일한 결과를 보장 -torch.backends.cudnn.benchmark = True # 성능 최적화를 활성화 (가능한 한 빠른 연산 수행) - - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - - -# 데이터셋 준비 함수 -def prepare_dataset(region, data_sample='pure', target='multi', fold=3): - # 파일 위치 기반으로 데이터 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) - - # 데이터 경로 지정 - dat_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_train.csv") - if data_sample == 'pure': - train_path = dat_path - else: - train_path = os.path.join(data_base_dir, f'data_oversampled/{data_sample}/{data_sample}_{fold}_{region}.csv') - test_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_test.csv") - drop_col = ['multi_class','year'] - target_col = f'{target}_class' - - # 데이터 로드 - region_dat = preprocessing(pd.read_csv(dat_path, index_col=0)) - if data_sample == 'pure': - region_train = region_dat.loc[~region_dat['year'].isin([2021-fold]), :] - else: - region_train = preprocessing(pd.read_csv(train_path)) - region_val = region_dat.loc[region_dat['year'].isin([2021-fold]), :] - region_test = preprocessing(pd.read_csv(test_path)) - - # 컬럼 정렬 (일관성 유지) - common_columns = region_train.columns.to_list() - train_data = region_train[common_columns] - val_data = region_val[common_columns] - test_data = region_test[common_columns] - - # 설명변수 & 타겟 분리 - X_train = train_data.drop(columns=drop_col) - y_train = train_data[target_col] - X_val = val_data.drop(columns=drop_col) - y_val = val_data[target_col] - X_test = test_data.drop(columns=drop_col) - y_test = test_data[target_col] - - # 범주형 & 연속형 변수 분리 - categorical_cols = X_train.select_dtypes(include=['object', 'category', 'int64']).columns - numerical_cols = X_train.select_dtypes(include=['float64']).columns - - # 범주형 변수 Label Encoding - label_encoders = {} - for col in categorical_cols: - le = LabelEncoder() - le.fit(X_train[col]) # Train 데이터 기준으로 학습 - label_encoders[col] = le - - # 변환 적용 - for col in categorical_cols: - X_train[col] = label_encoders[col].transform(X_train[col]) - X_val[col] = label_encoders[col].transform(X_val[col]) - X_test[col] = label_encoders[col].transform(X_test[col]) - - # 연속형 변수 Quantile Transformation - scaler = QuantileTransformer(output_distribution='normal') - scaler.fit(X_train[numerical_cols]) # Train 데이터 기준으로 학습 - - # 변환 적용 - X_train[numerical_cols] = scaler.transform(X_train[numerical_cols]) - X_val[numerical_cols] = scaler.transform(X_val[numerical_cols]) - X_test[numerical_cols] = scaler.transform(X_test[numerical_cols]) - - return X_train, X_val, X_test, y_train, y_val, y_test, categorical_cols, numerical_cols - - - -# 데이터 변환 및 dataloader 생성 함수 -def prepare_dataloader(region, data_sample='pure', target='multi', fold=3, random_state=None): - # 파일 위치 기반으로 데이터 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) - - # 데이터 경로 지정 - dat_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_train.csv") - if data_sample == 'pure': - train_path = dat_path - else: - train_path = os.path.join(data_base_dir, f'data_oversampled/{data_sample}/{data_sample}_{fold}_{region}.csv') - test_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_test.csv") - drop_col = ['multi_class','year'] - target_col = f'{target}_class' - - # 데이터 로드 - region_dat = preprocessing(pd.read_csv(dat_path, index_col=0)) - if data_sample == 'pure': - region_train = region_dat.loc[~region_dat['year'].isin([2021-fold]), :] - else: - region_train = preprocessing(pd.read_csv(train_path)) - region_val = region_dat.loc[region_dat['year'].isin([2021-fold]), :] - region_test = preprocessing(pd.read_csv(test_path)) - - # 컬럼 정렬 (일관성 유지) - common_columns = region_train.columns.to_list() - train_data = region_train[common_columns] - val_data = region_val[common_columns] - test_data = region_test[common_columns] - - # 설명변수 & 타겟 분리 - X_train = train_data.drop(columns=drop_col) - y_train = train_data[target_col] - X_val = val_data.drop(columns=drop_col) - y_val = val_data[target_col] - X_test = test_data.drop(columns=drop_col) - y_test = test_data[target_col] - - # 범주형 & 연속형 변수 분리 - categorical_cols = X_train.select_dtypes(include=['object', 'category', 'int64']).columns - numerical_cols = X_train.select_dtypes(include=['float64']).columns - - # 범주형 변수 Label Encoding - label_encoders = {} - for col in categorical_cols: - le = LabelEncoder() - le.fit(X_train[col]) # Train 데이터 기준으로 학습 - label_encoders[col] = le - - # 변환 적용 - for col in categorical_cols: - X_train[col] = label_encoders[col].transform(X_train[col]) - X_val[col] = label_encoders[col].transform(X_val[col]) - X_test[col] = label_encoders[col].transform(X_test[col]) - - # 연속형 변수 Quantile Transformation - scaler = QuantileTransformer(output_distribution='normal') - scaler.fit(X_train[numerical_cols]) # Train 데이터 기준으로 학습 - - # 변환 적용 - X_train[numerical_cols] = scaler.transform(X_train[numerical_cols]) - X_val[numerical_cols] = scaler.transform(X_val[numerical_cols]) - X_test[numerical_cols] = scaler.transform(X_test[numerical_cols]) - - # 연속형 변수와 범주형 변수 분리 - X_train_num = torch.tensor(X_train[numerical_cols].values, dtype=torch.float32) - X_train_cat = torch.tensor(X_train[categorical_cols].values, dtype=torch.long) - - X_val_num = torch.tensor(X_val[numerical_cols].values, dtype=torch.float32) - X_val_cat = torch.tensor(X_val[categorical_cols].values, dtype=torch.long) - - X_test_num = torch.tensor(X_test[numerical_cols].values, dtype=torch.float32) - X_test_cat = torch.tensor(X_test[categorical_cols].values, dtype=torch.long) - - # 레이블 변환 - if target == "binary": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.float32) # 이진 분류 → float32 - y_val_tensor = torch.tensor(y_val.values, dtype=torch.float32) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.float32) - elif target == "multi": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.long) # 다중 분류 → long - y_val_tensor = torch.tensor(y_val.values, dtype=torch.long) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.long) - else: - raise ValueError("target must be 'binary' or 'multi'") - - # TensorDataset 생성 - train_dataset = TensorDataset(X_train_num, X_train_cat, y_train_tensor) - val_dataset = TensorDataset(X_val_num, X_val_cat, y_val_tensor) - test_dataset = TensorDataset(X_test_num, X_test_cat, y_test_tensor) - - # DataLoader 생성 - if random_state == None: - train_loader = DataLoader(train_dataset, batch_size=64, shuffle=True) - else: - train_loader = DataLoader(train_dataset, batch_size=64, shuffle=True, generator=torch.Generator().manual_seed(random_state)) - val_loader = DataLoader(val_dataset, batch_size=64, shuffle=False) - test_loader = DataLoader(test_dataset, batch_size=64, shuffle=False) - - return X_train, categorical_cols, numerical_cols, train_loader, val_loader, test_loader - -# 데이터 변환 및 dataloader 생성 함수 (batch_size 파라미터 추가 버전) -def prepare_dataloader_with_batchsize(region, data_sample='pure', target='multi', fold=3, random_state=None, batch_size=64): - # 파일 위치 기반으로 데이터 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) - - # 데이터 경로 지정 - dat_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_train.csv") - if data_sample == 'pure': - train_path = dat_path - else: - train_path = os.path.join(data_base_dir, f'data_oversampled/{data_sample}/{data_sample}_{fold}_{region}.csv') - test_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_test.csv") - drop_col = ['multi_class','year'] - target_col = f'{target}_class' - - # 데이터 로드 - region_dat = preprocessing(pd.read_csv(dat_path, index_col=0)) - if data_sample == 'pure': - region_train = region_dat.loc[~region_dat['year'].isin([2021-fold]), :] - else: - region_train = preprocessing(pd.read_csv(train_path)) - region_val = region_dat.loc[region_dat['year'].isin([2021-fold]), :] - region_test = preprocessing(pd.read_csv(test_path)) - - # 컬럼 정렬 (일관성 유지) - common_columns = region_train.columns.to_list() - train_data = region_train[common_columns] - val_data = region_val[common_columns] - test_data = region_test[common_columns] - - # 설명변수 & 타겟 분리 - X_train = train_data.drop(columns=drop_col) - y_train = train_data[target_col] - X_val = val_data.drop(columns=drop_col) - y_val = val_data[target_col] - X_test = test_data.drop(columns=drop_col) - y_test = test_data[target_col] - - # 범주형 & 연속형 변수 분리 - categorical_cols = X_train.select_dtypes(include=['object', 'category', 'int64']).columns - numerical_cols = X_train.select_dtypes(include=['float64']).columns - - # 범주형 변수 Label Encoding - label_encoders = {} - for col in categorical_cols: - le = LabelEncoder() - le.fit(X_train[col]) # Train 데이터 기준으로 학습 - label_encoders[col] = le - - # 변환 적용 - for col in categorical_cols: - X_train[col] = label_encoders[col].transform(X_train[col]) - X_val[col] = label_encoders[col].transform(X_val[col]) - X_test[col] = label_encoders[col].transform(X_test[col]) - - # 연속형 변수 Quantile Transformation - scaler = QuantileTransformer(output_distribution='normal') - scaler.fit(X_train[numerical_cols]) # Train 데이터 기준으로 학습 - - # 변환 적용 - X_train[numerical_cols] = scaler.transform(X_train[numerical_cols]) - X_val[numerical_cols] = scaler.transform(X_val[numerical_cols]) - X_test[numerical_cols] = scaler.transform(X_test[numerical_cols]) - - # 연속형 변수와 범주형 변수 분리 - X_train_num = torch.tensor(X_train[numerical_cols].values, dtype=torch.float32) - X_train_cat = torch.tensor(X_train[categorical_cols].values, dtype=torch.long) - - X_val_num = torch.tensor(X_val[numerical_cols].values, dtype=torch.float32) - X_val_cat = torch.tensor(X_val[categorical_cols].values, dtype=torch.long) - - X_test_num = torch.tensor(X_test[numerical_cols].values, dtype=torch.float32) - X_test_cat = torch.tensor(X_test[categorical_cols].values, dtype=torch.long) - - # 레이블 변환 - if target == "binary": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.float32) # 이진 분류 → float32 - y_val_tensor = torch.tensor(y_val.values, dtype=torch.float32) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.float32) - elif target == "multi": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.long) # 다중 분류 → long - y_val_tensor = torch.tensor(y_val.values, dtype=torch.long) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.long) - else: - raise ValueError("target must be 'binary' or 'multi'") - - # TensorDataset 생성 - train_dataset = TensorDataset(X_train_num, X_train_cat, y_train_tensor) - val_dataset = TensorDataset(X_val_num, X_val_cat, y_val_tensor) - test_dataset = TensorDataset(X_test_num, X_test_cat, y_test_tensor) - - # DataLoader 생성 (batch_size 파라미터 사용) - if random_state == None: - train_loader = DataLoader(train_dataset, batch_size=batch_size, shuffle=True) - else: - train_loader = DataLoader(train_dataset, batch_size=batch_size, shuffle=True, generator=torch.Generator().manual_seed(random_state)) - val_loader = DataLoader(val_dataset, batch_size=batch_size, shuffle=False) - test_loader = DataLoader(test_dataset, batch_size=batch_size, shuffle=False) - - return X_train, categorical_cols, numerical_cols, train_loader, val_loader, test_loader, y_train, scaler - - -def calculate_csi(y_true, pred): - - cm = confusion_matrix(y_true, pred) # 변수 이름을 cm으로 변경 - # 혼동 행렬에서 H, F, M 추출 - H = (cm[0, 0] + cm[1, 1]) - - F = (cm[1, 0] + cm[2, 0] + - cm[0, 1] + cm[2, 1]) - - M = (cm[0, 2] + cm[1, 2]) - - # CSI 계산 - CSI = H / (H + F + M + 1e-10) - return CSI - -def sample_weight(y_train): - class_weights = compute_class_weight( - class_weight='balanced', - classes=np.unique(y_train), # 고유 클래스 - y=y_train # 학습 데이터 레이블 - ) - sample_weights = np.array([class_weights[label] for label in y_train]) - - return sample_weights - -# 하이퍼파라미터 최적화 함수 정의 -def objective(trial, model_choose, region, data_sample='pure', target='multi', n_folds=3, random_state=42): - # GPU 사용 가능 여부 확인 및 device 설정 - device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') - val_scores = [] - - # --- 1. 하이퍼파라미터 탐색 범위 정의 (수정됨) --- - if model_choose == "ft_transformer": - d_token = trial.suggest_int("d_token", 64, 256, step=32) - n_blocks = trial.suggest_int("n_blocks", 2, 6) # 깊이 축소로 과적합 방지 - n_heads = trial.suggest_categorical("n_heads", [4, 8]) - # d_token은 n_heads의 배수여야 함 (FT-Transformer의 구조적 제약 대응) - if d_token % n_heads != 0: - d_token = (d_token // n_heads) * n_heads - - attention_dropout = trial.suggest_float("attention_dropout", 0.1, 0.4) - ffn_dropout = trial.suggest_float("ffn_dropout", 0.1, 0.4) - lr = trial.suggest_float("lr", 1e-5, 1e-2, log=True) # 범위 확대 - weight_decay = trial.suggest_float("weight_decay", 1e-4, 1e-1, log=True) # 더 공격적인 범위로 확장 - batch_size = trial.suggest_categorical("batch_size", [32, 64, 128, 256]) # Batch Size 추가 - - elif model_choose == 'resnet_like': - d_main = trial.suggest_int("d_main", 64, 256, step=32) - d_hidden = trial.suggest_int("d_hidden", 64, 512, step=64) - n_blocks = trial.suggest_int("n_blocks", 2, 5) # 너무 깊지 않게 조절 - dropout_first = trial.suggest_float("dropout_first", 0.1, 0.4) - dropout_second = trial.suggest_float("dropout_second", 0.0, 0.2) - lr = trial.suggest_float("lr", 1e-5, 1e-2, log=True) - weight_decay = trial.suggest_float("weight_decay", 1e-4, 1e-1, log=True) # 더 공격적인 범위로 확장 - batch_size = trial.suggest_categorical("batch_size", [32, 64, 128, 256]) # Batch Size 추가 - - elif model_choose == 'deepgbm': - # DeepGBM의 경우 모델 특성에 맞춰 ResNet 블록 및 임베딩 차원 조절 - d_main = trial.suggest_int("d_main", 64, 256, step=32) - d_hidden = trial.suggest_int("d_hidden", 64, 256, step=64) - n_blocks = trial.suggest_int("n_blocks", 2, 6) - dropout = trial.suggest_float("dropout", 0.1, 0.4) - lr = trial.suggest_float("lr", 1e-5, 1e-2, log=True) - weight_decay = trial.suggest_float("weight_decay", 1e-4, 1e-1, log=True) # 더 공격적인 범위로 확장 - batch_size = trial.suggest_categorical("batch_size", [32, 64, 128, 256]) # Batch Size 추가 - - # --- 2. Fold별 학습 및 교차 검증 --- - for fold in range(1, n_folds + 1): - X_train_df, categorical_cols, numerical_cols, train_loader, val_loader, _, y_train, _ = prepare_dataloader_with_batchsize( - region, data_sample=data_sample, target=target, fold=fold, random_state=random_state, batch_size=batch_size - ) - - # 모델 초기화 - if model_choose == "ft_transformer": - model = FTTransformer( - num_features=len(numerical_cols), - cat_cardinalities=[len(X_train_df[col].unique()) for col in categorical_cols], - d_token=d_token, - n_blocks=n_blocks, - n_heads=n_heads, - attention_dropout=attention_dropout, - ffn_dropout=ffn_dropout, - num_classes=3 - ).to(device) - elif model_choose == 'resnet_like': - input_dim = len(numerical_cols) + len(categorical_cols) - model = ResNetLike( - input_dim=input_dim, - d_main=d_main, - d_hidden=d_hidden, - n_blocks=n_blocks, - dropout_first=dropout_first, - dropout_second=dropout_second, - num_classes=3 - ).to(device) - elif model_choose == 'deepgbm': - model = DeepGBM( - num_features=len(numerical_cols), - cat_features=[len(X_train_df[col].unique()) for col in categorical_cols], - d_main=d_main, - d_hidden=d_hidden, - n_blocks=n_blocks, - dropout=dropout, - num_classes=3 - ).to(device) - - # 클래스 가중치 계산 및 손실 함수 설정 (Label Smoothing 적용) - if target == 'multi': - class_weights = compute_class_weight( - class_weight='balanced', - classes=np.unique(y_train), - y=y_train - ) - # 클래스별 가중치 로그 출력 - unique_classes = np.unique(y_train) - class_counts = {cls: np.sum(y_train == cls) for cls in unique_classes} - print(f" Fold {fold} - 클래스별 가중치: {dict(zip(unique_classes, class_weights))} (클래스별 샘플 수: {class_counts})") - class_weights_tensor = torch.tensor(class_weights, dtype=torch.float32).to(device) - criterion = nn.CrossEntropyLoss(weight=class_weights_tensor, label_smoothing=0.0) # Label Smoothing 추가 - else: - criterion = nn.BCEWithLogitsLoss() - optimizer = optim.AdamW(model.parameters(), lr=lr, weight_decay=weight_decay) - - # 학습률 스케줄러 추가: 성능 정체 시 LR을 0.5배 감소 (검증 CSI 기준) - scheduler = optim.lr_scheduler.ReduceLROnPlateau(optimizer, mode='max', factor=0.5, patience=3) - - # 학습 설정 (에폭 및 페이션스 상향) - epochs = 200 - patience = 12 # 딥러닝의 정체 구간을 고려하여 소폭 상향 - best_fold_csi = 0 - counter = 0 - - for epoch in range(epochs): - model.train() - for x_num_batch, x_cat_batch, y_batch in train_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - - optimizer.zero_grad() - y_pred = model(x_num_batch, x_cat_batch) - loss = criterion(y_pred, y_batch if target == 'multi' else y_batch.float()) - loss.backward() - optimizer.step() - - # Validation 평가 - model.eval() - y_pred_val, y_true_val = [], [] - with torch.no_grad(): - for x_num_batch, x_cat_batch, y_batch in val_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - output = model(x_num_batch, x_cat_batch) - pred = output.argmax(dim=1) if target == 'multi' else (torch.sigmoid(output) >= 0.5).long() - - y_pred_val.extend(pred.cpu().numpy()) - y_true_val.extend(y_batch.cpu().numpy()) - - # CSI 계산 및 스케줄러 업데이트 - val_csi = calculate_csi(y_true_val, y_pred_val) - scheduler.step(val_csi) - - # Optuna Pruning 적용 (첫 번째 Fold에서 조기 종료 판단 강화) - trial.report(val_csi, epoch) - if trial.should_prune(): - raise optuna.exceptions.TrialPruned() - - # Early Stopping 체크 - if val_csi > best_fold_csi: - best_fold_csi = val_csi - counter = 0 - else: - counter += 1 - - if counter >= patience: - break - - val_scores.append(best_fold_csi) - - # 모든 fold의 평균 성능 반환 - return np.mean(val_scores) - - -# 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 함수 -def train_final_model(best_params, model_choose, region, data_sample='pure', target='multi', n_folds=3, random_state=42): - """ - 최적화된 하이퍼파라미터로 최종 모델을 학습하고 저장합니다. - - Args: - best_params: 최적화된 하이퍼파라미터 딕셔너리 - model_choose: 모델 선택 ('ft_transformer', 'resnet_like', 'deepgbm') - region: 지역명 - data_sample: 데이터 샘플 타입 ('pure', 'smote', etc.) - target: 타겟 타입 ('multi', 'binary') - n_folds: 교차 검증 fold 수 - random_state: 랜덤 시드 - - Returns: - 저장된 모델 경로 리스트 - """ - # GPU 사용 가능 여부 확인 및 device 설정 - device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') - - models = [] - scalers = [] # scaler 리스트 추가 - - print("최종 모델 학습 시작...") - - for fold in range(1, n_folds + 1): - print(f"Fold {fold} 학습 중...") - - # 최적화된 batch_size 사용 - batch_size = best_params.get("batch_size", 64) - X_train_df, categorical_cols, numerical_cols, train_loader, val_loader, _, y_train, scaler = prepare_dataloader_with_batchsize( - region, data_sample=data_sample, target=target, fold=fold, random_state=random_state, batch_size=batch_size - ) - - # 모델 초기화 - if model_choose == "ft_transformer": - d_token = best_params["d_token"] - n_heads = best_params.get("n_heads", 8) - # d_token은 n_heads의 배수여야 함 (FT-Transformer의 구조적 제약 대응) - if d_token % n_heads != 0: - d_token = (d_token // n_heads) * n_heads - - model = FTTransformer( - num_features=len(numerical_cols), - cat_cardinalities=[len(X_train_df[col].unique()) for col in categorical_cols], - d_token=d_token, - n_blocks=best_params["n_blocks"], - n_heads=n_heads, - attention_dropout=best_params["attention_dropout"], - ffn_dropout=best_params["ffn_dropout"], - num_classes=3 - ).to(device) - elif model_choose == 'resnet_like': - input_dim = len(numerical_cols) + len(categorical_cols) - model = ResNetLike( - input_dim=input_dim, - d_main=best_params["d_main"], - d_hidden=best_params["d_hidden"], - n_blocks=best_params["n_blocks"], - dropout_first=best_params["dropout_first"], - dropout_second=best_params["dropout_second"], - num_classes=3 - ).to(device) - elif model_choose == 'deepgbm': - model = DeepGBM( - num_features=len(numerical_cols), - cat_features=[len(X_train_df[col].unique()) for col in categorical_cols], - d_main=best_params["d_main"], - d_hidden=best_params["d_hidden"], - n_blocks=best_params["n_blocks"], - dropout=best_params["dropout"], - num_classes=3 - ).to(device) - else: - raise ValueError(f"Unknown model_choose: {model_choose}") - - # 클래스 가중치 계산 및 손실 함수 설정 (Label Smoothing 적용) - if target == 'multi': - class_weights = compute_class_weight( - class_weight='balanced', - classes=np.unique(y_train), - y=y_train - ) - class_weights_tensor = torch.tensor(class_weights, dtype=torch.float32).to(device) - criterion = nn.CrossEntropyLoss(weight=class_weights_tensor, label_smoothing=0.0) # Label Smoothing 추가 - else: - criterion = nn.BCEWithLogitsLoss() - optimizer = optim.AdamW(model.parameters(), lr=best_params["lr"], weight_decay=best_params["weight_decay"]) - - # 학습률 스케줄러 - scheduler = optim.lr_scheduler.ReduceLROnPlateau(optimizer, mode='max', factor=0.5, patience=3) - - # 학습 설정 - epochs = 200 - patience = 12 - best_fold_csi = 0 - counter = 0 - best_model = None - - for epoch in range(epochs): - model.train() - for x_num_batch, x_cat_batch, y_batch in train_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - - optimizer.zero_grad() - y_pred = model(x_num_batch, x_cat_batch) - loss = criterion(y_pred, y_batch if target == 'multi' else y_batch.float()) - loss.backward() - optimizer.step() - - # Validation 평가 - model.eval() - y_pred_val, y_true_val = [], [] - with torch.no_grad(): - for x_num_batch, x_cat_batch, y_batch in val_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - output = model(x_num_batch, x_cat_batch) - pred = output.argmax(dim=1) if target == 'multi' else (torch.sigmoid(output) >= 0.5).long() - - y_pred_val.extend(pred.cpu().numpy()) - y_true_val.extend(y_batch.cpu().numpy()) - - # CSI 계산 및 스케줄러 업데이트 - val_csi = calculate_csi(y_true_val, y_pred_val) - scheduler.step(val_csi) - - # Early Stopping 체크 - if val_csi > best_fold_csi: - best_fold_csi = val_csi - counter = 0 - best_model = copy.deepcopy(model) - else: - counter += 1 - - if counter >= patience: - print(f" Early stopping at epoch {epoch+1}, Best CSI: {best_fold_csi:.4f}") - break - - if best_model is None: - best_model = model - - scalers.append(scaler) # scaler 저장 (fold 순서대로) - models.append(best_model) - print(f" Fold {fold} 학습 완료 (검증 CSI: {best_fold_csi:.4f})") - - # 모델 저장 경로 설정 - save_dir = f'../save_model/{model_choose}_optima' - os.makedirs(save_dir, exist_ok=True) - - # 파일명 생성 - if data_sample == 'pure': - model_filename = f'{model_choose}_pure_{region}.pkl' - else: - model_filename = f'{model_choose}_{data_sample}_{region}.pkl' - - model_path = f'{save_dir}/{model_filename}' - - # 리스트에 담아 한 번에 저장 - joblib.dump(models, model_path) - print(f"\n모든 모델 저장 완료: {model_path} (총 {len(models)}개 fold)") - - # Scaler 별도 저장 - scaler_save_dir = f'../save_model/{model_choose}_optima/scaler' - os.makedirs(scaler_save_dir, exist_ok=True) - - # 파일명 생성 (모델과 동일한 패턴) - if data_sample == 'pure': - scaler_filename = f'{model_choose}_pure_{region}_scaler.pkl' - else: - scaler_filename = f'{model_choose}_{data_sample}_{region}_scaler.pkl' - - scaler_path = f'{scaler_save_dir}/{scaler_filename}' - joblib.dump(scalers, scaler_path) - print(f"Scaler 저장 완료: {scaler_path} (총 {len(scalers)}개 fold)") - - return model_path diff --git a/Analysis_code/5.optima/resnet_like_smotenc_ctgan20000/resnet_like_smotenc_ctgan20000_busan.py b/Analysis_code/5.optima/resnet_like_smotenc_ctgan20000/resnet_like_smotenc_ctgan20000_busan.py deleted file mode 100644 index ebe1bae0ff8eeea57e2fae84a0ebe1267f16700d..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/resnet_like_smotenc_ctgan20000/resnet_like_smotenc_ctgan20000_busan.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="resnet_like", region="busan", data_sample='smotenc_ctgan20000'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/resnet_like_smotenc_ctgan20000_busan_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="resnet_like", - region="busan", - data_sample='smotenc_ctgan20000', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/resnet_like_smotenc_ctgan20000/resnet_like_smotenc_ctgan20000_daegu.py b/Analysis_code/5.optima/resnet_like_smotenc_ctgan20000/resnet_like_smotenc_ctgan20000_daegu.py deleted file mode 100644 index afb176df65c04f16638e5bf3d55425fffeb9e64f..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/resnet_like_smotenc_ctgan20000/resnet_like_smotenc_ctgan20000_daegu.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="resnet_like", region="daegu", data_sample='smotenc_ctgan20000'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/resnet_like_smotenc_ctgan20000_daegu_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="resnet_like", - region="daegu", - data_sample='smotenc_ctgan20000', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/resnet_like_smotenc_ctgan20000/resnet_like_smotenc_ctgan20000_daejeon.py b/Analysis_code/5.optima/resnet_like_smotenc_ctgan20000/resnet_like_smotenc_ctgan20000_daejeon.py deleted file mode 100644 index 3816d409bc5e68a1dc0d9e9885f5aa14b8a871bd..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/resnet_like_smotenc_ctgan20000/resnet_like_smotenc_ctgan20000_daejeon.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="resnet_like", region="daejeon", data_sample='smotenc_ctgan20000'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/resnet_like_smotenc_ctgan20000_daejeon_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="resnet_like", - region="daejeon", - data_sample='smotenc_ctgan20000', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/resnet_like_smotenc_ctgan20000/resnet_like_smotenc_ctgan20000_gwangju.py b/Analysis_code/5.optima/resnet_like_smotenc_ctgan20000/resnet_like_smotenc_ctgan20000_gwangju.py deleted file mode 100644 index 09cbc4feb214eb3fe7badc308cf7a04ca5f4bb3b..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/resnet_like_smotenc_ctgan20000/resnet_like_smotenc_ctgan20000_gwangju.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="resnet_like", region="gwangju", data_sample='smotenc_ctgan20000'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/resnet_like_smotenc_ctgan20000_gwangju_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="resnet_like", - region="gwangju", - data_sample='smotenc_ctgan20000', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/resnet_like_smotenc_ctgan20000/resnet_like_smotenc_ctgan20000_incheon.py b/Analysis_code/5.optima/resnet_like_smotenc_ctgan20000/resnet_like_smotenc_ctgan20000_incheon.py deleted file mode 100644 index ddf03cee7171c8676f057d941ed14734e4fe0fba..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/resnet_like_smotenc_ctgan20000/resnet_like_smotenc_ctgan20000_incheon.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="resnet_like", region="incheon", data_sample='smotenc_ctgan20000'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/resnet_like_smotenc_ctgan20000_incheon_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="resnet_like", - region="incheon", - data_sample='smotenc_ctgan20000', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/resnet_like_smotenc_ctgan20000/resnet_like_smotenc_ctgan20000_seoul.py b/Analysis_code/5.optima/resnet_like_smotenc_ctgan20000/resnet_like_smotenc_ctgan20000_seoul.py deleted file mode 100644 index c704b8edeb06fd82e11346565bb3c35eef9c359c..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/resnet_like_smotenc_ctgan20000/resnet_like_smotenc_ctgan20000_seoul.py +++ /dev/null @@ -1,97 +0,0 @@ -import optuna -import numpy as np -import random -import pandas as pd -import joblib -import os -import torch -from utils import * -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - - -# 1. Study 생성 시 'maximize'로 설정 -study = optuna.create_study( - direction="maximize", # CSI 점수가 높을수록 좋으므로 maximize - pruner=optuna.pruners.MedianPruner(n_warmup_steps=10) # 초반 10에폭은 지켜보고 이후 가지치기 -) -# Trial 완료 시 상세 정보 출력하는 callback 함수 -def print_trial_callback(study, trial): - """각 trial 완료 시 best value를 포함한 상세 정보 출력""" - print(f"\n{'='*80}") - print(f"Trial {trial.number} 완료") - print(f" Value (CSI): {trial.value:.6f}" if trial.value is not None else f" Value: {trial.value}") - print(f" Parameters: {trial.params}") - print(f" Best Value (CSI): {study.best_value:.6f}" if study.best_value is not None else f" Best Value: {study.best_value}") - print(f" Best Trial: {study.best_trial.number}") - print(f" Best Parameters: {study.best_params}") - print(f"{'='*80}\n") - - - -# 2. 최적화 실행 -study.optimize( - lambda trial: objective(trial, model_choose="resnet_like", region="seoul", data_sample='smotenc_ctgan20000'), - n_trials=100 -, - callbacks=[print_trial_callback] -) - -# 3. 결과 확인 및 요약 -print(f"\n최적화 완료.") -print(f"Best CSI Score: {study.best_value:.4f}") -print(f"Best Hyperparameters: {study.best_params}") - -try: - # 모든 trial의 CSI 점수 추출 - csi_scores = [trial.value for trial in study.trials if trial.value is not None] - - if len(csi_scores) > 0: - print(f"\n최적화 과정 요약:") - print(f" - 총 시도 횟수: {len(study.trials)}") - print(f" - 성공한 시도: {len(csi_scores)}") - print(f" - 최초 CSI: {csi_scores[0]:.4f}") - print(f" - 최종 CSI: {csi_scores[-1]:.4f}") - print(f" - 최고 CSI: {max(csi_scores):.4f}") - print(f" - 최저 CSI: {min(csi_scores):.4f}") - print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - - # Study 객체 저장 - # 파일 위치 기반으로 base 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 - os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) - study_path = os.path.join(base_dir, "optimization_history/resnet_like_smotenc_ctgan20000_seoul_trials.pkl") - joblib.dump(study, study_path) - print(f"\n최적화 Study 객체가 {study_path}에 저장되었습니다.") - - # 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 - print("\n" + "="*50) - print("최적화된 하이퍼파라미터로 최종 모델 학습 시작") - print("="*50) - - best_params = study.best_params - model_path = train_final_model( - best_params=best_params, - model_choose="resnet_like", - region="seoul", - data_sample='smotenc_ctgan20000', - target='multi', - n_folds=3, - random_state=seed - ) - - print(f"\n최종 모델 학습 및 저장 완료!") - print(f"저장된 모델 경로: {model_path}") - -except Exception as e: - print(f"\n⚠️ 최적화 결과 분석 중 오류 발생: {e}") - import traceback - traceback.print_exc() - -# 정상 종료 -import sys -sys.exit(0) - diff --git a/Analysis_code/5.optima/resnet_like_smotenc_ctgan20000/utils.py b/Analysis_code/5.optima/resnet_like_smotenc_ctgan20000/utils.py deleted file mode 100644 index 2cebe5700041635baab0fec01daa0ea1b11f7c4e..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/resnet_like_smotenc_ctgan20000/utils.py +++ /dev/null @@ -1,718 +0,0 @@ -import torch -import torch.nn as nn -import torch.optim as optim -import numpy as np -import random -import os -import copy -from sklearn.preprocessing import QuantileTransformer, LabelEncoder -from torch.utils.data import DataLoader, TensorDataset -from sklearn.metrics import confusion_matrix -from sklearn.utils.class_weight import compute_class_weight -import pandas as pd -import optuna -from sklearn.metrics import accuracy_score, f1_score -import joblib - - -import sys -# 파일 위치 기반으로 models 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -models_path = os.path.abspath(os.path.join(current_file_dir, '../../models')) -sys.path.insert(0, models_path) -from ft_transformer import FTTransformer -from resnet_like import ResNetLike -from deepgbm import DeepGBM -import warnings -warnings.filterwarnings('ignore') - - -# Python 및 Numpy 시드 고정 -seed = 42 -random.seed(seed) -np.random.seed(seed) - -# PyTorch 시드 고정 -torch.manual_seed(seed) -torch.cuda.manual_seed(seed) -torch.cuda.manual_seed_all(seed) # Multi-GPU 환경에서 동일한 시드 적용 - -# PyTorch 연산의 결정적 모드 설정 -torch.backends.cudnn.deterministic = True # 실행마다 동일한 결과를 보장 -torch.backends.cudnn.benchmark = True # 성능 최적화를 활성화 (가능한 한 빠른 연산 수행) - - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - - -# 데이터셋 준비 함수 -def prepare_dataset(region, data_sample='pure', target='multi', fold=3): - # 파일 위치 기반으로 데이터 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) - - # 데이터 경로 지정 - dat_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_train.csv") - if data_sample == 'pure': - train_path = dat_path - else: - train_path = os.path.join(data_base_dir, f'data_oversampled/{data_sample}/{data_sample}_{fold}_{region}.csv') - test_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_test.csv") - drop_col = ['multi_class','year'] - target_col = f'{target}_class' - - # 데이터 로드 - region_dat = preprocessing(pd.read_csv(dat_path, index_col=0)) - if data_sample == 'pure': - region_train = region_dat.loc[~region_dat['year'].isin([2021-fold]), :] - else: - region_train = preprocessing(pd.read_csv(train_path)) - region_val = region_dat.loc[region_dat['year'].isin([2021-fold]), :] - region_test = preprocessing(pd.read_csv(test_path)) - - # 컬럼 정렬 (일관성 유지) - common_columns = region_train.columns.to_list() - train_data = region_train[common_columns] - val_data = region_val[common_columns] - test_data = region_test[common_columns] - - # 설명변수 & 타겟 분리 - X_train = train_data.drop(columns=drop_col) - y_train = train_data[target_col] - X_val = val_data.drop(columns=drop_col) - y_val = val_data[target_col] - X_test = test_data.drop(columns=drop_col) - y_test = test_data[target_col] - - # 범주형 & 연속형 변수 분리 - categorical_cols = X_train.select_dtypes(include=['object', 'category', 'int64']).columns - numerical_cols = X_train.select_dtypes(include=['float64']).columns - - # 범주형 변수 Label Encoding - label_encoders = {} - for col in categorical_cols: - le = LabelEncoder() - le.fit(X_train[col]) # Train 데이터 기준으로 학습 - label_encoders[col] = le - - # 변환 적용 - for col in categorical_cols: - X_train[col] = label_encoders[col].transform(X_train[col]) - X_val[col] = label_encoders[col].transform(X_val[col]) - X_test[col] = label_encoders[col].transform(X_test[col]) - - # 연속형 변수 Quantile Transformation - scaler = QuantileTransformer(output_distribution='normal') - scaler.fit(X_train[numerical_cols]) # Train 데이터 기준으로 학습 - - # 변환 적용 - X_train[numerical_cols] = scaler.transform(X_train[numerical_cols]) - X_val[numerical_cols] = scaler.transform(X_val[numerical_cols]) - X_test[numerical_cols] = scaler.transform(X_test[numerical_cols]) - - return X_train, X_val, X_test, y_train, y_val, y_test, categorical_cols, numerical_cols - - - -# 데이터 변환 및 dataloader 생성 함수 -def prepare_dataloader(region, data_sample='pure', target='multi', fold=3, random_state=None): - # 파일 위치 기반으로 데이터 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) - - # 데이터 경로 지정 - dat_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_train.csv") - if data_sample == 'pure': - train_path = dat_path - else: - train_path = os.path.join(data_base_dir, f'data_oversampled/{data_sample}/{data_sample}_{fold}_{region}.csv') - test_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_test.csv") - drop_col = ['multi_class','year'] - target_col = f'{target}_class' - - # 데이터 로드 - region_dat = preprocessing(pd.read_csv(dat_path, index_col=0)) - if data_sample == 'pure': - region_train = region_dat.loc[~region_dat['year'].isin([2021-fold]), :] - else: - region_train = preprocessing(pd.read_csv(train_path)) - region_val = region_dat.loc[region_dat['year'].isin([2021-fold]), :] - region_test = preprocessing(pd.read_csv(test_path)) - - # 컬럼 정렬 (일관성 유지) - common_columns = region_train.columns.to_list() - train_data = region_train[common_columns] - val_data = region_val[common_columns] - test_data = region_test[common_columns] - - # 설명변수 & 타겟 분리 - X_train = train_data.drop(columns=drop_col) - y_train = train_data[target_col] - X_val = val_data.drop(columns=drop_col) - y_val = val_data[target_col] - X_test = test_data.drop(columns=drop_col) - y_test = test_data[target_col] - - # 범주형 & 연속형 변수 분리 - categorical_cols = X_train.select_dtypes(include=['object', 'category', 'int64']).columns - numerical_cols = X_train.select_dtypes(include=['float64']).columns - - # 범주형 변수 Label Encoding - label_encoders = {} - for col in categorical_cols: - le = LabelEncoder() - le.fit(X_train[col]) # Train 데이터 기준으로 학습 - label_encoders[col] = le - - # 변환 적용 - for col in categorical_cols: - X_train[col] = label_encoders[col].transform(X_train[col]) - X_val[col] = label_encoders[col].transform(X_val[col]) - X_test[col] = label_encoders[col].transform(X_test[col]) - - # 연속형 변수 Quantile Transformation - scaler = QuantileTransformer(output_distribution='normal') - scaler.fit(X_train[numerical_cols]) # Train 데이터 기준으로 학습 - - # 변환 적용 - X_train[numerical_cols] = scaler.transform(X_train[numerical_cols]) - X_val[numerical_cols] = scaler.transform(X_val[numerical_cols]) - X_test[numerical_cols] = scaler.transform(X_test[numerical_cols]) - - # 연속형 변수와 범주형 변수 분리 - X_train_num = torch.tensor(X_train[numerical_cols].values, dtype=torch.float32) - X_train_cat = torch.tensor(X_train[categorical_cols].values, dtype=torch.long) - - X_val_num = torch.tensor(X_val[numerical_cols].values, dtype=torch.float32) - X_val_cat = torch.tensor(X_val[categorical_cols].values, dtype=torch.long) - - X_test_num = torch.tensor(X_test[numerical_cols].values, dtype=torch.float32) - X_test_cat = torch.tensor(X_test[categorical_cols].values, dtype=torch.long) - - # 레이블 변환 - if target == "binary": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.float32) # 이진 분류 → float32 - y_val_tensor = torch.tensor(y_val.values, dtype=torch.float32) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.float32) - elif target == "multi": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.long) # 다중 분류 → long - y_val_tensor = torch.tensor(y_val.values, dtype=torch.long) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.long) - else: - raise ValueError("target must be 'binary' or 'multi'") - - # TensorDataset 생성 - train_dataset = TensorDataset(X_train_num, X_train_cat, y_train_tensor) - val_dataset = TensorDataset(X_val_num, X_val_cat, y_val_tensor) - test_dataset = TensorDataset(X_test_num, X_test_cat, y_test_tensor) - - # DataLoader 생성 - if random_state == None: - train_loader = DataLoader(train_dataset, batch_size=64, shuffle=True) - else: - train_loader = DataLoader(train_dataset, batch_size=64, shuffle=True, generator=torch.Generator().manual_seed(random_state)) - val_loader = DataLoader(val_dataset, batch_size=64, shuffle=False) - test_loader = DataLoader(test_dataset, batch_size=64, shuffle=False) - - return X_train, categorical_cols, numerical_cols, train_loader, val_loader, test_loader - -# 데이터 변환 및 dataloader 생성 함수 (batch_size 파라미터 추가 버전) -def prepare_dataloader_with_batchsize(region, data_sample='pure', target='multi', fold=3, random_state=None, batch_size=64): - # 파일 위치 기반으로 데이터 디렉토리 경로 설정 - current_file_dir = os.path.dirname(os.path.abspath(__file__)) - data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) - - # 데이터 경로 지정 - dat_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_train.csv") - if data_sample == 'pure': - train_path = dat_path - else: - train_path = os.path.join(data_base_dir, f'data_oversampled/{data_sample}/{data_sample}_{fold}_{region}.csv') - test_path = os.path.join(data_base_dir, f"data_for_modeling/{region}_test.csv") - drop_col = ['multi_class','year'] - target_col = f'{target}_class' - - # 데이터 로드 - region_dat = preprocessing(pd.read_csv(dat_path, index_col=0)) - if data_sample == 'pure': - region_train = region_dat.loc[~region_dat['year'].isin([2021-fold]), :] - else: - region_train = preprocessing(pd.read_csv(train_path)) - region_val = region_dat.loc[region_dat['year'].isin([2021-fold]), :] - region_test = preprocessing(pd.read_csv(test_path)) - - # 컬럼 정렬 (일관성 유지) - common_columns = region_train.columns.to_list() - train_data = region_train[common_columns] - val_data = region_val[common_columns] - test_data = region_test[common_columns] - - # 설명변수 & 타겟 분리 - X_train = train_data.drop(columns=drop_col) - y_train = train_data[target_col] - X_val = val_data.drop(columns=drop_col) - y_val = val_data[target_col] - X_test = test_data.drop(columns=drop_col) - y_test = test_data[target_col] - - # 범주형 & 연속형 변수 분리 - categorical_cols = X_train.select_dtypes(include=['object', 'category', 'int64']).columns - numerical_cols = X_train.select_dtypes(include=['float64']).columns - - # 범주형 변수 Label Encoding - label_encoders = {} - for col in categorical_cols: - le = LabelEncoder() - le.fit(X_train[col]) # Train 데이터 기준으로 학습 - label_encoders[col] = le - - # 변환 적용 - for col in categorical_cols: - X_train[col] = label_encoders[col].transform(X_train[col]) - X_val[col] = label_encoders[col].transform(X_val[col]) - X_test[col] = label_encoders[col].transform(X_test[col]) - - # 연속형 변수 Quantile Transformation - scaler = QuantileTransformer(output_distribution='normal') - scaler.fit(X_train[numerical_cols]) # Train 데이터 기준으로 학습 - - # 변환 적용 - X_train[numerical_cols] = scaler.transform(X_train[numerical_cols]) - X_val[numerical_cols] = scaler.transform(X_val[numerical_cols]) - X_test[numerical_cols] = scaler.transform(X_test[numerical_cols]) - - # 연속형 변수와 범주형 변수 분리 - X_train_num = torch.tensor(X_train[numerical_cols].values, dtype=torch.float32) - X_train_cat = torch.tensor(X_train[categorical_cols].values, dtype=torch.long) - - X_val_num = torch.tensor(X_val[numerical_cols].values, dtype=torch.float32) - X_val_cat = torch.tensor(X_val[categorical_cols].values, dtype=torch.long) - - X_test_num = torch.tensor(X_test[numerical_cols].values, dtype=torch.float32) - X_test_cat = torch.tensor(X_test[categorical_cols].values, dtype=torch.long) - - # 레이블 변환 - if target == "binary": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.float32) # 이진 분류 → float32 - y_val_tensor = torch.tensor(y_val.values, dtype=torch.float32) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.float32) - elif target == "multi": - y_train_tensor = torch.tensor(y_train.values, dtype=torch.long) # 다중 분류 → long - y_val_tensor = torch.tensor(y_val.values, dtype=torch.long) - y_test_tensor = torch.tensor(y_test.values, dtype=torch.long) - else: - raise ValueError("target must be 'binary' or 'multi'") - - # TensorDataset 생성 - train_dataset = TensorDataset(X_train_num, X_train_cat, y_train_tensor) - val_dataset = TensorDataset(X_val_num, X_val_cat, y_val_tensor) - test_dataset = TensorDataset(X_test_num, X_test_cat, y_test_tensor) - - # DataLoader 생성 (batch_size 파라미터 사용) - if random_state == None: - train_loader = DataLoader(train_dataset, batch_size=batch_size, shuffle=True) - else: - train_loader = DataLoader(train_dataset, batch_size=batch_size, shuffle=True, generator=torch.Generator().manual_seed(random_state)) - val_loader = DataLoader(val_dataset, batch_size=batch_size, shuffle=False) - test_loader = DataLoader(test_dataset, batch_size=batch_size, shuffle=False) - - return X_train, categorical_cols, numerical_cols, train_loader, val_loader, test_loader, y_train, scaler - - -def calculate_csi(y_true, pred): - - cm = confusion_matrix(y_true, pred) # 변수 이름을 cm으로 변경 - # 혼동 행렬에서 H, F, M 추출 - H = (cm[0, 0] + cm[1, 1]) - - F = (cm[1, 0] + cm[2, 0] + - cm[0, 1] + cm[2, 1]) - - M = (cm[0, 2] + cm[1, 2]) - - # CSI 계산 - CSI = H / (H + F + M + 1e-10) - return CSI - -def sample_weight(y_train): - class_weights = compute_class_weight( - class_weight='balanced', - classes=np.unique(y_train), # 고유 클래스 - y=y_train # 학습 데이터 레이블 - ) - sample_weights = np.array([class_weights[label] for label in y_train]) - - return sample_weights - -# 하이퍼파라미터 최적화 함수 정의 -def objective(trial, model_choose, region, data_sample='pure', target='multi', n_folds=3, random_state=42): - # GPU 사용 가능 여부 확인 및 device 설정 - device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') - val_scores = [] - - # --- 1. 하이퍼파라미터 탐색 범위 정의 (수정됨) --- - if model_choose == "ft_transformer": - d_token = trial.suggest_int("d_token", 64, 256, step=32) - n_blocks = trial.suggest_int("n_blocks", 2, 6) # 깊이 축소로 과적합 방지 - n_heads = trial.suggest_categorical("n_heads", [4, 8]) - # d_token은 n_heads의 배수여야 함 (FT-Transformer의 구조적 제약 대응) - if d_token % n_heads != 0: - d_token = (d_token // n_heads) * n_heads - - attention_dropout = trial.suggest_float("attention_dropout", 0.1, 0.4) - ffn_dropout = trial.suggest_float("ffn_dropout", 0.1, 0.4) - lr = trial.suggest_float("lr", 1e-5, 1e-2, log=True) # 범위 확대 - weight_decay = trial.suggest_float("weight_decay", 1e-4, 1e-1, log=True) # 더 공격적인 범위로 확장 - batch_size = trial.suggest_categorical("batch_size", [32, 64, 128, 256]) # Batch Size 추가 - - elif model_choose == 'resnet_like': - d_main = trial.suggest_int("d_main", 64, 256, step=32) - d_hidden = trial.suggest_int("d_hidden", 64, 512, step=64) - n_blocks = trial.suggest_int("n_blocks", 2, 5) # 너무 깊지 않게 조절 - dropout_first = trial.suggest_float("dropout_first", 0.1, 0.4) - dropout_second = trial.suggest_float("dropout_second", 0.0, 0.2) - lr = trial.suggest_float("lr", 1e-5, 1e-2, log=True) - weight_decay = trial.suggest_float("weight_decay", 1e-4, 1e-1, log=True) # 더 공격적인 범위로 확장 - batch_size = trial.suggest_categorical("batch_size", [32, 64, 128, 256]) # Batch Size 추가 - - elif model_choose == 'deepgbm': - # DeepGBM의 경우 모델 특성에 맞춰 ResNet 블록 및 임베딩 차원 조절 - d_main = trial.suggest_int("d_main", 64, 256, step=32) - d_hidden = trial.suggest_int("d_hidden", 64, 256, step=64) - n_blocks = trial.suggest_int("n_blocks", 2, 6) - dropout = trial.suggest_float("dropout", 0.1, 0.4) - lr = trial.suggest_float("lr", 1e-5, 1e-2, log=True) - weight_decay = trial.suggest_float("weight_decay", 1e-4, 1e-1, log=True) # 더 공격적인 범위로 확장 - batch_size = trial.suggest_categorical("batch_size", [32, 64, 128, 256]) # Batch Size 추가 - - # --- 2. Fold별 학습 및 교차 검증 --- - for fold in range(1, n_folds + 1): - X_train_df, categorical_cols, numerical_cols, train_loader, val_loader, _, y_train, _ = prepare_dataloader_with_batchsize( - region, data_sample=data_sample, target=target, fold=fold, random_state=random_state, batch_size=batch_size - ) - - # 모델 초기화 - if model_choose == "ft_transformer": - model = FTTransformer( - num_features=len(numerical_cols), - cat_cardinalities=[len(X_train_df[col].unique()) for col in categorical_cols], - d_token=d_token, - n_blocks=n_blocks, - n_heads=n_heads, - attention_dropout=attention_dropout, - ffn_dropout=ffn_dropout, - num_classes=3 - ).to(device) - elif model_choose == 'resnet_like': - input_dim = len(numerical_cols) + len(categorical_cols) - model = ResNetLike( - input_dim=input_dim, - d_main=d_main, - d_hidden=d_hidden, - n_blocks=n_blocks, - dropout_first=dropout_first, - dropout_second=dropout_second, - num_classes=3 - ).to(device) - elif model_choose == 'deepgbm': - model = DeepGBM( - num_features=len(numerical_cols), - cat_features=[len(X_train_df[col].unique()) for col in categorical_cols], - d_main=d_main, - d_hidden=d_hidden, - n_blocks=n_blocks, - dropout=dropout, - num_classes=3 - ).to(device) - - # 클래스 가중치 계산 및 손실 함수 설정 (Label Smoothing 적용) - if target == 'multi': - class_weights = compute_class_weight( - class_weight='balanced', - classes=np.unique(y_train), - y=y_train - ) - # 클래스별 가중치 로그 출력 - unique_classes = np.unique(y_train) - class_counts = {cls: np.sum(y_train == cls) for cls in unique_classes} - print(f" Fold {fold} - 클래스별 가중치: {dict(zip(unique_classes, class_weights))} (클래스별 샘플 수: {class_counts})") - class_weights_tensor = torch.tensor(class_weights, dtype=torch.float32).to(device) - criterion = nn.CrossEntropyLoss(weight=class_weights_tensor, label_smoothing=0.0) # Label Smoothing 추가 - else: - criterion = nn.BCEWithLogitsLoss() - optimizer = optim.AdamW(model.parameters(), lr=lr, weight_decay=weight_decay) - - # 학습률 스케줄러 추가: 성능 정체 시 LR을 0.5배 감소 (검증 CSI 기준) - scheduler = optim.lr_scheduler.ReduceLROnPlateau(optimizer, mode='max', factor=0.5, patience=3) - - # 학습 설정 (에폭 및 페이션스 상향) - epochs = 200 - patience = 12 # 딥러닝의 정체 구간을 고려하여 소폭 상향 - best_fold_csi = 0 - counter = 0 - - for epoch in range(epochs): - model.train() - for x_num_batch, x_cat_batch, y_batch in train_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - - optimizer.zero_grad() - y_pred = model(x_num_batch, x_cat_batch) - loss = criterion(y_pred, y_batch if target == 'multi' else y_batch.float()) - loss.backward() - optimizer.step() - - # Validation 평가 - model.eval() - y_pred_val, y_true_val = [], [] - with torch.no_grad(): - for x_num_batch, x_cat_batch, y_batch in val_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - output = model(x_num_batch, x_cat_batch) - pred = output.argmax(dim=1) if target == 'multi' else (torch.sigmoid(output) >= 0.5).long() - - y_pred_val.extend(pred.cpu().numpy()) - y_true_val.extend(y_batch.cpu().numpy()) - - # CSI 계산 및 스케줄러 업데이트 - val_csi = calculate_csi(y_true_val, y_pred_val) - scheduler.step(val_csi) - - # Optuna Pruning 적용 (첫 번째 Fold에서 조기 종료 판단 강화) - trial.report(val_csi, epoch) - if trial.should_prune(): - raise optuna.exceptions.TrialPruned() - - # Early Stopping 체크 - if val_csi > best_fold_csi: - best_fold_csi = val_csi - counter = 0 - else: - counter += 1 - - if counter >= patience: - break - - val_scores.append(best_fold_csi) - - # 모든 fold의 평균 성능 반환 - return np.mean(val_scores) - - -# 최적화된 하이퍼파라미터로 최종 모델 학습 및 저장 함수 -def train_final_model(best_params, model_choose, region, data_sample='pure', target='multi', n_folds=3, random_state=42): - """ - 최적화된 하이퍼파라미터로 최종 모델을 학습하고 저장합니다. - - Args: - best_params: 최적화된 하이퍼파라미터 딕셔너리 - model_choose: 모델 선택 ('ft_transformer', 'resnet_like', 'deepgbm') - region: 지역명 - data_sample: 데이터 샘플 타입 ('pure', 'smote', etc.) - target: 타겟 타입 ('multi', 'binary') - n_folds: 교차 검증 fold 수 - random_state: 랜덤 시드 - - Returns: - 저장된 모델 경로 리스트 - """ - # GPU 사용 가능 여부 확인 및 device 설정 - device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') - - models = [] - scalers = [] # scaler 리스트 추가 - - print("최종 모델 학습 시작...") - - for fold in range(1, n_folds + 1): - print(f"Fold {fold} 학습 중...") - - # 최적화된 batch_size 사용 - batch_size = best_params.get("batch_size", 64) - X_train_df, categorical_cols, numerical_cols, train_loader, val_loader, _, y_train, scaler = prepare_dataloader_with_batchsize( - region, data_sample=data_sample, target=target, fold=fold, random_state=random_state, batch_size=batch_size - ) - - # 모델 초기화 - if model_choose == "ft_transformer": - d_token = best_params["d_token"] - n_heads = best_params.get("n_heads", 8) - # d_token은 n_heads의 배수여야 함 (FT-Transformer의 구조적 제약 대응) - if d_token % n_heads != 0: - d_token = (d_token // n_heads) * n_heads - - model = FTTransformer( - num_features=len(numerical_cols), - cat_cardinalities=[len(X_train_df[col].unique()) for col in categorical_cols], - d_token=d_token, - n_blocks=best_params["n_blocks"], - n_heads=n_heads, - attention_dropout=best_params["attention_dropout"], - ffn_dropout=best_params["ffn_dropout"], - num_classes=3 - ).to(device) - elif model_choose == 'resnet_like': - input_dim = len(numerical_cols) + len(categorical_cols) - model = ResNetLike( - input_dim=input_dim, - d_main=best_params["d_main"], - d_hidden=best_params["d_hidden"], - n_blocks=best_params["n_blocks"], - dropout_first=best_params["dropout_first"], - dropout_second=best_params["dropout_second"], - num_classes=3 - ).to(device) - elif model_choose == 'deepgbm': - model = DeepGBM( - num_features=len(numerical_cols), - cat_features=[len(X_train_df[col].unique()) for col in categorical_cols], - d_main=best_params["d_main"], - d_hidden=best_params["d_hidden"], - n_blocks=best_params["n_blocks"], - dropout=best_params["dropout"], - num_classes=3 - ).to(device) - else: - raise ValueError(f"Unknown model_choose: {model_choose}") - - # 클래스 가중치 계산 및 손실 함수 설정 (Label Smoothing 적용) - if target == 'multi': - class_weights = compute_class_weight( - class_weight='balanced', - classes=np.unique(y_train), - y=y_train - ) - class_weights_tensor = torch.tensor(class_weights, dtype=torch.float32).to(device) - criterion = nn.CrossEntropyLoss(weight=class_weights_tensor, label_smoothing=0.0) # Label Smoothing 추가 - else: - criterion = nn.BCEWithLogitsLoss() - optimizer = optim.AdamW(model.parameters(), lr=best_params["lr"], weight_decay=best_params["weight_decay"]) - - # 학습률 스케줄러 - scheduler = optim.lr_scheduler.ReduceLROnPlateau(optimizer, mode='max', factor=0.5, patience=3) - - # 학습 설정 - epochs = 200 - patience = 12 - best_fold_csi = 0 - counter = 0 - best_model = None - - for epoch in range(epochs): - model.train() - for x_num_batch, x_cat_batch, y_batch in train_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - - optimizer.zero_grad() - y_pred = model(x_num_batch, x_cat_batch) - loss = criterion(y_pred, y_batch if target == 'multi' else y_batch.float()) - loss.backward() - optimizer.step() - - # Validation 평가 - model.eval() - y_pred_val, y_true_val = [], [] - with torch.no_grad(): - for x_num_batch, x_cat_batch, y_batch in val_loader: - x_num_batch, x_cat_batch, y_batch = x_num_batch.to(device), x_cat_batch.to(device), y_batch.to(device) - output = model(x_num_batch, x_cat_batch) - pred = output.argmax(dim=1) if target == 'multi' else (torch.sigmoid(output) >= 0.5).long() - - y_pred_val.extend(pred.cpu().numpy()) - y_true_val.extend(y_batch.cpu().numpy()) - - # CSI 계산 및 스케줄러 업데이트 - val_csi = calculate_csi(y_true_val, y_pred_val) - scheduler.step(val_csi) - - # Early Stopping 체크 - if val_csi > best_fold_csi: - best_fold_csi = val_csi - counter = 0 - best_model = copy.deepcopy(model) - else: - counter += 1 - - if counter >= patience: - print(f" Early stopping at epoch {epoch+1}, Best CSI: {best_fold_csi:.4f}") - break - - if best_model is None: - best_model = model - - scalers.append(scaler) # scaler 저장 (fold 순서대로) - models.append(best_model) - print(f" Fold {fold} 학습 완료 (검증 CSI: {best_fold_csi:.4f})") - - # 모델 저장 경로 설정 - save_dir = f'../save_model/{model_choose}_optima' - os.makedirs(save_dir, exist_ok=True) - - # 파일명 생성 - if data_sample == 'pure': - model_filename = f'{model_choose}_pure_{region}.pkl' - else: - model_filename = f'{model_choose}_{data_sample}_{region}.pkl' - - model_path = f'{save_dir}/{model_filename}' - - # 리스트에 담아 한 번에 저장 - joblib.dump(models, model_path) - print(f"\n모든 모델 저장 완료: {model_path} (총 {len(models)}개 fold)") - - # Scaler 별도 저장 - scaler_save_dir = f'../save_model/{model_choose}_optima/scaler' - os.makedirs(scaler_save_dir, exist_ok=True) - - # 파일명 생성 (모델과 동일한 패턴) - if data_sample == 'pure': - scaler_filename = f'{model_choose}_pure_{region}_scaler.pkl' - else: - scaler_filename = f'{model_choose}_{data_sample}_{region}_scaler.pkl' - - scaler_path = f'{scaler_save_dir}/{scaler_filename}' - joblib.dump(scalers, scaler_path) - print(f"Scaler 저장 완료: {scaler_path} (총 {len(scalers)}개 fold)") - - return model_path diff --git a/Analysis_code/5.optima/run_bash/deepgbm/deepgbm_ctgan10000.log b/Analysis_code/5.optima/run_bash/deepgbm/deepgbm_ctgan10000.log deleted file mode 100644 index c06e5c042ae64e651c656263a7d0336882e17da5..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/run_bash/deepgbm/deepgbm_ctgan10000.log +++ /dev/null @@ -1,8016 +0,0 @@ -nohup: ignoring input -/bin/bash: /opt/conda/lib/libtinfo.so.6: no version information available (required by /bin/bash) -========================================== -DeepGBM CTGAN10000 파일 실행 시작 -시작 시간: 2025-12-28 12:36:02 -GPU: 0번 (CUDA_VISIBLE_DEVICES=0) -========================================== - ----------------------------------------- -실행 중: deepgbm_ctgan10000/deepgbm_ctgan10000_busan.py -시작 시간: 2025-12-28 12:36:02 ----------------------------------------- -[I 2025-12-28 12:36:03,350] A new study created in memory with name: no-name-f8f8163b-0d6b-44d7-b45d-92727874dc8c - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 12:38:32,701] Trial 0 finished with value: 0.38770751821594523 and parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.13084881692315956, 'lr': 0.00022258541076412326, 'weight_decay': 0.004868686949203451, 'batch_size': 32}. Best is trial 0 with value: 0.38770751821594523. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.387708 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.13084881692315956, 'lr': 0.00022258541076412326, 'weight_decay': 0.004868686949203451, 'batch_size': 32} - Best Value (CSI): 0.387708 - Best Trial: 0 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.13084881692315956, 'lr': 0.00022258541076412326, 'weight_decay': 0.004868686949203451, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 12:39:54,979] Trial 1 finished with value: 0.3882440532876936 and parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.30754261616949313, 'lr': 0.0004192024392841491, 'weight_decay': 0.0005190956971438232, 'batch_size': 128}. Best is trial 1 with value: 0.3882440532876936. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.388244 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.30754261616949313, 'lr': 0.0004192024392841491, 'weight_decay': 0.0005190956971438232, 'batch_size': 128} - Best Value (CSI): 0.388244 - Best Trial: 1 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.30754261616949313, 'lr': 0.0004192024392841491, 'weight_decay': 0.0005190956971438232, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 12:41:10,524] Trial 2 finished with value: 0.42343062277312127 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3415568705386193, 'lr': 0.00164419474736584, 'weight_decay': 0.0035618619985765265, 'batch_size': 64}. Best is trial 2 with value: 0.42343062277312127. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.423431 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3415568705386193, 'lr': 0.00164419474736584, 'weight_decay': 0.0035618619985765265, 'batch_size': 64} - Best Value (CSI): 0.423431 - Best Trial: 2 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3415568705386193, 'lr': 0.00164419474736584, 'weight_decay': 0.0035618619985765265, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 12:41:55,262] Trial 3 finished with value: 0.3909864259403904 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.34359376018237037, 'lr': 0.0025310441867235213, 'weight_decay': 0.0018249918792258464, 'batch_size': 256}. Best is trial 2 with value: 0.42343062277312127. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.390986 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.34359376018237037, 'lr': 0.0025310441867235213, 'weight_decay': 0.0018249918792258464, 'batch_size': 256} - Best Value (CSI): 0.423431 - Best Trial: 2 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3415568705386193, 'lr': 0.00164419474736584, 'weight_decay': 0.0035618619985765265, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 12:42:42,125] Trial 4 finished with value: 0.4302411821678192 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.35845930914090496, 'lr': 0.0009607581451670014, 'weight_decay': 0.07737669684354931, 'batch_size': 256}. Best is trial 4 with value: 0.4302411821678192. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.430241 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.35845930914090496, 'lr': 0.0009607581451670014, 'weight_decay': 0.07737669684354931, 'batch_size': 256} - Best Value (CSI): 0.430241 - Best Trial: 4 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.35845930914090496, 'lr': 0.0009607581451670014, 'weight_decay': 0.07737669684354931, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 12:45:12,111] Trial 5 finished with value: 0.3897682738591593 and parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.21560699439533046, 'lr': 0.0002706781911763059, 'weight_decay': 0.012669446375571386, 'batch_size': 64}. Best is trial 4 with value: 0.4302411821678192. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.389768 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.21560699439533046, 'lr': 0.0002706781911763059, 'weight_decay': 0.012669446375571386, 'batch_size': 64} - Best Value (CSI): 0.430241 - Best Trial: 4 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.35845930914090496, 'lr': 0.0009607581451670014, 'weight_decay': 0.07737669684354931, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 12:46:39,025] Trial 6 finished with value: 0.4123227960635745 and parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.3940862484422013, 'lr': 0.0006379474533784767, 'weight_decay': 0.0014063697626802458, 'batch_size': 64}. Best is trial 4 with value: 0.4302411821678192. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.412323 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.3940862484422013, 'lr': 0.0006379474533784767, 'weight_decay': 0.0014063697626802458, 'batch_size': 64} - Best Value (CSI): 0.430241 - Best Trial: 4 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.35845930914090496, 'lr': 0.0009607581451670014, 'weight_decay': 0.07737669684354931, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 12:47:47,595] Trial 7 finished with value: 0.40585947078618845 and parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.28524742235282563, 'lr': 0.0033161250617509287, 'weight_decay': 0.002063637723064899, 'batch_size': 128}. Best is trial 4 with value: 0.4302411821678192. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.405859 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.28524742235282563, 'lr': 0.0033161250617509287, 'weight_decay': 0.002063637723064899, 'batch_size': 128} - Best Value (CSI): 0.430241 - Best Trial: 4 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.35845930914090496, 'lr': 0.0009607581451670014, 'weight_decay': 0.07737669684354931, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 12:47:59,157] Trial 8 pruned. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.263520 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.2900111759899311, 'lr': 0.00012717483644731376, 'weight_decay': 0.0027471295555674966, 'batch_size': 64} - Best Value (CSI): 0.430241 - Best Trial: 4 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.35845930914090496, 'lr': 0.0009607581451670014, 'weight_decay': 0.07737669684354931, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 12:49:07,360] Trial 9 finished with value: 0.4179289942714603 and parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.334367210848393, 'lr': 0.0007013057642028161, 'weight_decay': 0.07876526285484178, 'batch_size': 128}. Best is trial 4 with value: 0.4302411821678192. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.417929 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.334367210848393, 'lr': 0.0007013057642028161, 'weight_decay': 0.07876526285484178, 'batch_size': 128} - Best Value (CSI): 0.430241 - Best Trial: 4 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.35845930914090496, 'lr': 0.0009607581451670014, 'weight_decay': 0.07737669684354931, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 12:49:12,033] Trial 10 pruned. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.215686 - Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.3913367761643475, 'lr': 3.309298885680783e-05, 'weight_decay': 0.08312517396355139, 'batch_size': 256} - Best Value (CSI): 0.430241 - Best Trial: 4 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.35845930914090496, 'lr': 0.0009607581451670014, 'weight_decay': 0.07737669684354931, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 12:49:17,492] Trial 11 pruned. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.363165 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.36258305078281133, 'lr': 0.008716866625548174, 'weight_decay': 0.00016533806804300337, 'batch_size': 256} - Best Value (CSI): 0.430241 - Best Trial: 4 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.35845930914090496, 'lr': 0.0009607581451670014, 'weight_decay': 0.07737669684354931, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 12:51:45,203] Trial 12 finished with value: 0.44544694808774704 and parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.24783461805657933, 'lr': 0.0015947013660579806, 'weight_decay': 0.020109718744301845, 'batch_size': 32}. Best is trial 12 with value: 0.44544694808774704. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.445447 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.24783461805657933, 'lr': 0.0015947013660579806, 'weight_decay': 0.020109718744301845, 'batch_size': 32} - Best Value (CSI): 0.445447 - Best Trial: 12 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.24783461805657933, 'lr': 0.0015947013660579806, 'weight_decay': 0.020109718744301845, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 12:54:01,205] Trial 13 finished with value: 0.416416711695267 and parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.23356519277597973, 'lr': 0.0012986320012849447, 'weight_decay': 0.022312140682743595, 'batch_size': 32}. Best is trial 12 with value: 0.44544694808774704. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.416417 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.23356519277597973, 'lr': 0.0012986320012849447, 'weight_decay': 0.022312140682743595, 'batch_size': 32} - Best Value (CSI): 0.445447 - Best Trial: 12 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.24783461805657933, 'lr': 0.0015947013660579806, 'weight_decay': 0.020109718744301845, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 12:57:40,919] Trial 14 finished with value: 0.46241360858882524 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.2611744671484639, 'lr': 0.006538644629674235, 'weight_decay': 0.028806140621950027, 'batch_size': 32}. Best is trial 14 with value: 0.46241360858882524. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.462414 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.2611744671484639, 'lr': 0.006538644629674235, 'weight_decay': 0.028806140621950027, 'batch_size': 32} - Best Value (CSI): 0.462414 - Best Trial: 14 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.2611744671484639, 'lr': 0.006538644629674235, 'weight_decay': 0.028806140621950027, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:00:52,126] Trial 15 finished with value: 0.4464678677018112 and parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.25075848648773574, 'lr': 0.008919562113582653, 'weight_decay': 0.0191937053680462, 'batch_size': 32}. Best is trial 14 with value: 0.46241360858882524. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.446468 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.25075848648773574, 'lr': 0.008919562113582653, 'weight_decay': 0.0191937053680462, 'batch_size': 32} - Best Value (CSI): 0.462414 - Best Trial: 14 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.2611744671484639, 'lr': 0.006538644629674235, 'weight_decay': 0.028806140621950027, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:04:31,687] Trial 16 finished with value: 0.45661394213281636 and parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.2092523244707838, 'lr': 0.008616714482940543, 'weight_decay': 0.009619886172702378, 'batch_size': 32}. Best is trial 14 with value: 0.46241360858882524. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.456614 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.2092523244707838, 'lr': 0.008616714482940543, 'weight_decay': 0.009619886172702378, 'batch_size': 32} - Best Value (CSI): 0.462414 - Best Trial: 14 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.2611744671484639, 'lr': 0.006538644629674235, 'weight_decay': 0.028806140621950027, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 13:05:06,150] Trial 17 pruned. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.352151 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.19446812848501352, 'lr': 0.004211874982670483, 'weight_decay': 0.008085903867602962, 'batch_size': 32} - Best Value (CSI): 0.462414 - Best Trial: 14 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.2611744671484639, 'lr': 0.006538644629674235, 'weight_decay': 0.028806140621950027, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:08:55,815] Trial 18 finished with value: 0.4503917494198751 and parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.1793479886428485, 'lr': 0.0050731893729288975, 'weight_decay': 0.041205522471970624, 'batch_size': 32}. Best is trial 14 with value: 0.46241360858882524. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.450392 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.1793479886428485, 'lr': 0.0050731893729288975, 'weight_decay': 0.041205522471970624, 'batch_size': 32} - Best Value (CSI): 0.462414 - Best Trial: 14 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.2611744671484639, 'lr': 0.006538644629674235, 'weight_decay': 0.028806140621950027, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 13:09:20,993] Trial 19 pruned. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.257967 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1507539012482862, 'lr': 0.009617177351847864, 'weight_decay': 0.009986063118577686, 'batch_size': 32} - Best Value (CSI): 0.462414 - Best Trial: 14 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.2611744671484639, 'lr': 0.006538644629674235, 'weight_decay': 0.028806140621950027, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:11:49,054] Trial 20 finished with value: 0.4569849465850864 and parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10725593660748117, 'lr': 0.0026297398066231557, 'weight_decay': 0.03510283410124723, 'batch_size': 32}. Best is trial 14 with value: 0.46241360858882524. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.456985 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10725593660748117, 'lr': 0.0026297398066231557, 'weight_decay': 0.03510283410124723, 'batch_size': 32} - Best Value (CSI): 0.462414 - Best Trial: 14 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.2611744671484639, 'lr': 0.006538644629674235, 'weight_decay': 0.028806140621950027, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:15:15,661] Trial 21 finished with value: 0.46479094271864296 and parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10122178387986465, 'lr': 0.005261462040436964, 'weight_decay': 0.026181584673643014, 'batch_size': 32}. Best is trial 21 with value: 0.46479094271864296. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.464791 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10122178387986465, 'lr': 0.005261462040436964, 'weight_decay': 0.026181584673643014, 'batch_size': 32} - Best Value (CSI): 0.464791 - Best Trial: 21 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10122178387986465, 'lr': 0.005261462040436964, 'weight_decay': 0.026181584673643014, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:18:48,885] Trial 22 finished with value: 0.45189603407528794 and parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10307647778905539, 'lr': 0.0026343990438759675, 'weight_decay': 0.038011678265953766, 'batch_size': 32}. Best is trial 21 with value: 0.46479094271864296. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.451896 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10307647778905539, 'lr': 0.0026343990438759675, 'weight_decay': 0.038011678265953766, 'batch_size': 32} - Best Value (CSI): 0.464791 - Best Trial: 21 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10122178387986465, 'lr': 0.005261462040436964, 'weight_decay': 0.026181584673643014, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:21:39,824] Trial 23 finished with value: 0.4609580591447227 and parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.11105704375127494, 'lr': 0.004508760543446181, 'weight_decay': 0.03463906506027731, 'batch_size': 32}. Best is trial 21 with value: 0.46479094271864296. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.460958 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.11105704375127494, 'lr': 0.004508760543446181, 'weight_decay': 0.03463906506027731, 'batch_size': 32} - Best Value (CSI): 0.464791 - Best Trial: 21 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10122178387986465, 'lr': 0.005261462040436964, 'weight_decay': 0.026181584673643014, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:24:57,375] Trial 24 finished with value: 0.4535577950195207 and parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.15115644174778628, 'lr': 0.005516124987225362, 'weight_decay': 0.051992726822051, 'batch_size': 32}. Best is trial 21 with value: 0.46479094271864296. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.453558 - Parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.15115644174778628, 'lr': 0.005516124987225362, 'weight_decay': 0.051992726822051, 'batch_size': 32} - Best Value (CSI): 0.464791 - Best Trial: 21 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10122178387986465, 'lr': 0.005261462040436964, 'weight_decay': 0.026181584673643014, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:27:54,788] Trial 25 finished with value: 0.44588746175292643 and parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.10071702532912205, 'lr': 0.0051029023957843015, 'weight_decay': 0.02371691397616606, 'batch_size': 32}. Best is trial 21 with value: 0.46479094271864296. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.445887 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.10071702532912205, 'lr': 0.0051029023957843015, 'weight_decay': 0.02371691397616606, 'batch_size': 32} - Best Value (CSI): 0.464791 - Best Trial: 21 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10122178387986465, 'lr': 0.005261462040436964, 'weight_decay': 0.026181584673643014, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:30:24,396] Trial 26 finished with value: 0.4544073306182926 and parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1617136172194275, 'lr': 0.002272032039904807, 'weight_decay': 0.047697142041128085, 'batch_size': 32}. Best is trial 21 with value: 0.46479094271864296. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.454407 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1617136172194275, 'lr': 0.002272032039904807, 'weight_decay': 0.047697142041128085, 'batch_size': 32} - Best Value (CSI): 0.464791 - Best Trial: 21 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10122178387986465, 'lr': 0.005261462040436964, 'weight_decay': 0.026181584673643014, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:33:34,350] Trial 27 finished with value: 0.43677552914507783 and parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.12751392106341228, 'lr': 0.005515105989642216, 'weight_decay': 0.01444822109613692, 'batch_size': 32}. Best is trial 21 with value: 0.46479094271864296. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.436776 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.12751392106341228, 'lr': 0.005515105989642216, 'weight_decay': 0.01444822109613692, 'batch_size': 32} - Best Value (CSI): 0.464791 - Best Trial: 21 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10122178387986465, 'lr': 0.005261462040436964, 'weight_decay': 0.026181584673643014, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 13:33:43,536] Trial 28 pruned. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.331135 - Parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.17668828464095798, 'lr': 0.0037596969295730326, 'weight_decay': 0.005879323998441681, 'batch_size': 128} - Best Value (CSI): 0.464791 - Best Trial: 21 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10122178387986465, 'lr': 0.005261462040436964, 'weight_decay': 0.026181584673643014, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:36:02,370] Trial 29 finished with value: 0.411336615785038 and parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.12604147478902364, 'lr': 0.0017261908985914732, 'weight_decay': 0.00537341089595442, 'batch_size': 32}. Best is trial 21 with value: 0.46479094271864296. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.411337 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.12604147478902364, 'lr': 0.0017261908985914732, 'weight_decay': 0.00537341089595442, 'batch_size': 32} - Best Value (CSI): 0.464791 - Best Trial: 21 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10122178387986465, 'lr': 0.005261462040436964, 'weight_decay': 0.026181584673643014, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:38:33,719] Trial 30 finished with value: 0.436291531392975 and parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.13807232179753698, 'lr': 0.001244116531033127, 'weight_decay': 0.02804924444213796, 'batch_size': 32}. Best is trial 21 with value: 0.46479094271864296. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.436292 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.13807232179753698, 'lr': 0.001244116531033127, 'weight_decay': 0.02804924444213796, 'batch_size': 32} - Best Value (CSI): 0.464791 - Best Trial: 21 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10122178387986465, 'lr': 0.005261462040436964, 'weight_decay': 0.026181584673643014, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 13:39:22,087] Trial 31 pruned. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.384286 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.11819095619538351, 'lr': 0.002951936508432688, 'weight_decay': 0.031125097849156198, 'batch_size': 32} - Best Value (CSI): 0.464791 - Best Trial: 21 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10122178387986465, 'lr': 0.005261462040436964, 'weight_decay': 0.026181584673643014, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:41:54,149] Trial 32 finished with value: 0.44661138426546776 and parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.11113022352947247, 'lr': 0.0037075977040380297, 'weight_decay': 0.05344766485153693, 'batch_size': 32}. Best is trial 21 with value: 0.46479094271864296. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.446611 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.11113022352947247, 'lr': 0.0037075977040380297, 'weight_decay': 0.05344766485153693, 'batch_size': 32} - Best Value (CSI): 0.464791 - Best Trial: 21 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10122178387986465, 'lr': 0.005261462040436964, 'weight_decay': 0.026181584673643014, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 13:42:26,321] Trial 33 pruned. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.383126 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.13771451569054052, 'lr': 0.0020245633410206974, 'weight_decay': 0.015324674011086075, 'batch_size': 32} - Best Value (CSI): 0.464791 - Best Trial: 21 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10122178387986465, 'lr': 0.005261462040436964, 'weight_decay': 0.026181584673643014, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 13:42:57,737] Trial 34 pruned. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.364985 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.11642584261961077, 'lr': 0.006218554854528793, 'weight_decay': 0.03113403361514693, 'batch_size': 32} - Best Value (CSI): 0.464791 - Best Trial: 21 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10122178387986465, 'lr': 0.005261462040436964, 'weight_decay': 0.026181584673643014, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:43:44,500] Trial 35 finished with value: 0.4281789509609424 and parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.1042205746603048, 'lr': 0.0026188889433300987, 'weight_decay': 0.09312064192113352, 'batch_size': 128}. Best is trial 21 with value: 0.46479094271864296. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.428179 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.1042205746603048, 'lr': 0.0026188889433300987, 'weight_decay': 0.09312064192113352, 'batch_size': 128} - Best Value (CSI): 0.464791 - Best Trial: 21 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10122178387986465, 'lr': 0.005261462040436964, 'weight_decay': 0.026181584673643014, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:44:13,582] Trial 36 finished with value: 0.42336660243247803 and parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.13564114396729246, 'lr': 0.0036374913181047137, 'weight_decay': 0.05564359252440134, 'batch_size': 256}. Best is trial 21 with value: 0.46479094271864296. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.423367 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.13564114396729246, 'lr': 0.0036374913181047137, 'weight_decay': 0.05564359252440134, 'batch_size': 256} - Best Value (CSI): 0.464791 - Best Trial: 21 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10122178387986465, 'lr': 0.005261462040436964, 'weight_decay': 0.026181584673643014, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 13:44:34,690] Trial 37 pruned. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.394109 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.15652875443434233, 'lr': 0.006423209304883422, 'weight_decay': 0.026512056853480997, 'batch_size': 64} - Best Value (CSI): 0.464791 - Best Trial: 21 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10122178387986465, 'lr': 0.005261462040436964, 'weight_decay': 0.026181584673643014, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:47:07,391] Trial 38 finished with value: 0.42500595760098253 and parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.12135498813409618, 'lr': 0.0020470207567328236, 'weight_decay': 0.01411206115390187, 'batch_size': 32}. Best is trial 21 with value: 0.46479094271864296. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.425006 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.12135498813409618, 'lr': 0.0020470207567328236, 'weight_decay': 0.01411206115390187, 'batch_size': 32} - Best Value (CSI): 0.464791 - Best Trial: 21 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10122178387986465, 'lr': 0.005261462040436964, 'weight_decay': 0.026181584673643014, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) -[I 2025-12-28 13:47:59,072] Trial 39 pruned. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.416890 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.13986533039171933, 'lr': 0.000928463224866854, 'weight_decay': 0.06465418678751561, 'batch_size': 64} - Best Value (CSI): 0.464791 - Best Trial: 21 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10122178387986465, 'lr': 0.005261462040436964, 'weight_decay': 0.026181584673643014, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 13:48:39,803] Trial 40 pruned. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.371191 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.16959807766757182, 'lr': 0.0004155789775893521, 'weight_decay': 0.03775287060763421, 'batch_size': 32} - Best Value (CSI): 0.464791 - Best Trial: 21 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10122178387986465, 'lr': 0.005261462040436964, 'weight_decay': 0.026181584673643014, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:52:15,800] Trial 41 finished with value: 0.45185650590929055 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.19584517151561193, 'lr': 0.00737049002941897, 'weight_decay': 0.009034137281013032, 'batch_size': 32}. Best is trial 21 with value: 0.46479094271864296. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.451857 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.19584517151561193, 'lr': 0.00737049002941897, 'weight_decay': 0.009034137281013032, 'batch_size': 32} - Best Value (CSI): 0.464791 - Best Trial: 21 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10122178387986465, 'lr': 0.005261462040436964, 'weight_decay': 0.026181584673643014, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 13:52:43,461] Trial 42 pruned. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.327965 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.11779860638751649, 'lr': 0.009670958943346705, 'weight_decay': 0.01645535886994672, 'batch_size': 32} - Best Value (CSI): 0.464791 - Best Trial: 21 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10122178387986465, 'lr': 0.005261462040436964, 'weight_decay': 0.026181584673643014, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 13:53:22,342] Trial 43 pruned. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.367199 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10302603776219135, 'lr': 0.0067005924419238465, 'weight_decay': 0.010029700937724319, 'batch_size': 32} - Best Value (CSI): 0.464791 - Best Trial: 21 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10122178387986465, 'lr': 0.005261462040436964, 'weight_decay': 0.026181584673643014, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 13:53:27,228] Trial 44 pruned. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.281609 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.2752722876172996, 'lr': 0.0040187047639353105, 'weight_decay': 0.022673099239101477, 'batch_size': 256} - Best Value (CSI): 0.464791 - Best Trial: 21 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10122178387986465, 'lr': 0.005261462040436964, 'weight_decay': 0.026181584673643014, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:54:32,507] Trial 45 finished with value: 0.45284617110666797 and parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.2161907226349917, 'lr': 0.007181153307994011, 'weight_decay': 0.06544232529977383, 'batch_size': 128}. Best is trial 21 with value: 0.46479094271864296. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.452846 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.2161907226349917, 'lr': 0.007181153307994011, 'weight_decay': 0.06544232529977383, 'batch_size': 128} - Best Value (CSI): 0.464791 - Best Trial: 21 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10122178387986465, 'lr': 0.005261462040436964, 'weight_decay': 0.026181584673643014, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:55:57,440] Trial 46 finished with value: 0.4433229672705871 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.1417831167136468, 'lr': 0.002916701166854368, 'weight_decay': 0.035568413022994606, 'batch_size': 64}. Best is trial 21 with value: 0.46479094271864296. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.443323 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.1417831167136468, 'lr': 0.002916701166854368, 'weight_decay': 0.035568413022994606, 'batch_size': 64} - Best Value (CSI): 0.464791 - Best Trial: 21 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10122178387986465, 'lr': 0.005261462040436964, 'weight_decay': 0.026181584673643014, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 13:56:28,960] Trial 47 pruned. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.285498 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.12721300165658223, 'lr': 0.009946420702544395, 'weight_decay': 0.09895065633513092, 'batch_size': 32} - Best Value (CSI): 0.464791 - Best Trial: 21 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10122178387986465, 'lr': 0.005261462040436964, 'weight_decay': 0.026181584673643014, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 13:56:57,512] Trial 48 pruned. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.326409 - Parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.26981512509188, 'lr': 0.00456976348098232, 'weight_decay': 0.019484460456292055, 'batch_size': 32} - Best Value (CSI): 0.464791 - Best Trial: 21 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10122178387986465, 'lr': 0.005261462040436964, 'weight_decay': 0.026181584673643014, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:57:26,976] Trial 49 finished with value: 0.44084978723353174 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.15907736145781765, 'lr': 0.0045340101411759795, 'weight_decay': 0.042833173761078674, 'batch_size': 256}. Best is trial 21 with value: 0.46479094271864296. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.440850 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.15907736145781765, 'lr': 0.0045340101411759795, 'weight_decay': 0.042833173761078674, 'batch_size': 256} - Best Value (CSI): 0.464791 - Best Trial: 21 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10122178387986465, 'lr': 0.005261462040436964, 'weight_decay': 0.026181584673643014, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 13:57:47,716] Trial 50 pruned. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.226754 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.18952506525604182, 'lr': 0.007338802903305222, 'weight_decay': 0.004133073092078845, 'batch_size': 32} - Best Value (CSI): 0.464791 - Best Trial: 21 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10122178387986465, 'lr': 0.005261462040436964, 'weight_decay': 0.026181584673643014, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 13:58:28,723] Trial 51 pruned. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.341679 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.11667768333099689, 'lr': 0.0021385759700771325, 'weight_decay': 0.051036187440769876, 'batch_size': 32} - Best Value (CSI): 0.464791 - Best Trial: 21 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10122178387986465, 'lr': 0.005261462040436964, 'weight_decay': 0.026181584673643014, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 13:58:59,209] Trial 52 pruned. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.384058 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1665605516326069, 'lr': 0.0027114013323183165, 'weight_decay': 0.030081803114934132, 'batch_size': 32} - Best Value (CSI): 0.464791 - Best Trial: 21 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10122178387986465, 'lr': 0.005261462040436964, 'weight_decay': 0.026181584673643014, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 13:59:44,641] Trial 53 pruned. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.414209 - Parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.21017050098317785, 'lr': 0.003173476165684324, 'weight_decay': 0.018886807968091716, 'batch_size': 32} - Best Value (CSI): 0.464791 - Best Trial: 21 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10122178387986465, 'lr': 0.005261462040436964, 'weight_decay': 0.026181584673643014, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:03:21,691] Trial 54 finished with value: 0.44251862842971423 and parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.15174339152956673, 'lr': 0.005240063937049505, 'weight_decay': 0.011619861616332576, 'batch_size': 32}. Best is trial 21 with value: 0.46479094271864296. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.442519 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.15174339152956673, 'lr': 0.005240063937049505, 'weight_decay': 0.011619861616332576, 'batch_size': 32} - Best Value (CSI): 0.464791 - Best Trial: 21 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10122178387986465, 'lr': 0.005261462040436964, 'weight_decay': 0.026181584673643014, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:06:10,772] Trial 55 finished with value: 0.442869983119529 and parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.13069244429924026, 'lr': 0.007684214921380267, 'weight_decay': 0.02516485977504387, 'batch_size': 32}. Best is trial 21 with value: 0.46479094271864296. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.442870 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.13069244429924026, 'lr': 0.007684214921380267, 'weight_decay': 0.02516485977504387, 'batch_size': 32} - Best Value (CSI): 0.464791 - Best Trial: 21 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10122178387986465, 'lr': 0.005261462040436964, 'weight_decay': 0.026181584673643014, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:09:38,036] Trial 56 finished with value: 0.46273493643091584 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.1123814822905133, 'lr': 0.004330519124921856, 'weight_decay': 0.07259394855034221, 'batch_size': 32}. Best is trial 21 with value: 0.46479094271864296. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.462735 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.1123814822905133, 'lr': 0.004330519124921856, 'weight_decay': 0.07259394855034221, 'batch_size': 32} - Best Value (CSI): 0.464791 - Best Trial: 21 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10122178387986465, 'lr': 0.005261462040436964, 'weight_decay': 0.026181584673643014, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:10:24,428] Trial 57 finished with value: 0.4531857523738472 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.11007150474436368, 'lr': 0.004960571020790247, 'weight_decay': 0.06613949240889548, 'batch_size': 128}. Best is trial 21 with value: 0.46479094271864296. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.453186 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.11007150474436368, 'lr': 0.004960571020790247, 'weight_decay': 0.06613949240889548, 'batch_size': 128} - Best Value (CSI): 0.464791 - Best Trial: 21 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10122178387986465, 'lr': 0.005261462040436964, 'weight_decay': 0.026181584673643014, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:12:47,837] Trial 58 finished with value: 0.46990461592330696 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.10343915151139849, 'lr': 0.003938328222874651, 'weight_decay': 0.04150194552991327, 'batch_size': 32}. Best is trial 58 with value: 0.46990461592330696. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.469905 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.10343915151139849, 'lr': 0.003938328222874651, 'weight_decay': 0.04150194552991327, 'batch_size': 32} - Best Value (CSI): 0.469905 - Best Trial: 58 - Best Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.10343915151139849, 'lr': 0.003938328222874651, 'weight_decay': 0.04150194552991327, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:15:41,492] Trial 59 finished with value: 0.4670418888225205 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.11026359600292551, 'lr': 0.0016035834439267957, 'weight_decay': 0.0707050534496364, 'batch_size': 32}. Best is trial 58 with value: 0.46990461592330696. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.467042 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.11026359600292551, 'lr': 0.0016035834439267957, 'weight_decay': 0.0707050534496364, 'batch_size': 32} - Best Value (CSI): 0.469905 - Best Trial: 58 - Best Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.10343915151139849, 'lr': 0.003938328222874651, 'weight_decay': 0.04150194552991327, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:16:56,665] Trial 60 finished with value: 0.46646606942286123 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.10062690897206789, 'lr': 0.0037346237439991998, 'weight_decay': 0.06930667304688505, 'batch_size': 64}. Best is trial 58 with value: 0.46990461592330696. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.466466 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.10062690897206789, 'lr': 0.0037346237439991998, 'weight_decay': 0.06930667304688505, 'batch_size': 64} - Best Value (CSI): 0.469905 - Best Trial: 58 - Best Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.10343915151139849, 'lr': 0.003938328222874651, 'weight_decay': 0.04150194552991327, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:18:09,887] Trial 61 finished with value: 0.46876379797793605 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.10315232437297442, 'lr': 0.0037298848727084825, 'weight_decay': 0.07763738944658308, 'batch_size': 64}. Best is trial 58 with value: 0.46990461592330696. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.468764 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.10315232437297442, 'lr': 0.0037298848727084825, 'weight_decay': 0.07763738944658308, 'batch_size': 64} - Best Value (CSI): 0.469905 - Best Trial: 58 - Best Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.10343915151139849, 'lr': 0.003938328222874651, 'weight_decay': 0.04150194552991327, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:19:26,138] Trial 62 finished with value: 0.4738494121182732 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.10516290838010475, 'lr': 0.0032132950134573578, 'weight_decay': 0.07963486715216589, 'batch_size': 64}. Best is trial 62 with value: 0.4738494121182732. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.473849 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.10516290838010475, 'lr': 0.0032132950134573578, 'weight_decay': 0.07963486715216589, 'batch_size': 64} - Best Value (CSI): 0.473849 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.10516290838010475, 'lr': 0.0032132950134573578, 'weight_decay': 0.07963486715216589, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 14:19:49,319] Trial 63 pruned. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.426367 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.10284306859644116, 'lr': 0.0016398667092600656, 'weight_decay': 0.07902567899317137, 'batch_size': 64} - Best Value (CSI): 0.473849 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.10516290838010475, 'lr': 0.0032132950134573578, 'weight_decay': 0.07963486715216589, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 14:20:12,866] Trial 64 pruned. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.417952 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.125395286308761, 'lr': 0.0031725733828850966, 'weight_decay': 0.07959297170092797, 'batch_size': 64} - Best Value (CSI): 0.473849 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.10516290838010475, 'lr': 0.0032132950134573578, 'weight_decay': 0.07963486715216589, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:21:47,750] Trial 65 finished with value: 0.4711780415622433 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.1002600080532499, 'lr': 0.0035002739099976644, 'weight_decay': 0.09814292599730294, 'batch_size': 64}. Best is trial 62 with value: 0.4738494121182732. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.471178 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.1002600080532499, 'lr': 0.0035002739099976644, 'weight_decay': 0.09814292599730294, 'batch_size': 64} - Best Value (CSI): 0.473849 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.10516290838010475, 'lr': 0.0032132950134573578, 'weight_decay': 0.07963486715216589, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:23:14,397] Trial 66 finished with value: 0.4556448111158719 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.10033705896488646, 'lr': 0.0013636874909160426, 'weight_decay': 0.09334606931126206, 'batch_size': 64}. Best is trial 62 with value: 0.4738494121182732. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.455645 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.10033705896488646, 'lr': 0.0013636874909160426, 'weight_decay': 0.09334606931126206, 'batch_size': 64} - Best Value (CSI): 0.473849 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.10516290838010475, 'lr': 0.0032132950134573578, 'weight_decay': 0.07963486715216589, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:24:31,240] Trial 67 finished with value: 0.45686511845331457 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.14583548989340966, 'lr': 0.0023115777231187593, 'weight_decay': 0.05734222305518099, 'batch_size': 64}. Best is trial 62 with value: 0.4738494121182732. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.456865 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.14583548989340966, 'lr': 0.0023115777231187593, 'weight_decay': 0.05734222305518099, 'batch_size': 64} - Best Value (CSI): 0.473849 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.10516290838010475, 'lr': 0.0032132950134573578, 'weight_decay': 0.07963486715216589, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:25:37,920] Trial 68 finished with value: 0.4483865038460711 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.13048935407867213, 'lr': 0.003367474008078338, 'weight_decay': 0.04266885489892994, 'batch_size': 64}. Best is trial 62 with value: 0.4738494121182732. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.448387 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.13048935407867213, 'lr': 0.003367474008078338, 'weight_decay': 0.04266885489892994, 'batch_size': 64} - Best Value (CSI): 0.473849 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.10516290838010475, 'lr': 0.0032132950134573578, 'weight_decay': 0.07963486715216589, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:26:43,027] Trial 69 finished with value: 0.45320364869775914 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.10007619348051804, 'lr': 0.0019504842734048885, 'weight_decay': 0.09866549740570842, 'batch_size': 64}. Best is trial 62 with value: 0.4738494121182732. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.453204 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.10007619348051804, 'lr': 0.0019504842734048885, 'weight_decay': 0.09866549740570842, 'batch_size': 64} - Best Value (CSI): 0.473849 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.10516290838010475, 'lr': 0.0032132950134573578, 'weight_decay': 0.07963486715216589, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:27:46,316] Trial 70 finished with value: 0.4708613257998487 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.12230284519911813, 'lr': 0.0036400093971619965, 'weight_decay': 0.07259447688909491, 'batch_size': 64}. Best is trial 62 with value: 0.4738494121182732. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.470861 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.12230284519911813, 'lr': 0.0036400093971619965, 'weight_decay': 0.07259447688909491, 'batch_size': 64} - Best Value (CSI): 0.473849 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.10516290838010475, 'lr': 0.0032132950134573578, 'weight_decay': 0.07963486715216589, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:29:06,943] Trial 71 finished with value: 0.4731921537729096 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.11135448839665767, 'lr': 0.003581153818834269, 'weight_decay': 0.07152234550254163, 'batch_size': 64}. Best is trial 62 with value: 0.4738494121182732. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.473192 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.11135448839665767, 'lr': 0.003581153818834269, 'weight_decay': 0.07152234550254163, 'batch_size': 64} - Best Value (CSI): 0.473849 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.10516290838010475, 'lr': 0.0032132950134573578, 'weight_decay': 0.07963486715216589, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:30:14,645] Trial 72 finished with value: 0.46805698597531925 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.12031078641920644, 'lr': 0.0035623507869844894, 'weight_decay': 0.07398905588782931, 'batch_size': 64}. Best is trial 62 with value: 0.4738494121182732. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.468057 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.12031078641920644, 'lr': 0.0035623507869844894, 'weight_decay': 0.07398905588782931, 'batch_size': 64} - Best Value (CSI): 0.473849 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.10516290838010475, 'lr': 0.0032132950134573578, 'weight_decay': 0.07963486715216589, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 14:30:36,230] Trial 73 pruned. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.372635 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.12284981061725049, 'lr': 0.0025909269665593026, 'weight_decay': 0.0791659736809234, 'batch_size': 64} - Best Value (CSI): 0.473849 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.10516290838010475, 'lr': 0.0032132950134573578, 'weight_decay': 0.07963486715216589, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:31:33,459] Trial 74 pruned. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.418367 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.11295129709500419, 'lr': 0.00333118017356316, 'weight_decay': 0.048185147779518274, 'batch_size': 64} - Best Value (CSI): 0.473849 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.10516290838010475, 'lr': 0.0032132950134573578, 'weight_decay': 0.07963486715216589, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 14:31:55,280] Trial 75 pruned. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.423913 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.13403363164525656, 'lr': 0.005860579013208639, 'weight_decay': 0.05991812168220642, 'batch_size': 64} - Best Value (CSI): 0.473849 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.10516290838010475, 'lr': 0.0032132950134573578, 'weight_decay': 0.07963486715216589, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:33:04,291] Trial 76 finished with value: 0.44953428367571197 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.12112144472725093, 'lr': 0.0023460409305517743, 'weight_decay': 0.07957573506983952, 'batch_size': 64}. Best is trial 62 with value: 0.4738494121182732. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.449534 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.12112144472725093, 'lr': 0.0023460409305517743, 'weight_decay': 0.07957573506983952, 'batch_size': 64} - Best Value (CSI): 0.473849 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.10516290838010475, 'lr': 0.0032132950134573578, 'weight_decay': 0.07963486715216589, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:34:01,668] Trial 77 pruned. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.391946 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.10885326124419174, 'lr': 0.001735083487313999, 'weight_decay': 0.05824872350565738, 'batch_size': 64} - Best Value (CSI): 0.473849 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.10516290838010475, 'lr': 0.0032132950134573578, 'weight_decay': 0.07963486715216589, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:35:13,713] Trial 78 finished with value: 0.4717733984888035 and parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.14553078594895047, 'lr': 0.004004563667245331, 'weight_decay': 0.09985783529457035, 'batch_size': 64}. Best is trial 62 with value: 0.4738494121182732. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.471773 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.14553078594895047, 'lr': 0.004004563667245331, 'weight_decay': 0.09985783529457035, 'batch_size': 64} - Best Value (CSI): 0.473849 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.10516290838010475, 'lr': 0.0032132950134573578, 'weight_decay': 0.07963486715216589, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 14:35:33,735] Trial 79 pruned. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.367781 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.13143458094008578, 'lr': 0.004094599159352513, 'weight_decay': 0.046042477082152124, 'batch_size': 64} - Best Value (CSI): 0.473849 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.10516290838010475, 'lr': 0.0032132950134573578, 'weight_decay': 0.07963486715216589, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:37:00,702] Trial 80 finished with value: 0.475435864212341 and parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.1477619274404685, 'lr': 0.00606559205480389, 'weight_decay': 0.08582651929034574, 'batch_size': 64}. Best is trial 80 with value: 0.475435864212341. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.475436 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.1477619274404685, 'lr': 0.00606559205480389, 'weight_decay': 0.08582651929034574, 'batch_size': 64} - Best Value (CSI): 0.475436 - Best Trial: 80 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.1477619274404685, 'lr': 0.00606559205480389, 'weight_decay': 0.08582651929034574, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:38:35,389] Trial 81 finished with value: 0.4690446720663903 and parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.11932083077605173, 'lr': 0.005327508564084069, 'weight_decay': 0.0955542128094541, 'batch_size': 64}. Best is trial 80 with value: 0.475435864212341. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.469045 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.11932083077605173, 'lr': 0.005327508564084069, 'weight_decay': 0.0955542128094541, 'batch_size': 64} - Best Value (CSI): 0.475436 - Best Trial: 80 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.1477619274404685, 'lr': 0.00606559205480389, 'weight_decay': 0.08582651929034574, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 14:38:50,092] Trial 82 pruned. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.360996 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.1466236461260512, 'lr': 0.00581030931160281, 'weight_decay': 0.09580554083173486, 'batch_size': 64} - Best Value (CSI): 0.475436 - Best Trial: 80 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.1477619274404685, 'lr': 0.00606559205480389, 'weight_decay': 0.08582651929034574, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:40:09,920] Trial 83 finished with value: 0.472596433737188 and parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.13864853760774892, 'lr': 0.0045085669563948464, 'weight_decay': 0.09993409982821864, 'batch_size': 64}. Best is trial 80 with value: 0.475435864212341. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.472596 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.13864853760774892, 'lr': 0.0045085669563948464, 'weight_decay': 0.09993409982821864, 'batch_size': 64} - Best Value (CSI): 0.475436 - Best Trial: 80 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.1477619274404685, 'lr': 0.00606559205480389, 'weight_decay': 0.08582651929034574, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:41:30,779] Trial 84 finished with value: 0.46617379263776587 and parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.14271446405676863, 'lr': 0.007843433754653706, 'weight_decay': 0.0885179361034867, 'batch_size': 64}. Best is trial 80 with value: 0.475435864212341. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.466174 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.14271446405676863, 'lr': 0.007843433754653706, 'weight_decay': 0.0885179361034867, 'batch_size': 64} - Best Value (CSI): 0.475436 - Best Trial: 80 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.1477619274404685, 'lr': 0.00606559205480389, 'weight_decay': 0.08582651929034574, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 14:41:44,591] Trial 85 pruned. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.350340 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.13498956855610997, 'lr': 0.00608829177479784, 'weight_decay': 0.09873587514278988, 'batch_size': 64} - Best Value (CSI): 0.475436 - Best Trial: 80 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.1477619274404685, 'lr': 0.00606559205480389, 'weight_decay': 0.08582651929034574, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 14:42:06,149] Trial 86 pruned. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.435933 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.15197546959070507, 'lr': 0.005053531333723819, 'weight_decay': 0.06145208310737065, 'batch_size': 64} - Best Value (CSI): 0.475436 - Best Trial: 80 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.1477619274404685, 'lr': 0.00606559205480389, 'weight_decay': 0.08582651929034574, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 14:42:27,824] Trial 87 pruned. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.365662 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.1163624835329164, 'lr': 0.0029144293825210956, 'weight_decay': 0.047220000884809654, 'batch_size': 64} - Best Value (CSI): 0.475436 - Best Trial: 80 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.1477619274404685, 'lr': 0.00606559205480389, 'weight_decay': 0.08582651929034574, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:43:52,567] Trial 88 finished with value: 0.46356758019824423 and parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.12258940699752771, 'lr': 0.008439770077051094, 'weight_decay': 0.05342405064288168, 'batch_size': 64}. Best is trial 80 with value: 0.475435864212341. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.463568 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.12258940699752771, 'lr': 0.008439770077051094, 'weight_decay': 0.05342405064288168, 'batch_size': 64} - Best Value (CSI): 0.475436 - Best Trial: 80 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.1477619274404685, 'lr': 0.00606559205480389, 'weight_decay': 0.08582651929034574, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:45:34,660] Trial 89 finished with value: 0.47435816635082356 and parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.1384057322190941, 'lr': 0.004651191677613838, 'weight_decay': 0.0854022089004165, 'batch_size': 64}. Best is trial 80 with value: 0.475435864212341. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.474358 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.1384057322190941, 'lr': 0.004651191677613838, 'weight_decay': 0.0854022089004165, 'batch_size': 64} - Best Value (CSI): 0.475436 - Best Trial: 80 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.1477619274404685, 'lr': 0.00606559205480389, 'weight_decay': 0.08582651929034574, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 14:45:49,395] Trial 90 pruned. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.373752 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.13906027469882676, 'lr': 0.004158496008141223, 'weight_decay': 0.03945712957909421, 'batch_size': 64} - Best Value (CSI): 0.475436 - Best Trial: 80 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.1477619274404685, 'lr': 0.00606559205480389, 'weight_decay': 0.08582651929034574, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:47:19,835] Trial 91 finished with value: 0.4634292315789265 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.12713761786644925, 'lr': 0.004717639209683438, 'weight_decay': 0.08401856519228396, 'batch_size': 64}. Best is trial 80 with value: 0.475435864212341. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.463429 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.12713761786644925, 'lr': 0.004717639209683438, 'weight_decay': 0.08401856519228396, 'batch_size': 64} - Best Value (CSI): 0.475436 - Best Trial: 80 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.1477619274404685, 'lr': 0.00606559205480389, 'weight_decay': 0.08582651929034574, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:48:39,581] Trial 92 finished with value: 0.473573455381163 and parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.11235688414616969, 'lr': 0.006265638139969192, 'weight_decay': 0.06397821422856823, 'batch_size': 64}. Best is trial 80 with value: 0.475435864212341. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.473573 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.11235688414616969, 'lr': 0.006265638139969192, 'weight_decay': 0.06397821422856823, 'batch_size': 64} - Best Value (CSI): 0.475436 - Best Trial: 80 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.1477619274404685, 'lr': 0.00606559205480389, 'weight_decay': 0.08582651929034574, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 14:48:54,286] Trial 93 pruned. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.378601 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.11254898329467997, 'lr': 0.006723318974407071, 'weight_decay': 0.06476623144532767, 'batch_size': 64} - Best Value (CSI): 0.475436 - Best Trial: 80 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.1477619274404685, 'lr': 0.00606559205480389, 'weight_decay': 0.08582651929034574, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 14:49:08,127] Trial 94 pruned. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.357616 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.10760543728653212, 'lr': 0.008536974636213146, 'weight_decay': 0.06023221056166393, 'batch_size': 64} - Best Value (CSI): 0.475436 - Best Trial: 80 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.1477619274404685, 'lr': 0.00606559205480389, 'weight_decay': 0.08582651929034574, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:50:44,209] Trial 95 finished with value: 0.47511877713247946 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.14624060851532672, 'lr': 0.004378197360170068, 'weight_decay': 0.08505725369582863, 'batch_size': 64}. Best is trial 80 with value: 0.475435864212341. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.475119 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.14624060851532672, 'lr': 0.004378197360170068, 'weight_decay': 0.08505725369582863, 'batch_size': 64} - Best Value (CSI): 0.475436 - Best Trial: 80 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.1477619274404685, 'lr': 0.00606559205480389, 'weight_decay': 0.08582651929034574, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 14:51:05,973] Trial 96 pruned. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.430707 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.15650543364430916, 'lr': 0.0061115730042290315, 'weight_decay': 0.08722889830883064, 'batch_size': 64} - Best Value (CSI): 0.475436 - Best Trial: 80 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.1477619274404685, 'lr': 0.00606559205480389, 'weight_decay': 0.08582651929034574, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:52:22,109] Trial 97 finished with value: 0.4711528919596078 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.1473454102000562, 'lr': 0.002963275714592843, 'weight_decay': 0.06796800285755306, 'batch_size': 64}. Best is trial 80 with value: 0.475435864212341. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.471153 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.1473454102000562, 'lr': 0.002963275714592843, 'weight_decay': 0.06796800285755306, 'batch_size': 64} - Best Value (CSI): 0.475436 - Best Trial: 80 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.1477619274404685, 'lr': 0.00606559205480389, 'weight_decay': 0.08582651929034574, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 14:52:44,032] Trial 98 pruned. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.394366 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.14698174253583804, 'lr': 0.0028240234823678225, 'weight_decay': 0.05104707902052777, 'batch_size': 64} - Best Value (CSI): 0.475436 - Best Trial: 80 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.1477619274404685, 'lr': 0.00606559205480389, 'weight_decay': 0.08582651929034574, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 14:52:50,486] Trial 99 pruned. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.408163 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.16378835933153857, 'lr': 0.004665472770577183, 'weight_decay': 0.06618511843932078, 'batch_size': 256} - Best Value (CSI): 0.475436 - Best Trial: 80 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.1477619274404685, 'lr': 0.00606559205480389, 'weight_decay': 0.08582651929034574, 'batch_size': 64} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.4754 -Best Hyperparameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.1477619274404685, 'lr': 0.00606559205480389, 'weight_decay': 0.08582651929034574, 'batch_size': 64} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.3877 - - 최종 CSI: 0.4082 - - 최고 CSI: 0.4754 - - 최저 CSI: 0.2157 - - 평균 CSI: 0.4151 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/deepgbm_ctgan10000_busan_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 27, Best CSI: 0.4443 - Fold 1 학습 완료 (검증 CSI: 0.4443) -Fold 2 학습 중... - Early stopping at epoch 40, Best CSI: 0.4866 - Fold 2 학습 완료 (검증 CSI: 0.4866) -Fold 3 학습 중... - Early stopping at epoch 27, Best CSI: 0.4576 - Fold 3 학습 완료 (검증 CSI: 0.4576) - -모든 모델 저장 완료: ../save_model/deepgbm_optima/deepgbm_ctgan10000_busan.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/deepgbm_optima/scaler/deepgbm_ctgan10000_busan_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: ../save_model/deepgbm_optima/deepgbm_ctgan10000_busan.pkl - -✓ 완료: deepgbm_ctgan10000/deepgbm_ctgan10000_busan.py (소요 시간: 8294초) - ----------------------------------------- -실행 중: deepgbm_ctgan10000/deepgbm_ctgan10000_daegu.py -시작 시간: 2025-12-28 14:54:16 ----------------------------------------- -[I 2025-12-28 14:54:17,294] A new study created in memory with name: no-name-1e4d0e56-5aa9-4335-b0a9-44df45f7ae9e - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 14:54:59,889] Trial 0 finished with value: 0.33960186302143996 and parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.10048263954190001, 'lr': 0.0002745507870780533, 'weight_decay': 0.001496979780233946, 'batch_size': 256}. Best is trial 0 with value: 0.33960186302143996. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.339602 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.10048263954190001, 'lr': 0.0002745507870780533, 'weight_decay': 0.001496979780233946, 'batch_size': 256} - Best Value (CSI): 0.339602 - Best Trial: 0 - Best Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.10048263954190001, 'lr': 0.0002745507870780533, 'weight_decay': 0.001496979780233946, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 14:58:12,514] Trial 1 finished with value: 0.378187050254666 and parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.22155329979083938, 'lr': 0.0023309763802577183, 'weight_decay': 0.0009183235132857968, 'batch_size': 32}. Best is trial 1 with value: 0.378187050254666. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.378187 - Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.22155329979083938, 'lr': 0.0023309763802577183, 'weight_decay': 0.0009183235132857968, 'batch_size': 32} - Best Value (CSI): 0.378187 - Best Trial: 1 - Best Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.22155329979083938, 'lr': 0.0023309763802577183, 'weight_decay': 0.0009183235132857968, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 15:00:30,934] Trial 2 finished with value: 0.35026477913685633 and parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.24210179642763666, 'lr': 0.000742302130252828, 'weight_decay': 0.0003503412323504509, 'batch_size': 32}. Best is trial 1 with value: 0.378187050254666. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.350265 - Parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.24210179642763666, 'lr': 0.000742302130252828, 'weight_decay': 0.0003503412323504509, 'batch_size': 32} - Best Value (CSI): 0.378187 - Best Trial: 1 - Best Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.22155329979083938, 'lr': 0.0023309763802577183, 'weight_decay': 0.0009183235132857968, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 15:04:38,292] Trial 3 finished with value: 0.3301398002787137 and parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.10234419782441666, 'lr': 0.00016253902796375507, 'weight_decay': 0.0006230230664403558, 'batch_size': 32}. Best is trial 1 with value: 0.378187050254666. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.330140 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.10234419782441666, 'lr': 0.00016253902796375507, 'weight_decay': 0.0006230230664403558, 'batch_size': 32} - Best Value (CSI): 0.378187 - Best Trial: 1 - Best Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.22155329979083938, 'lr': 0.0023309763802577183, 'weight_decay': 0.0009183235132857968, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 15:05:40,296] Trial 4 finished with value: 0.33245678200602513 and parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3887969411422143, 'lr': 0.00012747702678318117, 'weight_decay': 0.0002873462291200247, 'batch_size': 128}. Best is trial 1 with value: 0.378187050254666. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.332457 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3887969411422143, 'lr': 0.00012747702678318117, 'weight_decay': 0.0002873462291200247, 'batch_size': 128} - Best Value (CSI): 0.378187 - Best Trial: 1 - Best Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.22155329979083938, 'lr': 0.0023309763802577183, 'weight_decay': 0.0009183235132857968, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 15:06:06,739] Trial 5 pruned. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.216428 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3900404617305159, 'lr': 5.6741912267302266e-05, 'weight_decay': 0.00010384733848756253, 'batch_size': 32} - Best Value (CSI): 0.378187 - Best Trial: 1 - Best Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.22155329979083938, 'lr': 0.0023309763802577183, 'weight_decay': 0.0009183235132857968, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 15:06:11,806] Trial 6 pruned. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.189189 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.30698604510312133, 'lr': 0.00029992139445755725, 'weight_decay': 0.03440661181292897, 'batch_size': 256} - Best Value (CSI): 0.378187 - Best Trial: 1 - Best Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.22155329979083938, 'lr': 0.0023309763802577183, 'weight_decay': 0.0009183235132857968, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 15:06:24,384] Trial 7 pruned. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.173953 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.2256099266265833, 'lr': 1.7323035220239333e-05, 'weight_decay': 0.00046577441537449225, 'batch_size': 64} - Best Value (CSI): 0.378187 - Best Trial: 1 - Best Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.22155329979083938, 'lr': 0.0023309763802577183, 'weight_decay': 0.0009183235132857968, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 15:06:29,235] Trial 8 pruned. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.281713 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.12815968983554082, 'lr': 0.00030377436541432297, 'weight_decay': 0.060474452061187116, 'batch_size': 256} - Best Value (CSI): 0.378187 - Best Trial: 1 - Best Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.22155329979083938, 'lr': 0.0023309763802577183, 'weight_decay': 0.0009183235132857968, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 15:06:39,815] Trial 9 pruned. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.144216 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2369923546373676, 'lr': 1.1467383066888542e-05, 'weight_decay': 0.00018409455028139236, 'batch_size': 64} - Best Value (CSI): 0.378187 - Best Trial: 1 - Best Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.22155329979083938, 'lr': 0.0023309763802577183, 'weight_decay': 0.0009183235132857968, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 15:06:48,783] Trial 10 pruned. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.279107 - Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.17658483625448684, 'lr': 0.005871469039710539, 'weight_decay': 0.005421816186441453, 'batch_size': 128} - Best Value (CSI): 0.378187 - Best Trial: 1 - Best Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.22155329979083938, 'lr': 0.0023309763802577183, 'weight_decay': 0.0009183235132857968, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 15:07:52,242] Trial 11 pruned. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.339545 - Parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.27372157370147204, 'lr': 0.0016312172583869298, 'weight_decay': 0.001606280657702201, 'batch_size': 32} - Best Value (CSI): 0.378187 - Best Trial: 1 - Best Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.22155329979083938, 'lr': 0.0023309763802577183, 'weight_decay': 0.0009183235132857968, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 15:10:03,778] Trial 12 finished with value: 0.3575303736547419 and parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.1987882323157377, 'lr': 0.0010111621718003714, 'weight_decay': 0.0006788363622574628, 'batch_size': 32}. Best is trial 1 with value: 0.378187050254666. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.357530 - Parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.1987882323157377, 'lr': 0.0010111621718003714, 'weight_decay': 0.0006788363622574628, 'batch_size': 32} - Best Value (CSI): 0.378187 - Best Trial: 1 - Best Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.22155329979083938, 'lr': 0.0023309763802577183, 'weight_decay': 0.0009183235132857968, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 15:12:08,854] Trial 13 finished with value: 0.380394119570451 and parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.18477220842484451, 'lr': 0.0022024613385582784, 'weight_decay': 0.006098907755954173, 'batch_size': 32}. Best is trial 13 with value: 0.380394119570451. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.380394 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.18477220842484451, 'lr': 0.0022024613385582784, 'weight_decay': 0.006098907755954173, 'batch_size': 32} - Best Value (CSI): 0.380394 - Best Trial: 13 - Best Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.18477220842484451, 'lr': 0.0022024613385582784, 'weight_decay': 0.006098907755954173, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 15:12:28,091] Trial 14 pruned. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.142020 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.16258022061872707, 'lr': 0.009270721771587715, 'weight_decay': 0.007325433261845298, 'batch_size': 32} - Best Value (CSI): 0.380394 - Best Trial: 13 - Best Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.18477220842484451, 'lr': 0.0022024613385582784, 'weight_decay': 0.006098907755954173, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 15:14:55,717] Trial 15 finished with value: 0.39461737943964487 and parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.1924651597461154, 'lr': 0.0030885495511274873, 'weight_decay': 0.010611090514443111, 'batch_size': 32}. Best is trial 15 with value: 0.39461737943964487. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.394617 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.1924651597461154, 'lr': 0.0030885495511274873, 'weight_decay': 0.010611090514443111, 'batch_size': 32} - Best Value (CSI): 0.394617 - Best Trial: 15 - Best Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.1924651597461154, 'lr': 0.0030885495511274873, 'weight_decay': 0.010611090514443111, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 15:15:36,502] Trial 16 pruned. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.328571 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1692930291006192, 'lr': 0.0031251988683074893, 'weight_decay': 0.013115400056001382, 'batch_size': 32} - Best Value (CSI): 0.394617 - Best Trial: 15 - Best Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.1924651597461154, 'lr': 0.0030885495511274873, 'weight_decay': 0.010611090514443111, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 15:16:53,214] Trial 17 finished with value: 0.4000563717405678 and parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.14549554721861246, 'lr': 0.0042283154042823574, 'weight_decay': 0.01600657222055848, 'batch_size': 64}. Best is trial 17 with value: 0.4000563717405678. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.400056 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.14549554721861246, 'lr': 0.0042283154042823574, 'weight_decay': 0.01600657222055848, 'batch_size': 64} - Best Value (CSI): 0.400056 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.14549554721861246, 'lr': 0.0042283154042823574, 'weight_decay': 0.01600657222055848, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 15:17:13,935] Trial 18 pruned. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.325444 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.13852886777007783, 'lr': 0.0049130774112810475, 'weight_decay': 0.019039109136041434, 'batch_size': 64} - Best Value (CSI): 0.400056 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.14549554721861246, 'lr': 0.0042283154042823574, 'weight_decay': 0.01600657222055848, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 15:17:36,091] Trial 19 pruned. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.325820 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.14378125310157108, 'lr': 0.000853084962796281, 'weight_decay': 0.08374313816560215, 'batch_size': 64} - Best Value (CSI): 0.400056 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.14549554721861246, 'lr': 0.0042283154042823574, 'weight_decay': 0.01600657222055848, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 15:17:56,872] Trial 20 pruned. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.315197 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20430798181732893, 'lr': 0.009481253488026937, 'weight_decay': 0.003510821113638696, 'batch_size': 64} - Best Value (CSI): 0.400056 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.14549554721861246, 'lr': 0.0042283154042823574, 'weight_decay': 0.01600657222055848, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 15:18:11,231] Trial 21 pruned. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.323587 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.18849418379310373, 'lr': 0.0037008101568512786, 'weight_decay': 0.009709737963720209, 'batch_size': 128} - Best Value (CSI): 0.400056 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.14549554721861246, 'lr': 0.0042283154042823574, 'weight_decay': 0.01600657222055848, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 15:18:34,712] Trial 22 pruned. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.315682 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15679242807934113, 'lr': 0.001762002658743736, 'weight_decay': 0.023012999699570953, 'batch_size': 64} - Best Value (CSI): 0.400056 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.14549554721861246, 'lr': 0.0042283154042823574, 'weight_decay': 0.01600657222055848, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 15:19:15,853] Trial 23 pruned. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.334004 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.18552991449244122, 'lr': 0.004314857338256199, 'weight_decay': 0.004054433717502271, 'batch_size': 32} - Best Value (CSI): 0.400056 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.14549554721861246, 'lr': 0.0042283154042823574, 'weight_decay': 0.01600657222055848, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 15:21:19,243] Trial 24 finished with value: 0.3727207971690169 and parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.13495439472033993, 'lr': 0.0023581672617071455, 'weight_decay': 0.00925572156828387, 'batch_size': 32}. Best is trial 17 with value: 0.4000563717405678. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.372721 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.13495439472033993, 'lr': 0.0023581672617071455, 'weight_decay': 0.00925572156828387, 'batch_size': 32} - Best Value (CSI): 0.400056 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.14549554721861246, 'lr': 0.0042283154042823574, 'weight_decay': 0.01600657222055848, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 15:21:30,130] Trial 25 pruned. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.299228 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2023411205642721, 'lr': 0.0013934789006436795, 'weight_decay': 0.005917705091244245, 'batch_size': 64} - Best Value (CSI): 0.400056 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.14549554721861246, 'lr': 0.0042283154042823574, 'weight_decay': 0.01600657222055848, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 15:21:37,006] Trial 26 pruned. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.281588 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.16082080619188416, 'lr': 0.0007285685942847825, 'weight_decay': 0.014537818071242145, 'batch_size': 128} - Best Value (CSI): 0.400056 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.14549554721861246, 'lr': 0.0042283154042823574, 'weight_decay': 0.01600657222055848, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 15:22:02,727] Trial 27 finished with value: 0.3580498689706458 and parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.12046690457923395, 'lr': 0.00285404198894877, 'weight_decay': 0.032440512033505245, 'batch_size': 256}. Best is trial 17 with value: 0.4000563717405678. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.358050 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.12046690457923395, 'lr': 0.00285404198894877, 'weight_decay': 0.032440512033505245, 'batch_size': 256} - Best Value (CSI): 0.400056 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.14549554721861246, 'lr': 0.0042283154042823574, 'weight_decay': 0.01600657222055848, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) -[I 2025-12-28 15:23:21,663] Trial 28 pruned. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.364070 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.1594196831432449, 'lr': 0.005012351768452008, 'weight_decay': 0.0024195409645248636, 'batch_size': 32} - Best Value (CSI): 0.400056 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.14549554721861246, 'lr': 0.0042283154042823574, 'weight_decay': 0.01600657222055848, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 15:23:56,226] Trial 29 finished with value: 0.3418937482231015 and parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.10026137768943591, 'lr': 0.0005071182078194477, 'weight_decay': 0.0025616810444000424, 'batch_size': 256}. Best is trial 17 with value: 0.4000563717405678. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.341894 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.10026137768943591, 'lr': 0.0005071182078194477, 'weight_decay': 0.0025616810444000424, 'batch_size': 256} - Best Value (CSI): 0.400056 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.14549554721861246, 'lr': 0.0042283154042823574, 'weight_decay': 0.01600657222055848, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 15:24:19,863] Trial 30 pruned. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.283422 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.18096919005163525, 'lr': 0.0014103091954209583, 'weight_decay': 0.010927837450943074, 'batch_size': 64} - Best Value (CSI): 0.400056 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.14549554721861246, 'lr': 0.0042283154042823574, 'weight_decay': 0.01600657222055848, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 15:26:58,999] Trial 31 finished with value: 0.37935287568317616 and parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.21905504111672588, 'lr': 0.002465022033722438, 'weight_decay': 0.0013269388987709764, 'batch_size': 32}. Best is trial 17 with value: 0.4000563717405678. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.379353 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.21905504111672588, 'lr': 0.002465022033722438, 'weight_decay': 0.0013269388987709764, 'batch_size': 32} - Best Value (CSI): 0.400056 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.14549554721861246, 'lr': 0.0042283154042823574, 'weight_decay': 0.01600657222055848, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 15:27:44,971] Trial 32 pruned. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.314991 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.20884665205982916, 'lr': 0.0022217758252304656, 'weight_decay': 0.0013357889768425624, 'batch_size': 32} - Best Value (CSI): 0.400056 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.14549554721861246, 'lr': 0.0042283154042823574, 'weight_decay': 0.01600657222055848, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 15:30:45,257] Trial 33 finished with value: 0.3811670100504399 and parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.2200406257411401, 'lr': 0.0031756337291676904, 'weight_decay': 0.005099832816906901, 'batch_size': 32}. Best is trial 17 with value: 0.4000563717405678. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.381167 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.2200406257411401, 'lr': 0.0031756337291676904, 'weight_decay': 0.005099832816906901, 'batch_size': 32} - Best Value (CSI): 0.400056 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.14549554721861246, 'lr': 0.0042283154042823574, 'weight_decay': 0.01600657222055848, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 15:31:40,437] Trial 34 pruned. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.339583 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.18033519508295007, 'lr': 0.006467974921124283, 'weight_decay': 0.005628950349856029, 'batch_size': 32} - Best Value (CSI): 0.400056 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.14549554721861246, 'lr': 0.0042283154042823574, 'weight_decay': 0.01600657222055848, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 15:34:07,661] Trial 35 finished with value: 0.38558896650370217 and parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.24809515970884113, 'lr': 0.003314829018161552, 'weight_decay': 0.004163944482652498, 'batch_size': 32}. Best is trial 17 with value: 0.4000563717405678. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.385589 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.24809515970884113, 'lr': 0.003314829018161552, 'weight_decay': 0.004163944482652498, 'batch_size': 32} - Best Value (CSI): 0.400056 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.14549554721861246, 'lr': 0.0042283154042823574, 'weight_decay': 0.01600657222055848, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 15:34:53,121] Trial 36 pruned. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.297794 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.25497131234602605, 'lr': 0.0037933452381971084, 'weight_decay': 0.0038310440362187485, 'batch_size': 32} - Best Value (CSI): 0.400056 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.14549554721861246, 'lr': 0.0042283154042823574, 'weight_decay': 0.01600657222055848, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 15:35:22,208] Trial 37 pruned. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.308129 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.25670370008547383, 'lr': 0.006934659694851737, 'weight_decay': 0.008708763672140601, 'batch_size': 32} - Best Value (CSI): 0.400056 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.14549554721861246, 'lr': 0.0042283154042823574, 'weight_decay': 0.01600657222055848, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 15:37:53,008] Trial 38 finished with value: 0.40295645783222445 and parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.2331537495643457, 'lr': 0.003807932680873466, 'weight_decay': 0.016284937836895323, 'batch_size': 32}. Best is trial 38 with value: 0.40295645783222445. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.402956 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.2331537495643457, 'lr': 0.003807932680873466, 'weight_decay': 0.016284937836895323, 'batch_size': 32} - Best Value (CSI): 0.402956 - Best Trial: 38 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.2331537495643457, 'lr': 0.003807932680873466, 'weight_decay': 0.016284937836895323, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 15:38:07,573] Trial 39 pruned. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.338947 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.2801036692348856, 'lr': 0.007012452889600593, 'weight_decay': 0.015688854761380218, 'batch_size': 128} - Best Value (CSI): 0.402956 - Best Trial: 38 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.2331537495643457, 'lr': 0.003807932680873466, 'weight_decay': 0.016284937836895323, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 15:38:17,298] Trial 40 pruned. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.311321 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.2386862425847814, 'lr': 0.004478105841634324, 'weight_decay': 0.025823948725600267, 'batch_size': 256} - Best Value (CSI): 0.402956 - Best Trial: 38 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.2331537495643457, 'lr': 0.003807932680873466, 'weight_decay': 0.016284937836895323, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 15:41:22,270] Trial 41 finished with value: 0.40664550112368597 and parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.22224770351769335, 'lr': 0.0031850146121884565, 'weight_decay': 0.012819131240404945, 'batch_size': 32}. Best is trial 41 with value: 0.40664550112368597. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.406646 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.22224770351769335, 'lr': 0.0031850146121884565, 'weight_decay': 0.012819131240404945, 'batch_size': 32} - Best Value (CSI): 0.406646 - Best Trial: 41 - Best Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.22224770351769335, 'lr': 0.0031850146121884565, 'weight_decay': 0.012819131240404945, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 15:42:05,266] Trial 42 pruned. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.333333 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.22485139046358923, 'lr': 0.0034303581376202356, 'weight_decay': 0.012504761765884595, 'batch_size': 32} - Best Value (CSI): 0.406646 - Best Trial: 41 - Best Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.22224770351769335, 'lr': 0.0031850146121884565, 'weight_decay': 0.012819131240404945, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 15:42:45,376] Trial 43 pruned. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.316633 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23564010646592504, 'lr': 0.0013473863399158202, 'weight_decay': 0.017353789613487547, 'batch_size': 32} - Best Value (CSI): 0.406646 - Best Trial: 41 - Best Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.22224770351769335, 'lr': 0.0031850146121884565, 'weight_decay': 0.012819131240404945, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 15:43:06,863] Trial 44 pruned. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.302120 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2123574084395499, 'lr': 0.005857530768100317, 'weight_decay': 0.04076612701676704, 'batch_size': 32} - Best Value (CSI): 0.406646 - Best Trial: 41 - Best Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.22224770351769335, 'lr': 0.0031850146121884565, 'weight_decay': 0.012819131240404945, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 15:43:53,003] Trial 45 pruned. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.325349 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.19375415461702583, 'lr': 0.0018377324818930816, 'weight_decay': 0.01983152938067292, 'batch_size': 32} - Best Value (CSI): 0.406646 - Best Trial: 41 - Best Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.22224770351769335, 'lr': 0.0031850146121884565, 'weight_decay': 0.012819131240404945, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 15:45:06,371] Trial 46 finished with value: 0.37992762877813924 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.24701408663501526, 'lr': 0.009864887333526164, 'weight_decay': 0.007671297932674995, 'batch_size': 64}. Best is trial 41 with value: 0.40664550112368597. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.379928 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.24701408663501526, 'lr': 0.009864887333526164, 'weight_decay': 0.007671297932674995, 'batch_size': 64} - Best Value (CSI): 0.406646 - Best Trial: 41 - Best Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.22224770351769335, 'lr': 0.0031850146121884565, 'weight_decay': 0.012819131240404945, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 15:45:47,317] Trial 47 pruned. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.345416 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.26824946056927285, 'lr': 0.002635588805095361, 'weight_decay': 0.01055055196168097, 'batch_size': 32} - Best Value (CSI): 0.406646 - Best Trial: 41 - Best Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.22224770351769335, 'lr': 0.0031850146121884565, 'weight_decay': 0.012819131240404945, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 15:48:39,163] Trial 48 finished with value: 0.42145417609942265 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.23116500347660948, 'lr': 0.0043001569401369295, 'weight_decay': 0.02502971721388179, 'batch_size': 32}. Best is trial 48 with value: 0.42145417609942265. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.421454 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.23116500347660948, 'lr': 0.0043001569401369295, 'weight_decay': 0.02502971721388179, 'batch_size': 32} - Best Value (CSI): 0.421454 - Best Trial: 48 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.23116500347660948, 'lr': 0.0043001569401369295, 'weight_decay': 0.02502971721388179, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 15:49:29,063] Trial 49 finished with value: 0.4068470091998704 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.23226018453531014, 'lr': 0.005206590835911559, 'weight_decay': 0.04146263223013787, 'batch_size': 128}. Best is trial 48 with value: 0.42145417609942265. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.406847 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.23226018453531014, 'lr': 0.005206590835911559, 'weight_decay': 0.04146263223013787, 'batch_size': 128} - Best Value (CSI): 0.421454 - Best Trial: 48 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.23116500347660948, 'lr': 0.0043001569401369295, 'weight_decay': 0.02502971721388179, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 15:49:41,875] Trial 50 pruned. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.364606 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.23249384831817896, 'lr': 0.007857233876157093, 'weight_decay': 0.04779274217898951, 'batch_size': 128} - Best Value (CSI): 0.421454 - Best Trial: 48 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.23116500347660948, 'lr': 0.0043001569401369295, 'weight_decay': 0.02502971721388179, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 15:49:55,191] Trial 51 pruned. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.349036 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.21274418709485665, 'lr': 0.004610268512836974, 'weight_decay': 0.029319070111060556, 'batch_size': 128} - Best Value (CSI): 0.421454 - Best Trial: 48 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.23116500347660948, 'lr': 0.0043001569401369295, 'weight_decay': 0.02502971721388179, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 15:50:07,983] Trial 52 pruned. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.351515 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.19619780462285477, 'lr': 0.005012276268645425, 'weight_decay': 0.02343045489049477, 'batch_size': 128} - Best Value (CSI): 0.421454 - Best Trial: 48 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.23116500347660948, 'lr': 0.0043001569401369295, 'weight_decay': 0.02502971721388179, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 15:50:20,925] Trial 53 pruned. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.325758 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2258126480060682, 'lr': 0.005788950250086275, 'weight_decay': 0.036082202296057, 'batch_size': 128} - Best Value (CSI): 0.421454 - Best Trial: 48 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.23116500347660948, 'lr': 0.0043001569401369295, 'weight_decay': 0.02502971721388179, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 15:50:41,799] Trial 54 pruned. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.338677 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.20151910041807816, 'lr': 0.001985057449992942, 'weight_decay': 0.056769697494184486, 'batch_size': 64} - Best Value (CSI): 0.421454 - Best Trial: 48 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.23116500347660948, 'lr': 0.0043001569401369295, 'weight_decay': 0.02502971721388179, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 15:51:20,761] Trial 55 pruned. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.372043 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.23158974564775106, 'lr': 0.00398657424787013, 'weight_decay': 0.015653997838963384, 'batch_size': 32} - Best Value (CSI): 0.421454 - Best Trial: 48 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.23116500347660948, 'lr': 0.0043001569401369295, 'weight_decay': 0.02502971721388179, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 15:51:30,250] Trial 56 pruned. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.342553 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.17079815320472425, 'lr': 0.0073595517888106945, 'weight_decay': 0.021819150180444478, 'batch_size': 256} - Best Value (CSI): 0.421454 - Best Trial: 48 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.23116500347660948, 'lr': 0.0043001569401369295, 'weight_decay': 0.02502971721388179, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 15:52:06,930] Trial 57 finished with value: 0.3687659290710921 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.21336219315347604, 'lr': 0.002925132271490882, 'weight_decay': 0.031280854643638986, 'batch_size': 128}. Best is trial 48 with value: 0.42145417609942265. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.368766 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.21336219315347604, 'lr': 0.002925132271490882, 'weight_decay': 0.031280854643638986, 'batch_size': 128} - Best Value (CSI): 0.421454 - Best Trial: 48 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.23116500347660948, 'lr': 0.0043001569401369295, 'weight_decay': 0.02502971721388179, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 15:53:33,366] Trial 58 finished with value: 0.39936790701198577 and parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.1905684088156614, 'lr': 0.008469987984473362, 'weight_decay': 0.012933105493036955, 'batch_size': 64}. Best is trial 48 with value: 0.42145417609942265. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.399368 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.1905684088156614, 'lr': 0.008469987984473362, 'weight_decay': 0.012933105493036955, 'batch_size': 64} - Best Value (CSI): 0.421454 - Best Trial: 48 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.23116500347660948, 'lr': 0.0043001569401369295, 'weight_decay': 0.02502971721388179, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 15:54:14,485] Trial 59 pruned. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.382096 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.24173706505852102, 'lr': 0.008762272393309338, 'weight_decay': 0.04626382716456711, 'batch_size': 64} - Best Value (CSI): 0.421454 - Best Trial: 48 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.23116500347660948, 'lr': 0.0043001569401369295, 'weight_decay': 0.02502971721388179, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 15:55:36,538] Trial 60 finished with value: 0.3848774718042837 and parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.1487706625022873, 'lr': 0.005805394947233362, 'weight_decay': 0.013095605303222464, 'batch_size': 64}. Best is trial 48 with value: 0.42145417609942265. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.384877 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.1487706625022873, 'lr': 0.005805394947233362, 'weight_decay': 0.013095605303222464, 'batch_size': 64} - Best Value (CSI): 0.421454 - Best Trial: 48 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.23116500347660948, 'lr': 0.0043001569401369295, 'weight_decay': 0.02502971721388179, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 15:55:59,453] Trial 61 pruned. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.367059 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.1958102282739253, 'lr': 0.009919418871469524, 'weight_decay': 0.018543587937345493, 'batch_size': 64} - Best Value (CSI): 0.421454 - Best Trial: 48 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.23116500347660948, 'lr': 0.0043001569401369295, 'weight_decay': 0.02502971721388179, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 15:56:25,483] Trial 62 pruned. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.375286 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.18685303040593396, 'lr': 0.00399249857796903, 'weight_decay': 0.024774146741234238, 'batch_size': 64} - Best Value (CSI): 0.421454 - Best Trial: 48 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.23116500347660948, 'lr': 0.0043001569401369295, 'weight_decay': 0.02502971721388179, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 15:56:36,394] Trial 63 pruned. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.295539 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.1717267812500946, 'lr': 0.002740554054051416, 'weight_decay': 0.007621198778933801, 'batch_size': 64} - Best Value (CSI): 0.421454 - Best Trial: 48 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.23116500347660948, 'lr': 0.0043001569401369295, 'weight_decay': 0.02502971721388179, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 15:58:57,314] Trial 64 finished with value: 0.39822335379713375 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.20360696974109407, 'lr': 0.005455502272971773, 'weight_decay': 0.026327451893355905, 'batch_size': 32}. Best is trial 48 with value: 0.42145417609942265. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.398223 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.20360696974109407, 'lr': 0.005455502272971773, 'weight_decay': 0.026327451893355905, 'batch_size': 32} - Best Value (CSI): 0.421454 - Best Trial: 48 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.23116500347660948, 'lr': 0.0043001569401369295, 'weight_decay': 0.02502971721388179, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 16:01:26,250] Trial 65 finished with value: 0.4100355390772889 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2044385538858529, 'lr': 0.007565609810659757, 'weight_decay': 0.028303648802007017, 'batch_size': 32}. Best is trial 48 with value: 0.42145417609942265. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.410036 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2044385538858529, 'lr': 0.007565609810659757, 'weight_decay': 0.028303648802007017, 'batch_size': 32} - Best Value (CSI): 0.421454 - Best Trial: 48 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.23116500347660948, 'lr': 0.0043001569401369295, 'weight_decay': 0.02502971721388179, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 16:04:06,989] Trial 66 finished with value: 0.406772216728585 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.21973247126026793, 'lr': 0.007196792694573845, 'weight_decay': 0.03925927159021245, 'batch_size': 32}. Best is trial 48 with value: 0.42145417609942265. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.406772 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.21973247126026793, 'lr': 0.007196792694573845, 'weight_decay': 0.03925927159021245, 'batch_size': 32} - Best Value (CSI): 0.421454 - Best Trial: 48 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.23116500347660948, 'lr': 0.0043001569401369295, 'weight_decay': 0.02502971721388179, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 16:07:15,372] Trial 67 finished with value: 0.4139072734590785 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.22733156939039767, 'lr': 0.007122653237615367, 'weight_decay': 0.037180831575158044, 'batch_size': 32}. Best is trial 48 with value: 0.42145417609942265. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.413907 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.22733156939039767, 'lr': 0.007122653237615367, 'weight_decay': 0.037180831575158044, 'batch_size': 32} - Best Value (CSI): 0.421454 - Best Trial: 48 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.23116500347660948, 'lr': 0.0043001569401369295, 'weight_decay': 0.02502971721388179, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 16:08:17,808] Trial 68 pruned. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.383908 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.22439658111306635, 'lr': 0.006919926873655944, 'weight_decay': 0.07690462320789974, 'batch_size': 32} - Best Value (CSI): 0.421454 - Best Trial: 48 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.23116500347660948, 'lr': 0.0043001569401369295, 'weight_decay': 0.02502971721388179, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 16:11:08,649] Trial 69 finished with value: 0.41299611339727144 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.21866999306443635, 'lr': 0.0076109067142395665, 'weight_decay': 0.0367317698662934, 'batch_size': 32}. Best is trial 48 with value: 0.42145417609942265. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.412996 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.21866999306443635, 'lr': 0.0076109067142395665, 'weight_decay': 0.0367317698662934, 'batch_size': 32} - Best Value (CSI): 0.421454 - Best Trial: 48 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.23116500347660948, 'lr': 0.0043001569401369295, 'weight_decay': 0.02502971721388179, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 16:11:27,222] Trial 70 pruned. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.283654 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2183329985014209, 'lr': 0.008112519762534414, 'weight_decay': 0.035679005495839425, 'batch_size': 32} - Best Value (CSI): 0.421454 - Best Trial: 48 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.23116500347660948, 'lr': 0.0043001569401369295, 'weight_decay': 0.02502971721388179, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 16:13:33,932] Trial 71 finished with value: 0.41905412149125865 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2287060274529267, 'lr': 0.00547709275724029, 'weight_decay': 0.053076506127540495, 'batch_size': 32}. Best is trial 48 with value: 0.42145417609942265. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.419054 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2287060274529267, 'lr': 0.00547709275724029, 'weight_decay': 0.053076506127540495, 'batch_size': 32} - Best Value (CSI): 0.421454 - Best Trial: 48 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.23116500347660948, 'lr': 0.0043001569401369295, 'weight_decay': 0.02502971721388179, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 16:16:16,657] Trial 72 finished with value: 0.4186014599900927 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.20770082226395975, 'lr': 0.00606807599628275, 'weight_decay': 0.06567129952153568, 'batch_size': 32}. Best is trial 48 with value: 0.42145417609942265. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.418601 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.20770082226395975, 'lr': 0.00606807599628275, 'weight_decay': 0.06567129952153568, 'batch_size': 32} - Best Value (CSI): 0.421454 - Best Trial: 48 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.23116500347660948, 'lr': 0.0043001569401369295, 'weight_decay': 0.02502971721388179, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 16:18:47,045] Trial 73 finished with value: 0.40864056369216456 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.20924041176583225, 'lr': 0.006376913704037816, 'weight_decay': 0.06702888297269836, 'batch_size': 32}. Best is trial 48 with value: 0.42145417609942265. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.408641 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.20924041176583225, 'lr': 0.006376913704037816, 'weight_decay': 0.06702888297269836, 'batch_size': 32} - Best Value (CSI): 0.421454 - Best Trial: 48 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.23116500347660948, 'lr': 0.0043001569401369295, 'weight_decay': 0.02502971721388179, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 16:21:55,741] Trial 74 finished with value: 0.41871023894758524 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.24142825573496157, 'lr': 0.005427245020870652, 'weight_decay': 0.09447814212358446, 'batch_size': 32}. Best is trial 48 with value: 0.42145417609942265. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.418710 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.24142825573496157, 'lr': 0.005427245020870652, 'weight_decay': 0.09447814212358446, 'batch_size': 32} - Best Value (CSI): 0.421454 - Best Trial: 48 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.23116500347660948, 'lr': 0.0043001569401369295, 'weight_decay': 0.02502971721388179, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 16:25:12,038] Trial 75 finished with value: 0.4116528566426125 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.20830097869648045, 'lr': 0.006340004304316706, 'weight_decay': 0.09054060245619273, 'batch_size': 32}. Best is trial 48 with value: 0.42145417609942265. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.411653 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.20830097869648045, 'lr': 0.006340004304316706, 'weight_decay': 0.09054060245619273, 'batch_size': 32} - Best Value (CSI): 0.421454 - Best Trial: 48 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.23116500347660948, 'lr': 0.0043001569401369295, 'weight_decay': 0.02502971721388179, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 16:28:16,259] Trial 76 finished with value: 0.42023024352411414 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.24551386128059804, 'lr': 0.004670464514431808, 'weight_decay': 0.09122776608314831, 'batch_size': 32}. Best is trial 48 with value: 0.42145417609942265. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.420230 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.24551386128059804, 'lr': 0.004670464514431808, 'weight_decay': 0.09122776608314831, 'batch_size': 32} - Best Value (CSI): 0.421454 - Best Trial: 48 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.23116500347660948, 'lr': 0.0043001569401369295, 'weight_decay': 0.02502971721388179, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 16:31:46,788] Trial 77 finished with value: 0.4336459584801961 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.24410041707618135, 'lr': 0.004732944297044856, 'weight_decay': 0.0974623452373224, 'batch_size': 32}. Best is trial 77 with value: 0.4336459584801961. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.433646 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.24410041707618135, 'lr': 0.004732944297044856, 'weight_decay': 0.0974623452373224, 'batch_size': 32} - Best Value (CSI): 0.433646 - Best Trial: 77 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.24410041707618135, 'lr': 0.004732944297044856, 'weight_decay': 0.0974623452373224, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 16:34:15,274] Trial 78 finished with value: 0.4088962099990748 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.24879222983892657, 'lr': 0.004637999773823381, 'weight_decay': 0.09422939828215657, 'batch_size': 32}. Best is trial 77 with value: 0.4336459584801961. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.408896 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.24879222983892657, 'lr': 0.004637999773823381, 'weight_decay': 0.09422939828215657, 'batch_size': 32} - Best Value (CSI): 0.433646 - Best Trial: 77 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.24410041707618135, 'lr': 0.004732944297044856, 'weight_decay': 0.0974623452373224, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 16:37:26,807] Trial 79 finished with value: 0.4194113008104796 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2579362616190441, 'lr': 0.004608913401491574, 'weight_decay': 0.07371571181410137, 'batch_size': 32}. Best is trial 77 with value: 0.4336459584801961. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.419411 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2579362616190441, 'lr': 0.004608913401491574, 'weight_decay': 0.07371571181410137, 'batch_size': 32} - Best Value (CSI): 0.433646 - Best Trial: 77 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.24410041707618135, 'lr': 0.004732944297044856, 'weight_decay': 0.0974623452373224, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 16:40:11,988] Trial 80 finished with value: 0.4149447358213268 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2620328161630937, 'lr': 0.0035364091522824192, 'weight_decay': 0.09924501792907728, 'batch_size': 32}. Best is trial 77 with value: 0.4336459584801961. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.414945 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2620328161630937, 'lr': 0.0035364091522824192, 'weight_decay': 0.09924501792907728, 'batch_size': 32} - Best Value (CSI): 0.433646 - Best Trial: 77 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.24410041707618135, 'lr': 0.004732944297044856, 'weight_decay': 0.0974623452373224, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 16:43:08,486] Trial 81 finished with value: 0.4267709732798906 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2627913385028543, 'lr': 0.0038005715120737068, 'weight_decay': 0.07462341088349138, 'batch_size': 32}. Best is trial 77 with value: 0.4336459584801961. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.426771 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2627913385028543, 'lr': 0.0038005715120737068, 'weight_decay': 0.07462341088349138, 'batch_size': 32} - Best Value (CSI): 0.433646 - Best Trial: 77 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.24410041707618135, 'lr': 0.004732944297044856, 'weight_decay': 0.0974623452373224, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 16:46:19,377] Trial 82 finished with value: 0.43887148648963953 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.26535220341982607, 'lr': 0.003651382593765993, 'weight_decay': 0.07077194775760214, 'batch_size': 32}. Best is trial 82 with value: 0.43887148648963953. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.438871 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.26535220341982607, 'lr': 0.003651382593765993, 'weight_decay': 0.07077194775760214, 'batch_size': 32} - Best Value (CSI): 0.438871 - Best Trial: 82 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.26535220341982607, 'lr': 0.003651382593765993, 'weight_decay': 0.07077194775760214, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 16:48:53,951] Trial 83 finished with value: 0.43350709219849737 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2805473184485389, 'lr': 0.0024966441505826693, 'weight_decay': 0.07471475397380463, 'batch_size': 32}. Best is trial 82 with value: 0.43887148648963953. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.433507 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2805473184485389, 'lr': 0.0024966441505826693, 'weight_decay': 0.07471475397380463, 'batch_size': 32} - Best Value (CSI): 0.438871 - Best Trial: 82 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.26535220341982607, 'lr': 0.003651382593765993, 'weight_decay': 0.07077194775760214, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 16:51:36,633] Trial 84 finished with value: 0.4237787808223923 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.28033901284256657, 'lr': 0.002520707722208588, 'weight_decay': 0.07175925280524864, 'batch_size': 32}. Best is trial 82 with value: 0.43887148648963953. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.423779 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.28033901284256657, 'lr': 0.002520707722208588, 'weight_decay': 0.07175925280524864, 'batch_size': 32} - Best Value (CSI): 0.438871 - Best Trial: 82 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.26535220341982607, 'lr': 0.003651382593765993, 'weight_decay': 0.07077194775760214, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 16:54:20,276] Trial 85 finished with value: 0.430459197811045 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.27955479232846503, 'lr': 0.0023079514190269324, 'weight_decay': 0.07795637111854702, 'batch_size': 32}. Best is trial 82 with value: 0.43887148648963953. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.430459 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.27955479232846503, 'lr': 0.0023079514190269324, 'weight_decay': 0.07795637111854702, 'batch_size': 32} - Best Value (CSI): 0.438871 - Best Trial: 82 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.26535220341982607, 'lr': 0.003651382593765993, 'weight_decay': 0.07077194775760214, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 16:54:50,744] Trial 86 pruned. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.343137 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.28231132052934665, 'lr': 0.0023232322340101673, 'weight_decay': 0.07289883843242868, 'batch_size': 32} - Best Value (CSI): 0.438871 - Best Trial: 82 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.26535220341982607, 'lr': 0.003651382593765993, 'weight_decay': 0.07077194775760214, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 16:57:04,672] Trial 87 finished with value: 0.4390250453058284 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.29112938728448373, 'lr': 0.002745246324742509, 'weight_decay': 0.07823286969698617, 'batch_size': 32}. Best is trial 87 with value: 0.4390250453058284. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.439025 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.29112938728448373, 'lr': 0.002745246324742509, 'weight_decay': 0.07823286969698617, 'batch_size': 32} - Best Value (CSI): 0.439025 - Best Trial: 87 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.29112938728448373, 'lr': 0.002745246324742509, 'weight_decay': 0.07823286969698617, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 16:59:31,109] Trial 88 finished with value: 0.42285998951389975 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2911536842638407, 'lr': 0.0020898070139619045, 'weight_decay': 0.058777191590226804, 'batch_size': 32}. Best is trial 87 with value: 0.4390250453058284. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.422860 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2911536842638407, 'lr': 0.0020898070139619045, 'weight_decay': 0.058777191590226804, 'batch_size': 32} - Best Value (CSI): 0.439025 - Best Trial: 87 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.29112938728448373, 'lr': 0.002745246324742509, 'weight_decay': 0.07823286969698617, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 17:00:10,850] Trial 89 pruned. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.356077 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.28347326164910897, 'lr': 0.0021568717913645714, 'weight_decay': 0.05838825867869429, 'batch_size': 32} - Best Value (CSI): 0.439025 - Best Trial: 87 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.29112938728448373, 'lr': 0.002745246324742509, 'weight_decay': 0.07823286969698617, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 17:00:15,321] Trial 90 pruned. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.311538 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2935139811267915, 'lr': 0.0016911140289507722, 'weight_decay': 0.06322308068596527, 'batch_size': 256} - Best Value (CSI): 0.439025 - Best Trial: 87 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.29112938728448373, 'lr': 0.002745246324742509, 'weight_decay': 0.07823286969698617, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 17:02:42,027] Trial 91 finished with value: 0.4309823523652951 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.27171099481746264, 'lr': 0.002468130755060003, 'weight_decay': 0.08041006342147479, 'batch_size': 32}. Best is trial 87 with value: 0.4390250453058284. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.430982 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.27171099481746264, 'lr': 0.002468130755060003, 'weight_decay': 0.08041006342147479, 'batch_size': 32} - Best Value (CSI): 0.439025 - Best Trial: 87 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.29112938728448373, 'lr': 0.002745246324742509, 'weight_decay': 0.07823286969698617, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 17:05:42,588] Trial 92 finished with value: 0.4245009568961313 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.26983249591031966, 'lr': 0.002606599914736537, 'weight_decay': 0.07890547702174526, 'batch_size': 32}. Best is trial 87 with value: 0.4390250453058284. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.424501 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.26983249591031966, 'lr': 0.002606599914736537, 'weight_decay': 0.07890547702174526, 'batch_size': 32} - Best Value (CSI): 0.439025 - Best Trial: 87 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.29112938728448373, 'lr': 0.002745246324742509, 'weight_decay': 0.07823286969698617, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 17:08:13,837] Trial 93 finished with value: 0.42238462025647566 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2732389590474488, 'lr': 0.0026170588598050178, 'weight_decay': 0.07791997294371439, 'batch_size': 32}. Best is trial 87 with value: 0.4390250453058284. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.422385 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2732389590474488, 'lr': 0.0026170588598050178, 'weight_decay': 0.07791997294371439, 'batch_size': 32} - Best Value (CSI): 0.439025 - Best Trial: 87 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.29112938728448373, 'lr': 0.002745246324742509, 'weight_decay': 0.07823286969698617, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 17:08:33,459] Trial 94 pruned. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.335470 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.29101147699248886, 'lr': 0.001955437589587563, 'weight_decay': 0.07933581475488519, 'batch_size': 32} - Best Value (CSI): 0.439025 - Best Trial: 87 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.29112938728448373, 'lr': 0.002745246324742509, 'weight_decay': 0.07823286969698617, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 17:08:50,498] Trial 95 pruned. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.315888 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2687392075330634, 'lr': 0.0015733024558478752, 'weight_decay': 0.052703816757787056, 'batch_size': 32} - Best Value (CSI): 0.439025 - Best Trial: 87 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.29112938728448373, 'lr': 0.002745246324742509, 'weight_decay': 0.07823286969698617, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 17:11:32,329] Trial 96 finished with value: 0.4231507763328064 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3035920634866548, 'lr': 0.0028693459620136768, 'weight_decay': 0.061463871632928636, 'batch_size': 32}. Best is trial 87 with value: 0.4390250453058284. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.423151 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3035920634866548, 'lr': 0.0028693459620136768, 'weight_decay': 0.061463871632928636, 'batch_size': 32} - Best Value (CSI): 0.439025 - Best Trial: 87 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.29112938728448373, 'lr': 0.002745246324742509, 'weight_decay': 0.07823286969698617, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 17:14:15,498] Trial 97 finished with value: 0.42410064172874024 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3020755379445224, 'lr': 0.002925937276035293, 'weight_decay': 0.08297738255488343, 'batch_size': 32}. Best is trial 87 with value: 0.4390250453058284. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.424101 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3020755379445224, 'lr': 0.002925937276035293, 'weight_decay': 0.08297738255488343, 'batch_size': 32} - Best Value (CSI): 0.439025 - Best Trial: 87 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.29112938728448373, 'lr': 0.002745246324742509, 'weight_decay': 0.07823286969698617, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 17:16:41,182] Trial 98 finished with value: 0.42293613199096675 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.26562598128935794, 'lr': 0.003422584309241772, 'weight_decay': 0.07999711628016662, 'batch_size': 32}. Best is trial 87 with value: 0.4390250453058284. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.422936 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.26562598128935794, 'lr': 0.003422584309241772, 'weight_decay': 0.07999711628016662, 'batch_size': 32} - Best Value (CSI): 0.439025 - Best Trial: 87 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.29112938728448373, 'lr': 0.002745246324742509, 'weight_decay': 0.07823286969698617, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 17:16:59,948] Trial 99 pruned. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.333333 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2562045077269126, 'lr': 0.0025101616710141274, 'weight_decay': 0.047830149039415085, 'batch_size': 32} - Best Value (CSI): 0.439025 - Best Trial: 87 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.29112938728448373, 'lr': 0.002745246324742509, 'weight_decay': 0.07823286969698617, 'batch_size': 32} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.4390 -Best Hyperparameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.29112938728448373, 'lr': 0.002745246324742509, 'weight_decay': 0.07823286969698617, 'batch_size': 32} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.3396 - - 최종 CSI: 0.3333 - - 최고 CSI: 0.4390 - - 최저 CSI: 0.1420 - - 평균 CSI: 0.3576 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/deepgbm_ctgan10000_daegu_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 40, Best CSI: 0.4199 - Fold 1 학습 완료 (검증 CSI: 0.4199) -Fold 2 학습 중... - Early stopping at epoch 33, Best CSI: 0.4505 - Fold 2 학습 완료 (검증 CSI: 0.4505) -Fold 3 학습 중... - Early stopping at epoch 39, Best CSI: 0.4099 - Fold 3 학습 완료 (검증 CSI: 0.4099) - -모든 모델 저장 완료: ../save_model/deepgbm_optima/deepgbm_ctgan10000_daegu.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/deepgbm_optima/scaler/deepgbm_ctgan10000_daegu_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: ../save_model/deepgbm_optima/deepgbm_ctgan10000_daegu.pkl - -✓ 완료: deepgbm_ctgan10000/deepgbm_ctgan10000_daegu.py (소요 시간: 8754초) - ----------------------------------------- -실행 중: deepgbm_ctgan10000/deepgbm_ctgan10000_daejeon.py -시작 시간: 2025-12-28 17:20:10 ----------------------------------------- -[I 2025-12-28 17:20:11,320] A new study created in memory with name: no-name-964a1216-a290-4083-912e-508929ca66c4 - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 17:21:19,419] Trial 0 finished with value: 0.47091280722131773 and parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.17390268033497497, 'lr': 0.004799108459451018, 'weight_decay': 0.0006664019304836773, 'batch_size': 128}. Best is trial 0 with value: 0.47091280722131773. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.470913 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.17390268033497497, 'lr': 0.004799108459451018, 'weight_decay': 0.0006664019304836773, 'batch_size': 128} - Best Value (CSI): 0.470913 - Best Trial: 0 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.17390268033497497, 'lr': 0.004799108459451018, 'weight_decay': 0.0006664019304836773, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 17:23:48,448] Trial 1 finished with value: 0.3966883031027069 and parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.15238152933956228, 'lr': 5.9296846344998454e-05, 'weight_decay': 0.0025513910498295525, 'batch_size': 64}. Best is trial 0 with value: 0.47091280722131773. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.396688 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.15238152933956228, 'lr': 5.9296846344998454e-05, 'weight_decay': 0.0025513910498295525, 'batch_size': 64} - Best Value (CSI): 0.470913 - Best Trial: 0 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.17390268033497497, 'lr': 0.004799108459451018, 'weight_decay': 0.0006664019304836773, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 17:25:22,593] Trial 2 finished with value: 0.38109723850909494 and parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.20306034610770032, 'lr': 1.711285001790452e-05, 'weight_decay': 0.0008665871853341875, 'batch_size': 128}. Best is trial 0 with value: 0.47091280722131773. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.381097 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.20306034610770032, 'lr': 1.711285001790452e-05, 'weight_decay': 0.0008665871853341875, 'batch_size': 128} - Best Value (CSI): 0.470913 - Best Trial: 0 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.17390268033497497, 'lr': 0.004799108459451018, 'weight_decay': 0.0006664019304836773, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 17:26:48,345] Trial 3 finished with value: 0.46919425923951713 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.357622005513733, 'lr': 0.0008432612884923642, 'weight_decay': 0.02771504880690769, 'batch_size': 64}. Best is trial 0 with value: 0.47091280722131773. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.469194 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.357622005513733, 'lr': 0.0008432612884923642, 'weight_decay': 0.02771504880690769, 'batch_size': 64} - Best Value (CSI): 0.470913 - Best Trial: 0 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.17390268033497497, 'lr': 0.004799108459451018, 'weight_decay': 0.0006664019304836773, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 17:29:57,645] Trial 4 finished with value: 0.4172821776028532 and parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.16094916613594742, 'lr': 8.457040341630836e-05, 'weight_decay': 0.0005325836021360593, 'batch_size': 32}. Best is trial 0 with value: 0.47091280722131773. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.417282 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.16094916613594742, 'lr': 8.457040341630836e-05, 'weight_decay': 0.0005325836021360593, 'batch_size': 32} - Best Value (CSI): 0.470913 - Best Trial: 0 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.17390268033497497, 'lr': 0.004799108459451018, 'weight_decay': 0.0006664019304836773, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 17:30:09,696] Trial 5 pruned. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.313209 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.3757101393534783, 'lr': 3.13631846883115e-05, 'weight_decay': 0.000167927293001174, 'batch_size': 64} - Best Value (CSI): 0.470913 - Best Trial: 0 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.17390268033497497, 'lr': 0.004799108459451018, 'weight_decay': 0.0006664019304836773, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 17:31:49,735] Trial 6 finished with value: 0.46694427548927225 and parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.38560501080196474, 'lr': 0.0007003334636300012, 'weight_decay': 0.006145169968373231, 'batch_size': 64}. Best is trial 0 with value: 0.47091280722131773. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.466944 - Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.38560501080196474, 'lr': 0.0007003334636300012, 'weight_decay': 0.006145169968373231, 'batch_size': 64} - Best Value (CSI): 0.470913 - Best Trial: 0 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.17390268033497497, 'lr': 0.004799108459451018, 'weight_decay': 0.0006664019304836773, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 17:31:54,727] Trial 7 pruned. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.175655 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.12475260003909754, 'lr': 2.8443065231174017e-05, 'weight_decay': 0.00012100742042434264, 'batch_size': 256} - Best Value (CSI): 0.470913 - Best Trial: 0 - Best Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.17390268033497497, 'lr': 0.004799108459451018, 'weight_decay': 0.0006664019304836773, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 17:34:06,654] Trial 8 finished with value: 0.4865570363639032 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.3335192709099133, 'lr': 0.001658609697657929, 'weight_decay': 0.02935973246541922, 'batch_size': 32}. Best is trial 8 with value: 0.4865570363639032. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.486557 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.3335192709099133, 'lr': 0.001658609697657929, 'weight_decay': 0.02935973246541922, 'batch_size': 32} - Best Value (CSI): 0.486557 - Best Trial: 8 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.3335192709099133, 'lr': 0.001658609697657929, 'weight_decay': 0.02935973246541922, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 17:34:31,875] Trial 9 pruned. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.390077 - Parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.39374589522465897, 'lr': 0.001594977694675972, 'weight_decay': 0.002162277029541997, 'batch_size': 64} - Best Value (CSI): 0.486557 - Best Trial: 8 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.3335192709099133, 'lr': 0.001658609697657929, 'weight_decay': 0.02935973246541922, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 17:37:57,982] Trial 10 finished with value: 0.5022344337726664 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.29955819082733437, 'lr': 0.009777072830587137, 'weight_decay': 0.08870699223556335, 'batch_size': 32}. Best is trial 10 with value: 0.5022344337726664. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.502234 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.29955819082733437, 'lr': 0.009777072830587137, 'weight_decay': 0.08870699223556335, 'batch_size': 32} - Best Value (CSI): 0.502234 - Best Trial: 10 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.29955819082733437, 'lr': 0.009777072830587137, 'weight_decay': 0.08870699223556335, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 17:38:17,430] Trial 11 pruned. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.330309 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.30401618192102503, 'lr': 0.009996718108260706, 'weight_decay': 0.08874969033278796, 'batch_size': 32} - Best Value (CSI): 0.502234 - Best Trial: 10 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.29955819082733437, 'lr': 0.009777072830587137, 'weight_decay': 0.08870699223556335, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 17:41:42,016] Trial 12 finished with value: 0.5101248146449113 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32}. Best is trial 12 with value: 0.5101248146449113. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.510125 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 17:42:06,472] Trial 13 pruned. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.366667 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.26903915626912817, 'lr': 0.00844809745303296, 'weight_decay': 0.0815958464589299, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 17:44:34,916] Trial 14 finished with value: 0.49774830612605087 and parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2515666618686739, 'lr': 0.003421675045911773, 'weight_decay': 0.019692998745633985, 'batch_size': 32}. Best is trial 12 with value: 0.5101248146449113. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.497748 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2515666618686739, 'lr': 0.003421675045911773, 'weight_decay': 0.019692998745633985, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 17:45:04,791] Trial 15 finished with value: 0.4833623544177786 and parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2927453433088182, 'lr': 0.0035600698291556017, 'weight_decay': 0.09934047385924903, 'batch_size': 256}. Best is trial 12 with value: 0.5101248146449113. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.483362 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2927453433088182, 'lr': 0.0035600698291556017, 'weight_decay': 0.09934047385924903, 'batch_size': 256} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 17:48:00,027] Trial 16 finished with value: 0.4482004416498409 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.22622434320527612, 'lr': 0.0002503313245716792, 'weight_decay': 0.012362275435169177, 'batch_size': 32}. Best is trial 12 with value: 0.5101248146449113. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.448200 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.22622434320527612, 'lr': 0.0002503313245716792, 'weight_decay': 0.012362275435169177, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 17:48:24,354] Trial 17 pruned. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.379859 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.3183736308593409, 'lr': 0.009288432268907354, 'weight_decay': 0.049761678664403425, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 17:49:14,710] Trial 18 pruned. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.400000 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.27308844430955515, 'lr': 0.002224066549745564, 'weight_decay': 0.012027983137257506, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 17:49:23,062] Trial 19 pruned. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.365091 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.3423545521620392, 'lr': 0.00039961875580443626, 'weight_decay': 0.044343959617037194, 'batch_size': 128} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 17:49:56,807] Trial 20 finished with value: 0.4818067155568582 and parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.2996520802406873, 'lr': 0.004474181005361122, 'weight_decay': 0.04940550045195796, 'batch_size': 256}. Best is trial 12 with value: 0.5101248146449113. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.481807 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.2996520802406873, 'lr': 0.004474181005361122, 'weight_decay': 0.04940550045195796, 'batch_size': 256} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 17:52:16,120] Trial 21 finished with value: 0.4887879197351149 and parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.24330859482971923, 'lr': 0.003254579554696712, 'weight_decay': 0.01980122640043668, 'batch_size': 32}. Best is trial 12 with value: 0.5101248146449113. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.488788 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.24330859482971923, 'lr': 0.003254579554696712, 'weight_decay': 0.01980122640043668, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 17:55:30,946] Trial 22 finished with value: 0.501421797238383 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.26532681366022953, 'lr': 0.004489141122021316, 'weight_decay': 0.050438880265888004, 'batch_size': 32}. Best is trial 12 with value: 0.5101248146449113. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.501422 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.26532681366022953, 'lr': 0.004489141122021316, 'weight_decay': 0.050438880265888004, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 17:58:17,800] Trial 23 finished with value: 0.49621995589922263 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.27805030708182077, 'lr': 0.006711710926520925, 'weight_decay': 0.057370255990679325, 'batch_size': 32}. Best is trial 12 with value: 0.5101248146449113. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.496220 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.27805030708182077, 'lr': 0.006711710926520925, 'weight_decay': 0.057370255990679325, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 17:58:42,882] Trial 24 pruned. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.362657 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.301443361558529, 'lr': 0.005488303614799007, 'weight_decay': 0.09125198786125734, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 18:01:15,568] Trial 25 finished with value: 0.4998545913389673 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.31958061358918466, 'lr': 0.002439363924374219, 'weight_decay': 0.033923419303727435, 'batch_size': 32}. Best is trial 12 with value: 0.5101248146449113. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.499855 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.31958061358918466, 'lr': 0.002439363924374219, 'weight_decay': 0.033923419303727435, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:01:39,864] Trial 26 pruned. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.387067 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.25302440875857213, 'lr': 0.005559924145512478, 'weight_decay': 0.055993497515554436, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:02:24,743] Trial 27 pruned. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.389243 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.22403523433985434, 'lr': 0.001304932830912518, 'weight_decay': 0.017698278694635167, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 18:03:10,712] Trial 28 finished with value: 0.471591099326581 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2761121710210888, 'lr': 0.0026088435027735606, 'weight_decay': 0.03219341983681844, 'batch_size': 128}. Best is trial 12 with value: 0.5101248146449113. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.471591 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2761121710210888, 'lr': 0.0026088435027735606, 'weight_decay': 0.03219341983681844, 'batch_size': 128} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 18:03:37,070] Trial 29 finished with value: 0.46719755465755125 and parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.18903884737313537, 'lr': 0.004891352962031701, 'weight_decay': 0.007494667956670961, 'batch_size': 256}. Best is trial 12 with value: 0.5101248146449113. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.467198 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.18903884737313537, 'lr': 0.004891352962031701, 'weight_decay': 0.007494667956670961, 'batch_size': 256} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 18:04:36,431] Trial 30 finished with value: 0.5100542409277865 and parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.35528646597883196, 'lr': 0.005975833641923651, 'weight_decay': 0.06727342355696113, 'batch_size': 128}. Best is trial 12 with value: 0.5101248146449113. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.510054 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.35528646597883196, 'lr': 0.005975833641923651, 'weight_decay': 0.06727342355696113, 'batch_size': 128} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:04:45,946] Trial 31 pruned. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.368587 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.33237051240871407, 'lr': 0.005997564155847514, 'weight_decay': 0.06841381155916106, 'batch_size': 128} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:04:54,100] Trial 32 pruned. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.367958 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.3204440244271537, 'lr': 0.009289873900452232, 'weight_decay': 0.09812734956435876, 'batch_size': 128} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 18:05:49,288] Trial 33 finished with value: 0.49464760143239683 and parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.35919867400242994, 'lr': 0.004160465014675709, 'weight_decay': 0.04390312310592777, 'batch_size': 128}. Best is trial 12 with value: 0.5101248146449113. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.494648 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.35919867400242994, 'lr': 0.004160465014675709, 'weight_decay': 0.04390312310592777, 'batch_size': 128} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 18:06:41,172] Trial 34 finished with value: 0.5042487635648454 and parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.3418867157570947, 'lr': 0.006554115370437086, 'weight_decay': 0.06391484731798987, 'batch_size': 128}. Best is trial 12 with value: 0.5101248146449113. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.504249 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.3418867157570947, 'lr': 0.006554115370437086, 'weight_decay': 0.06391484731798987, 'batch_size': 128} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:07:00,605] Trial 35 pruned. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.421333 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3546571688594399, 'lr': 0.006791951636010245, 'weight_decay': 0.06912814216580676, 'batch_size': 128} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 18:07:46,505] Trial 36 finished with value: 0.48231200140552555 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3695806147496655, 'lr': 0.002675856042792232, 'weight_decay': 0.0338497342171349, 'batch_size': 128}. Best is trial 12 with value: 0.5101248146449113. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.482312 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3695806147496655, 'lr': 0.002675856042792232, 'weight_decay': 0.0338497342171349, 'batch_size': 128} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:08:06,688] Trial 37 pruned. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.420964 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.3456201153862546, 'lr': 0.006970257331670231, 'weight_decay': 0.0684213971982247, 'batch_size': 128} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:08:27,100] Trial 38 pruned. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.430944 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.37405254512499014, 'lr': 0.009583360216170903, 'weight_decay': 0.024572289856664965, 'batch_size': 128} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:08:44,795] Trial 39 pruned. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.392122 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.39227918934741374, 'lr': 0.001025120766394647, 'weight_decay': 0.038741989126993344, 'batch_size': 64} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:08:54,754] Trial 40 pruned. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.408574 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.3575502149755919, 'lr': 0.001808902525630881, 'weight_decay': 0.02522669014727317, 'batch_size': 128} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:09:48,036] Trial 41 pruned. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.429373 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.28690753592736007, 'lr': 0.005412098639235286, 'weight_decay': 0.06127566287517714, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:10:15,384] Trial 42 pruned. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.415867 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.30884013570704605, 'lr': 0.0038155021048132823, 'weight_decay': 0.04715393262917385, 'batch_size': 64} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 18:11:10,660] Trial 43 finished with value: 0.5022258467402851 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.2883613434066421, 'lr': 0.004578872815216211, 'weight_decay': 0.07211212035819524, 'batch_size': 128}. Best is trial 12 with value: 0.5101248146449113. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.502226 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.2883613434066421, 'lr': 0.004578872815216211, 'weight_decay': 0.07211212035819524, 'batch_size': 128} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:11:18,305] Trial 44 pruned. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.395703 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.33327468649108233, 'lr': 0.0029322067646842527, 'weight_decay': 0.09870449787234076, 'batch_size': 128} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:11:28,726] Trial 45 pruned. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.418100 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.28704773943534345, 'lr': 0.007373105822288396, 'weight_decay': 0.07161839773563837, 'batch_size': 128} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:11:40,312] Trial 46 pruned. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.411492 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3098514773753347, 'lr': 0.0018733901616811233, 'weight_decay': 0.03686992559432701, 'batch_size': 128} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 18:12:42,165] Trial 47 finished with value: 0.4992038039340496 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.3988887227740137, 'lr': 0.003917603560231747, 'weight_decay': 0.07323294816190767, 'batch_size': 128}. Best is trial 12 with value: 0.5101248146449113. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.499204 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.3988887227740137, 'lr': 0.003917603560231747, 'weight_decay': 0.07323294816190767, 'batch_size': 128} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:12:49,594] Trial 48 pruned. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.419087 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.29270400317795936, 'lr': 0.0068450702908284785, 'weight_decay': 0.027349624455736424, 'batch_size': 256} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) -[I 2025-12-28 18:13:20,288] Trial 49 pruned. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.468977 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.3252494732917137, 'lr': 0.0012924941723493337, 'weight_decay': 0.07829298866756979, 'batch_size': 128} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:13:33,514] Trial 50 pruned. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.385274 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.34202871483796915, 'lr': 0.0031787484372776693, 'weight_decay': 0.04311551375059074, 'batch_size': 64} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:13:55,637] Trial 51 pruned. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.382022 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.26185761290678383, 'lr': 0.00451124646439791, 'weight_decay': 0.05398042073561988, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:14:14,536] Trial 52 pruned. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.376442 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.309520172455306, 'lr': 0.007914455386396757, 'weight_decay': 0.058481470543485, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 18:17:07,244] Trial 53 finished with value: 0.5061308419442494 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.2622742326037925, 'lr': 0.004753571970329188, 'weight_decay': 0.09691894696122295, 'batch_size': 32}. Best is trial 12 with value: 0.5101248146449113. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.506131 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.2622742326037925, 'lr': 0.004753571970329188, 'weight_decay': 0.09691894696122295, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:17:33,906] Trial 54 pruned. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.389039 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.27742879474011145, 'lr': 0.00544644839283288, 'weight_decay': 0.0945740049533425, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:17:57,932] Trial 55 pruned. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.365601 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.29706448611415515, 'lr': 0.009837410962295422, 'weight_decay': 0.0690034953566541, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:18:09,427] Trial 56 pruned. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.414758 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.2830128153780071, 'lr': 0.0022502002602343284, 'weight_decay': 0.08091008387533014, 'batch_size': 256} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:18:20,024] Trial 57 pruned. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.412065 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.2658579889688746, 'lr': 0.0036533557518305788, 'weight_decay': 0.0388911068095591, 'batch_size': 128} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:18:45,061] Trial 58 pruned. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.387011 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.38235613021567505, 'lr': 0.00744518133489163, 'weight_decay': 0.0560710681278779, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 18:21:31,593] Trial 59 finished with value: 0.5053330514211721 and parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.29560956336451355, 'lr': 0.003040081756009423, 'weight_decay': 0.09580403460928869, 'batch_size': 32}. Best is trial 12 with value: 0.5101248146449113. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.505333 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.29560956336451355, 'lr': 0.003040081756009423, 'weight_decay': 0.09580403460928869, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:21:59,659] Trial 60 pruned. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.408889 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3011232392438384, 'lr': 0.003000504428500985, 'weight_decay': 0.09784326499069082, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:22:23,162] Trial 61 pruned. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.389365 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2963775737071764, 'lr': 0.00506861775703181, 'weight_decay': 0.08161289629084556, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:22:54,964] Trial 62 pruned. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.416065 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.2846157658372228, 'lr': 0.002151200731835764, 'weight_decay': 0.057036118781110826, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:23:41,198] Trial 63 pruned. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.416593 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.31405966282369663, 'lr': 0.005829428451562356, 'weight_decay': 0.04253416839807944, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:24:01,667] Trial 64 pruned. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.359927 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.3263409897720465, 'lr': 0.004145444708752362, 'weight_decay': 0.0999954549096991, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:24:32,406] Trial 65 pruned. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.406032 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.25762015133634975, 'lr': 0.007949438236119473, 'weight_decay': 0.0792248724215335, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:24:41,192] Trial 66 pruned. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.385035 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2508265201052113, 'lr': 0.003020886681352587, 'weight_decay': 0.03064112512487593, 'batch_size': 128} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:24:58,382] Trial 67 pruned. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.398866 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.27407198003924643, 'lr': 0.005028515362871348, 'weight_decay': 0.050038444995749616, 'batch_size': 64} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:25:30,164] Trial 68 pruned. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.422078 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.24333586523145578, 'lr': 0.0060810759425103545, 'weight_decay': 0.06673177649380793, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 18:26:11,152] Trial 69 finished with value: 0.4870335755832722 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2682809073630958, 'lr': 0.003599631844528232, 'weight_decay': 0.04685069695109793, 'batch_size': 128}. Best is trial 12 with value: 0.5101248146449113. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.487034 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2682809073630958, 'lr': 0.003599631844528232, 'weight_decay': 0.04685069695109793, 'batch_size': 128} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 18:26:47,595] Trial 70 finished with value: 0.5019749248092794 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.3159129816495217, 'lr': 0.009147405439382734, 'weight_decay': 0.08337005549467671, 'batch_size': 256}. Best is trial 12 with value: 0.5101248146449113. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.501975 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.3159129816495217, 'lr': 0.009147405439382734, 'weight_decay': 0.08337005549467671, 'batch_size': 256} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 18:27:29,066] Trial 71 finished with value: 0.4998149860292238 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.304585707332184, 'lr': 0.007580811594324356, 'weight_decay': 0.07606563639129538, 'batch_size': 256}. Best is trial 12 with value: 0.5101248146449113. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.499815 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.304585707332184, 'lr': 0.007580811594324356, 'weight_decay': 0.07606563639129538, 'batch_size': 256} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 18:28:13,329] Trial 72 finished with value: 0.4990164575619962 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.31505339518768294, 'lr': 0.009886834565477558, 'weight_decay': 0.0632719113834685, 'batch_size': 256}. Best is trial 12 with value: 0.5101248146449113. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.499016 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.31505339518768294, 'lr': 0.009886834565477558, 'weight_decay': 0.0632719113834685, 'batch_size': 256} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:28:20,717] Trial 73 pruned. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.409649 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.2911121024149011, 'lr': 0.004504295139028827, 'weight_decay': 0.07851203008208621, 'batch_size': 256} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:28:28,703] Trial 74 pruned. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.417697 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3290848599662435, 'lr': 0.0060926616573028815, 'weight_decay': 0.06166131238023137, 'batch_size': 256} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:28:53,723] Trial 75 pruned. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.379588 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.3209433660504459, 'lr': 0.008346520081415048, 'weight_decay': 0.08503921218042387, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 18:29:50,856] Trial 76 finished with value: 0.4952577805657872 and parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.3415048419518644, 'lr': 0.006223673717125244, 'weight_decay': 0.03855374688828488, 'batch_size': 128}. Best is trial 12 with value: 0.5101248146449113. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.495258 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.3415048419518644, 'lr': 0.006223673717125244, 'weight_decay': 0.03855374688828488, 'batch_size': 128} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:29:57,552] Trial 77 pruned. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.402878 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2807002058742021, 'lr': 0.0027024763217727205, 'weight_decay': 0.0489026436060842, 'batch_size': 256} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:30:18,897] Trial 78 pruned. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.435626 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.3063696719669886, 'lr': 0.008380282104991515, 'weight_decay': 0.09839814459188238, 'batch_size': 128} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:30:51,610] Trial 79 pruned. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.420552 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.2902530822374183, 'lr': 0.004839406787464274, 'weight_decay': 0.034564523990167385, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:31:09,825] Trial 80 pruned. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.424645 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.3164527313882728, 'lr': 0.0037687053454149755, 'weight_decay': 0.058521063197785037, 'batch_size': 128} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:31:37,362] Trial 81 pruned. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.410887 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.27109701178242446, 'lr': 0.004457679284564059, 'weight_decay': 0.08313239637185656, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 18:33:47,562] Trial 82 finished with value: 0.48825418527056746 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2624569320696532, 'lr': 0.006280747597616649, 'weight_decay': 0.06652184549352809, 'batch_size': 32}. Best is trial 12 with value: 0.5101248146449113. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.488254 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2624569320696532, 'lr': 0.006280747597616649, 'weight_decay': 0.06652184549352809, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 18:36:17,247] Trial 83 finished with value: 0.5061719330403941 and parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2996658956135587, 'lr': 0.003438306768301007, 'weight_decay': 0.04423976242941889, 'batch_size': 32}. Best is trial 12 with value: 0.5101248146449113. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.506172 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2996658956135587, 'lr': 0.003438306768301007, 'weight_decay': 0.04423976242941889, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:37:08,056] Trial 84 pruned. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.431858 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.29985267665654475, 'lr': 0.003223076085807653, 'weight_decay': 0.049650873217483155, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:37:38,537] Trial 85 pruned. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.405201 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.29612017548052844, 'lr': 0.0021204320924548877, 'weight_decay': 0.08151750374184714, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:37:56,062] Trial 86 pruned. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.426510 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.33745565488740514, 'lr': 0.006831185241651979, 'weight_decay': 0.06746145752511458, 'batch_size': 64} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:38:43,051] Trial 87 pruned. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.422974 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.28106674636282875, 'lr': 0.0025255775471508275, 'weight_decay': 0.04215124729566637, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:38:52,920] Trial 88 pruned. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.404914 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.32690375455095805, 'lr': 0.008514977587267531, 'weight_decay': 0.08914422755756038, 'batch_size': 128} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:39:00,048] Trial 89 pruned. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.399831 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.31175893236224994, 'lr': 0.005249788141357181, 'weight_decay': 0.05513959648210336, 'batch_size': 256} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:39:50,890] Trial 90 pruned. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.413603 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.3503783114843492, 'lr': 0.003402090045197869, 'weight_decay': 0.02792141894735297, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:40:20,669] Trial 91 pruned. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.427822 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.28888325596262904, 'lr': 0.00413708071505135, 'weight_decay': 0.06913474835995947, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 18:42:56,567] Trial 92 finished with value: 0.5033539046145203 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.27445581376558154, 'lr': 0.004774432138629257, 'weight_decay': 0.047537114023331516, 'batch_size': 32}. Best is trial 12 with value: 0.5101248146449113. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.503354 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.27445581376558154, 'lr': 0.004774432138629257, 'weight_decay': 0.047537114023331516, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:43:15,772] Trial 93 pruned. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.346681 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.3047317329477646, 'lr': 0.009909781348570993, 'weight_decay': 0.050787228372132905, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:43:36,309] Trial 94 pruned. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.373246 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2812721779928454, 'lr': 0.006899512521297028, 'weight_decay': 0.08475016723298338, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:43:58,853] Trial 95 pruned. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.386262 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.2730530822866347, 'lr': 0.005448444461461762, 'weight_decay': 0.03264842224458182, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:44:07,617] Trial 96 pruned. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.419183 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.29533616834646614, 'lr': 0.004122429282259635, 'weight_decay': 0.059492291256100095, 'batch_size': 128} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:44:57,803] Trial 97 pruned. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.431166 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.3641854375809598, 'lr': 0.002815556835940789, 'weight_decay': 0.04227223614147624, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:45:27,754] Trial 98 pruned. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.405757 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.31939572403757643, 'lr': 0.004840558741651972, 'weight_decay': 0.07521658115475248, 'batch_size': 32} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 18:45:38,541] Trial 99 pruned. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.422455 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.33485466177643086, 'lr': 0.007815277211069609, 'weight_decay': 0.09843197744086116, 'batch_size': 128} - Best Value (CSI): 0.510125 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.5101 -Best Hyperparameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2845653149911174, 'lr': 0.0030479748817488737, 'weight_decay': 0.08478209494184558, 'batch_size': 32} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.4709 - - 최종 CSI: 0.4225 - - 최고 CSI: 0.5101 - - 최저 CSI: 0.1757 - - 평균 CSI: 0.4269 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/deepgbm_ctgan10000_daejeon_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 21, Best CSI: 0.4333 - Fold 1 학습 완료 (검증 CSI: 0.4333) -Fold 2 학습 중... - Early stopping at epoch 22, Best CSI: 0.5188 - Fold 2 학습 완료 (검증 CSI: 0.5188) -Fold 3 학습 중... - Early stopping at epoch 36, Best CSI: 0.5534 - Fold 3 학습 완료 (검증 CSI: 0.5534) - -모든 모델 저장 완료: ../save_model/deepgbm_optima/deepgbm_ctgan10000_daejeon.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/deepgbm_optima/scaler/deepgbm_ctgan10000_daejeon_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: ../save_model/deepgbm_optima/deepgbm_ctgan10000_daejeon.pkl - -✓ 완료: deepgbm_ctgan10000/deepgbm_ctgan10000_daejeon.py (소요 시간: 5261초) - ----------------------------------------- -실행 중: deepgbm_ctgan10000/deepgbm_ctgan10000_gwangju.py -시작 시간: 2025-12-28 18:47:51 ----------------------------------------- -[I 2025-12-28 18:47:52,960] A new study created in memory with name: no-name-01b1a4b9-20d0-4156-8138-c38636494102 - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 18:49:07,207] Trial 0 finished with value: 0.45743779147083535 and parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.14717721520045274, 'lr': 0.0015945354588365946, 'weight_decay': 0.00032422769721220253, 'batch_size': 64}. Best is trial 0 with value: 0.45743779147083535. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.457438 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.14717721520045274, 'lr': 0.0015945354588365946, 'weight_decay': 0.00032422769721220253, 'batch_size': 64} - Best Value (CSI): 0.457438 - Best Trial: 0 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.14717721520045274, 'lr': 0.0015945354588365946, 'weight_decay': 0.00032422769721220253, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 18:50:38,923] Trial 1 finished with value: 0.3044843465528707 and parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.113608865076364, 'lr': 2.849025643295352e-05, 'weight_decay': 0.00045410524985854965, 'batch_size': 128}. Best is trial 0 with value: 0.45743779147083535. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.304484 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.113608865076364, 'lr': 2.849025643295352e-05, 'weight_decay': 0.00045410524985854965, 'batch_size': 128} - Best Value (CSI): 0.457438 - Best Trial: 0 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.14717721520045274, 'lr': 0.0015945354588365946, 'weight_decay': 0.00032422769721220253, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 18:54:26,647] Trial 2 finished with value: 0.4959397723639696 and parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.36010406104672654, 'lr': 0.007599512357460581, 'weight_decay': 0.03531587966911193, 'batch_size': 32}. Best is trial 2 with value: 0.4959397723639696. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.495940 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.36010406104672654, 'lr': 0.007599512357460581, 'weight_decay': 0.03531587966911193, 'batch_size': 32} - Best Value (CSI): 0.495940 - Best Trial: 2 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.36010406104672654, 'lr': 0.007599512357460581, 'weight_decay': 0.03531587966911193, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 18:58:14,411] Trial 3 finished with value: 0.4324411750429358 and parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.2566049316218987, 'lr': 0.00011622308664845337, 'weight_decay': 0.00411247906351364, 'batch_size': 32}. Best is trial 2 with value: 0.4959397723639696. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.432441 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.2566049316218987, 'lr': 0.00011622308664845337, 'weight_decay': 0.00411247906351364, 'batch_size': 32} - Best Value (CSI): 0.495940 - Best Trial: 2 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.36010406104672654, 'lr': 0.007599512357460581, 'weight_decay': 0.03531587966911193, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 19:00:43,120] Trial 4 finished with value: 0.46261403048889216 and parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.21728285466905572, 'lr': 0.0007765448864084281, 'weight_decay': 0.009455845611329351, 'batch_size': 32}. Best is trial 2 with value: 0.4959397723639696. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.462614 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.21728285466905572, 'lr': 0.0007765448864084281, 'weight_decay': 0.009455845611329351, 'batch_size': 32} - Best Value (CSI): 0.495940 - Best Trial: 2 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.36010406104672654, 'lr': 0.007599512357460581, 'weight_decay': 0.03531587966911193, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 19:01:06,396] Trial 5 pruned. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.323746 - Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.2866442522811028, 'lr': 1.0841707181535189e-05, 'weight_decay': 0.03746678424700817, 'batch_size': 32} - Best Value (CSI): 0.495940 - Best Trial: 2 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.36010406104672654, 'lr': 0.007599512357460581, 'weight_decay': 0.03531587966911193, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 19:01:10,679] Trial 6 pruned. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.317241 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.245480203575578, 'lr': 0.0003822605247828503, 'weight_decay': 0.022059437220133093, 'batch_size': 256} - Best Value (CSI): 0.495940 - Best Trial: 2 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.36010406104672654, 'lr': 0.007599512357460581, 'weight_decay': 0.03531587966911193, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 19:01:33,365] Trial 7 pruned. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.281807 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.25875377854530024, 'lr': 2.459051496954693e-05, 'weight_decay': 0.027852413459059405, 'batch_size': 32} - Best Value (CSI): 0.495940 - Best Trial: 2 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.36010406104672654, 'lr': 0.007599512357460581, 'weight_decay': 0.03531587966911193, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 19:03:31,451] Trial 8 finished with value: 0.46999725590122 and parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.14172372640790123, 'lr': 0.0004988308571126208, 'weight_decay': 0.003552889484955622, 'batch_size': 32}. Best is trial 2 with value: 0.4959397723639696. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.469997 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.14172372640790123, 'lr': 0.0004988308571126208, 'weight_decay': 0.003552889484955622, 'batch_size': 32} - Best Value (CSI): 0.495940 - Best Trial: 2 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.36010406104672654, 'lr': 0.007599512357460581, 'weight_decay': 0.03531587966911193, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 19:05:53,773] Trial 9 finished with value: 0.4770368761308679 and parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.1843173655160542, 'lr': 0.00185842092477608, 'weight_decay': 0.0011518304447969625, 'batch_size': 32}. Best is trial 2 with value: 0.4959397723639696. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.477037 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.1843173655160542, 'lr': 0.00185842092477608, 'weight_decay': 0.0011518304447969625, 'batch_size': 32} - Best Value (CSI): 0.495940 - Best Trial: 2 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.36010406104672654, 'lr': 0.007599512357460581, 'weight_decay': 0.03531587966911193, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 19:08:10,306] Trial 10 finished with value: 0.5053558761865672 and parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.384980080114916, 'lr': 0.00925024038802788, 'weight_decay': 0.055896684002468056, 'batch_size': 64}. Best is trial 10 with value: 0.5053558761865672. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.505356 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.384980080114916, 'lr': 0.00925024038802788, 'weight_decay': 0.055896684002468056, 'batch_size': 64} - Best Value (CSI): 0.505356 - Best Trial: 10 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.384980080114916, 'lr': 0.00925024038802788, 'weight_decay': 0.055896684002468056, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 19:10:12,441] Trial 11 finished with value: 0.5199080740628351 and parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.3881056771222904, 'lr': 0.007412799581213635, 'weight_decay': 0.098616753638106, 'batch_size': 64}. Best is trial 11 with value: 0.5199080740628351. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.519908 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.3881056771222904, 'lr': 0.007412799581213635, 'weight_decay': 0.098616753638106, 'batch_size': 64} - Best Value (CSI): 0.519908 - Best Trial: 11 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.3881056771222904, 'lr': 0.007412799581213635, 'weight_decay': 0.098616753638106, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 19:12:38,852] Trial 12 finished with value: 0.5204031176113428 and parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64}. Best is trial 12 with value: 0.5204031176113428. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.520403 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 19:14:35,275] Trial 13 finished with value: 0.511117993558572 and parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.3998589722411654, 'lr': 0.003933938973051474, 'weight_decay': 0.0875561412763022, 'batch_size': 64}. Best is trial 12 with value: 0.5204031176113428. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.511118 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.3998589722411654, 'lr': 0.003933938973051474, 'weight_decay': 0.0875561412763022, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 19:16:21,254] Trial 14 finished with value: 0.5080411436842638 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.3332621306917933, 'lr': 0.0033857813776511235, 'weight_decay': 0.08394133011073669, 'batch_size': 64}. Best is trial 12 with value: 0.5204031176113428. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.508041 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.3332621306917933, 'lr': 0.0033857813776511235, 'weight_decay': 0.08394133011073669, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 19:18:28,448] Trial 15 finished with value: 0.501066549545124 and parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3265857487248327, 'lr': 0.007806120877395297, 'weight_decay': 0.011139326332018678, 'batch_size': 64}. Best is trial 12 with value: 0.5204031176113428. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.501067 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3265857487248327, 'lr': 0.007806120877395297, 'weight_decay': 0.011139326332018678, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 19:19:09,302] Trial 16 finished with value: 0.4918268246952901 and parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.398193382094987, 'lr': 0.0016598203825901974, 'weight_decay': 0.07969200184494632, 'batch_size': 256}. Best is trial 12 with value: 0.5204031176113428. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.491827 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.398193382094987, 'lr': 0.0016598203825901974, 'weight_decay': 0.07969200184494632, 'batch_size': 256} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 19:20:06,632] Trial 17 finished with value: 0.4800523116396036 and parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3591385897551574, 'lr': 0.0038795861579728878, 'weight_decay': 0.016090387672401216, 'batch_size': 128}. Best is trial 12 with value: 0.5204031176113428. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.480052 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3591385897551574, 'lr': 0.0038795861579728878, 'weight_decay': 0.016090387672401216, 'batch_size': 128} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 19:22:10,202] Trial 18 finished with value: 0.5116760961997822 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.33721762564528424, 'lr': 0.009933408894517578, 'weight_decay': 0.09889253243637368, 'batch_size': 64}. Best is trial 12 with value: 0.5204031176113428. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.511676 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.33721762564528424, 'lr': 0.009933408894517578, 'weight_decay': 0.09889253243637368, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 19:23:30,459] Trial 19 finished with value: 0.4651229430660629 and parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2992064004470284, 'lr': 0.0008238636802500891, 'weight_decay': 0.00012118299714530565, 'batch_size': 64}. Best is trial 12 with value: 0.5204031176113428. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.465123 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2992064004470284, 'lr': 0.0008238636802500891, 'weight_decay': 0.00012118299714530565, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 19:23:44,925] Trial 20 pruned. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.325507 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3700174880178303, 'lr': 0.00017979913464595, 'weight_decay': 0.04605876780378306, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 19:24:06,749] Trial 21 pruned. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.404908 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3411540823524105, 'lr': 0.009510521958097012, 'weight_decay': 0.09304744568353097, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 19:24:48,291] Trial 22 pruned. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.446934 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.3750657095350376, 'lr': 0.0045721363736998, 'weight_decay': 0.04625643937639819, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 19:26:19,098] Trial 23 finished with value: 0.5170982255559309 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3500003701256375, 'lr': 0.005477077118286817, 'weight_decay': 0.09959296853057667, 'batch_size': 64}. Best is trial 12 with value: 0.5204031176113428. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.517098 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3500003701256375, 'lr': 0.005477077118286817, 'weight_decay': 0.09959296853057667, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 19:26:24,959] Trial 24 pruned. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.350446 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3995102689199929, 'lr': 0.002500039361204995, 'weight_decay': 0.026550619886303597, 'batch_size': 256} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 19:26:46,026] Trial 25 pruned. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.431285 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.3609304211829338, 'lr': 0.0049790046166129556, 'weight_decay': 0.04892268311422608, 'batch_size': 128} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 19:27:23,020] Trial 26 pruned. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.435976 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.31402987742933763, 'lr': 0.005448633008595281, 'weight_decay': 0.01564241389619987, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 19:28:02,554] Trial 27 pruned. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.436034 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.3588065818147843, 'lr': 0.002258142222328861, 'weight_decay': 0.05659625530811039, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 19:28:36,790] Trial 28 pruned. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.436205 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.30961753632547556, 'lr': 0.005563776228929742, 'weight_decay': 0.02700555807675681, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 19:29:08,516] Trial 29 pruned. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.426894 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3830012013755625, 'lr': 0.0013755361919013287, 'weight_decay': 0.05750401993276429, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 19:29:45,678] Trial 30 pruned. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.398278 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3443202106944347, 'lr': 0.002876283189771078, 'weight_decay': 0.00690752387785095, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 19:31:49,794] Trial 31 finished with value: 0.5176978246543809 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.34220512150959276, 'lr': 0.006677798109302621, 'weight_decay': 0.09892723183934939, 'batch_size': 64}. Best is trial 12 with value: 0.5204031176113428. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.517698 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.34220512150959276, 'lr': 0.006677798109302621, 'weight_decay': 0.09892723183934939, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 19:33:48,322] Trial 32 finished with value: 0.5081249069634662 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3769301620579597, 'lr': 0.004996929463025663, 'weight_decay': 0.06794618120793647, 'batch_size': 64}. Best is trial 12 with value: 0.5204031176113428. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.508125 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3769301620579597, 'lr': 0.004996929463025663, 'weight_decay': 0.06794618120793647, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 19:34:08,662] Trial 33 pruned. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.447095 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.3505453699572437, 'lr': 0.005998206793397177, 'weight_decay': 0.0964058067730205, 'batch_size': 128} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 19:34:48,396] Trial 34 pruned. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.433036 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.3722618203665385, 'lr': 0.0072047428155664305, 'weight_decay': 0.03900775573121464, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 19:35:22,392] Trial 35 pruned. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.429907 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3228156502649429, 'lr': 0.002980973985833703, 'weight_decay': 0.03435142505939458, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 19:35:28,190] Trial 36 pruned. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.376485 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.3520670707733077, 'lr': 0.0014862420355476493, 'weight_decay': 0.061611426953799335, 'batch_size': 256} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 19:36:32,103] Trial 37 finished with value: 0.5044889449664779 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.3856623911830082, 'lr': 0.006823704920271817, 'weight_decay': 0.03740612290843219, 'batch_size': 128}. Best is trial 12 with value: 0.5204031176113428. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.504489 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.3856623911830082, 'lr': 0.006823704920271817, 'weight_decay': 0.03740612290843219, 'batch_size': 128} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 19:38:06,166] Trial 38 finished with value: 0.506440163335977 and parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.2810932856255846, 'lr': 0.0034473837651149654, 'weight_decay': 0.05961893721568134, 'batch_size': 64}. Best is trial 12 with value: 0.5204031176113428. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.506440 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.2810932856255846, 'lr': 0.0034473837651149654, 'weight_decay': 0.05961893721568134, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 19:39:40,865] Trial 39 finished with value: 0.502510350337439 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.32894589631606913, 'lr': 0.009732789830784249, 'weight_decay': 0.019794287929635966, 'batch_size': 64}. Best is trial 12 with value: 0.5204031176113428. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.502510 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.32894589631606913, 'lr': 0.009732789830784249, 'weight_decay': 0.019794287929635966, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 19:39:46,686] Trial 40 pruned. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.379977 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3677425353944939, 'lr': 0.0011607579562786057, 'weight_decay': 0.030406269617775872, 'batch_size': 256} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 19:41:25,338] Trial 41 finished with value: 0.5034208506091843 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3473503172141952, 'lr': 0.006987761614334529, 'weight_decay': 0.09577222910774748, 'batch_size': 64}. Best is trial 12 with value: 0.5204031176113428. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.503421 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3473503172141952, 'lr': 0.006987761614334529, 'weight_decay': 0.09577222910774748, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 19:43:50,304] Trial 42 finished with value: 0.5086736536039177 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3407549871808069, 'lr': 0.008877451941847277, 'weight_decay': 0.07721072964520237, 'batch_size': 64}. Best is trial 12 with value: 0.5204031176113428. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.508674 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3407549871808069, 'lr': 0.008877451941847277, 'weight_decay': 0.07721072964520237, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 19:45:39,013] Trial 43 finished with value: 0.5150498433084334 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3900501995426364, 'lr': 0.002177143528597078, 'weight_decay': 0.09845970535203796, 'batch_size': 64}. Best is trial 12 with value: 0.5204031176113428. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.515050 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3900501995426364, 'lr': 0.002177143528597078, 'weight_decay': 0.09845970535203796, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 19:48:20,734] Trial 44 finished with value: 0.5021726224447053 and parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3907544036636971, 'lr': 0.0021642182681941066, 'weight_decay': 0.0691194717563556, 'batch_size': 32}. Best is trial 12 with value: 0.5204031176113428. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.502173 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3907544036636971, 'lr': 0.0021642182681941066, 'weight_decay': 0.0691194717563556, 'batch_size': 32} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 19:50:13,397] Trial 45 finished with value: 0.5004065455793114 and parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3841291380226531, 'lr': 0.004310026808714425, 'weight_decay': 0.04409591947695909, 'batch_size': 64}. Best is trial 12 with value: 0.5204031176113428. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.500407 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3841291380226531, 'lr': 0.004310026808714425, 'weight_decay': 0.04409591947695909, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 19:51:47,366] Trial 46 finished with value: 0.5079051495459682 and parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3674735083721002, 'lr': 0.0029273384918499803, 'weight_decay': 0.07016013088540546, 'batch_size': 64}. Best is trial 12 with value: 0.5204031176113428. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.507905 - Parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3674735083721002, 'lr': 0.0029273384918499803, 'weight_decay': 0.07016013088540546, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 19:52:10,976] Trial 47 pruned. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.421329 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.38946409727911796, 'lr': 0.006355604523829454, 'weight_decay': 0.03289101832683543, 'batch_size': 32} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 19:53:50,525] Trial 48 finished with value: 0.5059740512548597 and parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.3986515076146073, 'lr': 0.0041429917652249775, 'weight_decay': 0.09931130157498179, 'batch_size': 64}. Best is trial 12 with value: 0.5204031176113428. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.505974 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.3986515076146073, 'lr': 0.0041429917652249775, 'weight_decay': 0.09931130157498179, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 19:54:04,556] Trial 49 pruned. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.408016 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.35497029070060426, 'lr': 0.0019073106378240394, 'weight_decay': 0.0020564244775307765, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 19:54:21,353] Trial 50 pruned. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.428058 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.3773156905989508, 'lr': 0.0036568958982546706, 'weight_decay': 0.0478866685367857, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 19:54:37,716] Trial 51 pruned. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.432658 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3676909346208033, 'lr': 0.007932443093623398, 'weight_decay': 0.09803464820400955, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 19:54:54,189] Trial 52 pruned. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.384615 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3394647166307227, 'lr': 0.009768570790528338, 'weight_decay': 0.06312181544589911, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 19:55:09,069] Trial 53 pruned. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.426096 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.33147154266516576, 'lr': 0.005728460947095907, 'weight_decay': 0.07191086796752749, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 19:57:30,045] Trial 54 finished with value: 0.508911125648539 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.3617603791368776, 'lr': 0.0072359233646866255, 'weight_decay': 0.08101064744545525, 'batch_size': 64}. Best is trial 12 with value: 0.5204031176113428. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.508911 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.3617603791368776, 'lr': 0.0072359233646866255, 'weight_decay': 0.08101064744545525, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 19:57:38,718] Trial 55 pruned. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.402373 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.38845977883892696, 'lr': 0.004337115924785338, 'weight_decay': 0.04330609701996728, 'batch_size': 128} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 19:57:55,176] Trial 56 pruned. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.426060 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.39979300903690446, 'lr': 0.0027480933860287555, 'weight_decay': 0.05203480123349231, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 19:58:27,893] Trial 57 pruned. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.430998 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3751722139545968, 'lr': 0.005196821091551595, 'weight_decay': 0.07850419215127004, 'batch_size': 32} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 19:58:33,686] Trial 58 pruned. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.394111 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3474796173754939, 'lr': 0.0035529842587499745, 'weight_decay': 0.0216526854527647, 'batch_size': 256} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 20:00:17,970] Trial 59 finished with value: 0.5088051330627582 and parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.31807444949166586, 'lr': 0.008269296703923002, 'weight_decay': 0.05234547965214455, 'batch_size': 64}. Best is trial 12 with value: 0.5204031176113428. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.508805 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.31807444949166586, 'lr': 0.008269296703923002, 'weight_decay': 0.05234547965214455, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 20:01:37,307] Trial 60 finished with value: 0.5041930391312742 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.35826086966277776, 'lr': 0.006024463382471898, 'weight_decay': 0.09975303675746902, 'batch_size': 64}. Best is trial 12 with value: 0.5204031176113428. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.504193 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.35826086966277776, 'lr': 0.006024463382471898, 'weight_decay': 0.09975303675746902, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 20:01:52,166] Trial 61 pruned. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.390547 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.39339640691194744, 'lr': 0.004522221264429776, 'weight_decay': 0.07709033967068188, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 20:02:26,661] Trial 62 pruned. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.440476 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.3797558899228809, 'lr': 0.002357416200781271, 'weight_decay': 0.06226967323248316, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 20:04:30,286] Trial 63 finished with value: 0.5166375925228691 and parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.3805126512796094, 'lr': 0.007158943594021254, 'weight_decay': 0.08183199905323905, 'batch_size': 64}. Best is trial 12 with value: 0.5204031176113428. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.516638 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.3805126512796094, 'lr': 0.007158943594021254, 'weight_decay': 0.08183199905323905, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 20:04:44,145] Trial 64 pruned. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.405286 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.33594168187673046, 'lr': 0.007837992761350792, 'weight_decay': 0.03914224483638975, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 20:04:55,951] Trial 65 pruned. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.392265 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.3645588384042396, 'lr': 0.00608143170501572, 'weight_decay': 0.08004634258009205, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 20:05:08,867] Trial 66 pruned. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.391032 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3806279489908581, 'lr': 0.009899980612007819, 'weight_decay': 0.05185735622181592, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 20:06:59,967] Trial 67 finished with value: 0.5032839050901277 and parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.35335652649777266, 'lr': 0.0051508066889706305, 'weight_decay': 0.028356610636243052, 'batch_size': 64}. Best is trial 12 with value: 0.5204031176113428. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.503284 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.35335652649777266, 'lr': 0.0051508066889706305, 'weight_decay': 0.028356610636243052, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 20:07:07,915] Trial 68 pruned. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.395349 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3710738162347643, 'lr': 0.003374167354308752, 'weight_decay': 0.09902248698973977, 'batch_size': 128} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 20:08:46,163] Trial 69 finished with value: 0.5045980532417332 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3058634332483628, 'lr': 0.007647998183362028, 'weight_decay': 0.062172097749050866, 'batch_size': 64}. Best is trial 12 with value: 0.5204031176113428. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.504598 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3058634332483628, 'lr': 0.007647998183362028, 'weight_decay': 0.062172097749050866, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 20:08:51,465] Trial 70 pruned. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.368293 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.3906560588498733, 'lr': 0.006578461867642616, 'weight_decay': 0.04006887533784696, 'batch_size': 256} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 20:09:05,536] Trial 71 pruned. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.403867 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.39729521499778986, 'lr': 0.004096324922086911, 'weight_decay': 0.07963015121522148, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 20:09:18,543] Trial 72 pruned. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.380328 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.38388079840317463, 'lr': 0.004775941018164819, 'weight_decay': 0.08265809754921269, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 20:09:31,590] Trial 73 pruned. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.330442 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.3766161705152674, 'lr': 0.008674091121096817, 'weight_decay': 0.05811512619123711, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 20:09:43,640] Trial 74 pruned. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.381531 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3619962901342814, 'lr': 0.009978027527024782, 'weight_decay': 0.07147563810715965, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 20:09:56,596] Trial 75 pruned. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.396396 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.399796099634898, 'lr': 0.00550559733648782, 'weight_decay': 0.04894645144100689, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 20:11:20,551] Trial 76 finished with value: 0.5062130595844381 and parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.389793156021762, 'lr': 0.003195443595202035, 'weight_decay': 0.08107323235573854, 'batch_size': 64}. Best is trial 12 with value: 0.5204031176113428. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.506213 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.389793156021762, 'lr': 0.003195443595202035, 'weight_decay': 0.08107323235573854, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 20:11:43,646] Trial 77 pruned. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.436492 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.34578383036128174, 'lr': 0.0069806713462778665, 'weight_decay': 0.09955220678899207, 'batch_size': 32} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 20:12:49,671] Trial 78 finished with value: 0.5082231389897766 and parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.3704746268178663, 'lr': 0.0038930792018943613, 'weight_decay': 0.0657254661836288, 'batch_size': 64}. Best is trial 12 with value: 0.5204031176113428. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.508223 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.3704746268178663, 'lr': 0.0038930792018943613, 'weight_decay': 0.0657254661836288, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 20:14:18,922] Trial 79 pruned. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.465830 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3225595329386204, 'lr': 0.002569397503968321, 'weight_decay': 0.03550951700125492, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 20:15:52,249] Trial 80 finished with value: 0.5096813875615697 and parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.35452999786506867, 'lr': 0.006342425153953135, 'weight_decay': 0.05599566181101483, 'batch_size': 64}. Best is trial 12 with value: 0.5204031176113428. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.509681 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.35452999786506867, 'lr': 0.006342425153953135, 'weight_decay': 0.05599566181101483, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 20:17:18,539] Trial 81 finished with value: 0.5046004283096744 and parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3541279811789449, 'lr': 0.006453351298458861, 'weight_decay': 0.08618260375637439, 'batch_size': 64}. Best is trial 12 with value: 0.5204031176113428. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.504600 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3541279811789449, 'lr': 0.006453351298458861, 'weight_decay': 0.08618260375637439, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 20:17:30,320] Trial 82 pruned. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.421986 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.38292209580662984, 'lr': 0.005041842975123803, 'weight_decay': 0.0666670338382839, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 20:18:47,364] Trial 83 finished with value: 0.5099096075821573 and parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3383571923899666, 'lr': 0.008165408527606194, 'weight_decay': 0.053596564033258666, 'batch_size': 64}. Best is trial 12 with value: 0.5204031176113428. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.509910 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3383571923899666, 'lr': 0.008165408527606194, 'weight_decay': 0.053596564033258666, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 20:18:59,095] Trial 84 pruned. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.424808 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.32883171317145266, 'lr': 0.008411782966371094, 'weight_decay': 0.043737586459351066, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 20:19:07,201] Trial 85 pruned. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.403681 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.33871355415942905, 'lr': 0.008039782885410398, 'weight_decay': 0.088523724585261, 'batch_size': 128} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 20:20:30,678] Trial 86 finished with value: 0.5095629775063902 and parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3741070360149087, 'lr': 0.004185701812380822, 'weight_decay': 0.06971742318226766, 'batch_size': 64}. Best is trial 12 with value: 0.5204031176113428. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.509563 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3741070360149087, 'lr': 0.004185701812380822, 'weight_decay': 0.06971742318226766, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 20:20:45,223] Trial 87 pruned. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.439614 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.36508987886450606, 'lr': 0.00574015205955465, 'weight_decay': 0.0885151169252504, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 20:20:50,293] Trial 88 pruned. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.428902 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3919604914336178, 'lr': 0.007245477909339212, 'weight_decay': 0.05378963211164918, 'batch_size': 256} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 20:21:16,593] Trial 89 pruned. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.422007 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.3448586961766934, 'lr': 0.003162417904567774, 'weight_decay': 0.06751461721588688, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 20:21:48,329] Trial 90 pruned. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.457424 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.38523321401740646, 'lr': 0.004645304598476381, 'weight_decay': 0.04598278871423093, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 20:22:04,759] Trial 91 pruned. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.438576 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3591861909604221, 'lr': 0.006688083071799077, 'weight_decay': 0.059125180589416085, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 20:22:16,679] Trial 92 pruned. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.423163 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.35293037835917845, 'lr': 0.008663685736743518, 'weight_decay': 0.0878068488380457, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 20:23:52,859] Trial 93 finished with value: 0.511811444479353 and parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3337772978611656, 'lr': 0.005873939465557939, 'weight_decay': 0.05530202022867509, 'batch_size': 64}. Best is trial 12 with value: 0.5204031176113428. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.511811 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3337772978611656, 'lr': 0.005873939465557939, 'weight_decay': 0.05530202022867509, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 20:24:04,633] Trial 94 pruned. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.430733 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3338894398817575, 'lr': 0.005379871238429161, 'weight_decay': 0.07393759792663299, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 20:24:25,430] Trial 95 pruned. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.438515 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.32383959018102515, 'lr': 0.0036146494538285374, 'weight_decay': 0.08636106054022934, 'batch_size': 32} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 20:24:51,653] Trial 96 pruned. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.448619 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.34022208575779045, 'lr': 0.00847648418996258, 'weight_decay': 0.09986260182361341, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 20:25:04,580] Trial 97 pruned. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.416092 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3784231007827543, 'lr': 0.0045227156739380365, 'weight_decay': 0.050991099005961625, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 20:25:16,379] Trial 98 pruned. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.434637 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.39434691555411766, 'lr': 0.0072289292457852925, 'weight_decay': 0.0358452974515514, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 20:25:28,197] Trial 99 pruned. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.401075 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.36941442601879393, 'lr': 0.009921348963153302, 'weight_decay': 0.07098423143762086, 'batch_size': 64} - Best Value (CSI): 0.520403 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.5204 -Best Hyperparameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3938212564993552, 'lr': 0.007164979269975063, 'weight_decay': 0.0923681134285374, 'batch_size': 64} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.4574 - - 최종 CSI: 0.4011 - - 최고 CSI: 0.5204 - - 최저 CSI: 0.2818 - - 평균 CSI: 0.4456 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/deepgbm_ctgan10000_gwangju_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 50, Best CSI: 0.4590 - Fold 1 학습 완료 (검증 CSI: 0.4590) -Fold 2 학습 중... - Early stopping at epoch 33, Best CSI: 0.5391 - Fold 2 학습 완료 (검증 CSI: 0.5391) -Fold 3 학습 중... - Early stopping at epoch 34, Best CSI: 0.5169 - Fold 3 학습 완료 (검증 CSI: 0.5169) - -모든 모델 저장 완료: ../save_model/deepgbm_optima/deepgbm_ctgan10000_gwangju.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/deepgbm_optima/scaler/deepgbm_ctgan10000_gwangju_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: ../save_model/deepgbm_optima/deepgbm_ctgan10000_gwangju.pkl - -✓ 완료: deepgbm_ctgan10000/deepgbm_ctgan10000_gwangju.py (소요 시간: 5981초) - ----------------------------------------- -실행 중: deepgbm_ctgan10000/deepgbm_ctgan10000_incheon.py -시작 시간: 2025-12-28 20:27:32 ----------------------------------------- -[I 2025-12-28 20:27:33,401] A new study created in memory with name: no-name-8edaa145-8bb7-48ef-a771-758b35d3f973 - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 20:28:37,462] Trial 0 finished with value: 0.5035583243789783 and parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.10281805062299142, 'lr': 0.0004094547946910562, 'weight_decay': 0.006084708900936006, 'batch_size': 128}. Best is trial 0 with value: 0.5035583243789783. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.503558 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.10281805062299142, 'lr': 0.0004094547946910562, 'weight_decay': 0.006084708900936006, 'batch_size': 128} - Best Value (CSI): 0.503558 - Best Trial: 0 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.10281805062299142, 'lr': 0.0004094547946910562, 'weight_decay': 0.006084708900936006, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 20:29:52,625] Trial 1 finished with value: 0.5114078009850181 and parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.16675316028175197, 'lr': 0.00026360224664090707, 'weight_decay': 0.005503476811570524, 'batch_size': 64}. Best is trial 1 with value: 0.5114078009850181. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.511408 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.16675316028175197, 'lr': 0.00026360224664090707, 'weight_decay': 0.005503476811570524, 'batch_size': 64} - Best Value (CSI): 0.511408 - Best Trial: 1 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.16675316028175197, 'lr': 0.00026360224664090707, 'weight_decay': 0.005503476811570524, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 20:30:42,562] Trial 2 finished with value: 0.5218245071097826 and parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.17741559083803368, 'lr': 0.0008052752456691312, 'weight_decay': 0.0008816500025451825, 'batch_size': 64}. Best is trial 2 with value: 0.5218245071097826. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.521825 - Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.17741559083803368, 'lr': 0.0008052752456691312, 'weight_decay': 0.0008816500025451825, 'batch_size': 64} - Best Value (CSI): 0.521825 - Best Trial: 2 - Best Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.17741559083803368, 'lr': 0.0008052752456691312, 'weight_decay': 0.0008816500025451825, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 20:32:25,707] Trial 3 finished with value: 0.4519947920478018 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.22975447608056218, 'lr': 1.679045813497873e-05, 'weight_decay': 0.0015285353589354915, 'batch_size': 128}. Best is trial 2 with value: 0.5218245071097826. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.451995 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.22975447608056218, 'lr': 1.679045813497873e-05, 'weight_decay': 0.0015285353589354915, 'batch_size': 128} - Best Value (CSI): 0.521825 - Best Trial: 2 - Best Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.17741559083803368, 'lr': 0.0008052752456691312, 'weight_decay': 0.0008816500025451825, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 20:34:02,766] Trial 4 finished with value: 0.4638606519912772 and parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.10077230027579337, 'lr': 1.4508941024024848e-05, 'weight_decay': 0.0012147781600427053, 'batch_size': 128}. Best is trial 2 with value: 0.5218245071097826. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.463861 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.10077230027579337, 'lr': 1.4508941024024848e-05, 'weight_decay': 0.0012147781600427053, 'batch_size': 128} - Best Value (CSI): 0.521825 - Best Trial: 2 - Best Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.17741559083803368, 'lr': 0.0008052752456691312, 'weight_decay': 0.0008816500025451825, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 20:34:46,082] Trial 5 finished with value: 0.5206829575178441 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.11049435817265445, 'lr': 0.0006684809043764866, 'weight_decay': 0.034577590638617, 'batch_size': 128}. Best is trial 2 with value: 0.5218245071097826. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.520683 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.11049435817265445, 'lr': 0.0006684809043764866, 'weight_decay': 0.034577590638617, 'batch_size': 128} - Best Value (CSI): 0.521825 - Best Trial: 2 - Best Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.17741559083803368, 'lr': 0.0008052752456691312, 'weight_decay': 0.0008816500025451825, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 20:35:02,454] Trial 6 pruned. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.405694 - Parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.2929604526456821, 'lr': 0.00011432999981178968, 'weight_decay': 0.026160192865894515, 'batch_size': 64} - Best Value (CSI): 0.521825 - Best Trial: 2 - Best Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.17741559083803368, 'lr': 0.0008052752456691312, 'weight_decay': 0.0008816500025451825, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 20:35:42,118] Trial 7 finished with value: 0.5175670562898792 and parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.388394709939174, 'lr': 0.00013044892881589949, 'weight_decay': 0.03361641678858114, 'batch_size': 256}. Best is trial 2 with value: 0.5218245071097826. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.517567 - Parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.388394709939174, 'lr': 0.00013044892881589949, 'weight_decay': 0.03361641678858114, 'batch_size': 256} - Best Value (CSI): 0.521825 - Best Trial: 2 - Best Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.17741559083803368, 'lr': 0.0008052752456691312, 'weight_decay': 0.0008816500025451825, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 20:36:13,179] Trial 8 pruned. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.429080 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.2387566055950624, 'lr': 0.0004484398377982173, 'weight_decay': 0.051286402108193754, 'batch_size': 64} - Best Value (CSI): 0.521825 - Best Trial: 2 - Best Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.17741559083803368, 'lr': 0.0008052752456691312, 'weight_decay': 0.0008816500025451825, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 20:36:20,178] Trial 9 pruned. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.263276 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.23023134914783494, 'lr': 1.1223329568539183e-05, 'weight_decay': 0.051230003255330725, 'batch_size': 128} - Best Value (CSI): 0.521825 - Best Trial: 2 - Best Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.17741559083803368, 'lr': 0.0008052752456691312, 'weight_decay': 0.0008816500025451825, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 20:37:02,007] Trial 10 pruned. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.471853 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.17651674688923996, 'lr': 0.004374698606638214, 'weight_decay': 0.00013233360202172123, 'batch_size': 32} - Best Value (CSI): 0.521825 - Best Trial: 2 - Best Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.17741559083803368, 'lr': 0.0008052752456691312, 'weight_decay': 0.0008816500025451825, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 20:37:38,852] Trial 11 pruned. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.456005 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.15903182312222638, 'lr': 0.002230379249302043, 'weight_decay': 0.09218640657939937, 'batch_size': 32} - Best Value (CSI): 0.521825 - Best Trial: 2 - Best Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.17741559083803368, 'lr': 0.0008052752456691312, 'weight_decay': 0.0008816500025451825, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 20:38:05,424] Trial 12 pruned. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.504042 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.146393204316876, 'lr': 0.0014310228865868407, 'weight_decay': 0.0126276360797855, 'batch_size': 256} - Best Value (CSI): 0.521825 - Best Trial: 2 - Best Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.17741559083803368, 'lr': 0.0008052752456691312, 'weight_decay': 0.0008816500025451825, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 20:39:09,645] Trial 13 finished with value: 0.5525887443618827 and parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.12022799581247412, 'lr': 0.0074950162350266485, 'weight_decay': 0.0009847165297610762, 'batch_size': 64}. Best is trial 13 with value: 0.5525887443618827. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.552589 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.12022799581247412, 'lr': 0.0074950162350266485, 'weight_decay': 0.0009847165297610762, 'batch_size': 64} - Best Value (CSI): 0.552589 - Best Trial: 13 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.12022799581247412, 'lr': 0.0074950162350266485, 'weight_decay': 0.0009847165297610762, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 20:39:33,904] Trial 14 pruned. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.450758 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.19498200900332885, 'lr': 0.009893611778306687, 'weight_decay': 0.0004338299706188968, 'batch_size': 64} - Best Value (CSI): 0.552589 - Best Trial: 13 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.12022799581247412, 'lr': 0.0074950162350266485, 'weight_decay': 0.0009847165297610762, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 20:40:00,627] Trial 15 pruned. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.456703 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.13535999933645929, 'lr': 0.009248265759705006, 'weight_decay': 0.0006625876622580232, 'batch_size': 64} - Best Value (CSI): 0.552589 - Best Trial: 13 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.12022799581247412, 'lr': 0.0074950162350266485, 'weight_decay': 0.0009847165297610762, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 20:40:21,808] Trial 16 pruned. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.488000 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.19870200024636508, 'lr': 0.0028956090097254483, 'weight_decay': 0.0020779444761752515, 'batch_size': 64} - Best Value (CSI): 0.552589 - Best Trial: 13 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.12022799581247412, 'lr': 0.0074950162350266485, 'weight_decay': 0.0009847165297610762, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 20:41:11,403] Trial 17 finished with value: 0.5275211063263553 and parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.1464431349235381, 'lr': 0.001373487342070769, 'weight_decay': 0.00038985610024115994, 'batch_size': 64}. Best is trial 13 with value: 0.5525887443618827. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.527521 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.1464431349235381, 'lr': 0.001373487342070769, 'weight_decay': 0.00038985610024115994, 'batch_size': 64} - Best Value (CSI): 0.552589 - Best Trial: 13 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.12022799581247412, 'lr': 0.0074950162350266485, 'weight_decay': 0.0009847165297610762, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) -[I 2025-12-28 20:42:04,013] Trial 18 pruned. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.572043 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.14543241966993234, 'lr': 0.00621609641985209, 'weight_decay': 0.00040571717146254847, 'batch_size': 64} - Best Value (CSI): 0.552589 - Best Trial: 13 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.12022799581247412, 'lr': 0.0074950162350266485, 'weight_decay': 0.0009847165297610762, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 20:42:27,472] Trial 19 finished with value: 0.5277419807061007 and parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.12611740317819922, 'lr': 0.0038539989258168355, 'weight_decay': 0.00017455043966780616, 'batch_size': 256}. Best is trial 13 with value: 0.5525887443618827. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.527742 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.12611740317819922, 'lr': 0.0038539989258168355, 'weight_decay': 0.00017455043966780616, 'batch_size': 256} - Best Value (CSI): 0.552589 - Best Trial: 13 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.12022799581247412, 'lr': 0.0074950162350266485, 'weight_decay': 0.0009847165297610762, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 20:42:49,397] Trial 20 finished with value: 0.5363796260473088 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.12837074699695597, 'lr': 0.0038529643611446254, 'weight_decay': 0.00010111382854533909, 'batch_size': 256}. Best is trial 13 with value: 0.5525887443618827. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.536380 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.12837074699695597, 'lr': 0.0038529643611446254, 'weight_decay': 0.00010111382854533909, 'batch_size': 256} - Best Value (CSI): 0.552589 - Best Trial: 13 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.12022799581247412, 'lr': 0.0074950162350266485, 'weight_decay': 0.0009847165297610762, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 20:43:14,718] Trial 21 pruned. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.512080 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.12884370776307674, 'lr': 0.004726120780706167, 'weight_decay': 0.00011345485774027207, 'batch_size': 256} - Best Value (CSI): 0.552589 - Best Trial: 13 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.12022799581247412, 'lr': 0.0074950162350266485, 'weight_decay': 0.0009847165297610762, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 20:43:36,224] Trial 22 finished with value: 0.5378022212421132 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.11956309976931895, 'lr': 0.0032185244622791416, 'weight_decay': 0.0002378583050787927, 'batch_size': 256}. Best is trial 13 with value: 0.5525887443618827. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.537802 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.11956309976931895, 'lr': 0.0032185244622791416, 'weight_decay': 0.0002378583050787927, 'batch_size': 256} - Best Value (CSI): 0.552589 - Best Trial: 13 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.12022799581247412, 'lr': 0.0074950162350266485, 'weight_decay': 0.0009847165297610762, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 20:44:00,149] Trial 23 finished with value: 0.521566981008169 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.11960937608096459, 'lr': 0.0023342401190555744, 'weight_decay': 0.0002205002445413614, 'batch_size': 256}. Best is trial 13 with value: 0.5525887443618827. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.521567 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.11960937608096459, 'lr': 0.0023342401190555744, 'weight_decay': 0.0002205002445413614, 'batch_size': 256} - Best Value (CSI): 0.552589 - Best Trial: 13 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.12022799581247412, 'lr': 0.0074950162350266485, 'weight_decay': 0.0009847165297610762, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 20:44:25,011] Trial 24 finished with value: 0.5310643305162138 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.10106281200861522, 'lr': 0.007240658610974353, 'weight_decay': 0.00024569987550007667, 'batch_size': 256}. Best is trial 13 with value: 0.5525887443618827. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.531064 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.10106281200861522, 'lr': 0.007240658610974353, 'weight_decay': 0.00024569987550007667, 'batch_size': 256} - Best Value (CSI): 0.552589 - Best Trial: 13 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.12022799581247412, 'lr': 0.0074950162350266485, 'weight_decay': 0.0009847165297610762, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 20:44:50,104] Trial 25 finished with value: 0.5385497513139267 and parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.1332549919788319, 'lr': 0.005443883549428839, 'weight_decay': 0.0002301110670036112, 'batch_size': 256}. Best is trial 13 with value: 0.5525887443618827. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.538550 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.1332549919788319, 'lr': 0.005443883549428839, 'weight_decay': 0.0002301110670036112, 'batch_size': 256} - Best Value (CSI): 0.552589 - Best Trial: 13 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.12022799581247412, 'lr': 0.0074950162350266485, 'weight_decay': 0.0009847165297610762, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 20:45:13,574] Trial 26 finished with value: 0.5513822481901878 and parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.15746769345916276, 'lr': 0.009936298633893755, 'weight_decay': 0.0007183498875337535, 'batch_size': 256}. Best is trial 13 with value: 0.5525887443618827. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.551382 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.15746769345916276, 'lr': 0.009936298633893755, 'weight_decay': 0.0007183498875337535, 'batch_size': 256} - Best Value (CSI): 0.552589 - Best Trial: 13 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.12022799581247412, 'lr': 0.0074950162350266485, 'weight_decay': 0.0009847165297610762, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 20:45:34,671] Trial 27 pruned. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.406946 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.16144100170670295, 'lr': 0.006507288328540219, 'weight_decay': 0.0007074983235018028, 'batch_size': 32} - Best Value (CSI): 0.552589 - Best Trial: 13 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.12022799581247412, 'lr': 0.0074950162350266485, 'weight_decay': 0.0009847165297610762, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 20:46:03,680] Trial 28 pruned. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.524291 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.1947422358422172, 'lr': 0.00957308106416948, 'weight_decay': 0.0022228895721241753, 'batch_size': 256} - Best Value (CSI): 0.552589 - Best Trial: 13 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.12022799581247412, 'lr': 0.0074950162350266485, 'weight_decay': 0.0009847165297610762, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 20:46:29,420] Trial 29 pruned. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.512218 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.10759421679650272, 'lr': 0.005807783064775652, 'weight_decay': 0.0036816594060894697, 'batch_size': 256} - Best Value (CSI): 0.552589 - Best Trial: 13 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.12022799581247412, 'lr': 0.0074950162350266485, 'weight_decay': 0.0009847165297610762, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 20:46:51,627] Trial 30 pruned. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.375486 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.14481769963212696, 'lr': 0.009885012893340085, 'weight_decay': 0.0010679321706356304, 'batch_size': 32} - Best Value (CSI): 0.552589 - Best Trial: 13 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.12022799581247412, 'lr': 0.0074950162350266485, 'weight_decay': 0.0009847165297610762, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 20:47:14,616] Trial 31 finished with value: 0.5334388665940594 and parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.12312150998341437, 'lr': 0.004260319336614774, 'weight_decay': 0.00027742952350576526, 'batch_size': 256}. Best is trial 13 with value: 0.5525887443618827. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.533439 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.12312150998341437, 'lr': 0.004260319336614774, 'weight_decay': 0.00027742952350576526, 'batch_size': 256} - Best Value (CSI): 0.552589 - Best Trial: 13 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.12022799581247412, 'lr': 0.0074950162350266485, 'weight_decay': 0.0009847165297610762, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 20:47:22,774] Trial 32 pruned. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.445841 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.11812917319439357, 'lr': 0.006032144409797176, 'weight_decay': 0.0005622279041040653, 'batch_size': 256} - Best Value (CSI): 0.552589 - Best Trial: 13 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.12022799581247412, 'lr': 0.0074950162350266485, 'weight_decay': 0.0009847165297610762, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 20:47:31,048] Trial 33 pruned. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.442883 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.16336013012062325, 'lr': 0.002421148683661409, 'weight_decay': 0.0008337646690032803, 'batch_size': 256} - Best Value (CSI): 0.552589 - Best Trial: 13 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.12022799581247412, 'lr': 0.0074950162350266485, 'weight_decay': 0.0009847165297610762, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 20:47:36,247] Trial 34 pruned. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.431442 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.10110369446073636, 'lr': 0.003096452269201278, 'weight_decay': 0.0003148508107841231, 'batch_size': 256} - Best Value (CSI): 0.552589 - Best Trial: 13 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.12022799581247412, 'lr': 0.0074950162350266485, 'weight_decay': 0.0009847165297610762, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 20:47:41,064] Trial 35 pruned. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.443684 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.17695118708292357, 'lr': 0.0015028743862582161, 'weight_decay': 0.0005236099374172995, 'batch_size': 256} - Best Value (CSI): 0.552589 - Best Trial: 13 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.12022799581247412, 'lr': 0.0074950162350266485, 'weight_decay': 0.0009847165297610762, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 20:48:14,300] Trial 36 finished with value: 0.552627867752313 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.13804213033188278, 'lr': 0.00666980471505662, 'weight_decay': 0.00018744416376778518, 'batch_size': 128}. Best is trial 36 with value: 0.552627867752313. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.552628 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.13804213033188278, 'lr': 0.00666980471505662, 'weight_decay': 0.00018744416376778518, 'batch_size': 128} - Best Value (CSI): 0.552628 - Best Trial: 36 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.13804213033188278, 'lr': 0.00666980471505662, 'weight_decay': 0.00018744416376778518, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 20:48:57,039] Trial 37 finished with value: 0.5516927856928084 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1402324842234663, 'lr': 0.006636739687073565, 'weight_decay': 0.00016182492203133933, 'batch_size': 128}. Best is trial 36 with value: 0.552627867752313. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.551693 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1402324842234663, 'lr': 0.006636739687073565, 'weight_decay': 0.00016182492203133933, 'batch_size': 128} - Best Value (CSI): 0.552628 - Best Trial: 36 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.13804213033188278, 'lr': 0.00666980471505662, 'weight_decay': 0.00018744416376778518, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 20:49:13,762] Trial 38 pruned. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.484663 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.15841307765272056, 'lr': 0.0069671211314324966, 'weight_decay': 0.0001537450779196032, 'batch_size': 128} - Best Value (CSI): 0.552628 - Best Trial: 36 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.13804213033188278, 'lr': 0.00666980471505662, 'weight_decay': 0.00018744416376778518, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 20:49:27,052] Trial 39 pruned. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.479738 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.20791938600145665, 'lr': 0.0019037293031849319, 'weight_decay': 0.0012668679979656464, 'batch_size': 128} - Best Value (CSI): 0.552628 - Best Trial: 36 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.13804213033188278, 'lr': 0.00666980471505662, 'weight_decay': 0.00018744416376778518, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 20:50:06,378] Trial 40 finished with value: 0.5434342159450714 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.18222127522923576, 'lr': 0.003852184714086002, 'weight_decay': 0.0008802825988495726, 'batch_size': 128}. Best is trial 36 with value: 0.552627867752313. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.543434 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.18222127522923576, 'lr': 0.003852184714086002, 'weight_decay': 0.0008802825988495726, 'batch_size': 128} - Best Value (CSI): 0.552628 - Best Trial: 36 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.13804213033188278, 'lr': 0.00666980471505662, 'weight_decay': 0.00018744416376778518, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 20:50:47,575] Trial 41 finished with value: 0.5438192585622175 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.1770580475070806, 'lr': 0.004528158262329327, 'weight_decay': 0.0009106646664395158, 'batch_size': 128}. Best is trial 36 with value: 0.552627867752313. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.543819 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.1770580475070806, 'lr': 0.004528158262329327, 'weight_decay': 0.0009106646664395158, 'batch_size': 128} - Best Value (CSI): 0.552628 - Best Trial: 36 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.13804213033188278, 'lr': 0.00666980471505662, 'weight_decay': 0.00018744416376778518, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 20:51:30,023] Trial 42 finished with value: 0.5502364039892521 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.150486901812303, 'lr': 0.007264732590789507, 'weight_decay': 0.0014740223707663718, 'batch_size': 128}. Best is trial 36 with value: 0.552627867752313. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.550236 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.150486901812303, 'lr': 0.007264732590789507, 'weight_decay': 0.0014740223707663718, 'batch_size': 128} - Best Value (CSI): 0.552628 - Best Trial: 36 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.13804213033188278, 'lr': 0.00666980471505662, 'weight_decay': 0.00018744416376778518, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 20:52:05,647] Trial 43 finished with value: 0.5395463832387208 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.1510478381812438, 'lr': 0.007310521170910806, 'weight_decay': 0.0018681007141710157, 'batch_size': 128}. Best is trial 36 with value: 0.552627867752313. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.539546 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.1510478381812438, 'lr': 0.007310521170910806, 'weight_decay': 0.0018681007141710157, 'batch_size': 128} - Best Value (CSI): 0.552628 - Best Trial: 36 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.13804213033188278, 'lr': 0.00666980471505662, 'weight_decay': 0.00018744416376778518, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 20:52:50,844] Trial 44 finished with value: 0.5526658397235988 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.1381605783099045, 'lr': 0.009993818847757572, 'weight_decay': 0.000146558800057306, 'batch_size': 128}. Best is trial 44 with value: 0.5526658397235988. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.552666 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.1381605783099045, 'lr': 0.009993818847757572, 'weight_decay': 0.000146558800057306, 'batch_size': 128} - Best Value (CSI): 0.552666 - Best Trial: 44 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.1381605783099045, 'lr': 0.009993818847757572, 'weight_decay': 0.000146558800057306, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 20:52:58,071] Trial 45 pruned. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.409012 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.13761231654135025, 'lr': 0.0009986456042909958, 'weight_decay': 0.00016328005892009723, 'batch_size': 128} - Best Value (CSI): 0.552666 - Best Trial: 44 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.1381605783099045, 'lr': 0.009993818847757572, 'weight_decay': 0.000146558800057306, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 20:53:38,200] Trial 46 finished with value: 0.5428695905026595 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.16578408733573052, 'lr': 0.009748857333802688, 'weight_decay': 0.00010115269326018381, 'batch_size': 128}. Best is trial 44 with value: 0.5526658397235988. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.542870 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.16578408733573052, 'lr': 0.009748857333802688, 'weight_decay': 0.00010115269326018381, 'batch_size': 128} - Best Value (CSI): 0.552666 - Best Trial: 44 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.1381605783099045, 'lr': 0.009993818847757572, 'weight_decay': 0.000146558800057306, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 20:53:53,357] Trial 47 pruned. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.449970 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.10704114904448213, 'lr': 0.005099756611182526, 'weight_decay': 0.0003192811083118881, 'batch_size': 128} - Best Value (CSI): 0.552666 - Best Trial: 44 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.1381605783099045, 'lr': 0.009993818847757572, 'weight_decay': 0.000146558800057306, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 20:54:27,799] Trial 48 finished with value: 0.5309709300204094 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.11634655419178058, 'lr': 0.0031116093331770792, 'weight_decay': 0.00018344646159815345, 'batch_size': 128}. Best is trial 44 with value: 0.5526658397235988. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.530971 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.11634655419178058, 'lr': 0.0031116093331770792, 'weight_decay': 0.00018344646159815345, 'batch_size': 128} - Best Value (CSI): 0.552666 - Best Trial: 44 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.1381605783099045, 'lr': 0.009993818847757572, 'weight_decay': 0.000146558800057306, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 20:56:04,937] Trial 49 finished with value: 0.5512153584620476 and parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.13759436474325948, 'lr': 0.00801475269334421, 'weight_decay': 0.00014296985811924757, 'batch_size': 64}. Best is trial 44 with value: 0.5526658397235988. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.551215 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.13759436474325948, 'lr': 0.00801475269334421, 'weight_decay': 0.00014296985811924757, 'batch_size': 64} - Best Value (CSI): 0.552666 - Best Trial: 44 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.1381605783099045, 'lr': 0.009993818847757572, 'weight_decay': 0.000146558800057306, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 20:56:51,356] Trial 50 finished with value: 0.5444042024748891 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.26131374001608554, 'lr': 0.0053223541304732265, 'weight_decay': 0.00038785448496057916, 'batch_size': 128}. Best is trial 44 with value: 0.5526658397235988. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.544404 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.26131374001608554, 'lr': 0.0053223541304732265, 'weight_decay': 0.00038785448496057916, 'batch_size': 128} - Best Value (CSI): 0.552666 - Best Trial: 44 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.1381605783099045, 'lr': 0.009993818847757572, 'weight_decay': 0.000146558800057306, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 20:57:19,572] Trial 51 pruned. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.487635 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.13881393587773386, 'lr': 0.00904373630047427, 'weight_decay': 0.00013723037792367547, 'batch_size': 64} - Best Value (CSI): 0.552666 - Best Trial: 44 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.1381605783099045, 'lr': 0.009993818847757572, 'weight_decay': 0.000146558800057306, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 20:58:41,522] Trial 52 finished with value: 0.5522679238658653 and parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.13198411605031007, 'lr': 0.007771443815937695, 'weight_decay': 0.00013605329702851807, 'batch_size': 64}. Best is trial 44 with value: 0.5526658397235988. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.552268 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.13198411605031007, 'lr': 0.007771443815937695, 'weight_decay': 0.00013605329702851807, 'batch_size': 64} - Best Value (CSI): 0.552666 - Best Trial: 44 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.1381605783099045, 'lr': 0.009993818847757572, 'weight_decay': 0.000146558800057306, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 20:59:58,883] Trial 53 finished with value: 0.5461612245473196 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.11417811994182488, 'lr': 0.007256187932963692, 'weight_decay': 0.00019558196385629736, 'batch_size': 64}. Best is trial 44 with value: 0.5526658397235988. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.546161 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.11417811994182488, 'lr': 0.007256187932963692, 'weight_decay': 0.00019558196385629736, 'batch_size': 64} - Best Value (CSI): 0.552666 - Best Trial: 44 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.1381605783099045, 'lr': 0.009993818847757572, 'weight_decay': 0.000146558800057306, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 21:01:18,161] Trial 54 finished with value: 0.5511642815842203 and parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.12927572221608072, 'lr': 0.005368295486019479, 'weight_decay': 0.00012809372043801339, 'batch_size': 64}. Best is trial 44 with value: 0.5526658397235988. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.551164 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.12927572221608072, 'lr': 0.005368295486019479, 'weight_decay': 0.00012809372043801339, 'batch_size': 64} - Best Value (CSI): 0.552666 - Best Trial: 44 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.1381605783099045, 'lr': 0.009993818847757572, 'weight_decay': 0.000146558800057306, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 21:02:08,825] Trial 55 finished with value: 0.5382657651058985 and parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.15467731108980148, 'lr': 0.0037310700818680253, 'weight_decay': 0.0003397931916256659, 'batch_size': 64}. Best is trial 44 with value: 0.5526658397235988. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.538266 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.15467731108980148, 'lr': 0.0037310700818680253, 'weight_decay': 0.0003397931916256659, 'batch_size': 64} - Best Value (CSI): 0.552666 - Best Trial: 44 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.1381605783099045, 'lr': 0.009993818847757572, 'weight_decay': 0.000146558800057306, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 21:02:56,214] Trial 56 finished with value: 0.5644485264432356 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128}. Best is trial 56 with value: 0.5644485264432356. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.564449 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 21:03:30,821] Trial 57 finished with value: 0.5401849496176356 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16884541712051412, 'lr': 0.004480434929250742, 'weight_decay': 0.0005006702682682651, 'batch_size': 128}. Best is trial 56 with value: 0.5644485264432356. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.540185 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16884541712051412, 'lr': 0.004480434929250742, 'weight_decay': 0.0005006702682682651, 'batch_size': 128} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 21:04:12,057] Trial 58 finished with value: 0.5583019600461835 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.1403443515202148, 'lr': 0.0073746308956520144, 'weight_decay': 0.00018858367651560897, 'batch_size': 128}. Best is trial 56 with value: 0.5644485264432356. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.558302 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.1403443515202148, 'lr': 0.0073746308956520144, 'weight_decay': 0.00018858367651560897, 'batch_size': 128} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 21:04:21,162] Trial 59 pruned. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.448757 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.12801695707228683, 'lr': 0.002861767671521901, 'weight_decay': 0.0002560839447216127, 'batch_size': 128} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 21:04:51,902] Trial 60 pruned. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.468176 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.11393178193721737, 'lr': 0.007611046874514047, 'weight_decay': 0.00021636367672213627, 'batch_size': 64} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 21:05:08,735] Trial 61 pruned. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.462668 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.14205573912216174, 'lr': 0.005747599274205612, 'weight_decay': 0.00017585722568585284, 'batch_size': 128} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 21:05:44,974] Trial 62 finished with value: 0.5466624781627548 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.14863606700740828, 'lr': 0.007818373948897735, 'weight_decay': 0.00011539263451515848, 'batch_size': 128}. Best is trial 56 with value: 0.5644485264432356. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.546662 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.14863606700740828, 'lr': 0.007818373948897735, 'weight_decay': 0.00011539263451515848, 'batch_size': 128} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 21:06:22,646] Trial 63 finished with value: 0.5464776373208452 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.13315542605462802, 'lr': 0.006130577652585583, 'weight_decay': 0.00030809857554184864, 'batch_size': 128}. Best is trial 56 with value: 0.5644485264432356. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.546478 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.13315542605462802, 'lr': 0.006130577652585583, 'weight_decay': 0.00030809857554184864, 'batch_size': 128} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 21:07:07,381] Trial 64 pruned. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.467228 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.10979940005355489, 'lr': 0.003614732664716501, 'weight_decay': 0.00019022633032522626, 'batch_size': 32} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 21:07:16,207] Trial 65 pruned. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.470944 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.12664916293655118, 'lr': 0.004520623088306594, 'weight_decay': 0.00013194437841817169, 'batch_size': 128} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 21:07:59,377] Trial 66 finished with value: 0.5591047207082122 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.14297398821729423, 'lr': 0.00791153374632006, 'weight_decay': 0.00025820616073126237, 'batch_size': 128}. Best is trial 56 with value: 0.5644485264432356. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.559105 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.14297398821729423, 'lr': 0.00791153374632006, 'weight_decay': 0.00025820616073126237, 'batch_size': 128} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 21:09:26,460] Trial 67 finished with value: 0.5563757274389706 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.12223487335508174, 'lr': 0.00843563094272057, 'weight_decay': 0.0004567724897560505, 'batch_size': 64}. Best is trial 56 with value: 0.5644485264432356. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.556376 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.12223487335508174, 'lr': 0.00843563094272057, 'weight_decay': 0.0004567724897560505, 'batch_size': 64} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 21:09:33,961] Trial 68 pruned. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.446903 - Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.12060625335562272, 'lr': 0.008534689512597497, 'weight_decay': 0.0006110478654668953, 'batch_size': 128} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 21:09:51,032] Trial 69 pruned. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.475030 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.10199904803106835, 'lr': 0.009929520965415998, 'weight_decay': 0.0004739526975566487, 'batch_size': 64} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 21:10:18,353] Trial 70 pruned. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.412976 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.152570100154129, 'lr': 0.004980637643241967, 'weight_decay': 0.00037276498335706324, 'batch_size': 32} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 21:11:33,848] Trial 71 finished with value: 0.549818206883998 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.13573956575055868, 'lr': 0.0063179594810047045, 'weight_decay': 0.00025379494809594377, 'batch_size': 64}. Best is trial 56 with value: 0.5644485264432356. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.549818 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.13573956575055868, 'lr': 0.0063179594810047045, 'weight_decay': 0.00025379494809594377, 'batch_size': 64} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 21:12:03,483] Trial 72 pruned. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.478342 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.12432316115593231, 'lr': 0.008210270879621546, 'weight_decay': 0.0004080807834238328, 'batch_size': 64} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 21:13:12,965] Trial 73 finished with value: 0.5507199744219553 and parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.1457916000663571, 'lr': 0.008127576078909146, 'weight_decay': 0.00027152595883661297, 'batch_size': 64}. Best is trial 56 with value: 0.5644485264432356. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.550720 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.1457916000663571, 'lr': 0.008127576078909146, 'weight_decay': 0.00027152595883661297, 'batch_size': 64} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 21:14:13,914] Trial 74 finished with value: 0.5525845465691134 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.11212983631965275, 'lr': 0.005963619508207302, 'weight_decay': 0.00021374867440367628, 'batch_size': 64}. Best is trial 56 with value: 0.5644485264432356. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.552585 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.11212983631965275, 'lr': 0.005963619508207302, 'weight_decay': 0.00021374867440367628, 'batch_size': 64} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 21:14:24,998] Trial 75 pruned. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.458665 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.11073889268550598, 'lr': 0.005925005612992019, 'weight_decay': 0.00043136417956511126, 'batch_size': 128} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 21:14:36,108] Trial 76 pruned. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.445768 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.10022271521420009, 'lr': 0.003972959551450464, 'weight_decay': 0.00021054783163272541, 'batch_size': 128} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 21:15:47,829] Trial 77 finished with value: 0.5413655997299855 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.11884193149946026, 'lr': 0.004755900670655561, 'weight_decay': 0.0006608760350254661, 'batch_size': 64}. Best is trial 56 with value: 0.5644485264432356. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.541366 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.11884193149946026, 'lr': 0.004755900670655561, 'weight_decay': 0.0006608760350254661, 'batch_size': 64} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 21:16:27,141] Trial 78 finished with value: 0.5488693099109199 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.1687992270797759, 'lr': 0.006279245789470673, 'weight_decay': 0.0003034539394951718, 'batch_size': 128}. Best is trial 56 with value: 0.5644485264432356. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.548869 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.1687992270797759, 'lr': 0.006279245789470673, 'weight_decay': 0.0003034539394951718, 'batch_size': 128} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 21:17:33,549] Trial 79 finished with value: 0.5387880992326108 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.14247799789447735, 'lr': 0.0026473358404261902, 'weight_decay': 0.0004869065094112459, 'batch_size': 64}. Best is trial 56 with value: 0.5644485264432356. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.538788 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.14247799789447735, 'lr': 0.0026473358404261902, 'weight_decay': 0.0004869065094112459, 'batch_size': 64} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 21:17:42,359] Trial 80 pruned. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.432561 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.15869021629446295, 'lr': 0.002260366358397602, 'weight_decay': 0.0002365933925797734, 'batch_size': 128} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 21:18:12,111] Trial 81 pruned. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.500614 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.13088681017005405, 'lr': 0.0083268641155692, 'weight_decay': 0.00015120553279700493, 'batch_size': 64} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 21:18:38,210] Trial 82 pruned. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.481149 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.12412305681560211, 'lr': 0.006471869151337779, 'weight_decay': 0.00020159727795449086, 'batch_size': 64} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 21:19:42,237] Trial 83 finished with value: 0.5425596378076011 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.13380365490975396, 'lr': 0.003293840445705116, 'weight_decay': 0.00011500435998749942, 'batch_size': 64}. Best is trial 56 with value: 0.5644485264432356. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.542560 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.13380365490975396, 'lr': 0.003293840445705116, 'weight_decay': 0.00011500435998749942, 'batch_size': 64} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 21:20:10,877] Trial 84 pruned. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.471346 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.10826970740460654, 'lr': 0.008698171465099503, 'weight_decay': 0.00017171963428280472, 'batch_size': 64} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 21:20:21,060] Trial 85 pruned. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.459920 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.11642496678569736, 'lr': 0.005079738235353199, 'weight_decay': 0.00028007026272535156, 'batch_size': 128} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 21:20:35,863] Trial 86 pruned. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.447103 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.14759474016350158, 'lr': 0.009867683548540415, 'weight_decay': 0.0003539531954940543, 'batch_size': 64} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 21:21:19,505] Trial 87 finished with value: 0.5393082296797388 and parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.13546148701172994, 'lr': 0.0069468501421974015, 'weight_decay': 0.00022685517637057858, 'batch_size': 128}. Best is trial 56 with value: 0.5644485264432356. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.539308 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.13546148701172994, 'lr': 0.0069468501421974015, 'weight_decay': 0.00022685517637057858, 'batch_size': 128} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 21:23:47,408] Trial 88 finished with value: 0.5539615439342908 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.15432134461796648, 'lr': 0.004368718128055782, 'weight_decay': 0.0005933406319756243, 'batch_size': 32}. Best is trial 56 with value: 0.5644485264432356. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.553962 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.15432134461796648, 'lr': 0.004368718128055782, 'weight_decay': 0.0005933406319756243, 'batch_size': 32} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) -[I 2025-12-28 21:25:09,687] Trial 89 pruned. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.574559 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.1557769379230941, 'lr': 0.0036440132761718894, 'weight_decay': 0.0005584553456636461, 'batch_size': 32} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) -[I 2025-12-28 21:26:38,006] Trial 90 pruned. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.571205 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.14107327296414077, 'lr': 0.0043826980063356395, 'weight_decay': 0.0006949914528162474, 'batch_size': 32} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 21:27:00,637] Trial 91 pruned. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.414397 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.12764769254487093, 'lr': 0.007033835266080436, 'weight_decay': 0.00010035222447790803, 'batch_size': 32} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 21:27:23,243] Trial 92 pruned. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.471710 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.12149022163376003, 'lr': 0.005735976033430046, 'weight_decay': 0.000332401136807744, 'batch_size': 32} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 21:28:33,882] Trial 93 pruned. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.527356 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.16088968004904097, 'lr': 0.008117725108960324, 'weight_decay': 0.0001606794604031563, 'batch_size': 64} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 21:28:42,748] Trial 94 pruned. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.459903 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15309450190472612, 'lr': 0.005485578686672786, 'weight_decay': 0.00042030885444263355, 'batch_size': 128} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 21:29:10,087] Trial 95 pruned. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.411533 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.14445497223448572, 'lr': 0.006990923413303166, 'weight_decay': 0.0007674298137507321, 'batch_size': 32} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) -[I 2025-12-28 21:29:44,629] Trial 96 pruned. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.566069 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.10954693544660513, 'lr': 0.008405647449623596, 'weight_decay': 0.0002791517339263404, 'batch_size': 128} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 21:30:15,412] Trial 97 pruned. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.472309 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.16622570817251361, 'lr': 0.00981338571024433, 'weight_decay': 0.0005828781242231709, 'batch_size': 64} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 21:30:29,267] Trial 98 pruned. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.468301 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.13338427187704002, 'lr': 0.005102294337218716, 'weight_decay': 0.00018592584892562257, 'batch_size': 128} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 21:31:41,689] Trial 99 finished with value: 0.5398996117646979 and parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.11444183072574908, 'lr': 0.0041157111018092895, 'weight_decay': 0.0010113978851207346, 'batch_size': 64}. Best is trial 56 with value: 0.5644485264432356. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.539900 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.11444183072574908, 'lr': 0.0041157111018092895, 'weight_decay': 0.0010113978851207346, 'batch_size': 64} - Best Value (CSI): 0.564449 - Best Trial: 56 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.5644 -Best Hyperparameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.16846849111235224, 'lr': 0.007871644587352598, 'weight_decay': 0.0005399258093557023, 'batch_size': 128} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.5036 - - 최종 CSI: 0.5399 - - 최고 CSI: 0.5746 - - 최저 CSI: 0.2633 - - 평균 CSI: 0.5004 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/deepgbm_ctgan10000_incheon_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 27, Best CSI: 0.5119 - Fold 1 학습 완료 (검증 CSI: 0.5119) -Fold 2 학습 중... - Early stopping at epoch 24, Best CSI: 0.5883 - Fold 2 학습 완료 (검증 CSI: 0.5883) -Fold 3 학습 중... - Early stopping at epoch 24, Best CSI: 0.5554 - Fold 3 학습 완료 (검증 CSI: 0.5554) - -모든 모델 저장 완료: ../save_model/deepgbm_optima/deepgbm_ctgan10000_incheon.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/deepgbm_optima/scaler/deepgbm_ctgan10000_incheon_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: ../save_model/deepgbm_optima/deepgbm_ctgan10000_incheon.pkl - -✓ 완료: deepgbm_ctgan10000/deepgbm_ctgan10000_incheon.py (소요 시간: 3893초) - ----------------------------------------- -실행 중: deepgbm_ctgan10000/deepgbm_ctgan10000_seoul.py -시작 시간: 2025-12-28 21:32:25 ----------------------------------------- -[I 2025-12-28 21:32:26,789] A new study created in memory with name: no-name-fdf0f58a-0d25-4898-b54e-1a0ac9760424 - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-28 21:36:02,943] Trial 0 finished with value: 0.4703025378092154 and parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.22117231179668684, 'lr': 2.2371365327741396e-05, 'weight_decay': 0.005447814868861018, 'batch_size': 32}. Best is trial 0 with value: 0.4703025378092154. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.470303 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.22117231179668684, 'lr': 2.2371365327741396e-05, 'weight_decay': 0.005447814868861018, 'batch_size': 32} - Best Value (CSI): 0.470303 - Best Trial: 0 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.22117231179668684, 'lr': 2.2371365327741396e-05, 'weight_decay': 0.005447814868861018, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-28 21:36:39,726] Trial 1 finished with value: 0.4782679190593994 and parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.1177310104629107, 'lr': 0.00015740664660188913, 'weight_decay': 0.01044268185401063, 'batch_size': 256}. Best is trial 1 with value: 0.4782679190593994. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.478268 - Parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.1177310104629107, 'lr': 0.00015740664660188913, 'weight_decay': 0.01044268185401063, 'batch_size': 256} - Best Value (CSI): 0.478268 - Best Trial: 1 - Best Parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.1177310104629107, 'lr': 0.00015740664660188913, 'weight_decay': 0.01044268185401063, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-28 21:37:28,118] Trial 2 finished with value: 0.5455396057210445 and parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.35307077202667325, 'lr': 0.005328589578343898, 'weight_decay': 0.0038473436240858876, 'batch_size': 128}. Best is trial 2 with value: 0.5455396057210445. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.545540 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.35307077202667325, 'lr': 0.005328589578343898, 'weight_decay': 0.0038473436240858876, 'batch_size': 128} - Best Value (CSI): 0.545540 - Best Trial: 2 - Best Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.35307077202667325, 'lr': 0.005328589578343898, 'weight_decay': 0.0038473436240858876, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-28 21:40:22,948] Trial 3 finished with value: 0.5620475905480543 and parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32}. Best is trial 3 with value: 0.5620475905480543. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.562048 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-28 21:41:10,277] Trial 4 finished with value: 0.5052463257058484 and parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3233917068741079, 'lr': 0.0012901844148085352, 'weight_decay': 0.00010791010452093161, 'batch_size': 128}. Best is trial 3 with value: 0.5620475905480543. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.505246 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3233917068741079, 'lr': 0.0012901844148085352, 'weight_decay': 0.00010791010452093161, 'batch_size': 128} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 21:41:21,330] Trial 5 pruned. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.386049 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.24338330110286954, 'lr': 0.0002981406736392642, 'weight_decay': 0.0435257538860857, 'batch_size': 64} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 21:41:27,208] Trial 6 pruned. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.399249 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.32779218232717294, 'lr': 0.0015166860628446337, 'weight_decay': 0.0005085687904213193, 'batch_size': 256} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 21:41:34,832] Trial 7 pruned. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.365982 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.3684422721230156, 'lr': 2.9109909960689975e-05, 'weight_decay': 0.012069255334381067, 'batch_size': 128} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 21:42:00,225] Trial 8 pruned. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.387931 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.16933043492079625, 'lr': 0.00012546124259549425, 'weight_decay': 0.017151725646977315, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 21:42:06,172] Trial 9 pruned. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.397704 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.23303260737828432, 'lr': 0.0014137451570338272, 'weight_decay': 0.04853179100400946, 'batch_size': 256} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-28 21:44:27,672] Trial 10 finished with value: 0.5326173924885841 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.2863503544985895, 'lr': 0.007321720573037164, 'weight_decay': 0.000977185408305386, 'batch_size': 32}. Best is trial 3 with value: 0.5620475905480543. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.532617 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.2863503544985895, 'lr': 0.007321720573037164, 'weight_decay': 0.000977185408305386, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 21:44:43,884] Trial 11 pruned. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.456771 - Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3890093922021857, 'lr': 0.006150209277111024, 'weight_decay': 0.0016888917996709712, 'batch_size': 128} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 21:45:10,811] Trial 12 pruned. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.460000 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2876718339564919, 'lr': 0.009433469713448798, 'weight_decay': 0.003169850483575423, 'batch_size': 64} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 21:45:21,685] Trial 13 pruned. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.443243 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.39496107079554615, 'lr': 0.002902326843206018, 'weight_decay': 0.0004136177088423997, 'batch_size': 128} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-28 21:47:49,852] Trial 14 finished with value: 0.5530388425925558 and parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.1942780607301383, 'lr': 0.0031231786739227144, 'weight_decay': 0.002264776124164396, 'batch_size': 32}. Best is trial 3 with value: 0.5620475905480543. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.553039 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.1942780607301383, 'lr': 0.0031231786739227144, 'weight_decay': 0.002264776124164396, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 21:48:11,027] Trial 15 pruned. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.394036 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.19193895709295405, 'lr': 0.0007569776979325284, 'weight_decay': 0.001305061027099884, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 21:49:11,843] Trial 16 pruned. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.427252 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.17694472428740324, 'lr': 0.0028799138178403293, 'weight_decay': 0.0001514470608266138, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 21:49:33,070] Trial 17 pruned. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.417489 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.27957823003342624, 'lr': 0.0006083444395893277, 'weight_decay': 0.00029526595315422586, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 21:50:23,410] Trial 18 pruned. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.431526 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.2003002380151626, 'lr': 0.0026517474434389087, 'weight_decay': 0.0008709722825504827, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 21:51:18,967] Trial 19 pruned. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.448889 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.1477948472804278, 'lr': 0.003449391306108875, 'weight_decay': 0.0020365913228150433, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 21:51:31,541] Trial 20 pruned. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.316417 - Parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.21741538505954397, 'lr': 0.008670832340904256, 'weight_decay': 0.00019763252947298753, 'batch_size': 64} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 21:51:37,596] Trial 21 pruned. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.438844 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.25574433936427143, 'lr': 0.004265850964536, 'weight_decay': 0.0035315398616997083, 'batch_size': 128} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 21:51:52,882] Trial 22 pruned. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.438972 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2635805814605773, 'lr': 0.005716008854633256, 'weight_decay': 0.0006751277630046174, 'batch_size': 128} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 21:52:19,193] Trial 23 pruned. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.451635 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.21152017185820635, 'lr': 0.0018433456093989839, 'weight_decay': 0.001973883298781508, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-28 21:54:29,927] Trial 24 finished with value: 0.5306565524756649 and parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.24836995128034023, 'lr': 0.004581375265898128, 'weight_decay': 0.0002689930299836126, 'batch_size': 32}. Best is trial 3 with value: 0.5620475905480543. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.530657 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.24836995128034023, 'lr': 0.004581375265898128, 'weight_decay': 0.0002689930299836126, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 21:54:46,589] Trial 25 pruned. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.437765 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.22757168259469565, 'lr': 0.009965681124996623, 'weight_decay': 0.0006037254364241354, 'batch_size': 128} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 21:55:18,285] Trial 26 pruned. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.447018 - Parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3124985979081019, 'lr': 0.00482736172287, 'weight_decay': 0.005486498588848869, 'batch_size': 64} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 21:55:23,118] Trial 27 pruned. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.394050 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3572839024193176, 'lr': 0.002210041760749496, 'weight_decay': 0.0012452870980601593, 'batch_size': 256} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 21:55:48,638] Trial 28 pruned. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.430894 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2712046572294762, 'lr': 0.0009246527103353629, 'weight_decay': 0.0008927080053397817, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-28 21:57:31,122] Trial 29 pruned. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.503226 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.23353177648878198, 'lr': 0.002265255415792327, 'weight_decay': 0.003951447423395857, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 21:57:41,551] Trial 30 pruned. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.439847 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3024163989002844, 'lr': 0.003968212512522471, 'weight_decay': 0.0021836364287323557, 'batch_size': 128} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 21:58:16,783] Trial 31 pruned. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.445091 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.28943846539936097, 'lr': 0.0065329781776994845, 'weight_decay': 0.0010084125741559639, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 21:59:17,690] Trial 32 pruned. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.457122 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.342068082982951, 'lr': 0.0061860776465791625, 'weight_decay': 0.0056176475067692775, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:00:18,523] Trial 33 pruned. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.448042 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.2631292658658078, 'lr': 0.003373264901847713, 'weight_decay': 0.00042153133749043236, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:01:14,022] Trial 34 pruned. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.438860 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.30134311278438647, 'lr': 0.0017789818378242674, 'weight_decay': 0.0012865682141716096, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:01:18,613] Trial 35 pruned. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.409594 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.32753555712545135, 'lr': 0.0010856137660270359, 'weight_decay': 0.0007675629090892598, 'batch_size': 256} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:01:38,586] Trial 36 pruned. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.372708 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.24507992637407922, 'lr': 0.007930549535741033, 'weight_decay': 0.002704755854775388, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:01:45,820] Trial 37 pruned. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.398058 - Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.27612305161537387, 'lr': 0.004279145876258088, 'weight_decay': 0.006957355250702544, 'batch_size': 128} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:01:58,927] Trial 38 pruned. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.437899 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.3411125002404894, 'lr': 0.0013021735711344013, 'weight_decay': 0.0006000926524871888, 'batch_size': 64} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:02:04,534] Trial 39 pruned. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.438974 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.31620778399144445, 'lr': 0.006314552074196195, 'weight_decay': 0.0016021867751390463, 'batch_size': 256} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:02:21,371] Trial 40 pruned. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.433060 - Parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.37284411785517035, 'lr': 0.002125472389231902, 'weight_decay': 0.0026613109838984727, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:03:01,430] Trial 41 pruned. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.444934 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.24411461733570816, 'lr': 0.004619659234152188, 'weight_decay': 0.000330874073539053, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:03:41,314] Trial 42 pruned. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.438241 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.25404620178690934, 'lr': 0.0034909630080711277, 'weight_decay': 0.0002635397557913019, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:03:55,684] Trial 43 pruned. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.322434 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.23653372289701638, 'lr': 0.009757009730980513, 'weight_decay': 0.00011268254240914734, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-28 22:06:21,218] Trial 44 finished with value: 0.5603929479636361 and parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.21886426127489722, 'lr': 0.0052312368820888605, 'weight_decay': 0.0005188908329885096, 'batch_size': 32}. Best is trial 3 with value: 0.5620475905480543. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.560393 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.21886426127489722, 'lr': 0.0052312368820888605, 'weight_decay': 0.0005188908329885096, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:06:28,139] Trial 45 pruned. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.419118 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.22101976267114848, 'lr': 0.006454106084272818, 'weight_decay': 0.0005569254543235998, 'batch_size': 128} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:06:47,297] Trial 46 pruned. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.436610 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.20544510579160744, 'lr': 0.00271693202841955, 'weight_decay': 0.0010127879107889736, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:07:37,770] Trial 47 pruned. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.446512 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.181442220699703, 'lr': 0.0014255881393654367, 'weight_decay': 0.0016481262051730098, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:08:06,008] Trial 48 pruned. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.428091 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.1979998169543779, 'lr': 0.007623543771169269, 'weight_decay': 0.00051987717429119, 'batch_size': 64} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:08:12,630] Trial 49 pruned. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.419332 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.22216805293532454, 'lr': 0.0031635558796524895, 'weight_decay': 0.0004524733516007845, 'batch_size': 128} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:08:17,782] Trial 50 pruned. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.382767 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.15707112203333234, 'lr': 0.00056361375632203, 'weight_decay': 0.004094238990782842, 'batch_size': 256} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:08:32,009] Trial 51 pruned. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.368421 - Parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.25481513070975503, 'lr': 0.005400753686732274, 'weight_decay': 0.00021852620873257008, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:09:17,381] Trial 52 pruned. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.450622 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.21396035456604992, 'lr': 0.0049504546500309735, 'weight_decay': 0.00035869284651317615, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-28 22:11:29,166] Trial 53 finished with value: 0.5503224344986251 and parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.24354084836010303, 'lr': 0.0037886796385869113, 'weight_decay': 0.00025918523440955524, 'batch_size': 32}. Best is trial 3 with value: 0.5620475905480543. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.550322 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.24354084836010303, 'lr': 0.0037886796385869113, 'weight_decay': 0.00025918523440955524, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-28 22:13:32,375] Trial 54 finished with value: 0.5481211899784894 and parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2349153945283539, 'lr': 0.002642755066461728, 'weight_decay': 0.0007479154284589059, 'batch_size': 32}. Best is trial 3 with value: 0.5620475905480543. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.548121 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2349153945283539, 'lr': 0.002642755066461728, 'weight_decay': 0.0007479154284589059, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-28 22:15:44,400] Trial 55 finished with value: 0.5413516107549424 and parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2331075105545691, 'lr': 0.0026779308719154186, 'weight_decay': 0.0003764709158128595, 'batch_size': 32}. Best is trial 3 with value: 0.5620475905480543. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.541352 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2331075105545691, 'lr': 0.0026779308719154186, 'weight_decay': 0.0003764709158128595, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:16:07,401] Trial 56 pruned. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.446388 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.20802773442935416, 'lr': 0.0016529522347821521, 'weight_decay': 0.0001796590299176935, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:16:33,794] Trial 57 pruned. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.457496 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.1908681845263833, 'lr': 0.003639186447670738, 'weight_decay': 0.000780191324017324, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:16:43,572] Trial 58 pruned. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.430425 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.2256412623268874, 'lr': 0.002295320064472111, 'weight_decay': 0.00024553804314374954, 'batch_size': 128} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:17:23,631] Trial 59 pruned. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.450450 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.23799836602570099, 'lr': 0.0029148146861254476, 'weight_decay': 0.00031298615727994006, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:17:49,595] Trial 60 pruned. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.452681 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2674596935208798, 'lr': 0.0018627412451897927, 'weight_decay': 0.00047066737020138466, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-28 22:19:47,265] Trial 61 finished with value: 0.5562218245470287 and parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23170266377001675, 'lr': 0.0024849146998217842, 'weight_decay': 0.00036656655057741686, 'batch_size': 32}. Best is trial 3 with value: 0.5620475905480543. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.556222 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23170266377001675, 'lr': 0.0024849146998217842, 'weight_decay': 0.00036656655057741686, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:20:32,252] Trial 62 pruned. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.437922 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.21445980842694135, 'lr': 0.003966491852749469, 'weight_decay': 0.0006805350097843359, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:20:55,382] Trial 63 pruned. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.433155 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.22663616047802956, 'lr': 0.007627647166894666, 'weight_decay': 0.0001719158921806444, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:21:24,841] Trial 64 pruned. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.467513 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.24174369152426978, 'lr': 0.004813772622652762, 'weight_decay': 0.0003922058078536395, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:21:35,755] Trial 65 pruned. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.436865 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.252444347772953, 'lr': 0.0025989824596362524, 'weight_decay': 0.0002831566072012636, 'batch_size': 64} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:22:20,726] Trial 66 pruned. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.470183 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2612588301700684, 'lr': 0.0054547042503612, 'weight_decay': 0.000601168068237752, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:22:26,851] Trial 67 pruned. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.418754 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.19953239839761286, 'lr': 0.003449357478300865, 'weight_decay': 0.0002182200000717981, 'batch_size': 128} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:22:53,004] Trial 68 pruned. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.438822 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.22968910338097914, 'lr': 0.002017260853687685, 'weight_decay': 0.0004906274793717003, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:23:14,383] Trial 69 pruned. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.440933 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.27747113112358435, 'lr': 0.0011358865805161363, 'weight_decay': 0.0010501968223815147, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:23:19,899] Trial 70 pruned. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.420708 - Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.24710700222277662, 'lr': 0.0014776813260005683, 'weight_decay': 0.00030929117850830493, 'batch_size': 256} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-28 22:25:18,452] Trial 71 finished with value: 0.5527063019876816 and parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2374883615748952, 'lr': 0.0025648369617845, 'weight_decay': 0.0003729523751117234, 'batch_size': 32}. Best is trial 3 with value: 0.5620475905480543. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.552706 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2374883615748952, 'lr': 0.0025648369617845, 'weight_decay': 0.0003729523751117234, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:26:03,437] Trial 72 pruned. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.448378 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2177769181899023, 'lr': 0.003906992113028214, 'weight_decay': 0.0003999065295626568, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:26:48,183] Trial 73 pruned. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.446442 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23521398070413804, 'lr': 0.0030414575905052007, 'weight_decay': 0.0007245138185713923, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:27:33,234] Trial 74 pruned. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.449376 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2586058636179824, 'lr': 0.005457460371337615, 'weight_decay': 0.0002337834582572608, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:27:56,145] Trial 75 pruned. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.470772 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.24330207022925252, 'lr': 0.0023681128889006696, 'weight_decay': 0.0003501210630469124, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:28:02,922] Trial 76 pruned. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.420220 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.2235148545508787, 'lr': 0.001653585936561436, 'weight_decay': 0.00015173214498392476, 'batch_size': 128} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:28:32,065] Trial 77 pruned. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.463933 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.20659535094166062, 'lr': 0.004357256519075715, 'weight_decay': 0.00079925933422267, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:29:11,556] Trial 78 pruned. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.462500 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.25003388648291147, 'lr': 0.00729989555120143, 'weight_decay': 0.0005366043616712213, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:29:23,490] Trial 79 pruned. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.447785 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.23313724887706339, 'lr': 0.002044433233223082, 'weight_decay': 0.0002836600314209355, 'batch_size': 64} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:29:42,535] Trial 80 pruned. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.422862 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.26411735130763625, 'lr': 0.0033709147987772176, 'weight_decay': 0.0013643076702286668, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-28 22:31:49,109] Trial 81 finished with value: 0.5558661836412612 and parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23646998988200052, 'lr': 0.002512206490926576, 'weight_decay': 0.0004476731977099644, 'batch_size': 32}. Best is trial 3 with value: 0.5620475905480543. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.555866 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23646998988200052, 'lr': 0.002512206490926576, 'weight_decay': 0.0004476731977099644, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:32:08,252] Trial 82 pruned. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.412961 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23936683299117223, 'lr': 0.0025507477397768495, 'weight_decay': 0.0005004234220988308, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-28 22:34:45,425] Trial 83 finished with value: 0.553362968787864 and parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.21468391172642293, 'lr': 0.0038842305407804493, 'weight_decay': 0.00044073421328091607, 'batch_size': 32}. Best is trial 3 with value: 0.5620475905480543. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.553363 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.21468391172642293, 'lr': 0.0038842305407804493, 'weight_decay': 0.00044073421328091607, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:35:11,757] Trial 84 pruned. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.471299 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.21728173922860716, 'lr': 0.0029758273856928447, 'weight_decay': 0.00041455333169100703, 'batch_size': 32} - Best Value (CSI): 0.562048 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.24378639566603055, 'lr': 0.0032011721381719196, 'weight_decay': 0.0003798946802423518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-28 22:37:12,405] Trial 85 finished with value: 0.5652632820174084 and parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2113225708109025, 'lr': 0.0038029027900849553, 'weight_decay': 0.0005824342055366228, 'batch_size': 32}. Best is trial 85 with value: 0.5652632820174084. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.565263 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2113225708109025, 'lr': 0.0038029027900849553, 'weight_decay': 0.0005824342055366228, 'batch_size': 32} - Best Value (CSI): 0.565263 - Best Trial: 85 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2113225708109025, 'lr': 0.0038029027900849553, 'weight_decay': 0.0005824342055366228, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:37:31,378] Trial 86 pruned. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.446873 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.20915288466397505, 'lr': 0.004004039591117556, 'weight_decay': 0.0004499394315111278, 'batch_size': 32} - Best Value (CSI): 0.565263 - Best Trial: 85 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2113225708109025, 'lr': 0.0038029027900849553, 'weight_decay': 0.0005824342055366228, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:37:50,427] Trial 87 pruned. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.398437 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.1915000777145732, 'lr': 0.0047043310019172745, 'weight_decay': 0.0006183023021636469, 'batch_size': 32} - Best Value (CSI): 0.565263 - Best Trial: 85 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2113225708109025, 'lr': 0.0038029027900849553, 'weight_decay': 0.0005824342055366228, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:38:40,768] Trial 88 pruned. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.449819 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.22704103323465272, 'lr': 0.006077462590548687, 'weight_decay': 0.0003236915611164814, 'batch_size': 32} - Best Value (CSI): 0.565263 - Best Trial: 85 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2113225708109025, 'lr': 0.0038029027900849553, 'weight_decay': 0.0005824342055366228, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:38:59,962] Trial 89 pruned. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.443966 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.2185043404150587, 'lr': 0.001972563928737882, 'weight_decay': 0.00027015839794317174, 'batch_size': 32} - Best Value (CSI): 0.565263 - Best Trial: 85 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2113225708109025, 'lr': 0.0038029027900849553, 'weight_decay': 0.0005824342055366228, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-28 22:41:03,497] Trial 90 pruned. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.549296 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.20066925110093495, 'lr': 0.0037434173209479806, 'weight_decay': 0.00019963838758493388, 'batch_size': 32} - Best Value (CSI): 0.565263 - Best Trial: 85 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2113225708109025, 'lr': 0.0038029027900849553, 'weight_decay': 0.0005824342055366228, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:41:48,745] Trial 91 pruned. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.443452 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2294606756105856, 'lr': 0.0024161714969528976, 'weight_decay': 0.0006533549791388401, 'batch_size': 32} - Best Value (CSI): 0.565263 - Best Trial: 85 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2113225708109025, 'lr': 0.0038029027900849553, 'weight_decay': 0.0005824342055366228, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-28 22:44:00,733] Trial 92 finished with value: 0.5579868620185066 and parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2468107137142098, 'lr': 0.0030513613777232436, 'weight_decay': 0.0008727125163609398, 'batch_size': 32}. Best is trial 85 with value: 0.5652632820174084. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.557987 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2468107137142098, 'lr': 0.0030513613777232436, 'weight_decay': 0.0008727125163609398, 'batch_size': 32} - Best Value (CSI): 0.565263 - Best Trial: 85 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2113225708109025, 'lr': 0.0038029027900849553, 'weight_decay': 0.0005824342055366228, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:44:19,749] Trial 93 pruned. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.451812 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.24442773199082987, 'lr': 0.0034409839901405476, 'weight_decay': 0.0003670916633367426, 'batch_size': 32} - Best Value (CSI): 0.565263 - Best Trial: 85 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2113225708109025, 'lr': 0.0038029027900849553, 'weight_decay': 0.0005824342055366228, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:45:03,138] Trial 94 pruned. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.465558 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2563096279676195, 'lr': 0.0030681168612820696, 'weight_decay': 0.0005158527566906674, 'batch_size': 32} - Best Value (CSI): 0.565263 - Best Trial: 85 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2113225708109025, 'lr': 0.0038029027900849553, 'weight_decay': 0.0005824342055366228, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:45:46,485] Trial 95 pruned. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.449926 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.24852356304335238, 'lr': 0.004178472892000451, 'weight_decay': 0.0009594083516398163, 'batch_size': 32} - Best Value (CSI): 0.565263 - Best Trial: 85 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2113225708109025, 'lr': 0.0038029027900849553, 'weight_decay': 0.0005824342055366228, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:46:30,074] Trial 96 pruned. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.467269 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.21342476040806263, 'lr': 0.0049975412484920476, 'weight_decay': 0.00042266624033273384, 'batch_size': 32} - Best Value (CSI): 0.565263 - Best Trial: 85 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2113225708109025, 'lr': 0.0038029027900849553, 'weight_decay': 0.0005824342055366228, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:46:35,517] Trial 97 pruned. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.389715 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.22121448769131613, 'lr': 0.001684079881540931, 'weight_decay': 0.0005730806650962919, 'batch_size': 256} - Best Value (CSI): 0.565263 - Best Trial: 85 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2113225708109025, 'lr': 0.0038029027900849553, 'weight_decay': 0.0005824342055366228, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:46:56,796] Trial 98 pruned. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.336916 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.24146942128955776, 'lr': 0.008925330383976348, 'weight_decay': 0.0003498236440129695, 'batch_size': 32} - Best Value (CSI): 0.565263 - Best Trial: 85 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2113225708109025, 'lr': 0.0038029027900849553, 'weight_decay': 0.0005824342055366228, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-28 22:47:22,929] Trial 99 pruned. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.459877 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.21168673025532303, 'lr': 0.002265459607689244, 'weight_decay': 0.0006478976303694914, 'batch_size': 32} - Best Value (CSI): 0.565263 - Best Trial: 85 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2113225708109025, 'lr': 0.0038029027900849553, 'weight_decay': 0.0005824342055366228, 'batch_size': 32} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.5653 -Best Hyperparameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2113225708109025, 'lr': 0.0038029027900849553, 'weight_decay': 0.0005824342055366228, 'batch_size': 32} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.4703 - - 최종 CSI: 0.4599 - - 최고 CSI: 0.5653 - - 최저 CSI: 0.3164 - - 평균 CSI: 0.4514 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/deepgbm_ctgan10000_seoul_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 30, Best CSI: 0.4693 - Fold 1 학습 완료 (검증 CSI: 0.4693) -Fold 2 학습 중... - Early stopping at epoch 36, Best CSI: 0.5956 - Fold 2 학습 완료 (검증 CSI: 0.5956) -Fold 3 학습 중... - Early stopping at epoch 33, Best CSI: 0.5764 - Fold 3 학습 완료 (검증 CSI: 0.5764) - -모든 모델 저장 완료: ../save_model/deepgbm_optima/deepgbm_ctgan10000_seoul.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/deepgbm_optima/scaler/deepgbm_ctgan10000_seoul_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: ../save_model/deepgbm_optima/deepgbm_ctgan10000_seoul.pkl - -✓ 완료: deepgbm_ctgan10000/deepgbm_ctgan10000_seoul.py (소요 시간: 4642초) - -========================================== -DeepGBM CTGAN10000 파일 실행 완료 -종료 시간: 2025-12-28 22:49:47 -총 소요 시간: 10시간 13분 45초 -성공: 6개 -실패: 0개 -========================================== diff --git a/Analysis_code/5.optima/run_bash/deepgbm/deepgbm_pure.log b/Analysis_code/5.optima/run_bash/deepgbm/deepgbm_pure.log deleted file mode 100644 index 57b11b8e7a3a5448265ee4e2ba58e9c01777a05a..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/run_bash/deepgbm/deepgbm_pure.log +++ /dev/null @@ -1,8278 +0,0 @@ -nohup: ignoring input -/bin/bash: /opt/conda/lib/libtinfo.so.6: no version information available (required by /bin/bash) -========================================== -DeepGBM Pure 파일 실행 시작 -시작 시간: 2025-12-25 07:12:47 -GPU: 1번 (CUDA_VISIBLE_DEVICES=1) -========================================== - ----------------------------------------- -실행 중: deepgbm_pure/deepgbm_pure_busan.py -시작 시간: 2025-12-25 07:12:47 ----------------------------------------- -[I 2025-12-25 07:12:48,794] A new study created in memory with name: no-name-95e65c94-322c-4f2d-ab51-de244853e3ce - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 07:15:01,396] Trial 0 finished with value: 0.29823525510094706 and parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.30130697401793793, 'lr': 1.0944997248144388e-05, 'weight_decay': 0.030782514168786284, 'batch_size': 64}. Best is trial 0 with value: 0.29823525510094706. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.298235 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.30130697401793793, 'lr': 1.0944997248144388e-05, 'weight_decay': 0.030782514168786284, 'batch_size': 64} - Best Value (CSI): 0.298235 - Best Trial: 0 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.30130697401793793, 'lr': 1.0944997248144388e-05, 'weight_decay': 0.030782514168786284, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 07:16:16,491] Trial 1 finished with value: 0.42061306891331257 and parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.15187919006284847, 'lr': 0.003210388356330597, 'weight_decay': 0.002336535148045246, 'batch_size': 64}. Best is trial 1 with value: 0.42061306891331257. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.420613 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.15187919006284847, 'lr': 0.003210388356330597, 'weight_decay': 0.002336535148045246, 'batch_size': 64} - Best Value (CSI): 0.420613 - Best Trial: 1 - Best Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.15187919006284847, 'lr': 0.003210388356330597, 'weight_decay': 0.002336535148045246, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 07:18:15,870] Trial 2 finished with value: 0.34862068935744994 and parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.15697462255773653, 'lr': 4.0057889173887365e-05, 'weight_decay': 0.004669152539176615, 'batch_size': 32}. Best is trial 1 with value: 0.42061306891331257. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.348621 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.15697462255773653, 'lr': 4.0057889173887365e-05, 'weight_decay': 0.004669152539176615, 'batch_size': 32} - Best Value (CSI): 0.420613 - Best Trial: 1 - Best Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.15187919006284847, 'lr': 0.003210388356330597, 'weight_decay': 0.002336535148045246, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 07:18:42,872] Trial 3 finished with value: 0.39905664024501797 and parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.38413306863671703, 'lr': 0.0006927086413115795, 'weight_decay': 0.00016837945747428436, 'batch_size': 256}. Best is trial 1 with value: 0.42061306891331257. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.399057 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.38413306863671703, 'lr': 0.0006927086413115795, 'weight_decay': 0.00016837945747428436, 'batch_size': 256} - Best Value (CSI): 0.420613 - Best Trial: 1 - Best Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.15187919006284847, 'lr': 0.003210388356330597, 'weight_decay': 0.002336535148045246, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 07:19:55,490] Trial 4 finished with value: 0.4168004802672301 and parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.18913803390045314, 'lr': 0.004511146584470227, 'weight_decay': 0.012890324961972215, 'batch_size': 32}. Best is trial 1 with value: 0.42061306891331257. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.416800 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.18913803390045314, 'lr': 0.004511146584470227, 'weight_decay': 0.012890324961972215, 'batch_size': 32} - Best Value (CSI): 0.420613 - Best Trial: 1 - Best Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.15187919006284847, 'lr': 0.003210388356330597, 'weight_decay': 0.002336535148045246, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 07:21:14,528] Trial 5 finished with value: 0.43330593175484283 and parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.19671038709067606, 'lr': 0.004234303420399854, 'weight_decay': 0.07298535228610625, 'batch_size': 64}. Best is trial 5 with value: 0.43330593175484283. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.433306 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.19671038709067606, 'lr': 0.004234303420399854, 'weight_decay': 0.07298535228610625, 'batch_size': 64} - Best Value (CSI): 0.433306 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.19671038709067606, 'lr': 0.004234303420399854, 'weight_decay': 0.07298535228610625, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-25 07:21:18,803] Trial 6 pruned. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.308386 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3588699817214325, 'lr': 3.361443845491422e-05, 'weight_decay': 0.041989233308419714, 'batch_size': 128} - Best Value (CSI): 0.433306 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.19671038709067606, 'lr': 0.004234303420399854, 'weight_decay': 0.07298535228610625, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 07:22:01,361] Trial 7 finished with value: 0.41056958685699313 and parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.29942765890370904, 'lr': 0.0019327979142769224, 'weight_decay': 0.00019783714338179696, 'batch_size': 128}. Best is trial 5 with value: 0.43330593175484283. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.410570 - Parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.29942765890370904, 'lr': 0.0019327979142769224, 'weight_decay': 0.00019783714338179696, 'batch_size': 128} - Best Value (CSI): 0.433306 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.19671038709067606, 'lr': 0.004234303420399854, 'weight_decay': 0.07298535228610625, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-25 07:22:07,347] Trial 8 pruned. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.399317 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.3583316574144909, 'lr': 0.00026682845093796713, 'weight_decay': 0.0004675521405400373, 'batch_size': 128} - Best Value (CSI): 0.433306 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.19671038709067606, 'lr': 0.004234303420399854, 'weight_decay': 0.07298535228610625, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 07:22:27,872] Trial 9 finished with value: 0.40626728893942343 and parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.32023100886307554, 'lr': 0.0013911041450717062, 'weight_decay': 0.002498688356169491, 'batch_size': 256}. Best is trial 5 with value: 0.43330593175484283. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.406267 - Parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.32023100886307554, 'lr': 0.0013911041450717062, 'weight_decay': 0.002498688356169491, 'batch_size': 256} - Best Value (CSI): 0.433306 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.19671038709067606, 'lr': 0.004234303420399854, 'weight_decay': 0.07298535228610625, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 07:23:36,546] Trial 10 finished with value: 0.40934490561413533 and parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.10294883514616024, 'lr': 0.007520000390977766, 'weight_decay': 0.04316434639035447, 'batch_size': 64}. Best is trial 5 with value: 0.43330593175484283. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.409345 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.10294883514616024, 'lr': 0.007520000390977766, 'weight_decay': 0.04316434639035447, 'batch_size': 64} - Best Value (CSI): 0.433306 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.19671038709067606, 'lr': 0.004234303420399854, 'weight_decay': 0.07298535228610625, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 07:24:41,717] Trial 11 finished with value: 0.3988392153092462 and parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.21643846910822256, 'lr': 0.0070327157740486404, 'weight_decay': 0.08793673670711175, 'batch_size': 64}. Best is trial 5 with value: 0.43330593175484283. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.398839 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.21643846910822256, 'lr': 0.0070327157740486404, 'weight_decay': 0.08793673670711175, 'batch_size': 64} - Best Value (CSI): 0.433306 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.19671038709067606, 'lr': 0.004234303420399854, 'weight_decay': 0.07298535228610625, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 07:25:57,590] Trial 12 finished with value: 0.42089110545175606 and parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.23662066012800737, 'lr': 0.002737004512202818, 'weight_decay': 0.0019476481398097234, 'batch_size': 64}. Best is trial 5 with value: 0.43330593175484283. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.420891 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.23662066012800737, 'lr': 0.002737004512202818, 'weight_decay': 0.0019476481398097234, 'batch_size': 64} - Best Value (CSI): 0.433306 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.19671038709067606, 'lr': 0.004234303420399854, 'weight_decay': 0.07298535228610625, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 07:27:00,678] Trial 13 finished with value: 0.38963699770043125 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.23167852507473857, 'lr': 0.009923336426151907, 'weight_decay': 0.008546648278843242, 'batch_size': 64}. Best is trial 5 with value: 0.43330593175484283. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.389637 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.23167852507473857, 'lr': 0.009923336426151907, 'weight_decay': 0.008546648278843242, 'batch_size': 64} - Best Value (CSI): 0.433306 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.19671038709067606, 'lr': 0.004234303420399854, 'weight_decay': 0.07298535228610625, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 07:28:04,475] Trial 14 finished with value: 0.4212009075531929 and parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.25117551573288077, 'lr': 0.0010514938787670016, 'weight_decay': 0.0008149923853038282, 'batch_size': 64}. Best is trial 5 with value: 0.43330593175484283. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.421201 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.25117551573288077, 'lr': 0.0010514938787670016, 'weight_decay': 0.0008149923853038282, 'batch_size': 64} - Best Value (CSI): 0.433306 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.19671038709067606, 'lr': 0.004234303420399854, 'weight_decay': 0.07298535228610625, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 07:29:22,467] Trial 15 finished with value: 0.4144640051136475 and parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.26862634739359853, 'lr': 0.0005341646472769822, 'weight_decay': 0.0009098710900940931, 'batch_size': 64}. Best is trial 5 with value: 0.43330593175484283. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.414464 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.26862634739359853, 'lr': 0.0005341646472769822, 'weight_decay': 0.0009098710900940931, 'batch_size': 64} - Best Value (CSI): 0.433306 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.19671038709067606, 'lr': 0.004234303420399854, 'weight_decay': 0.07298535228610625, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 07:30:40,412] Trial 16 finished with value: 0.42460414890675685 and parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.27626380202469797, 'lr': 0.0011787389195905855, 'weight_decay': 0.0009061973478158533, 'batch_size': 64}. Best is trial 5 with value: 0.43330593175484283. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.424604 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.27626380202469797, 'lr': 0.0011787389195905855, 'weight_decay': 0.0009061973478158533, 'batch_size': 64} - Best Value (CSI): 0.433306 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.19671038709067606, 'lr': 0.004234303420399854, 'weight_decay': 0.07298535228610625, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-25 07:30:43,264] Trial 17 pruned. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.394763 - Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2736666673701975, 'lr': 0.00037398720237395255, 'weight_decay': 0.010985730874969617, 'batch_size': 256} - Best Value (CSI): 0.433306 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.19671038709067606, 'lr': 0.004234303420399854, 'weight_decay': 0.07298535228610625, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 07:32:35,534] Trial 18 finished with value: 0.41783335629961976 and parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.2120976598901862, 'lr': 0.0018652484981811004, 'weight_decay': 0.003983522811201947, 'batch_size': 32}. Best is trial 5 with value: 0.43330593175484283. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.417833 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.2120976598901862, 'lr': 0.0018652484981811004, 'weight_decay': 0.003983522811201947, 'batch_size': 32} - Best Value (CSI): 0.433306 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.19671038709067606, 'lr': 0.004234303420399854, 'weight_decay': 0.07298535228610625, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 07:33:32,485] Trial 19 finished with value: 0.4042205250298421 and parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.19853621578542058, 'lr': 0.004082897975875579, 'weight_decay': 0.07466711529893352, 'batch_size': 64}. Best is trial 5 with value: 0.43330593175484283. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.404221 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.19853621578542058, 'lr': 0.004082897975875579, 'weight_decay': 0.07466711529893352, 'batch_size': 64} - Best Value (CSI): 0.433306 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.19671038709067606, 'lr': 0.004234303420399854, 'weight_decay': 0.07298535228610625, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 07:34:41,470] Trial 20 finished with value: 0.4295910732789183 and parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.2560425381661397, 'lr': 0.0009954497642888764, 'weight_decay': 0.020545726397665373, 'batch_size': 64}. Best is trial 5 with value: 0.43330593175484283. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.429591 - Parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.2560425381661397, 'lr': 0.0009954497642888764, 'weight_decay': 0.020545726397665373, 'batch_size': 64} - Best Value (CSI): 0.433306 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.19671038709067606, 'lr': 0.004234303420399854, 'weight_decay': 0.07298535228610625, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 07:35:57,228] Trial 21 finished with value: 0.41805867669986485 and parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.2606106226536055, 'lr': 0.0010814763395855175, 'weight_decay': 0.02069948231039989, 'batch_size': 64}. Best is trial 5 with value: 0.43330593175484283. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.418059 - Parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.2606106226536055, 'lr': 0.0010814763395855175, 'weight_decay': 0.02069948231039989, 'batch_size': 64} - Best Value (CSI): 0.433306 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.19671038709067606, 'lr': 0.004234303420399854, 'weight_decay': 0.07298535228610625, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 07:37:31,189] Trial 22 finished with value: 0.42611624487400607 and parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.2800629606447031, 'lr': 0.0007725613669697337, 'weight_decay': 0.08992747565675441, 'batch_size': 64}. Best is trial 5 with value: 0.43330593175484283. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.426116 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.2800629606447031, 'lr': 0.0007725613669697337, 'weight_decay': 0.08992747565675441, 'batch_size': 64} - Best Value (CSI): 0.433306 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.19671038709067606, 'lr': 0.004234303420399854, 'weight_decay': 0.07298535228610625, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 07:38:39,119] Trial 23 finished with value: 0.4153535246456032 and parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.2944586579239618, 'lr': 0.0002971486219855901, 'weight_decay': 0.08718583399633069, 'batch_size': 64}. Best is trial 5 with value: 0.43330593175484283. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.415354 - Parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.2944586579239618, 'lr': 0.0002971486219855901, 'weight_decay': 0.08718583399633069, 'batch_size': 64} - Best Value (CSI): 0.433306 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.19671038709067606, 'lr': 0.004234303420399854, 'weight_decay': 0.07298535228610625, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 07:40:16,225] Trial 24 finished with value: 0.43222467462978614 and parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.24377669698630552, 'lr': 0.0024548076202543937, 'weight_decay': 0.02444804846833798, 'batch_size': 64}. Best is trial 5 with value: 0.43330593175484283. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.432225 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.24377669698630552, 'lr': 0.0024548076202543937, 'weight_decay': 0.02444804846833798, 'batch_size': 64} - Best Value (CSI): 0.433306 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.19671038709067606, 'lr': 0.004234303420399854, 'weight_decay': 0.07298535228610625, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 07:41:34,995] Trial 25 finished with value: 0.4044945853578377 and parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.24855495112850662, 'lr': 0.0049686278459612045, 'weight_decay': 0.021688513710339346, 'batch_size': 64}. Best is trial 5 with value: 0.43330593175484283. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.404495 - Parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.24855495112850662, 'lr': 0.0049686278459612045, 'weight_decay': 0.021688513710339346, 'batch_size': 64} - Best Value (CSI): 0.433306 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.19671038709067606, 'lr': 0.004234303420399854, 'weight_decay': 0.07298535228610625, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 07:43:58,087] Trial 26 finished with value: 0.430320425502517 and parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.22889072227700327, 'lr': 0.0025163829444444087, 'weight_decay': 0.0412827176612248, 'batch_size': 32}. Best is trial 5 with value: 0.43330593175484283. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.430320 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.22889072227700327, 'lr': 0.0025163829444444087, 'weight_decay': 0.0412827176612248, 'batch_size': 32} - Best Value (CSI): 0.433306 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.19671038709067606, 'lr': 0.004234303420399854, 'weight_decay': 0.07298535228610625, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 07:45:58,791] Trial 27 finished with value: 0.4429286988285861 and parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.442929 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 07:47:35,223] Trial 28 finished with value: 0.3957449942405788 and parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.19223506681181798, 'lr': 0.005305778290776273, 'weight_decay': 0.05519144475138222, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.395745 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.19223506681181798, 'lr': 0.005305778290776273, 'weight_decay': 0.05519144475138222, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 07:49:00,034] Trial 29 finished with value: 0.4157058269745397 and parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.17383667595469454, 'lr': 0.002977002349445128, 'weight_decay': 0.02449497691429468, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.415706 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.17383667595469454, 'lr': 0.002977002349445128, 'weight_decay': 0.02449497691429468, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 07:51:17,361] Trial 30 finished with value: 0.43512888982941167 and parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.21314303984382058, 'lr': 0.0018332562289866418, 'weight_decay': 0.03678311019558235, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.435129 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.21314303984382058, 'lr': 0.0018332562289866418, 'weight_decay': 0.03678311019558235, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 07:53:22,169] Trial 31 finished with value: 0.4392284645967813 and parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.2176790159380544, 'lr': 0.002118370470644845, 'weight_decay': 0.03189682939222798, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.439228 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.2176790159380544, 'lr': 0.002118370470644845, 'weight_decay': 0.03189682939222798, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 07:55:53,941] Trial 32 finished with value: 0.4263005696740409 and parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.21665354348724894, 'lr': 0.0016816815366577312, 'weight_decay': 0.05251774252145229, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.426301 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.21665354348724894, 'lr': 0.0016816815366577312, 'weight_decay': 0.05251774252145229, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 07:57:57,758] Trial 33 finished with value: 0.4191332685322016 and parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.16859553912867448, 'lr': 0.003669431266552787, 'weight_decay': 0.03428190483638938, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.419133 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.16859553912867448, 'lr': 0.003669431266552787, 'weight_decay': 0.03428190483638938, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 07:59:29,361] Trial 34 finished with value: 0.3995773702635142 and parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.19938535183699335, 'lr': 0.009914169103956429, 'weight_decay': 0.06502286104192165, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.399577 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.19938535183699335, 'lr': 0.009914169103956429, 'weight_decay': 0.06502286104192165, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 08:01:57,258] Trial 35 finished with value: 0.41929638886535575 and parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.17823229353208553, 'lr': 0.00342103593967629, 'weight_decay': 0.034439741369936806, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.419296 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.17823229353208553, 'lr': 0.00342103593967629, 'weight_decay': 0.034439741369936806, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 08:03:21,818] Trial 36 finished with value: 0.43036307728916506 and parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.15021278626343798, 'lr': 0.001920601279054819, 'weight_decay': 0.060582421402961745, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.430363 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.15021278626343798, 'lr': 0.001920601279054819, 'weight_decay': 0.060582421402961745, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 08:04:27,480] Trial 37 finished with value: 0.3783848953593809 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.22518832489509458, 'lr': 0.005452850454546586, 'weight_decay': 0.015345659469504601, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.378385 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.22518832489509458, 'lr': 0.005452850454546586, 'weight_decay': 0.015345659469504601, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-25 08:04:31,222] Trial 38 pruned. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.338338 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.20858892635757123, 'lr': 0.0015417598005733539, 'weight_decay': 0.031866297149149514, 'batch_size': 128} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-25 08:04:34,063] Trial 39 pruned. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.411469 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23339651754672316, 'lr': 0.002320601765962264, 'weight_decay': 0.05394359028539781, 'batch_size': 256} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 08:06:46,132] Trial 40 finished with value: 0.4211252416119314 and parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.18407622807413854, 'lr': 0.00349328788358961, 'weight_decay': 0.007624493417497092, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.421125 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.18407622807413854, 'lr': 0.00349328788358961, 'weight_decay': 0.007624493417497092, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 08:08:52,963] Trial 41 finished with value: 0.4295636210424456 and parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.20531067340934492, 'lr': 0.00249317154002033, 'weight_decay': 0.028022788721182388, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.429564 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.20531067340934492, 'lr': 0.00249317154002033, 'weight_decay': 0.028022788721182388, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 08:09:18,421] Trial 42 finished with value: 0.39466533423848266 and parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.24321572862665827, 'lr': 0.0059758088949262165, 'weight_decay': 0.09932160707869436, 'batch_size': 128}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.394665 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.24321572862665827, 'lr': 0.0059758088949262165, 'weight_decay': 0.09932160707869436, 'batch_size': 128} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 08:11:25,117] Trial 43 finished with value: 0.42377772923788 and parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.22030738268298594, 'lr': 0.0037271009198078012, 'weight_decay': 0.04549651100536438, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.423778 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.22030738268298594, 'lr': 0.0037271009198078012, 'weight_decay': 0.04549651100536438, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 08:12:01,171] Trial 44 finished with value: 0.41453349477712403 and parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.24511649162910865, 'lr': 0.0015683814299448254, 'weight_decay': 0.013969506791069234, 'batch_size': 256}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.414533 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.24511649162910865, 'lr': 0.0015683814299448254, 'weight_decay': 0.013969506791069234, 'batch_size': 256} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 08:13:50,829] Trial 45 finished with value: 0.4213148684286902 and parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.23570944551728484, 'lr': 0.0024092440527776846, 'weight_decay': 0.03751219755841374, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.421315 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.23570944551728484, 'lr': 0.0024092440527776846, 'weight_decay': 0.03751219755841374, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 08:14:30,152] Trial 46 finished with value: 0.4102403378605648 and parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.22100345435776164, 'lr': 0.007238564607635275, 'weight_decay': 0.06772144301521185, 'batch_size': 128}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.410240 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.22100345435776164, 'lr': 0.007238564607635275, 'weight_decay': 0.06772144301521185, 'batch_size': 128} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 08:15:56,317] Trial 47 finished with value: 0.39461949283066766 and parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.1911541786089016, 'lr': 0.004596193377356162, 'weight_decay': 0.026703744163665777, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.394619 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.1911541786089016, 'lr': 0.004596193377356162, 'weight_decay': 0.026703744163665777, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-25 08:16:06,278] Trial 48 pruned. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.410405 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2614617593906483, 'lr': 0.001218941020892418, 'weight_decay': 0.017351071176684028, 'batch_size': 64} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-25 08:16:08,798] Trial 49 pruned. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.344203 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.2079251673416201, 'lr': 0.0007434825214536403, 'weight_decay': 0.04599605394912415, 'batch_size': 256} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-25 08:16:27,001] Trial 50 pruned. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.372064 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.23926403162880455, 'lr': 0.0021304330961535918, 'weight_decay': 0.027970189449142733, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 08:17:57,741] Trial 51 finished with value: 0.42390436976889473 and parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.15303822637443357, 'lr': 0.00181683612012313, 'weight_decay': 0.05935205836285391, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.423904 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.15303822637443357, 'lr': 0.00181683612012313, 'weight_decay': 0.05935205836285391, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 08:19:40,511] Trial 52 finished with value: 0.4066564944925382 and parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.1334477140720548, 'lr': 0.0029927138173563646, 'weight_decay': 0.06648985199392311, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.406656 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.1334477140720548, 'lr': 0.0029927138173563646, 'weight_decay': 0.06648985199392311, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 08:21:24,348] Trial 53 finished with value: 0.42289923052802636 and parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.16236682632786031, 'lr': 0.0014371620147278293, 'weight_decay': 0.04160243622301881, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.422899 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.16236682632786031, 'lr': 0.0014371620147278293, 'weight_decay': 0.04160243622301881, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 08:22:25,039] Trial 54 finished with value: 0.4283823388413606 and parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.1806288529793588, 'lr': 0.0018113620428779334, 'weight_decay': 0.07318410850868626, 'batch_size': 64}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.428382 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.1806288529793588, 'lr': 0.0018113620428779334, 'weight_decay': 0.07318410850868626, 'batch_size': 64} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 08:24:18,837] Trial 55 finished with value: 0.4131681153296736 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.14416650629018124, 'lr': 0.0029737555950320026, 'weight_decay': 0.09579559774328306, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.413168 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.14416650629018124, 'lr': 0.0029737555950320026, 'weight_decay': 0.09579559774328306, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 08:25:19,060] Trial 56 finished with value: 0.40318147395509757 and parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.19324577582374083, 'lr': 0.004209374764020571, 'weight_decay': 0.01902075071669369, 'batch_size': 64}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.403181 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.19324577582374083, 'lr': 0.004209374764020571, 'weight_decay': 0.01902075071669369, 'batch_size': 64} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 08:27:22,096] Trial 57 finished with value: 0.4262074854675609 and parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.22576910305990883, 'lr': 0.00220343658019399, 'weight_decay': 0.032912866302873336, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.426207 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.22576910305990883, 'lr': 0.00220343658019399, 'weight_decay': 0.032912866302873336, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 08:28:19,953] Trial 58 finished with value: 0.42647440375548973 and parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2024601515289508, 'lr': 0.0012793769282458574, 'weight_decay': 0.05143193969856393, 'batch_size': 64}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.426474 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2024601515289508, 'lr': 0.0012793769282458574, 'weight_decay': 0.05143193969856393, 'batch_size': 64} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-25 08:28:24,301] Trial 59 pruned. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.399501 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.21637010689860087, 'lr': 0.0009702469677626237, 'weight_decay': 0.025269574675852172, 'batch_size': 128} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 08:29:17,328] Trial 60 finished with value: 0.38895778680181187 and parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.2522223601367995, 'lr': 0.006255561082350736, 'weight_decay': 0.011491294362941667, 'batch_size': 64}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.388958 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.2522223601367995, 'lr': 0.006255561082350736, 'weight_decay': 0.011491294362941667, 'batch_size': 64} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 08:31:10,575] Trial 61 finished with value: 0.41294894817357725 and parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.23599216477577017, 'lr': 0.002738754707717849, 'weight_decay': 0.04119546611175334, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.412949 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.23599216477577017, 'lr': 0.002738754707717849, 'weight_decay': 0.04119546611175334, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 08:33:04,861] Trial 62 finished with value: 0.4305293582915195 and parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.2275486734964554, 'lr': 0.0021027590926097615, 'weight_decay': 0.07068437902210996, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.430529 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.2275486734964554, 'lr': 0.0021027590926097615, 'weight_decay': 0.07068437902210996, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 08:34:37,428] Trial 63 finished with value: 0.3866016227371925 and parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.21195767347779876, 'lr': 0.004283664359395512, 'weight_decay': 0.07887816543266966, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.386602 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.21195767347779876, 'lr': 0.004283664359395512, 'weight_decay': 0.07887816543266966, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 08:36:22,129] Trial 64 finished with value: 0.4280266618628834 and parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.22666255928670673, 'lr': 0.0019640162844038168, 'weight_decay': 0.06530486408656519, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.428027 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.22666255928670673, 'lr': 0.0019640162844038168, 'weight_decay': 0.06530486408656519, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 08:38:30,667] Trial 65 finished with value: 0.4296646966324022 and parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.18622920306864366, 'lr': 0.0008853644306592279, 'weight_decay': 0.05178404717009992, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.429665 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.18622920306864366, 'lr': 0.0008853644306592279, 'weight_decay': 0.05178404717009992, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 08:40:27,006] Trial 66 finished with value: 0.42381692102757196 and parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.2030043170865337, 'lr': 0.0005672422273682855, 'weight_decay': 0.0792938263017876, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.423817 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.2030043170865337, 'lr': 0.0005672422273682855, 'weight_decay': 0.0792938263017876, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 08:41:41,129] Trial 67 finished with value: 0.42066251812416056 and parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.247337167813791, 'lr': 0.0032921555738210195, 'weight_decay': 0.03417244477067255, 'batch_size': 64}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.420663 - Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.247337167813791, 'lr': 0.0032921555738210195, 'weight_decay': 0.03417244477067255, 'batch_size': 64} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-25 08:41:44,158] Trial 68 pruned. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.408342 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.1680716561338434, 'lr': 0.0013233942995370992, 'weight_decay': 0.022595952668545055, 'batch_size': 256} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 08:44:11,578] Trial 69 finished with value: 0.43362393591925863 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19742051142814077, 'lr': 0.0020728444365855614, 'weight_decay': 0.044858999005631825, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.433624 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19742051142814077, 'lr': 0.0020728444365855614, 'weight_decay': 0.044858999005631825, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 08:46:18,067] Trial 70 finished with value: 0.42424320503521556 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19457336929608418, 'lr': 0.0045697296665932466, 'weight_decay': 0.045771741552819246, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.424243 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19457336929608418, 'lr': 0.0045697296665932466, 'weight_decay': 0.045771741552819246, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 08:47:38,552] Trial 71 finished with value: 0.4103482656157047 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.2130590150402775, 'lr': 0.002110543855274591, 'weight_decay': 0.055758834282470394, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.410348 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.2130590150402775, 'lr': 0.002110543855274591, 'weight_decay': 0.055758834282470394, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 08:49:17,759] Trial 72 finished with value: 0.41934089302049865 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.2277183597213174, 'lr': 0.00154157926963339, 'weight_decay': 0.07744233041123381, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.419341 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.2277183597213174, 'lr': 0.00154157926963339, 'weight_decay': 0.07744233041123381, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 08:51:53,625] Trial 73 finished with value: 0.43084739273608275 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.18543968688237536, 'lr': 0.0026261483539853276, 'weight_decay': 0.036781618311016666, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.430847 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.18543968688237536, 'lr': 0.0026261483539853276, 'weight_decay': 0.036781618311016666, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 08:53:41,292] Trial 74 finished with value: 0.4228673049391096 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.1984950482767201, 'lr': 0.002668128531126033, 'weight_decay': 0.028620390814155267, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.422867 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.1984950482767201, 'lr': 0.002668128531126033, 'weight_decay': 0.028620390814155267, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-25 08:53:50,991] Trial 75 pruned. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.420610 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.21729860180278754, 'lr': 0.0033610521145788588, 'weight_decay': 0.03779124734783946, 'batch_size': 64} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 08:56:33,460] Trial 76 finished with value: 0.4344697735296894 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.18264291430362548, 'lr': 0.0028039605941193486, 'weight_decay': 0.018336911439353946, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.434470 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.18264291430362548, 'lr': 0.0028039605941193486, 'weight_decay': 0.018336911439353946, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 08:58:37,555] Trial 77 finished with value: 0.4229707096536239 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.1814247302841254, 'lr': 0.005062240229279633, 'weight_decay': 0.01781714181977861, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.422971 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.1814247302841254, 'lr': 0.005062240229279633, 'weight_decay': 0.01781714181977861, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-25 08:58:41,307] Trial 78 pruned. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.348108 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.18703392529411514, 'lr': 0.003872321330900037, 'weight_decay': 0.023042202460987128, 'batch_size': 128} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 08:59:52,323] Trial 79 finished with value: 0.4267301942329437 and parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.17413055103006175, 'lr': 0.0028426235209454294, 'weight_decay': 0.03287156326322141, 'batch_size': 64}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.426730 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.17413055103006175, 'lr': 0.0028426235209454294, 'weight_decay': 0.03287156326322141, 'batch_size': 64} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 09:01:50,986] Trial 80 finished with value: 0.4213320825609406 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2021579696004458, 'lr': 0.0016501830407631172, 'weight_decay': 0.01540902306968921, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.421332 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2021579696004458, 'lr': 0.0016501830407631172, 'weight_decay': 0.01540902306968921, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 09:04:03,510] Trial 81 finished with value: 0.43576767933817767 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.210816098663159, 'lr': 0.002321781089740796, 'weight_decay': 0.04668921075194866, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.435768 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.210816098663159, 'lr': 0.002321781089740796, 'weight_decay': 0.04668921075194866, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 09:05:36,017] Trial 82 finished with value: 0.4148640011295644 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.20734202965403847, 'lr': 0.002658141273413158, 'weight_decay': 0.039298970714823564, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.414864 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.20734202965403847, 'lr': 0.002658141273413158, 'weight_decay': 0.039298970714823564, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 09:07:29,885] Trial 83 finished with value: 0.4333042751539682 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19081271754602028, 'lr': 0.001182594193983033, 'weight_decay': 0.026454156472370316, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.433304 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19081271754602028, 'lr': 0.001182594193983033, 'weight_decay': 0.026454156472370316, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-25 09:07:48,591] Trial 84 pruned. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.401220 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.21973823521384794, 'lr': 0.0010546582109614382, 'weight_decay': 0.028064254855311777, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-25 09:08:01,223] Trial 85 pruned. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.380448 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.21239979242029458, 'lr': 0.001340932197622327, 'weight_decay': 0.02118393136897684, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-25 09:08:04,217] Trial 86 pruned. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.406832 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.19391476393658713, 'lr': 0.0016696574170405995, 'weight_decay': 0.04541983404116574, 'batch_size': 256} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 09:09:45,765] Trial 87 finished with value: 0.4170212085424527 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.23777275751002536, 'lr': 0.0036118630472872417, 'weight_decay': 0.024097178694965693, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.417021 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.23777275751002536, 'lr': 0.0036118630472872417, 'weight_decay': 0.024097178694965693, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 09:10:56,242] Trial 88 finished with value: 0.4328217563804486 and parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.19644138075265755, 'lr': 0.0022931673628983173, 'weight_decay': 0.03075003055423546, 'batch_size': 64}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.432822 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.19644138075265755, 'lr': 0.0022931673628983173, 'weight_decay': 0.03075003055423546, 'batch_size': 64} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 09:12:05,926] Trial 89 finished with value: 0.4141963959390667 and parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.1962422560975072, 'lr': 0.0011374261946315329, 'weight_decay': 0.02970388111443431, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.414196 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.1962422560975072, 'lr': 0.0011374261946315329, 'weight_decay': 0.02970388111443431, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-25 09:12:12,772] Trial 90 pruned. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.414838 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.20590426986012517, 'lr': 0.0014630834981008728, 'weight_decay': 0.04998662835730308, 'batch_size': 64} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-25 09:12:19,642] Trial 91 pruned. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.374412 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.18885069372997473, 'lr': 0.002327272934043665, 'weight_decay': 0.06023274307404068, 'batch_size': 64} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-25 09:12:29,600] Trial 92 pruned. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.421164 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.22163069190824541, 'lr': 0.0019515420663356003, 'weight_decay': 0.019294099620924883, 'batch_size': 64} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 09:13:32,138] Trial 93 finished with value: 0.41635196163528193 and parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.19848717559761242, 'lr': 0.0031150425299506057, 'weight_decay': 0.03178523722029595, 'batch_size': 64}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.416352 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.19848717559761242, 'lr': 0.0031150425299506057, 'weight_decay': 0.03178523722029595, 'batch_size': 64} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-25 09:13:39,077] Trial 94 pruned. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.390244 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.231731812150328, 'lr': 0.0022595324737116856, 'weight_decay': 0.02548135940528196, 'batch_size': 64} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 09:16:02,045] Trial 95 finished with value: 0.430144000432314 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.2104171542032818, 'lr': 0.0017098030508820089, 'weight_decay': 0.04074275374848452, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.430144 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.2104171542032818, 'lr': 0.0017098030508820089, 'weight_decay': 0.04074275374848452, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 09:17:25,338] Trial 96 finished with value: 0.426479841148762 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.17803511039282005, 'lr': 0.00324853647150159, 'weight_decay': 0.04592220088959651, 'batch_size': 64}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.426480 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.17803511039282005, 'lr': 0.00324853647150159, 'weight_decay': 0.04592220088959651, 'batch_size': 64} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 09:18:59,815] Trial 97 finished with value: 0.3982962852205854 and parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.21763520282217308, 'lr': 0.00401714020476418, 'weight_decay': 0.08884824293451812, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.398296 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.21763520282217308, 'lr': 0.00401714020476418, 'weight_decay': 0.08884824293451812, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 09:19:40,498] Trial 98 finished with value: 0.4282526373336119 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.20173626542593018, 'lr': 0.0023529673872743594, 'weight_decay': 0.05685969465496294, 'batch_size': 128}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.428253 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.20173626542593018, 'lr': 0.0023529673872743594, 'weight_decay': 0.05685969465496294, 'batch_size': 128} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 09:21:17,754] Trial 99 finished with value: 0.4083305455151313 and parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.24205343770509608, 'lr': 0.0019379253503240498, 'weight_decay': 0.03507102572203717, 'batch_size': 32}. Best is trial 27 with value: 0.4429286988285861. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.408331 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.24205343770509608, 'lr': 0.0019379253503240498, 'weight_decay': 0.03507102572203717, 'batch_size': 32} - Best Value (CSI): 0.442929 - Best Trial: 27 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.4429 -Best Hyperparameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2275228702990485, 'lr': 0.002636923316902024, 'weight_decay': 0.05132270066782015, 'batch_size': 32} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.2982 - - 최종 CSI: 0.4083 - - 최고 CSI: 0.4429 - - 최저 CSI: 0.2982 - - 평균 CSI: 0.4102 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/deepgbm_pure_busan_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 32, Best CSI: 0.4431 - Fold 1 학습 완료 (검증 CSI: 0.4431) -Fold 2 학습 중... - Early stopping at epoch 22, Best CSI: 0.3943 - Fold 2 학습 완료 (검증 CSI: 0.3943) -Fold 3 학습 중... - Early stopping at epoch 57, Best CSI: 0.3869 - Fold 3 학습 완료 (검증 CSI: 0.3869) - -모든 모델 저장 완료: ../save_model/deepgbm_optima/deepgbm_pure_busan.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/deepgbm_optima/scaler/deepgbm_pure_busan_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: - - . - - . - - / - - s - - a - - v - - e - - _ - - m - - o - - d - - e - - l - - / - - d - - e - - e - - p - - g - - b - - m - - _ - - o - - p - - t - - i - - m - - a - - / - - d - - e - - e - - p - - g - - b - - m - - _ - - p - - u - - r - - e - - _ - - b - - u - - s - - a - - n - - . - - p - - k - - l - -✓ 완료: deepgbm_pure/deepgbm_pure_busan.py (소요 시간: 7818초) - ----------------------------------------- -실행 중: deepgbm_pure/deepgbm_pure_daegu.py -시작 시간: 2025-12-25 09:23:05 ----------------------------------------- -[I 2025-12-25 09:23:06,776] A new study created in memory with name: no-name-632ff73b-1a18-47a4-b287-5c1bfa376446 - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 09:24:06,290] Trial 0 finished with value: 0.3211738526227763 and parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3603539962069603, 'lr': 0.00776810886532722, 'weight_decay': 0.00194203072923637, 'batch_size': 32}. Best is trial 0 with value: 0.3211738526227763. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.321174 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3603539962069603, 'lr': 0.00776810886532722, 'weight_decay': 0.00194203072923637, 'batch_size': 32} - Best Value (CSI): 0.321174 - Best Trial: 0 - Best Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3603539962069603, 'lr': 0.00776810886532722, 'weight_decay': 0.00194203072923637, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 09:25:40,158] Trial 1 finished with value: 0.3117709641442636 and parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3346652140145605, 'lr': 7.012911191438772e-05, 'weight_decay': 0.009564386997272002, 'batch_size': 32}. Best is trial 0 with value: 0.3211738526227763. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.311771 - Parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3346652140145605, 'lr': 7.012911191438772e-05, 'weight_decay': 0.009564386997272002, 'batch_size': 32} - Best Value (CSI): 0.321174 - Best Trial: 0 - Best Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3603539962069603, 'lr': 0.00776810886532722, 'weight_decay': 0.00194203072923637, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 09:27:28,675] Trial 2 finished with value: 0.22955974922303732 and parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.25694805752034755, 'lr': 1.0058697706390474e-05, 'weight_decay': 0.005237027171769066, 'batch_size': 128}. Best is trial 0 with value: 0.3211738526227763. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.229560 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.25694805752034755, 'lr': 1.0058697706390474e-05, 'weight_decay': 0.005237027171769066, 'batch_size': 128} - Best Value (CSI): 0.321174 - Best Trial: 0 - Best Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3603539962069603, 'lr': 0.00776810886532722, 'weight_decay': 0.00194203072923637, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 09:28:07,987] Trial 3 finished with value: 0.28618028093587605 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.35894036618065406, 'lr': 0.00020572854288295278, 'weight_decay': 0.0016166411991867546, 'batch_size': 128}. Best is trial 0 with value: 0.3211738526227763. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.286180 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.35894036618065406, 'lr': 0.00020572854288295278, 'weight_decay': 0.0016166411991867546, 'batch_size': 128} - Best Value (CSI): 0.321174 - Best Trial: 0 - Best Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3603539962069603, 'lr': 0.00776810886532722, 'weight_decay': 0.00194203072923637, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 09:28:34,656] Trial 4 finished with value: 0.269446632081497 and parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.35791048615835985, 'lr': 5.430522001859318e-05, 'weight_decay': 0.0012539679734478012, 'batch_size': 256}. Best is trial 0 with value: 0.3211738526227763. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.269447 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.35791048615835985, 'lr': 5.430522001859318e-05, 'weight_decay': 0.0012539679734478012, 'batch_size': 256} - Best Value (CSI): 0.321174 - Best Trial: 0 - Best Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3603539962069603, 'lr': 0.00776810886532722, 'weight_decay': 0.00194203072923637, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 09:28:55,352] Trial 5 finished with value: 0.29678490292990584 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.34469032090107965, 'lr': 0.00859538952300509, 'weight_decay': 0.0012074861952991371, 'batch_size': 256}. Best is trial 0 with value: 0.3211738526227763. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.296785 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.34469032090107965, 'lr': 0.00859538952300509, 'weight_decay': 0.0012074861952991371, 'batch_size': 256} - Best Value (CSI): 0.321174 - Best Trial: 0 - Best Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3603539962069603, 'lr': 0.00776810886532722, 'weight_decay': 0.00194203072923637, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 09:29:06,015] Trial 6 pruned. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.241162 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.13924205621186847, 'lr': 0.003106659520585436, 'weight_decay': 0.001928066722359402, 'batch_size': 128} - Best Value (CSI): 0.321174 - Best Trial: 0 - Best Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3603539962069603, 'lr': 0.00776810886532722, 'weight_decay': 0.00194203072923637, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 09:29:16,093] Trial 7 pruned. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.251337 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.38268717558760723, 'lr': 0.00016214398789818078, 'weight_decay': 0.053102875997042866, 'batch_size': 128} - Best Value (CSI): 0.321174 - Best Trial: 0 - Best Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3603539962069603, 'lr': 0.00776810886532722, 'weight_decay': 0.00194203072923637, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 09:29:34,121] Trial 8 finished with value: 0.3089368281867812 and parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.29456110940560076, 'lr': 0.0007697578041443896, 'weight_decay': 0.0005941987631498153, 'batch_size': 256}. Best is trial 0 with value: 0.3211738526227763. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.308937 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.29456110940560076, 'lr': 0.0007697578041443896, 'weight_decay': 0.0005941987631498153, 'batch_size': 256} - Best Value (CSI): 0.321174 - Best Trial: 0 - Best Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3603539962069603, 'lr': 0.00776810886532722, 'weight_decay': 0.00194203072923637, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 09:29:48,392] Trial 9 pruned. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.281250 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.25446942189530836, 'lr': 0.0005283556947193749, 'weight_decay': 0.0010652842234194573, 'batch_size': 64} - Best Value (CSI): 0.321174 - Best Trial: 0 - Best Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3603539962069603, 'lr': 0.00776810886532722, 'weight_decay': 0.00194203072923637, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 09:30:50,134] Trial 10 finished with value: 0.2959142053991111 and parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.39615870442875856, 'lr': 0.008253767878279611, 'weight_decay': 0.00010191273685888612, 'batch_size': 32}. Best is trial 0 with value: 0.3211738526227763. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.295914 - Parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.39615870442875856, 'lr': 0.008253767878279611, 'weight_decay': 0.00010191273685888612, 'batch_size': 32} - Best Value (CSI): 0.321174 - Best Trial: 0 - Best Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3603539962069603, 'lr': 0.00776810886532722, 'weight_decay': 0.00194203072923637, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 09:31:13,712] Trial 11 pruned. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.281847 - Parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.307490823904731, 'lr': 0.0019398000376572285, 'weight_decay': 0.007606583047828093, 'batch_size': 32} - Best Value (CSI): 0.321174 - Best Trial: 0 - Best Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3603539962069603, 'lr': 0.00776810886532722, 'weight_decay': 0.00194203072923637, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 09:32:48,689] Trial 12 finished with value: 0.3172053811554351 and parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.3207599246651656, 'lr': 7.861420000709811e-05, 'weight_decay': 0.013797735899863023, 'batch_size': 32}. Best is trial 0 with value: 0.3211738526227763. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.317205 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.3207599246651656, 'lr': 7.861420000709811e-05, 'weight_decay': 0.013797735899863023, 'batch_size': 32} - Best Value (CSI): 0.321174 - Best Trial: 0 - Best Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3603539962069603, 'lr': 0.00776810886532722, 'weight_decay': 0.00194203072923637, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 09:33:14,935] Trial 13 pruned. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.295222 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.3015753028749495, 'lr': 0.0012215458166718496, 'weight_decay': 0.02939315084272547, 'batch_size': 32} - Best Value (CSI): 0.321174 - Best Trial: 0 - Best Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3603539962069603, 'lr': 0.00776810886532722, 'weight_decay': 0.00194203072923637, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 09:34:55,145] Trial 14 finished with value: 0.3456540663017031 and parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39256911985925436, 'lr': 0.003684187296320797, 'weight_decay': 0.01812464235732703, 'batch_size': 32}. Best is trial 14 with value: 0.3456540663017031. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.345654 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39256911985925436, 'lr': 0.003684187296320797, 'weight_decay': 0.01812464235732703, 'batch_size': 32} - Best Value (CSI): 0.345654 - Best Trial: 14 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39256911985925436, 'lr': 0.003684187296320797, 'weight_decay': 0.01812464235732703, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 09:35:48,248] Trial 15 finished with value: 0.3511967933982092 and parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3995585976219087, 'lr': 0.003702477490742026, 'weight_decay': 0.09931601654680236, 'batch_size': 64}. Best is trial 15 with value: 0.3511967933982092. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.351197 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3995585976219087, 'lr': 0.003702477490742026, 'weight_decay': 0.09931601654680236, 'batch_size': 64} - Best Value (CSI): 0.351197 - Best Trial: 15 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3995585976219087, 'lr': 0.003702477490742026, 'weight_decay': 0.09931601654680236, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 09:36:37,558] Trial 16 finished with value: 0.3455341271698713 and parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3975475660796756, 'lr': 0.003218998759247259, 'weight_decay': 0.09685476360854658, 'batch_size': 64}. Best is trial 15 with value: 0.3511967933982092. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.345534 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3975475660796756, 'lr': 0.003218998759247259, 'weight_decay': 0.09685476360854658, 'batch_size': 64} - Best Value (CSI): 0.351197 - Best Trial: 15 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3995585976219087, 'lr': 0.003702477490742026, 'weight_decay': 0.09931601654680236, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 09:37:01,865] Trial 17 pruned. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.323202 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39019984632693416, 'lr': 0.0032810013367108814, 'weight_decay': 0.026993831479335283, 'batch_size': 64} - Best Value (CSI): 0.351197 - Best Trial: 15 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3995585976219087, 'lr': 0.003702477490742026, 'weight_decay': 0.09931601654680236, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 09:37:17,373] Trial 18 pruned. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.271293 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.19894777695354093, 'lr': 0.001244055484613898, 'weight_decay': 0.09967288461898587, 'batch_size': 64} - Best Value (CSI): 0.351197 - Best Trial: 15 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3995585976219087, 'lr': 0.003702477490742026, 'weight_decay': 0.09931601654680236, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 09:37:29,044] Trial 19 pruned. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.246930 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.27382305124829853, 'lr': 0.00047145995641346505, 'weight_decay': 0.029098097222363433, 'batch_size': 64} - Best Value (CSI): 0.351197 - Best Trial: 15 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3995585976219087, 'lr': 0.003702477490742026, 'weight_decay': 0.09931601654680236, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 09:37:54,948] Trial 20 pruned. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.306316 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.33022522998417536, 'lr': 0.004935055322952153, 'weight_decay': 0.016168000482248278, 'batch_size': 64} - Best Value (CSI): 0.351197 - Best Trial: 15 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3995585976219087, 'lr': 0.003702477490742026, 'weight_decay': 0.09931601654680236, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 09:38:36,328] Trial 21 finished with value: 0.3334402475650773 and parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39981821396441725, 'lr': 0.002840855686376136, 'weight_decay': 0.09416631148452637, 'batch_size': 64}. Best is trial 15 with value: 0.3511967933982092. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.333440 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39981821396441725, 'lr': 0.002840855686376136, 'weight_decay': 0.09416631148452637, 'batch_size': 64} - Best Value (CSI): 0.351197 - Best Trial: 15 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3995585976219087, 'lr': 0.003702477490742026, 'weight_decay': 0.09931601654680236, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 09:39:20,800] Trial 22 finished with value: 0.3348865202597204 and parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.37321843707999874, 'lr': 0.0041808003137705895, 'weight_decay': 0.05291538809416649, 'batch_size': 64}. Best is trial 15 with value: 0.3511967933982092. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.334887 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.37321843707999874, 'lr': 0.0041808003137705895, 'weight_decay': 0.05291538809416649, 'batch_size': 64} - Best Value (CSI): 0.351197 - Best Trial: 15 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3995585976219087, 'lr': 0.003702477490742026, 'weight_decay': 0.09931601654680236, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 09:39:44,549] Trial 23 pruned. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.331595 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.36853722930457966, 'lr': 0.001791488765565398, 'weight_decay': 0.05522539224579616, 'batch_size': 64} - Best Value (CSI): 0.351197 - Best Trial: 15 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3995585976219087, 'lr': 0.003702477490742026, 'weight_decay': 0.09931601654680236, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 09:40:08,644] Trial 24 pruned. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.313043 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.395926958521568, 'lr': 0.004982852295352129, 'weight_decay': 0.0876338895737716, 'batch_size': 64} - Best Value (CSI): 0.351197 - Best Trial: 15 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3995585976219087, 'lr': 0.003702477490742026, 'weight_decay': 0.09931601654680236, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 09:40:48,617] Trial 25 finished with value: 0.3269635659091787 and parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3440765022355288, 'lr': 0.002001109784999372, 'weight_decay': 0.04252776583517005, 'batch_size': 64}. Best is trial 15 with value: 0.3511967933982092. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.326964 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3440765022355288, 'lr': 0.002001109784999372, 'weight_decay': 0.04252776583517005, 'batch_size': 64} - Best Value (CSI): 0.351197 - Best Trial: 15 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3995585976219087, 'lr': 0.003702477490742026, 'weight_decay': 0.09931601654680236, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 09:42:27,482] Trial 26 finished with value: 0.3535268793319816 and parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32}. Best is trial 26 with value: 0.3535268793319816. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.353527 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} - Best Value (CSI): 0.353527 - Best Trial: 26 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 09:42:47,949] Trial 27 pruned. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.255495 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.37275289946582335, 'lr': 0.0010602441422322244, 'weight_decay': 0.019949586412152335, 'batch_size': 32} - Best Value (CSI): 0.353527 - Best Trial: 26 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 09:43:05,398] Trial 28 pruned. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.214922 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3474655673683627, 'lr': 0.0007529702884681428, 'weight_decay': 0.01255953555262677, 'batch_size': 32} - Best Value (CSI): 0.353527 - Best Trial: 26 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 09:43:21,245] Trial 29 pruned. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.212254 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.36608231491647614, 'lr': 0.006891296370024119, 'weight_decay': 0.004845016597575762, 'batch_size': 32} - Best Value (CSI): 0.353527 - Best Trial: 26 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 09:44:10,511] Trial 30 pruned. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.334350 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3734655591379893, 'lr': 0.009130400985381263, 'weight_decay': 0.022650198546184993, 'batch_size': 32} - Best Value (CSI): 0.353527 - Best Trial: 26 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 09:44:54,690] Trial 31 pruned. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.336943 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3988591190488784, 'lr': 0.0026003654481788164, 'weight_decay': 0.03505977350400173, 'batch_size': 32} - Best Value (CSI): 0.353527 - Best Trial: 26 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 09:45:18,082] Trial 32 pruned. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.175405 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.37801749589394207, 'lr': 0.00548500515080908, 'weight_decay': 0.0639331703116523, 'batch_size': 32} - Best Value (CSI): 0.353527 - Best Trial: 26 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 09:45:20,865] Trial 33 pruned. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.175514 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3298203011679228, 'lr': 0.0038567726243452184, 'weight_decay': 0.06956138109002757, 'batch_size': 256} - Best Value (CSI): 0.353527 - Best Trial: 26 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 09:46:04,924] Trial 34 finished with value: 0.3374852992792213 and parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.38304826555806254, 'lr': 0.0019253834810190355, 'weight_decay': 0.03925439541255437, 'batch_size': 64}. Best is trial 26 with value: 0.3535268793319816. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.337485 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.38304826555806254, 'lr': 0.0019253834810190355, 'weight_decay': 0.03925439541255437, 'batch_size': 64} - Best Value (CSI): 0.353527 - Best Trial: 26 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 09:46:11,288] Trial 35 pruned. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.242744 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.3557222384394494, 'lr': 0.0051651905302877825, 'weight_decay': 0.018732372383929972, 'batch_size': 128} - Best Value (CSI): 0.353527 - Best Trial: 26 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 09:46:53,423] Trial 36 pruned. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.339829 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.3543416385084988, 'lr': 0.002576683840667209, 'weight_decay': 0.010067313244866614, 'batch_size': 32} - Best Value (CSI): 0.353527 - Best Trial: 26 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 09:46:57,820] Trial 37 pruned. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.222092 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.3411024894529777, 'lr': 0.006741517639322595, 'weight_decay': 0.03824924444068077, 'batch_size': 256} - Best Value (CSI): 0.353527 - Best Trial: 26 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 09:47:04,808] Trial 38 pruned. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.261871 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.35866708089468785, 'lr': 0.001381012731738566, 'weight_decay': 0.07012895678154477, 'batch_size': 128} - Best Value (CSI): 0.353527 - Best Trial: 26 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 09:48:21,957] Trial 39 finished with value: 0.34905280442622216 and parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.3864872958838429, 'lr': 0.0031284469919609106, 'weight_decay': 0.022333205338773334, 'batch_size': 64}. Best is trial 26 with value: 0.3535268793319816. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.349053 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.3864872958838429, 'lr': 0.0031284469919609106, 'weight_decay': 0.022333205338773334, 'batch_size': 64} - Best Value (CSI): 0.353527 - Best Trial: 26 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 09:49:38,239] Trial 40 finished with value: 0.32886602003908916 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.3803815754837445, 'lr': 0.001529353860491224, 'weight_decay': 0.007563864499638978, 'batch_size': 32}. Best is trial 26 with value: 0.3535268793319816. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.328866 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.3803815754837445, 'lr': 0.001529353860491224, 'weight_decay': 0.007563864499638978, 'batch_size': 32} - Best Value (CSI): 0.353527 - Best Trial: 26 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 09:50:05,755] Trial 41 pruned. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.308642 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.3840813032838395, 'lr': 0.003585218552555223, 'weight_decay': 0.025781916005025413, 'batch_size': 64} - Best Value (CSI): 0.353527 - Best Trial: 26 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 09:50:28,964] Trial 42 pruned. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.303862 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3987423464717651, 'lr': 0.002405816605206721, 'weight_decay': 0.054178328078042355, 'batch_size': 64} - Best Value (CSI): 0.353527 - Best Trial: 26 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 09:50:39,566] Trial 43 pruned. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.240102 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.3611102165468887, 'lr': 0.003344989184591785, 'weight_decay': 0.017194999834375068, 'batch_size': 64} - Best Value (CSI): 0.353527 - Best Trial: 26 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 09:50:51,155] Trial 44 pruned. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.205422 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.3845507356993787, 'lr': 0.006295171178465965, 'weight_decay': 0.04582650235244081, 'batch_size': 64} - Best Value (CSI): 0.353527 - Best Trial: 26 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 09:50:55,425] Trial 45 pruned. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.202783 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3615882486646692, 'lr': 0.009951521758361125, 'weight_decay': 0.0768292408466316, 'batch_size': 256} - Best Value (CSI): 0.353527 - Best Trial: 26 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 09:51:21,746] Trial 46 finished with value: 0.32806444508821603 and parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3860123859470919, 'lr': 0.0022369377492000284, 'weight_decay': 0.03266023226201664, 'batch_size': 128}. Best is trial 26 with value: 0.3535268793319816. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.328064 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3860123859470919, 'lr': 0.0022369377492000284, 'weight_decay': 0.03266023226201664, 'batch_size': 128} - Best Value (CSI): 0.353527 - Best Trial: 26 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 09:51:31,798] Trial 47 pruned. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.252427 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.32347331471842916, 'lr': 0.0009628966668271027, 'weight_decay': 0.011928194755299078, 'batch_size': 64} - Best Value (CSI): 0.353527 - Best Trial: 26 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 09:52:51,298] Trial 48 finished with value: 0.3358730358729914 and parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3369348646662839, 'lr': 0.0031587214855213815, 'weight_decay': 0.09888798093440782, 'batch_size': 32}. Best is trial 26 with value: 0.3535268793319816. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.335873 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3369348646662839, 'lr': 0.0031587214855213815, 'weight_decay': 0.09888798093440782, 'batch_size': 32} - Best Value (CSI): 0.353527 - Best Trial: 26 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 09:53:11,244] Trial 49 pruned. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.296432 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3482366853269903, 'lr': 0.0015984323322113822, 'weight_decay': 0.02257353421965316, 'batch_size': 64} - Best Value (CSI): 0.353527 - Best Trial: 26 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 09:53:28,685] Trial 50 pruned. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.227064 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3682950533475557, 'lr': 0.004531133894935865, 'weight_decay': 0.04535146569262296, 'batch_size': 32} - Best Value (CSI): 0.353527 - Best Trial: 26 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 09:53:38,681] Trial 51 pruned. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.221960 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3870431160213021, 'lr': 0.002063687210879681, 'weight_decay': 0.03629536889198091, 'batch_size': 64} - Best Value (CSI): 0.353527 - Best Trial: 26 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 09:54:03,495] Trial 52 pruned. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.334078 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.399804413942057, 'lr': 0.0017061552945146403, 'weight_decay': 0.06598555619380585, 'batch_size': 64} - Best Value (CSI): 0.353527 - Best Trial: 26 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 09:54:28,798] Trial 53 pruned. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.312312 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.3861123580485158, 'lr': 0.003879578488195251, 'weight_decay': 0.02827618368826431, 'batch_size': 64} - Best Value (CSI): 0.353527 - Best Trial: 26 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 09:55:12,583] Trial 54 finished with value: 0.3441388340180298 and parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.37653694754336803, 'lr': 0.0026215299671236494, 'weight_decay': 0.043817471582361635, 'batch_size': 64}. Best is trial 26 with value: 0.3535268793319816. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.344139 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.37653694754336803, 'lr': 0.0026215299671236494, 'weight_decay': 0.043817471582361635, 'batch_size': 64} - Best Value (CSI): 0.353527 - Best Trial: 26 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 09:55:23,772] Trial 55 pruned. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.236808 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.37560903379613175, 'lr': 0.0029150145113316134, 'weight_decay': 0.07506153320514584, 'batch_size': 64} - Best Value (CSI): 0.353527 - Best Trial: 26 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 09:55:54,375] Trial 56 pruned. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.263081 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39085835157820603, 'lr': 0.007452691143522961, 'weight_decay': 0.016183462140058953, 'batch_size': 64} - Best Value (CSI): 0.353527 - Best Trial: 26 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 09:55:58,233] Trial 57 pruned. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.207120 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.3678865982366426, 'lr': 0.004369088053358216, 'weight_decay': 0.050135905513470434, 'batch_size': 256} - Best Value (CSI): 0.353527 - Best Trial: 26 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 09:56:22,426] Trial 58 pruned. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.324211 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3502825021762811, 'lr': 0.001335592517801473, 'weight_decay': 0.09968945731172013, 'batch_size': 64} - Best Value (CSI): 0.353527 - Best Trial: 26 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 09:56:28,891] Trial 59 pruned. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.191126 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.310110114435153, 'lr': 0.005818531474747003, 'weight_decay': 0.022994582668962718, 'batch_size': 128} - Best Value (CSI): 0.353527 - Best Trial: 26 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 09:57:16,777] Trial 60 pruned. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.281724 - Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.3923311263832425, 'lr': 0.0025719501619559685, 'weight_decay': 0.05749158979249872, 'batch_size': 32} - Best Value (CSI): 0.353527 - Best Trial: 26 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 09:57:26,875] Trial 61 pruned. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.225352 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3771989669297165, 'lr': 0.0019875415940147083, 'weight_decay': 0.04137462388501686, 'batch_size': 64} - Best Value (CSI): 0.353527 - Best Trial: 26 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 09:57:37,377] Trial 62 pruned. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.183318 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3821781447499956, 'lr': 0.0032341188563269857, 'weight_decay': 0.02940856225505476, 'batch_size': 64} - Best Value (CSI): 0.353527 - Best Trial: 26 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 09:57:48,025] Trial 63 pruned. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.225030 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3673050153687432, 'lr': 0.0018894063088074095, 'weight_decay': 0.03577189617755486, 'batch_size': 64} - Best Value (CSI): 0.353527 - Best Trial: 26 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 09:58:10,292] Trial 64 pruned. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.324713 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3903974391429976, 'lr': 0.004441357521013829, 'weight_decay': 0.04599387170553661, 'batch_size': 64} - Best Value (CSI): 0.353527 - Best Trial: 26 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 09:58:21,076] Trial 65 pruned. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.241466 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3743475082809785, 'lr': 0.001009800078694752, 'weight_decay': 0.08026392312787002, 'batch_size': 64} - Best Value (CSI): 0.353527 - Best Trial: 26 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3793696205015752, 'lr': 0.0010156276868696769, 'weight_decay': 0.017973304541100032, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 10:00:16,941] Trial 66 finished with value: 0.3570454117885781 and parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39867335991930597, 'lr': 0.002428396450034936, 'weight_decay': 0.05750366129158036, 'batch_size': 32}. Best is trial 66 with value: 0.3570454117885781. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.357045 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39867335991930597, 'lr': 0.002428396450034936, 'weight_decay': 0.05750366129158036, 'batch_size': 32} - Best Value (CSI): 0.357045 - Best Trial: 66 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39867335991930597, 'lr': 0.002428396450034936, 'weight_decay': 0.05750366129158036, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 10:00:53,272] Trial 67 pruned. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.270032 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3998085396934203, 'lr': 0.0026450582820101093, 'weight_decay': 0.060413638902758963, 'batch_size': 32} - Best Value (CSI): 0.357045 - Best Trial: 66 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39867335991930597, 'lr': 0.002428396450034936, 'weight_decay': 0.05750366129158036, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 10:01:32,537] Trial 68 pruned. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.294118 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3587696613164656, 'lr': 0.008116271682448249, 'weight_decay': 0.08480804731238503, 'batch_size': 32} - Best Value (CSI): 0.357045 - Best Trial: 66 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39867335991930597, 'lr': 0.002428396450034936, 'weight_decay': 0.05750366129158036, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 10:02:12,714] Trial 69 pruned. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.303738 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.39168105543257464, 'lr': 0.0037960839899104774, 'weight_decay': 0.05977742124427266, 'batch_size': 32} - Best Value (CSI): 0.357045 - Best Trial: 66 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39867335991930597, 'lr': 0.002428396450034936, 'weight_decay': 0.05750366129158036, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 10:02:48,491] Trial 70 pruned. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.226812 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.33919688138707704, 'lr': 0.005793574422117081, 'weight_decay': 0.014304083608104918, 'batch_size': 32} - Best Value (CSI): 0.357045 - Best Trial: 66 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39867335991930597, 'lr': 0.002428396450034936, 'weight_decay': 0.05750366129158036, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 10:03:31,464] Trial 71 pruned. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.349112 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.38231592679760046, 'lr': 0.0022667869710546675, 'weight_decay': 0.021448581611157324, 'batch_size': 32} - Best Value (CSI): 0.357045 - Best Trial: 66 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39867335991930597, 'lr': 0.002428396450034936, 'weight_decay': 0.05750366129158036, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 10:03:41,433] Trial 72 pruned. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.238394 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.373451744147425, 'lr': 0.0015559298164676083, 'weight_decay': 0.04050027645557986, 'batch_size': 64} - Best Value (CSI): 0.357045 - Best Trial: 66 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39867335991930597, 'lr': 0.002428396450034936, 'weight_decay': 0.05750366129158036, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 10:04:03,450] Trial 73 pruned. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.313824 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39247715235059116, 'lr': 0.002931749053685896, 'weight_decay': 0.029049950434521743, 'batch_size': 64} - Best Value (CSI): 0.357045 - Best Trial: 66 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39867335991930597, 'lr': 0.002428396450034936, 'weight_decay': 0.05750366129158036, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 10:05:19,602] Trial 74 finished with value: 0.3254914410208114 and parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.36531840025471074, 'lr': 0.003596006231922426, 'weight_decay': 0.08288762241156256, 'batch_size': 32}. Best is trial 66 with value: 0.3570454117885781. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.325491 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.36531840025471074, 'lr': 0.003596006231922426, 'weight_decay': 0.08288762241156256, 'batch_size': 32} - Best Value (CSI): 0.357045 - Best Trial: 66 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39867335991930597, 'lr': 0.002428396450034936, 'weight_decay': 0.05750366129158036, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 10:05:40,064] Trial 75 pruned. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.321897 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3549992570151698, 'lr': 0.0012311933435854643, 'weight_decay': 0.03362076509770742, 'batch_size': 64} - Best Value (CSI): 0.357045 - Best Trial: 66 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39867335991930597, 'lr': 0.002428396450034936, 'weight_decay': 0.05750366129158036, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 10:05:43,200] Trial 76 pruned. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.217338 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3788901832364308, 'lr': 0.0022146880359427026, 'weight_decay': 0.048289915907297074, 'batch_size': 256} - Best Value (CSI): 0.357045 - Best Trial: 66 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39867335991930597, 'lr': 0.002428396450034936, 'weight_decay': 0.05750366129158036, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 10:06:03,405] Trial 77 pruned. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.251969 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3941576819842596, 'lr': 0.005009047787894385, 'weight_decay': 0.018440909907897002, 'batch_size': 32} - Best Value (CSI): 0.357045 - Best Trial: 66 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39867335991930597, 'lr': 0.002428396450034936, 'weight_decay': 0.05750366129158036, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 10:06:17,599] Trial 78 pruned. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.353005 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.37854116809675487, 'lr': 0.0018027162032029141, 'weight_decay': 0.070252053002538, 'batch_size': 128} - Best Value (CSI): 0.357045 - Best Trial: 66 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39867335991930597, 'lr': 0.002428396450034936, 'weight_decay': 0.05750366129158036, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 10:06:37,659] Trial 79 pruned. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.314286 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.34749793287239744, 'lr': 0.0029477608087059696, 'weight_decay': 0.024368751522866196, 'batch_size': 64} - Best Value (CSI): 0.357045 - Best Trial: 66 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39867335991930597, 'lr': 0.002428396450034936, 'weight_decay': 0.05750366129158036, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 10:06:55,263] Trial 80 pruned. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.213666 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.36366304410055217, 'lr': 0.003937726395727747, 'weight_decay': 0.0588287031400143, 'batch_size': 32} - Best Value (CSI): 0.357045 - Best Trial: 66 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39867335991930597, 'lr': 0.002428396450034936, 'weight_decay': 0.05750366129158036, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 10:08:20,701] Trial 81 finished with value: 0.3502052758792251 and parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.38795952346853324, 'lr': 0.0028552503046633997, 'weight_decay': 0.09777400569073981, 'batch_size': 32}. Best is trial 66 with value: 0.3570454117885781. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.350205 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.38795952346853324, 'lr': 0.0028552503046633997, 'weight_decay': 0.09777400569073981, 'batch_size': 32} - Best Value (CSI): 0.357045 - Best Trial: 66 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39867335991930597, 'lr': 0.002428396450034936, 'weight_decay': 0.05750366129158036, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 10:09:05,030] Trial 82 pruned. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.303821 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.387191299920261, 'lr': 0.0024609610009473427, 'weight_decay': 0.09947474296306784, 'batch_size': 32} - Best Value (CSI): 0.357045 - Best Trial: 66 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39867335991930597, 'lr': 0.002428396450034936, 'weight_decay': 0.05750366129158036, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 10:09:41,745] Trial 83 pruned. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.290406 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3735405783401792, 'lr': 0.003357012198279736, 'weight_decay': 0.08178467543470748, 'batch_size': 32} - Best Value (CSI): 0.357045 - Best Trial: 66 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39867335991930597, 'lr': 0.002428396450034936, 'weight_decay': 0.05750366129158036, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 10:10:02,019] Trial 84 pruned. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.223131 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.39672267276909806, 'lr': 0.001515583027154899, 'weight_decay': 0.06986527894303228, 'batch_size': 32} - Best Value (CSI): 0.357045 - Best Trial: 66 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39867335991930597, 'lr': 0.002428396450034936, 'weight_decay': 0.05750366129158036, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 10:10:11,185] Trial 85 pruned. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.238733 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39966671495446976, 'lr': 0.0021717687919341703, 'weight_decay': 0.04869237195348397, 'batch_size': 64} - Best Value (CSI): 0.357045 - Best Trial: 66 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39867335991930597, 'lr': 0.002428396450034936, 'weight_decay': 0.05750366129158036, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 10:10:54,876] Trial 86 pruned. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.320952 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.38493003439675183, 'lr': 0.0028461644958205903, 'weight_decay': 0.04157143041290745, 'batch_size': 32} - Best Value (CSI): 0.357045 - Best Trial: 66 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39867335991930597, 'lr': 0.002428396450034936, 'weight_decay': 0.05750366129158036, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 10:11:16,724] Trial 87 pruned. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.289819 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.3906116592514006, 'lr': 0.004966245136988055, 'weight_decay': 0.05366504775031226, 'batch_size': 64} - Best Value (CSI): 0.357045 - Best Trial: 66 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39867335991930597, 'lr': 0.002428396450034936, 'weight_decay': 0.05750366129158036, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 10:12:37,285] Trial 88 finished with value: 0.3433431303817149 and parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3688878510187413, 'lr': 0.001760461511215137, 'weight_decay': 0.08700580055179918, 'batch_size': 32}. Best is trial 66 with value: 0.3570454117885781. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.343343 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3688878510187413, 'lr': 0.001760461511215137, 'weight_decay': 0.08700580055179918, 'batch_size': 32} - Best Value (CSI): 0.357045 - Best Trial: 66 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39867335991930597, 'lr': 0.002428396450034936, 'weight_decay': 0.05750366129158036, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 10:12:57,465] Trial 89 pruned. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.263870 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3712758274504494, 'lr': 0.00672419563652991, 'weight_decay': 0.06848157568229121, 'batch_size': 32} - Best Value (CSI): 0.357045 - Best Trial: 66 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39867335991930597, 'lr': 0.002428396450034936, 'weight_decay': 0.05750366129158036, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 10:13:44,150] Trial 90 pruned. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.340319 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.35721621167499296, 'lr': 0.004455954490231797, 'weight_decay': 0.08536238769155813, 'batch_size': 32} - Best Value (CSI): 0.357045 - Best Trial: 66 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39867335991930597, 'lr': 0.002428396450034936, 'weight_decay': 0.05750366129158036, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 10:14:28,432] Trial 91 pruned. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.319352 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3806812881186199, 'lr': 0.001843904051720861, 'weight_decay': 0.0892469184978765, 'batch_size': 32} - Best Value (CSI): 0.357045 - Best Trial: 66 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39867335991930597, 'lr': 0.002428396450034936, 'weight_decay': 0.05750366129158036, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 10:14:47,034] Trial 92 pruned. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.223404 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.38732236434942585, 'lr': 0.0024755879204806587, 'weight_decay': 0.06334773289495309, 'batch_size': 32} - Best Value (CSI): 0.357045 - Best Trial: 66 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39867335991930597, 'lr': 0.002428396450034936, 'weight_decay': 0.05750366129158036, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 10:14:56,945] Trial 93 pruned. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.242228 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3648020536618921, 'lr': 0.0014141038051556324, 'weight_decay': 0.0377598049989734, 'batch_size': 64} - Best Value (CSI): 0.357045 - Best Trial: 66 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39867335991930597, 'lr': 0.002428396450034936, 'weight_decay': 0.05750366129158036, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 10:15:15,553] Trial 94 pruned. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.211623 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.379058914365698, 'lr': 0.0034191489024478963, 'weight_decay': 0.07676492874261205, 'batch_size': 32} - Best Value (CSI): 0.357045 - Best Trial: 66 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39867335991930597, 'lr': 0.002428396450034936, 'weight_decay': 0.05750366129158036, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 10:15:19,570] Trial 95 pruned. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.222732 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3916293292183291, 'lr': 0.0018202636148758502, 'weight_decay': 0.032327567507564776, 'batch_size': 256} - Best Value (CSI): 0.357045 - Best Trial: 66 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39867335991930597, 'lr': 0.002428396450034936, 'weight_decay': 0.05750366129158036, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 10:15:30,738] Trial 96 pruned. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.248285 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.3697266245122834, 'lr': 0.0011733907062980438, 'weight_decay': 0.05464305256180052, 'batch_size': 64} - Best Value (CSI): 0.357045 - Best Trial: 66 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39867335991930597, 'lr': 0.002428396450034936, 'weight_decay': 0.05750366129158036, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 10:15:42,741] Trial 97 pruned. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.307026 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3946511746981355, 'lr': 0.0021358668187100743, 'weight_decay': 0.01946970464946195, 'batch_size': 128} - Best Value (CSI): 0.357045 - Best Trial: 66 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39867335991930597, 'lr': 0.002428396450034936, 'weight_decay': 0.05750366129158036, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 10:16:23,212] Trial 98 pruned. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.313953 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3835370318417222, 'lr': 0.00288991794879386, 'weight_decay': 0.025845123377123136, 'batch_size': 32} - Best Value (CSI): 0.357045 - Best Trial: 66 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39867335991930597, 'lr': 0.002428396450034936, 'weight_decay': 0.05750366129158036, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 10:17:04,943] Trial 99 finished with value: 0.3257227140205455 and parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3528007079196296, 'lr': 0.003907616936352821, 'weight_decay': 0.0938273790795194, 'batch_size': 64}. Best is trial 66 with value: 0.3570454117885781. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.325723 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3528007079196296, 'lr': 0.003907616936352821, 'weight_decay': 0.0938273790795194, 'batch_size': 64} - Best Value (CSI): 0.357045 - Best Trial: 66 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39867335991930597, 'lr': 0.002428396450034936, 'weight_decay': 0.05750366129158036, 'batch_size': 32} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.3570 -Best Hyperparameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39867335991930597, 'lr': 0.002428396450034936, 'weight_decay': 0.05750366129158036, 'batch_size': 32} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.3212 - - 최종 CSI: 0.3257 - - 최고 CSI: 0.3570 - - 최저 CSI: 0.1754 - - 평균 CSI: 0.2830 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/deepgbm_pure_daegu_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 16, Best CSI: 0.2918 - Fold 1 학습 완료 (검증 CSI: 0.2918) -Fold 2 학습 중... - Early stopping at epoch 52, Best CSI: 0.3634 - Fold 2 학습 완료 (검증 CSI: 0.3634) -Fold 3 학습 중... - Early stopping at epoch 42, Best CSI: 0.4041 - Fold 3 학습 완료 (검증 CSI: 0.4041) - -모든 모델 저장 완료: ../save_model/deepgbm_optima/deepgbm_pure_daegu.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/deepgbm_optima/scaler/deepgbm_pure_daegu_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: - - . - - . - - / - - s - - a - - v - - e - - _ - - m - - o - - d - - e - - l - - / - - d - - e - - e - - p - - g - - b - - m - - _ - - o - - p - - t - - i - - m - - a - - / - - d - - e - - e - - p - - g - - b - - m - - _ - - p - - u - - r - - e - - _ - - d - - a - - e - - g - - u - - . - - p - - k - - l - -✓ 완료: deepgbm_pure/deepgbm_pure_daegu.py (소요 시간: 3350초) - ----------------------------------------- -실행 중: deepgbm_pure/deepgbm_pure_daejeon.py -시작 시간: 2025-12-25 10:18:55 ----------------------------------------- -[I 2025-12-25 10:18:56,335] A new study created in memory with name: no-name-f56bbbe8-81da-4176-a3ec-4b1a48cf8efc - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 10:19:54,276] Trial 0 finished with value: 0.3940257777440504 and parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.17758344925738373, 'lr': 2.7316325835544222e-05, 'weight_decay': 0.021776773502379807, 'batch_size': 128}. Best is trial 0 with value: 0.3940257777440504. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.394026 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.17758344925738373, 'lr': 2.7316325835544222e-05, 'weight_decay': 0.021776773502379807, 'batch_size': 128} - Best Value (CSI): 0.394026 - Best Trial: 0 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.17758344925738373, 'lr': 2.7316325835544222e-05, 'weight_decay': 0.021776773502379807, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 10:20:17,043] Trial 1 finished with value: 0.4284010028039515 and parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.10786293631745852, 'lr': 0.006228976616201245, 'weight_decay': 0.001575405483765232, 'batch_size': 256}. Best is trial 1 with value: 0.4284010028039515. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.428401 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.10786293631745852, 'lr': 0.006228976616201245, 'weight_decay': 0.001575405483765232, 'batch_size': 256} - Best Value (CSI): 0.428401 - Best Trial: 1 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.10786293631745852, 'lr': 0.006228976616201245, 'weight_decay': 0.001575405483765232, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 10:22:12,150] Trial 2 finished with value: 0.44796062291358374 and parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19550123497683172, 'lr': 0.00018397591710369075, 'weight_decay': 0.0276880883039035, 'batch_size': 32}. Best is trial 2 with value: 0.44796062291358374. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.447961 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19550123497683172, 'lr': 0.00018397591710369075, 'weight_decay': 0.0276880883039035, 'batch_size': 32} - Best Value (CSI): 0.447961 - Best Trial: 2 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19550123497683172, 'lr': 0.00018397591710369075, 'weight_decay': 0.0276880883039035, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 10:22:38,198] Trial 3 finished with value: 0.4294886087978618 and parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.39221049193913693, 'lr': 0.007119721637040267, 'weight_decay': 0.00041957646534478713, 'batch_size': 256}. Best is trial 2 with value: 0.44796062291358374. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.429489 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.39221049193913693, 'lr': 0.007119721637040267, 'weight_decay': 0.00041957646534478713, 'batch_size': 256} - Best Value (CSI): 0.447961 - Best Trial: 2 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19550123497683172, 'lr': 0.00018397591710369075, 'weight_decay': 0.0276880883039035, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 10:23:10,388] Trial 4 finished with value: 0.4231542863761202 and parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.24286038022638232, 'lr': 0.0005746597344174932, 'weight_decay': 0.0002448536974952823, 'batch_size': 256}. Best is trial 2 with value: 0.44796062291358374. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.423154 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.24286038022638232, 'lr': 0.0005746597344174932, 'weight_decay': 0.0002448536974952823, 'batch_size': 256} - Best Value (CSI): 0.447961 - Best Trial: 2 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19550123497683172, 'lr': 0.00018397591710369075, 'weight_decay': 0.0276880883039035, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 10:23:16,422] Trial 5 pruned. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.305292 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2361275363708682, 'lr': 0.0001406453553691641, 'weight_decay': 0.0002677748612860312, 'batch_size': 64} - Best Value (CSI): 0.447961 - Best Trial: 2 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19550123497683172, 'lr': 0.00018397591710369075, 'weight_decay': 0.0276880883039035, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 10:23:30,054] Trial 6 pruned. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.324919 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.18441274310179545, 'lr': 0.008372335958071988, 'weight_decay': 0.009921027153441777, 'batch_size': 64} - Best Value (CSI): 0.447961 - Best Trial: 2 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19550123497683172, 'lr': 0.00018397591710369075, 'weight_decay': 0.0276880883039035, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 10:24:44,509] Trial 7 finished with value: 0.44137434465368636 and parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.21712007836564223, 'lr': 0.0010301173763569054, 'weight_decay': 0.00018922793095417677, 'batch_size': 32}. Best is trial 2 with value: 0.44796062291358374. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.441374 - Parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.21712007836564223, 'lr': 0.0010301173763569054, 'weight_decay': 0.00018922793095417677, 'batch_size': 32} - Best Value (CSI): 0.447961 - Best Trial: 2 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19550123497683172, 'lr': 0.00018397591710369075, 'weight_decay': 0.0276880883039035, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 10:25:18,398] Trial 8 pruned. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.359331 - Parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.10174031801824389, 'lr': 0.004389836916405382, 'weight_decay': 0.0010073598478688751, 'batch_size': 32} - Best Value (CSI): 0.447961 - Best Trial: 2 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19550123497683172, 'lr': 0.00018397591710369075, 'weight_decay': 0.0276880883039035, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 10:26:31,849] Trial 9 finished with value: 0.4474030068492641 and parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.24100461910496837, 'lr': 0.0005508367785952316, 'weight_decay': 0.00011176796394356728, 'batch_size': 32}. Best is trial 2 with value: 0.44796062291358374. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.447403 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.24100461910496837, 'lr': 0.0005508367785952316, 'weight_decay': 0.00011176796394356728, 'batch_size': 32} - Best Value (CSI): 0.447961 - Best Trial: 2 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19550123497683172, 'lr': 0.00018397591710369075, 'weight_decay': 0.0276880883039035, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 10:26:35,380] Trial 10 pruned. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.102139 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3074171445210522, 'lr': 1.374169244555383e-05, 'weight_decay': 0.07159920497887605, 'batch_size': 128} - Best Value (CSI): 0.447961 - Best Trial: 2 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19550123497683172, 'lr': 0.00018397591710369075, 'weight_decay': 0.0276880883039035, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 10:28:06,126] Trial 11 finished with value: 0.44176866517291963 and parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.2965989807464764, 'lr': 0.00025755757245645914, 'weight_decay': 0.00010393759251923111, 'batch_size': 32}. Best is trial 2 with value: 0.44796062291358374. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.441769 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.2965989807464764, 'lr': 0.00025755757245645914, 'weight_decay': 0.00010393759251923111, 'batch_size': 32} - Best Value (CSI): 0.447961 - Best Trial: 2 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19550123497683172, 'lr': 0.00018397591710369075, 'weight_decay': 0.0276880883039035, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 10:28:41,278] Trial 12 pruned. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.358520 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15591991731909277, 'lr': 9.537414355974201e-05, 'weight_decay': 0.005286527972601182, 'batch_size': 32} - Best Value (CSI): 0.447961 - Best Trial: 2 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19550123497683172, 'lr': 0.00018397591710369075, 'weight_decay': 0.0276880883039035, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 10:29:10,855] Trial 13 pruned. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.365786 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.2821769476424921, 'lr': 0.0007790728521000511, 'weight_decay': 0.001929287979483621, 'batch_size': 32} - Best Value (CSI): 0.447961 - Best Trial: 2 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19550123497683172, 'lr': 0.00018397591710369075, 'weight_decay': 0.0276880883039035, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) -[I 2025-12-25 10:30:06,219] Trial 14 pruned. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.456051 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.21689046412806318, 'lr': 7.728360464581584e-05, 'weight_decay': 0.0007419050237730995, 'batch_size': 32} - Best Value (CSI): 0.447961 - Best Trial: 2 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19550123497683172, 'lr': 0.00018397591710369075, 'weight_decay': 0.0276880883039035, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 10:30:33,971] Trial 15 pruned. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.356061 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.25817284058981416, 'lr': 0.001850347988556737, 'weight_decay': 0.005216733581483976, 'batch_size': 32} - Best Value (CSI): 0.447961 - Best Trial: 2 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19550123497683172, 'lr': 0.00018397591710369075, 'weight_decay': 0.0276880883039035, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) -[I 2025-12-25 10:31:39,792] Trial 16 pruned. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.470544 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.14992656953168754, 'lr': 0.0015265137714518772, 'weight_decay': 0.0983651449381398, 'batch_size': 32} - Best Value (CSI): 0.447961 - Best Trial: 2 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19550123497683172, 'lr': 0.00018397591710369075, 'weight_decay': 0.0276880883039035, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 10:32:33,491] Trial 17 finished with value: 0.4381452253092051 and parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.1880953352024412, 'lr': 0.00037886502261606244, 'weight_decay': 0.01818815921281143, 'batch_size': 64}. Best is trial 2 with value: 0.44796062291358374. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.438145 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.1880953352024412, 'lr': 0.00037886502261606244, 'weight_decay': 0.01818815921281143, 'batch_size': 64} - Best Value (CSI): 0.447961 - Best Trial: 2 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19550123497683172, 'lr': 0.00018397591710369075, 'weight_decay': 0.0276880883039035, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 10:32:36,923] Trial 18 pruned. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.321202 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.3330196015457065, 'lr': 0.00021463797883342103, 'weight_decay': 0.0028311607704800774, 'batch_size': 128} - Best Value (CSI): 0.447961 - Best Trial: 2 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19550123497683172, 'lr': 0.00018397591710369075, 'weight_decay': 0.0276880883039035, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 10:34:22,603] Trial 19 finished with value: 0.44550214277536876 and parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.26656767420301647, 'lr': 0.0003879979835749484, 'weight_decay': 0.000626312802121689, 'batch_size': 32}. Best is trial 2 with value: 0.44796062291358374. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.445502 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.26656767420301647, 'lr': 0.0003879979835749484, 'weight_decay': 0.000626312802121689, 'batch_size': 32} - Best Value (CSI): 0.447961 - Best Trial: 2 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19550123497683172, 'lr': 0.00018397591710369075, 'weight_decay': 0.0276880883039035, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 10:35:01,869] Trial 20 pruned. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.351456 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.2152512874930491, 'lr': 6.62363139946012e-05, 'weight_decay': 0.00010599371320139144, 'batch_size': 32} - Best Value (CSI): 0.447961 - Best Trial: 2 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19550123497683172, 'lr': 0.00018397591710369075, 'weight_decay': 0.0276880883039035, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 10:35:36,497] Trial 21 pruned. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.358178 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.2596840246081209, 'lr': 0.00047567976201401765, 'weight_decay': 0.0007179026058299383, 'batch_size': 32} - Best Value (CSI): 0.447961 - Best Trial: 2 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19550123497683172, 'lr': 0.00018397591710369075, 'weight_decay': 0.0276880883039035, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) -[I 2025-12-25 10:36:48,237] Trial 22 pruned. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.458996 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.2700182567375296, 'lr': 0.0002386039837789117, 'weight_decay': 0.00037324124781802414, 'batch_size': 32} - Best Value (CSI): 0.447961 - Best Trial: 2 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19550123497683172, 'lr': 0.00018397591710369075, 'weight_decay': 0.0276880883039035, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) -[I 2025-12-25 10:37:44,495] Trial 23 pruned. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.460400 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.23512599467799639, 'lr': 0.00040289594597533573, 'weight_decay': 0.0005651259785087139, 'batch_size': 32} - Best Value (CSI): 0.447961 - Best Trial: 2 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19550123497683172, 'lr': 0.00018397591710369075, 'weight_decay': 0.0276880883039035, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 10:37:56,837] Trial 24 pruned. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.341657 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.2810198455930045, 'lr': 0.00019033391861993763, 'weight_decay': 0.0014249107574402892, 'batch_size': 32} - Best Value (CSI): 0.447961 - Best Trial: 2 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19550123497683172, 'lr': 0.00018397591710369075, 'weight_decay': 0.0276880883039035, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 10:38:28,454] Trial 25 pruned. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.360681 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.20319151903372795, 'lr': 0.0007174129353507367, 'weight_decay': 0.00016562421484712966, 'batch_size': 32} - Best Value (CSI): 0.447961 - Best Trial: 2 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19550123497683172, 'lr': 0.00018397591710369075, 'weight_decay': 0.0276880883039035, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 10:38:31,058] Trial 26 pruned. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.325668 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.24232206603313822, 'lr': 0.0003552029712005522, 'weight_decay': 0.00032897648222521704, 'batch_size': 256} - Best Value (CSI): 0.447961 - Best Trial: 2 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19550123497683172, 'lr': 0.00018397591710369075, 'weight_decay': 0.0276880883039035, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 10:38:34,860] Trial 27 pruned. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.283483 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3144041973281634, 'lr': 0.00013720752000779578, 'weight_decay': 0.0005403819295850753, 'batch_size': 128} - Best Value (CSI): 0.447961 - Best Trial: 2 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19550123497683172, 'lr': 0.00018397591710369075, 'weight_decay': 0.0276880883039035, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 10:38:42,540] Trial 28 pruned. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.341740 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.26723510652338134, 'lr': 0.0011477759727362804, 'weight_decay': 0.001098103737223824, 'batch_size': 64} - Best Value (CSI): 0.447961 - Best Trial: 2 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19550123497683172, 'lr': 0.00018397591710369075, 'weight_decay': 0.0276880883039035, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 10:38:46,212] Trial 29 pruned. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.257267 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19834801313021788, 'lr': 4.478766566695732e-05, 'weight_decay': 0.030639149608688625, 'batch_size': 128} - Best Value (CSI): 0.447961 - Best Trial: 2 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19550123497683172, 'lr': 0.00018397591710369075, 'weight_decay': 0.0276880883039035, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 10:40:27,838] Trial 30 finished with value: 0.44563089436342906 and parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16290277306152412, 'lr': 0.000140365906452286, 'weight_decay': 0.00016031182769459386, 'batch_size': 32}. Best is trial 2 with value: 0.44796062291358374. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.445631 - Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16290277306152412, 'lr': 0.000140365906452286, 'weight_decay': 0.00016031182769459386, 'batch_size': 32} - Best Value (CSI): 0.447961 - Best Trial: 2 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19550123497683172, 'lr': 0.00018397591710369075, 'weight_decay': 0.0276880883039035, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 10:41:57,436] Trial 31 finished with value: 0.45092661677493817 and parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32}. Best is trial 31 with value: 0.45092661677493817. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.450927 - Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 10:42:26,999] Trial 32 pruned. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.368065 - Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16675625046699152, 'lr': 0.00015953225883641141, 'weight_decay': 0.00014779662018541003, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 10:42:55,224] Trial 33 pruned. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.351698 - Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.13494690280017937, 'lr': 0.00011600837026802775, 'weight_decay': 0.00022982444510811787, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 10:42:57,599] Trial 34 pruned. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.248659 - Parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.17701092536761073, 'lr': 5.491546995207874e-05, 'weight_decay': 0.00013200257820501524, 'batch_size': 256} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 10:43:07,251] Trial 35 pruned. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.300913 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.12873631820960724, 'lr': 4.121408343664626e-05, 'weight_decay': 0.00021687127661351835, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 10:43:09,639] Trial 36 pruned. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.271204 - Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.17241730428555052, 'lr': 9.698586914992203e-05, 'weight_decay': 0.0003246476157711589, 'batch_size': 256} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 10:43:26,867] Trial 37 pruned. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.373710 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.19331843895714265, 'lr': 0.00025991400416075614, 'weight_decay': 0.00015898969767533323, 'batch_size': 64} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) -[I 2025-12-25 10:44:33,713] Trial 38 pruned. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.458555 - Parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.12086315293412832, 'lr': 0.00015735025711385826, 'weight_decay': 0.0002460590433535005, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 10:45:03,791] Trial 39 pruned. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.361816 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.15014956165690851, 'lr': 0.00010391810256317822, 'weight_decay': 0.00047919472474369616, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 10:45:06,458] Trial 40 pruned. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.325378 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.17096248999079647, 'lr': 0.0002964521352721603, 'weight_decay': 0.00010862750489254662, 'batch_size': 256} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) -[I 2025-12-25 10:46:10,524] Trial 41 pruned. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.479853 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.22954684519160748, 'lr': 0.0005244046027372838, 'weight_decay': 0.0002863550871079466, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 10:48:09,785] Trial 42 finished with value: 0.44288449269943536 and parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.21086105679611689, 'lr': 0.00018922231431416482, 'weight_decay': 0.00018861334586335203, 'batch_size': 32}. Best is trial 31 with value: 0.45092661677493817. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.442884 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.21086105679611689, 'lr': 0.00018922231431416482, 'weight_decay': 0.00018861334586335203, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) -[I 2025-12-25 10:49:09,842] Trial 43 pruned. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.472241 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1876455851451055, 'lr': 0.0003083782688071137, 'weight_decay': 0.0004326018440100582, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 10:49:21,439] Trial 44 pruned. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.328707 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2250780982760359, 'lr': 0.00013695449338410904, 'weight_decay': 0.00010075054262964053, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) -[I 2025-12-25 10:50:37,969] Trial 45 pruned. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.458301 - Parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.2035282336826644, 'lr': 0.0006939592800898452, 'weight_decay': 0.00018704025862421313, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) -[I 2025-12-25 10:51:36,223] Trial 46 pruned. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.469697 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.24624562037091385, 'lr': 0.0004952297078784309, 'weight_decay': 0.00028668337572516076, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 10:51:41,190] Trial 47 pruned. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.278851 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1609088205448429, 'lr': 7.975730037256229e-05, 'weight_decay': 0.0001368222878398568, 'batch_size': 64} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 10:51:45,100] Trial 48 pruned. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.317222 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.18205311325636536, 'lr': 0.00022542914484937102, 'weight_decay': 0.00021137904151618414, 'batch_size': 128} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 10:52:15,488] Trial 49 pruned. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.362909 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1486128398238962, 'lr': 0.0002882322870811331, 'weight_decay': 0.00040121454698792533, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 10:53:14,300] Trial 50 finished with value: 0.4449080652916848 and parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.22534581779179358, 'lr': 0.00039456874354341725, 'weight_decay': 0.00013003374752694225, 'batch_size': 32}. Best is trial 31 with value: 0.45092661677493817. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.444908 - Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.22534581779179358, 'lr': 0.00039456874354341725, 'weight_decay': 0.00013003374752694225, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 10:53:42,727] Trial 51 pruned. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.374598 - Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.22252000695493981, 'lr': 0.00037323578325284455, 'weight_decay': 0.0001300415482928195, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 10:55:03,374] Trial 52 finished with value: 0.44783157470047347 and parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2353580566763135, 'lr': 0.0001875079707140538, 'weight_decay': 0.0001679099519247204, 'batch_size': 32}. Best is trial 31 with value: 0.45092661677493817. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.447832 - Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2353580566763135, 'lr': 0.0001875079707140538, 'weight_decay': 0.0001679099519247204, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 10:55:29,377] Trial 53 pruned. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.363239 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.24764265119382256, 'lr': 0.00017624490605091533, 'weight_decay': 0.000316538981143567, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 10:55:59,989] Trial 54 pruned. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.367969 - Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.23384639311775518, 'lr': 0.00013297757535418885, 'weight_decay': 0.00019233929633079164, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 10:56:09,436] Trial 55 pruned. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.346703 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.20500618706181212, 'lr': 8.944158752133566e-05, 'weight_decay': 0.0006589457111997837, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 10:56:19,090] Trial 56 pruned. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.347613 - Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.19038499615781068, 'lr': 0.00023070621900657832, 'weight_decay': 0.0008788599040695274, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 10:56:30,802] Trial 57 pruned. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.349686 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.25616938334999234, 'lr': 0.0005833854006139874, 'weight_decay': 0.0002546188521164588, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 10:57:00,534] Trial 58 pruned. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.365608 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.2134841728083585, 'lr': 0.00019062912206538918, 'weight_decay': 0.0004267371126775438, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 10:57:03,710] Trial 59 pruned. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.269841 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.23635367306251712, 'lr': 0.00011316471261159884, 'weight_decay': 0.000599674340211041, 'batch_size': 128} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 10:57:09,967] Trial 60 pruned. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.325553 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.18183869801461044, 'lr': 0.0002890162670057679, 'weight_decay': 0.00017659309723594204, 'batch_size': 64} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 10:58:16,287] Trial 61 finished with value: 0.44691647515621885 and parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.22384233581455343, 'lr': 0.0004056328478853049, 'weight_decay': 0.00012528385825803383, 'batch_size': 32}. Best is trial 31 with value: 0.45092661677493817. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.446916 - Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.22384233581455343, 'lr': 0.0004056328478853049, 'weight_decay': 0.00012528385825803383, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 10:58:45,636] Trial 62 pruned. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.369038 - Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2522937657290299, 'lr': 0.0004061658358385566, 'weight_decay': 0.00010460293299328125, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 11:00:15,135] Trial 63 finished with value: 0.44322883510804106 and parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.21915533649848215, 'lr': 0.00021876737471631307, 'weight_decay': 0.00015905219038225696, 'batch_size': 32}. Best is trial 31 with value: 0.45092661677493817. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.443229 - Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.21915533649848215, 'lr': 0.00021876737471631307, 'weight_decay': 0.00015905219038225696, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 11:01:17,620] Trial 64 finished with value: 0.44503156795509397 and parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.19501756533920095, 'lr': 0.0008938000277554096, 'weight_decay': 0.00023310496818787068, 'batch_size': 32}. Best is trial 31 with value: 0.45092661677493817. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.445032 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.19501756533920095, 'lr': 0.0008938000277554096, 'weight_decay': 0.00023310496818787068, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 11:01:44,506] Trial 65 pruned. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.370956 - Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2416350737613313, 'lr': 0.00015901090085894672, 'weight_decay': 0.00035744714662713166, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 11:02:53,378] Trial 66 finished with value: 0.4470467394559974 and parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20526961014840067, 'lr': 0.0006078197345344748, 'weight_decay': 0.00012884051599414674, 'batch_size': 32}. Best is trial 31 with value: 0.45092661677493817. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.447047 - Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20526961014840067, 'lr': 0.0006078197345344748, 'weight_decay': 0.00012884051599414674, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 11:02:55,906] Trial 67 pruned. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.325373 - Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2087970596835425, 'lr': 0.0005671930854327032, 'weight_decay': 0.00012473025712066664, 'batch_size': 256} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 11:03:05,442] Trial 68 pruned. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.342911 - Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.19955119386976944, 'lr': 0.00045537676548894096, 'weight_decay': 0.00016877800353146528, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 11:03:15,234] Trial 69 pruned. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.348742 - Parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.1640846878998979, 'lr': 0.0006740869037562875, 'weight_decay': 0.00010045534702508177, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 11:03:24,794] Trial 70 pruned. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.348269 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.17636156404103775, 'lr': 0.000326561617769869, 'weight_decay': 0.0001484936501589295, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 11:03:34,578] Trial 71 pruned. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.353867 - Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.21624098404173955, 'lr': 0.00026609817482095696, 'weight_decay': 0.00024946685305520286, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 11:04:58,301] Trial 72 finished with value: 0.4398823712442786 and parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.23324133184884896, 'lr': 0.0009125249480122455, 'weight_decay': 0.0001290717970946803, 'batch_size': 32}. Best is trial 31 with value: 0.45092661677493817. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.439882 - Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.23324133184884896, 'lr': 0.0009125249480122455, 'weight_decay': 0.0001290717970946803, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 11:05:32,220] Trial 73 pruned. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.373050 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.2628981944133996, 'lr': 0.0003461335497400206, 'weight_decay': 0.00020299474135992415, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 11:07:29,529] Trial 74 finished with value: 0.4470939291072689 and parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.18809237972564313, 'lr': 0.00043164969675095775, 'weight_decay': 0.00028846416050752746, 'batch_size': 32}. Best is trial 31 with value: 0.45092661677493817. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.447094 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.18809237972564313, 'lr': 0.00043164969675095775, 'weight_decay': 0.00028846416050752746, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 11:07:41,522] Trial 75 pruned. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.356356 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.1861684694689218, 'lr': 0.000122330432587066, 'weight_decay': 0.00015315030259584818, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 11:07:44,797] Trial 76 pruned. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.302338 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.19342946573197373, 'lr': 0.00047077320391525183, 'weight_decay': 0.0001199203836453875, 'batch_size': 128} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 11:08:15,242] Trial 77 pruned. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.365578 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.17209390123887075, 'lr': 0.00018779049269951228, 'weight_decay': 0.0002945060132333284, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 11:08:20,688] Trial 78 pruned. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.346376 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.20817847192257277, 'lr': 0.0002520395600091549, 'weight_decay': 0.00021203455429129556, 'batch_size': 64} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 11:08:30,318] Trial 79 pruned. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.340623 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.19861827932542192, 'lr': 0.0006074974423350181, 'weight_decay': 0.00016328502639119434, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 11:08:32,933] Trial 80 pruned. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.350890 - Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15822387547904782, 'lr': 0.0004499197607492598, 'weight_decay': 0.00011603328705404967, 'batch_size': 256} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 11:09:05,494] Trial 81 pruned. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.367177 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.22541990845969198, 'lr': 0.0003272112901353542, 'weight_decay': 0.00025560756922716023, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 11:09:15,838] Trial 82 pruned. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.340150 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1816931667907011, 'lr': 0.0007132901563793507, 'weight_decay': 0.0005080017880859748, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 11:09:26,466] Trial 83 pruned. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.342778 - Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.24372820552870172, 'lr': 0.0001495679666546287, 'weight_decay': 0.00036359602480958266, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 11:09:41,321] Trial 84 pruned. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.339308 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2705577798724165, 'lr': 0.001189334868716753, 'weight_decay': 0.0001873422840225167, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 11:09:53,960] Trial 85 pruned. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.337116 - Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.21527807818932088, 'lr': 0.0005407937476241713, 'weight_decay': 0.00014109386621058518, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 11:11:45,443] Trial 86 finished with value: 0.4443041849559564 and parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.20435401557569322, 'lr': 0.00021299488973214924, 'weight_decay': 0.00021838328707681309, 'batch_size': 32}. Best is trial 31 with value: 0.45092661677493817. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.444304 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.20435401557569322, 'lr': 0.00021299488973214924, 'weight_decay': 0.00021838328707681309, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 11:12:13,694] Trial 87 pruned. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.366358 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.16945769125407717, 'lr': 0.00038067314389826114, 'weight_decay': 0.00011675647990632944, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 11:12:24,415] Trial 88 pruned. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.342822 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2501958176440875, 'lr': 0.00028296897502149955, 'weight_decay': 0.0002812145432083346, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 11:12:56,264] Trial 89 pruned. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.351485 - Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.23888912136217025, 'lr': 0.00011107401275892124, 'weight_decay': 0.00017624811891272287, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) -[I 2025-12-25 11:13:56,756] Trial 90 pruned. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.460808 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.2262068479595044, 'lr': 0.00016801307310289454, 'weight_decay': 0.00014236302218727316, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 11:14:08,033] Trial 91 pruned. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.356450 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.19614953200914115, 'lr': 0.000725124378595637, 'weight_decay': 0.00023406899859013962, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 11:14:38,808] Trial 92 pruned. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.354357 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.18994171413825792, 'lr': 0.0008954796529042835, 'weight_decay': 0.00021733150346510858, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 11:15:06,114] Trial 93 pruned. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.359350 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.175648407831703, 'lr': 0.0005760253393067626, 'weight_decay': 0.00032705549815717836, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 11:15:19,825] Trial 94 pruned. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.352493 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.21156317457465149, 'lr': 0.0008142655809860179, 'weight_decay': 0.00016614841896659646, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 11:15:24,619] Trial 95 pruned. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.337401 - Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.22023410506325738, 'lr': 0.0004350784442349151, 'weight_decay': 0.00011046382731770107, 'batch_size': 128} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 11:16:00,521] Trial 96 pruned. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.368339 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.19511875586890368, 'lr': 0.0003847677114332395, 'weight_decay': 0.00026804109748029, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 11:16:08,093] Trial 97 pruned. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.311421 - Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.18355035484571125, 'lr': 0.00014311589142438976, 'weight_decay': 0.00014836777234701758, 'batch_size': 64} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 11:16:44,160] Trial 98 pruned. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.368051 - Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.166272634246498, 'lr': 0.0003223406215163742, 'weight_decay': 0.0004613109161087418, 'batch_size': 32} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 11:16:47,270] Trial 99 pruned. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.327051 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.23184998426367662, 'lr': 0.0004942548010027101, 'weight_decay': 0.0001931505851213513, 'batch_size': 256} - Best Value (CSI): 0.450927 - Best Trial: 31 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.4509 -Best Hyperparameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16512768923755844, 'lr': 0.00013316728360925615, 'weight_decay': 0.0001651587899552549, 'batch_size': 32} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.3940 - - 최종 CSI: 0.3271 - - 최고 CSI: 0.4799 - - 최저 CSI: 0.1021 - - 평균 CSI: 0.3726 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/deepgbm_pure_daejeon_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 56, Best CSI: 0.3744 - Fold 1 학습 완료 (검증 CSI: 0.3744) -Fold 2 학습 중... - Early stopping at epoch 27, Best CSI: 0.4690 - Fold 2 학습 완료 (검증 CSI: 0.4690) -Fold 3 학습 중... - Early stopping at epoch 27, Best CSI: 0.4717 - Fold 3 학습 완료 (검증 CSI: 0.4717) - -모든 모델 저장 완료: ../save_model/deepgbm_optima/deepgbm_pure_daejeon.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/deepgbm_optima/scaler/deepgbm_pure_daejeon_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: - - . - - . - - / - - s - - a - - v - - e - - _ - - m - - o - - d - - e - - l - - / - - d - - e - - e - - p - - g - - b - - m - - _ - - o - - p - - t - - i - - m - - a - - / - - d - - e - - e - - p - - g - - b - - m - - _ - - p - - u - - r - - e - - _ - - d - - a - - e - - j - - e - - o - - n - - . - - p - - k - - l - -✓ 완료: deepgbm_pure/deepgbm_pure_daejeon.py (소요 시간: 3592초) - ----------------------------------------- -실행 중: deepgbm_pure/deepgbm_pure_gwangju.py -시작 시간: 2025-12-25 11:18:47 ----------------------------------------- -[I 2025-12-25 11:18:49,190] A new study created in memory with name: no-name-2f87277f-279f-499f-afaa-0740b860cc63 - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 114.66666666666667, 1: 4.335063009636768, 2: 0.3622398414271556} (클래스별 샘플 수: {0: 51, 1: 1349, 2: 16144}) -[I 2025-12-25 11:19:44,580] Trial 0 finished with value: 0.443918453722397 and parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.39144524175354123, 'lr': 0.00181996974931356, 'weight_decay': 0.0012848593150166913, 'batch_size': 128}. Best is trial 0 with value: 0.443918453722397. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.443918 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.39144524175354123, 'lr': 0.00181996974931356, 'weight_decay': 0.0012848593150166913, 'batch_size': 128} - Best Value (CSI): 0.443918 - Best Trial: 0 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.39144524175354123, 'lr': 0.00181996974931356, 'weight_decay': 0.0012848593150166913, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 114.66666666666667, 1: 4.335063009636768, 2: 0.3622398414271556} (클래스별 샘플 수: {0: 51, 1: 1349, 2: 16144}) -[I 2025-12-25 11:20:42,499] Trial 1 finished with value: 0.4477261877611352 and parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15492701504622297, 'lr': 0.004790714575437963, 'weight_decay': 0.01894502304388308, 'batch_size': 128}. Best is trial 1 with value: 0.4477261877611352. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.447726 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15492701504622297, 'lr': 0.004790714575437963, 'weight_decay': 0.01894502304388308, 'batch_size': 128} - Best Value (CSI): 0.447726 - Best Trial: 1 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15492701504622297, 'lr': 0.004790714575437963, 'weight_decay': 0.01894502304388308, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 114.66666666666667, 1: 4.335063009636768, 2: 0.3622398414271556} (클래스별 샘플 수: {0: 51, 1: 1349, 2: 16144}) -[I 2025-12-25 11:21:38,913] Trial 2 finished with value: 0.402424804774832 and parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.11445791944342971, 'lr': 2.946647583132162e-05, 'weight_decay': 0.001416192107875026, 'batch_size': 128}. Best is trial 1 with value: 0.4477261877611352. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.402425 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.11445791944342971, 'lr': 2.946647583132162e-05, 'weight_decay': 0.001416192107875026, 'batch_size': 128} - Best Value (CSI): 0.447726 - Best Trial: 1 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15492701504622297, 'lr': 0.004790714575437963, 'weight_decay': 0.01894502304388308, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 114.66666666666667, 1: 4.335063009636768, 2: 0.3622398414271556} (클래스별 샘플 수: {0: 51, 1: 1349, 2: 16144}) -[I 2025-12-25 11:22:55,343] Trial 3 finished with value: 0.44462301822331485 and parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.24011263809276123, 'lr': 0.0009075865612920347, 'weight_decay': 0.09789385037826631, 'batch_size': 64}. Best is trial 1 with value: 0.4477261877611352. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.444623 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.24011263809276123, 'lr': 0.0009075865612920347, 'weight_decay': 0.09789385037826631, 'batch_size': 64} - Best Value (CSI): 0.447726 - Best Trial: 1 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15492701504622297, 'lr': 0.004790714575437963, 'weight_decay': 0.01894502304388308, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 114.66666666666667, 1: 4.335063009636768, 2: 0.3622398414271556} (클래스별 샘플 수: {0: 51, 1: 1349, 2: 16144}) -[I 2025-12-25 11:23:52,277] Trial 4 finished with value: 0.4431957741393968 and parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.15610275129305623, 'lr': 0.0005037997854858172, 'weight_decay': 0.001715701217840938, 'batch_size': 64}. Best is trial 1 with value: 0.4477261877611352. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.443196 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.15610275129305623, 'lr': 0.0005037997854858172, 'weight_decay': 0.001715701217840938, 'batch_size': 64} - Best Value (CSI): 0.447726 - Best Trial: 1 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15492701504622297, 'lr': 0.004790714575437963, 'weight_decay': 0.01894502304388308, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:23:55,746] Trial 5 pruned. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.216769 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.20560001737328243, 'lr': 3.860764391436906e-05, 'weight_decay': 0.00015051664796118694, 'batch_size': 256} - Best Value (CSI): 0.447726 - Best Trial: 1 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15492701504622297, 'lr': 0.004790714575437963, 'weight_decay': 0.01894502304388308, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:24:02,858] Trial 6 pruned. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.313668 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3948674082691017, 'lr': 0.0057228817532646295, 'weight_decay': 0.0003795042856829671, 'batch_size': 64} - Best Value (CSI): 0.447726 - Best Trial: 1 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15492701504622297, 'lr': 0.004790714575437963, 'weight_decay': 0.01894502304388308, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:24:06,139] Trial 7 pruned. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.218336 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2506879114711197, 'lr': 3.0067409752387486e-05, 'weight_decay': 0.004035747466529336, 'batch_size': 256} - Best Value (CSI): 0.447726 - Best Trial: 1 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15492701504622297, 'lr': 0.004790714575437963, 'weight_decay': 0.01894502304388308, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:24:24,484] Trial 8 pruned. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.327247 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.1269563140110468, 'lr': 1.1854992028013826e-05, 'weight_decay': 0.0008672004564048775, 'batch_size': 32} - Best Value (CSI): 0.447726 - Best Trial: 1 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15492701504622297, 'lr': 0.004790714575437963, 'weight_decay': 0.01894502304388308, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:24:27,399] Trial 9 pruned. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.262048 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.10050460378868137, 'lr': 4.605353807940237e-05, 'weight_decay': 0.0003409778771938715, 'batch_size': 256} - Best Value (CSI): 0.447726 - Best Trial: 1 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15492701504622297, 'lr': 0.004790714575437963, 'weight_decay': 0.01894502304388308, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:24:35,914] Trial 10 pruned. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.388386 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.18017921051676775, 'lr': 0.005025282055836632, 'weight_decay': 0.010463734332060904, 'batch_size': 128} - Best Value (CSI): 0.447726 - Best Trial: 1 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15492701504622297, 'lr': 0.004790714575437963, 'weight_decay': 0.01894502304388308, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 114.66666666666667, 1: 4.335063009636768, 2: 0.3622398414271556} (클래스별 샘플 수: {0: 51, 1: 1349, 2: 16144}) -[I 2025-12-25 11:26:01,428] Trial 11 finished with value: 0.4444390608624696 and parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.2447896833575917, 'lr': 0.001181616480669707, 'weight_decay': 0.08902792296398974, 'batch_size': 64}. Best is trial 1 with value: 0.4477261877611352. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.444439 - Parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.2447896833575917, 'lr': 0.001181616480669707, 'weight_decay': 0.08902792296398974, 'batch_size': 64} - Best Value (CSI): 0.447726 - Best Trial: 1 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15492701504622297, 'lr': 0.004790714575437963, 'weight_decay': 0.01894502304388308, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) -[I 2025-12-25 11:28:05,199] Trial 12 pruned. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.449731 - Parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.22143097066641632, 'lr': 0.00024328314710851678, 'weight_decay': 0.07561633852103439, 'batch_size': 32} - Best Value (CSI): 0.447726 - Best Trial: 1 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15492701504622297, 'lr': 0.004790714575437963, 'weight_decay': 0.01894502304388308, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:28:13,059] Trial 13 pruned. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.343730 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.28838196270098604, 'lr': 0.007960337783163797, 'weight_decay': 0.031113760681083867, 'batch_size': 64} - Best Value (CSI): 0.447726 - Best Trial: 1 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15492701504622297, 'lr': 0.004790714575437963, 'weight_decay': 0.01894502304388308, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:28:19,724] Trial 14 pruned. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.381265 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.17242930051212768, 'lr': 0.0020660756992890946, 'weight_decay': 0.024751178417005117, 'batch_size': 128} - Best Value (CSI): 0.447726 - Best Trial: 1 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15492701504622297, 'lr': 0.004790714575437963, 'weight_decay': 0.01894502304388308, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:28:28,775] Trial 15 pruned. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.351667 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3069640844837134, 'lr': 0.009980177084063775, 'weight_decay': 0.009418049221536795, 'batch_size': 64} - Best Value (CSI): 0.447726 - Best Trial: 1 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15492701504622297, 'lr': 0.004790714575437963, 'weight_decay': 0.01894502304388308, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:28:34,162] Trial 16 pruned. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.363636 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.1461200700875148, 'lr': 0.0031007436503946656, 'weight_decay': 0.04445745025302459, 'batch_size': 128} - Best Value (CSI): 0.447726 - Best Trial: 1 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15492701504622297, 'lr': 0.004790714575437963, 'weight_decay': 0.01894502304388308, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) -[I 2025-12-25 11:30:24,709] Trial 17 pruned. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.463050 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.19340084633140683, 'lr': 0.0008332627655977123, 'weight_decay': 0.0948936343101127, 'batch_size': 32} - Best Value (CSI): 0.447726 - Best Trial: 1 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15492701504622297, 'lr': 0.004790714575437963, 'weight_decay': 0.01894502304388308, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:30:29,761] Trial 18 pruned. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.370229 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.1493001352008992, 'lr': 0.0037527398623624993, 'weight_decay': 0.02390706960553259, 'batch_size': 128} - Best Value (CSI): 0.447726 - Best Trial: 1 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15492701504622297, 'lr': 0.004790714575437963, 'weight_decay': 0.01894502304388308, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 114.66666666666667, 1: 4.335063009636768, 2: 0.3622398414271556} (클래스별 샘플 수: {0: 51, 1: 1349, 2: 16144}) -[I 2025-12-25 11:31:39,992] Trial 19 finished with value: 0.4395199794410929 and parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.21922294740444473, 'lr': 0.0003020559054258976, 'weight_decay': 0.013809385812044673, 'batch_size': 64}. Best is trial 1 with value: 0.4477261877611352. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.439520 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.21922294740444473, 'lr': 0.0003020559054258976, 'weight_decay': 0.013809385812044673, 'batch_size': 64} - Best Value (CSI): 0.447726 - Best Trial: 1 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15492701504622297, 'lr': 0.004790714575437963, 'weight_decay': 0.01894502304388308, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:31:54,829] Trial 20 pruned. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.401717 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.17594665738436635, 'lr': 0.002446742382956489, 'weight_decay': 0.04954623350657012, 'batch_size': 64} - Best Value (CSI): 0.447726 - Best Trial: 1 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15492701504622297, 'lr': 0.004790714575437963, 'weight_decay': 0.01894502304388308, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:32:11,345] Trial 21 pruned. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.382947 - Parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.249573426364846, 'lr': 0.0014225397413278754, 'weight_decay': 0.09929622412385344, 'batch_size': 64} - Best Value (CSI): 0.447726 - Best Trial: 1 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15492701504622297, 'lr': 0.004790714575437963, 'weight_decay': 0.01894502304388308, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:32:29,143] Trial 22 pruned. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.407567 - Parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.23985764564827933, 'lr': 0.0010390261748889588, 'weight_decay': 0.04218664012411587, 'batch_size': 64} - Best Value (CSI): 0.447726 - Best Trial: 1 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15492701504622297, 'lr': 0.004790714575437963, 'weight_decay': 0.01894502304388308, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:32:40,795] Trial 23 pruned. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.398251 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.2726010304232981, 'lr': 0.0008359690756014077, 'weight_decay': 0.05953646234037236, 'batch_size': 64} - Best Value (CSI): 0.447726 - Best Trial: 1 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15492701504622297, 'lr': 0.004790714575437963, 'weight_decay': 0.01894502304388308, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:32:54,988] Trial 24 pruned. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.398034 - Parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.20606200203569666, 'lr': 0.0028421797964718813, 'weight_decay': 0.098244021388388, 'batch_size': 64} - Best Value (CSI): 0.447726 - Best Trial: 1 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15492701504622297, 'lr': 0.004790714575437963, 'weight_decay': 0.01894502304388308, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:32:59,501] Trial 25 pruned. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.386964 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.1344714837697332, 'lr': 0.0005198052606854128, 'weight_decay': 0.01974274705900937, 'batch_size': 128} - Best Value (CSI): 0.447726 - Best Trial: 1 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15492701504622297, 'lr': 0.004790714575437963, 'weight_decay': 0.01894502304388308, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:33:03,250] Trial 26 pruned. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.327608 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.16333327224538202, 'lr': 0.005295307085866455, 'weight_decay': 0.051317939561949175, 'batch_size': 256} - Best Value (CSI): 0.447726 - Best Trial: 1 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15492701504622297, 'lr': 0.004790714575437963, 'weight_decay': 0.01894502304388308, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:33:24,709] Trial 27 pruned. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.403300 - Parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.19059405623673217, 'lr': 0.0014940328279102943, 'weight_decay': 0.03353091910431805, 'batch_size': 32} - Best Value (CSI): 0.447726 - Best Trial: 1 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15492701504622297, 'lr': 0.004790714575437963, 'weight_decay': 0.01894502304388308, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) -[I 2025-12-25 11:33:47,691] Trial 28 pruned. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.322113 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.23289523637221324, 'lr': 0.0036157055541180044, 'weight_decay': 0.06386187584876131, 'batch_size': 64} - Best Value (CSI): 0.447726 - Best Trial: 1 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15492701504622297, 'lr': 0.004790714575437963, 'weight_decay': 0.01894502304388308, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:33:54,781] Trial 29 pruned. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.397093 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3331160558112436, 'lr': 0.001732212012259171, 'weight_decay': 0.017833848783541467, 'batch_size': 128} - Best Value (CSI): 0.447726 - Best Trial: 1 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15492701504622297, 'lr': 0.004790714575437963, 'weight_decay': 0.01894502304388308, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:33:59,501] Trial 30 pruned. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.371033 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.3481318288237071, 'lr': 0.00018536105636902342, 'weight_decay': 0.007358635824640577, 'batch_size': 128} - Best Value (CSI): 0.447726 - Best Trial: 1 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15492701504622297, 'lr': 0.004790714575437963, 'weight_decay': 0.01894502304388308, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:34:08,744] Trial 31 pruned. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.394104 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.25933698543592565, 'lr': 0.002096587943984251, 'weight_decay': 0.005415249088189138, 'batch_size': 128} - Best Value (CSI): 0.447726 - Best Trial: 1 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15492701504622297, 'lr': 0.004790714575437963, 'weight_decay': 0.01894502304388308, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:34:13,980] Trial 32 pruned. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.369803 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.2717307827536979, 'lr': 0.0011541092562035568, 'weight_decay': 0.00230570663559891, 'batch_size': 128} - Best Value (CSI): 0.447726 - Best Trial: 1 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15492701504622297, 'lr': 0.004790714575437963, 'weight_decay': 0.01894502304388308, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:34:32,207] Trial 33 pruned. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.424787 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.22480959511663498, 'lr': 0.0006051628069507728, 'weight_decay': 0.032100299244303555, 'batch_size': 128} - Best Value (CSI): 0.447726 - Best Trial: 1 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15492701504622297, 'lr': 0.004790714575437963, 'weight_decay': 0.01894502304388308, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:34:37,582] Trial 34 pruned. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.367121 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2989766016947342, 'lr': 0.001539120718298835, 'weight_decay': 0.0030477473227371347, 'batch_size': 128} - Best Value (CSI): 0.447726 - Best Trial: 1 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15492701504622297, 'lr': 0.004790714575437963, 'weight_decay': 0.01894502304388308, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:34:49,660] Trial 35 pruned. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.400307 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.39936672009343077, 'lr': 0.0006937758858294182, 'weight_decay': 0.06541829127900496, 'batch_size': 64} - Best Value (CSI): 0.447726 - Best Trial: 1 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15492701504622297, 'lr': 0.004790714575437963, 'weight_decay': 0.01894502304388308, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:34:53,466] Trial 36 pruned. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.388979 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.23627391447641077, 'lr': 0.0004322368144029006, 'weight_decay': 0.0013532437549450844, 'batch_size': 256} - Best Value (CSI): 0.447726 - Best Trial: 1 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15492701504622297, 'lr': 0.004790714575437963, 'weight_decay': 0.01894502304388308, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 114.66666666666667, 1: 4.335063009636768, 2: 0.3622398414271556} (클래스별 샘플 수: {0: 51, 1: 1349, 2: 16144}) -[I 2025-12-25 11:35:47,759] Trial 37 finished with value: 0.44816122490496063 and parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64}. Best is trial 37 with value: 0.44816122490496063. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.448161 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:35:54,420] Trial 38 pruned. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.386861 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2027802448703, 'lr': 0.0010737483196264612, 'weight_decay': 0.015881589618897223, 'batch_size': 64} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:36:06,555] Trial 39 pruned. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.408593 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2114556716059095, 'lr': 0.002139721810350589, 'weight_decay': 0.01394618851457447, 'batch_size': 64} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:36:13,417] Trial 40 pruned. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.321321 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.1855378594845776, 'lr': 0.004286845096459427, 'weight_decay': 0.036847183628398936, 'batch_size': 64} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) -[I 2025-12-25 11:36:48,464] Trial 41 pruned. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.447960 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.25176582848175894, 'lr': 0.0027774834287179273, 'weight_decay': 0.07326939625821681, 'batch_size': 64} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:36:51,693] Trial 42 pruned. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.385965 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.16575111198303175, 'lr': 0.0012625032586990482, 'weight_decay': 0.00518786215464051, 'batch_size': 256} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:37:22,935] Trial 43 pruned. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.389660 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.11659086184866224, 'lr': 0.006264729540971545, 'weight_decay': 0.025274208174256053, 'batch_size': 32} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:37:27,783] Trial 44 pruned. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.365028 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.22300751326667262, 'lr': 0.0020661160619874492, 'weight_decay': 0.010628979638777628, 'batch_size': 128} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:37:35,242] Trial 45 pruned. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.370872 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2021063096077948, 'lr': 0.00684918695002896, 'weight_decay': 0.03853754944949, 'batch_size': 64} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:37:39,827] Trial 46 pruned. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.324736 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3787051570337361, 'lr': 0.004430760061621055, 'weight_decay': 0.02390235592509709, 'batch_size': 128} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:37:54,927] Trial 47 pruned. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.398089 - Parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.17955233322663136, 'lr': 0.003048961071834542, 'weight_decay': 0.07262356889406453, 'batch_size': 64} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:38:18,148] Trial 48 pruned. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.398214 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15535365210204063, 'lr': 0.0008805601124507625, 'weight_decay': 0.04968037442245291, 'batch_size': 32} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:38:31,624] Trial 49 pruned. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.396610 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.2162252047424006, 'lr': 0.0016385648454963946, 'weight_decay': 0.0007231334428876373, 'batch_size': 64} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:38:35,843] Trial 50 pruned. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.387816 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.19500510698965245, 'lr': 0.003495179997774031, 'weight_decay': 0.07949720831880243, 'batch_size': 256} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 114.66666666666667, 1: 4.335063009636768, 2: 0.3622398414271556} (클래스별 샘플 수: {0: 51, 1: 1349, 2: 16144}) -[I 2025-12-25 11:39:40,134] Trial 51 finished with value: 0.44774635827536163 and parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.1376880921290856, 'lr': 0.00044727480939194404, 'weight_decay': 0.0021023856660726823, 'batch_size': 64}. Best is trial 37 with value: 0.44816122490496063. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.447746 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.1376880921290856, 'lr': 0.00044727480939194404, 'weight_decay': 0.0021023856660726823, 'batch_size': 64} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:40:08,116] Trial 52 pruned. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.410405 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.13961323544232704, 'lr': 0.0004080211717123132, 'weight_decay': 0.0034332015642035206, 'batch_size': 64} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:40:19,704] Trial 53 pruned. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.394472 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.12583133163059923, 'lr': 0.0006547505200785773, 'weight_decay': 0.001737874752845813, 'batch_size': 64} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:40:29,261] Trial 54 pruned. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.380516 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.10652111121093999, 'lr': 0.0009370454559882561, 'weight_decay': 0.011174454878565448, 'batch_size': 64} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:40:41,001] Trial 55 pruned. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.383256 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.15288554314604308, 'lr': 0.0011907360019519564, 'weight_decay': 0.0069346706402535225, 'batch_size': 64} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:40:46,557] Trial 56 pruned. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.388245 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.1678446189862752, 'lr': 0.0007557698049698369, 'weight_decay': 0.05272276154106409, 'batch_size': 128} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:40:54,105] Trial 57 pruned. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.294419 - Parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.24295364142360706, 'lr': 0.008667567006518438, 'weight_decay': 0.0968643990699073, 'batch_size': 64} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:41:07,509] Trial 58 pruned. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.403662 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.23095920648889826, 'lr': 0.0025542476815941266, 'weight_decay': 0.041383347370145776, 'batch_size': 64} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:41:12,748] Trial 59 pruned. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.375000 - Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.14510132040356896, 'lr': 0.0018175738374901916, 'weight_decay': 0.0263028605044428, 'batch_size': 128} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:41:31,903] Trial 60 pruned. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.365079 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.18315445194604754, 'lr': 0.005573647564108807, 'weight_decay': 0.06238490671883822, 'batch_size': 32} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:41:49,858] Trial 61 pruned. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.416120 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.1297732124889889, 'lr': 0.0009104092660999349, 'weight_decay': 0.0009982757459262202, 'batch_size': 64} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 114.66666666666667, 1: 4.335063009636768, 2: 0.3622398414271556} (클래스별 샘플 수: {0: 51, 1: 1349, 2: 16144}) -[I 2025-12-25 11:43:01,926] Trial 62 finished with value: 0.44768891770812586 and parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.1558463003013768, 'lr': 0.000497447280170072, 'weight_decay': 0.0024163369251744274, 'batch_size': 64}. Best is trial 37 with value: 0.44816122490496063. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.447689 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.1558463003013768, 'lr': 0.000497447280170072, 'weight_decay': 0.0024163369251744274, 'batch_size': 64} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:43:17,366] Trial 63 pruned. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.395283 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.16119322461322866, 'lr': 0.0005346454128948379, 'weight_decay': 0.0026649370832573824, 'batch_size': 64} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 114.66666666666667, 1: 4.335063009636768, 2: 0.3622398414271556} (클래스별 샘플 수: {0: 51, 1: 1349, 2: 16144}) -[I 2025-12-25 11:44:20,921] Trial 64 finished with value: 0.44285374601620225 and parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.17634362816656693, 'lr': 0.0013145196371219087, 'weight_decay': 0.0020289318570847134, 'batch_size': 64}. Best is trial 37 with value: 0.44816122490496063. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.442854 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.17634362816656693, 'lr': 0.0013145196371219087, 'weight_decay': 0.0020289318570847134, 'batch_size': 64} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:44:29,802] Trial 65 pruned. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.380603 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.15580462671506878, 'lr': 0.0003243579690255897, 'weight_decay': 0.004093626310397787, 'batch_size': 64} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:44:38,472] Trial 66 pruned. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.377344 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.14301732410842527, 'lr': 0.0007630047079667055, 'weight_decay': 0.020231080371619733, 'batch_size': 128} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:44:52,677] Trial 67 pruned. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.387803 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.26919286621495664, 'lr': 0.0005691799817981422, 'weight_decay': 0.0025907586102909778, 'batch_size': 64} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:44:58,081] Trial 68 pruned. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.388084 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.17176606977367798, 'lr': 0.0010548128137286953, 'weight_decay': 0.0465659058513687, 'batch_size': 128} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:45:15,635] Trial 69 pruned. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.413238 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.21472182179096022, 'lr': 0.0016944535988209, 'weight_decay': 0.08138490753694164, 'batch_size': 64} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:45:18,877] Trial 70 pruned. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.368580 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2841262717668259, 'lr': 0.0006855462949081674, 'weight_decay': 0.001392889567715036, 'batch_size': 256} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:45:36,742] Trial 71 pruned. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.417493 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.13811982528875624, 'lr': 0.00045306016120506376, 'weight_decay': 0.0020116025252501393, 'batch_size': 64} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:45:45,695] Trial 72 pruned. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.389498 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.24580169670672125, 'lr': 0.0012811079833226666, 'weight_decay': 0.003155650138715497, 'batch_size': 64} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:46:01,257] Trial 73 pruned. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.401977 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.19448235836607863, 'lr': 0.00032428712079409676, 'weight_decay': 0.029366331791445398, 'batch_size': 64} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:46:14,485] Trial 74 pruned. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.403595 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.2300631096449643, 'lr': 0.0002445548835509296, 'weight_decay': 0.0017106464048713764, 'batch_size': 64} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:46:19,744] Trial 75 pruned. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.368343 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.14866831044860618, 'lr': 0.0009846465637409945, 'weight_decay': 0.0330172574508005, 'batch_size': 128} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:46:29,178] Trial 76 pruned. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.384953 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2573202124094121, 'lr': 0.0008048064822718791, 'weight_decay': 0.003949991993233293, 'batch_size': 64} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:46:57,945] Trial 77 pruned. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.412897 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.15978382548429595, 'lr': 0.0006126889371955803, 'weight_decay': 0.06008599445060642, 'batch_size': 64} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) -[I 2025-12-25 11:48:18,193] Trial 78 pruned. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.439931 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.23885412684485408, 'lr': 0.0014279908689190384, 'weight_decay': 0.012920310558495001, 'batch_size': 32} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:48:22,843] Trial 79 pruned. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.368882 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.17410288222722178, 'lr': 0.0005183844990527258, 'weight_decay': 0.0836314455459107, 'batch_size': 128} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:48:36,869] Trial 80 pruned. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.396771 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.18766290565122748, 'lr': 0.002059461725487175, 'weight_decay': 0.008964530660885409, 'batch_size': 64} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:48:49,470] Trial 81 pruned. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.385771 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.17380153855532954, 'lr': 0.0011350995507829842, 'weight_decay': 0.0021410303723386546, 'batch_size': 64} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:48:58,936] Trial 82 pruned. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.389860 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.16525958082387043, 'lr': 0.0013958814714231974, 'weight_decay': 0.0011136067602839472, 'batch_size': 64} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:49:16,275] Trial 83 pruned. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.390476 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.1790090495364099, 'lr': 0.0008344931822502928, 'weight_decay': 0.001749235087269648, 'batch_size': 64} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:49:33,117] Trial 84 pruned. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.387772 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.20420983865733175, 'lr': 0.001033582282509382, 'weight_decay': 0.002578535095609122, 'batch_size': 64} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 114.66666666666667, 1: 4.335063009636768, 2: 0.3622398414271556} (클래스별 샘플 수: {0: 51, 1: 1349, 2: 16144}) -[I 2025-12-25 11:50:31,690] Trial 85 finished with value: 0.44584915155314336 and parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.15431675578543055, 'lr': 0.0024397231857583037, 'weight_decay': 0.019206121754617663, 'batch_size': 64}. Best is trial 37 with value: 0.44816122490496063. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.445849 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.15431675578543055, 'lr': 0.0024397231857583037, 'weight_decay': 0.019206121754617663, 'batch_size': 64} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:50:35,160] Trial 86 pruned. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.382120 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.12303849868900861, 'lr': 0.002371005998928449, 'weight_decay': 0.018467423727802468, 'batch_size': 256} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:50:48,517] Trial 87 pruned. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.391904 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.1307307002535191, 'lr': 0.0029719422486376482, 'weight_decay': 0.03764763952300637, 'batch_size': 64} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:50:57,388] Trial 88 pruned. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.394951 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.14929148570798723, 'lr': 0.0036358389299900144, 'weight_decay': 0.016213356140612874, 'batch_size': 128} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:51:05,808] Trial 89 pruned. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.381399 - Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.13756156988261178, 'lr': 0.004274772212844333, 'weight_decay': 0.019844552519632724, 'batch_size': 64} - Best Value (CSI): 0.448161 - Best Trial: 37 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20609934359713367, 'lr': 0.0012235239081177934, 'weight_decay': 0.017042320460742038, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 114.66666666666667, 1: 4.335063009636768, 2: 0.3622398414271556} (클래스별 샘플 수: {0: 51, 1: 1349, 2: 16144}) -[I 2025-12-25 11:52:26,755] Trial 90 finished with value: 0.4507852210916714 and parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.22201246225002172, 'lr': 0.0018802322915298384, 'weight_decay': 0.04341402361540322, 'batch_size': 64}. Best is trial 90 with value: 0.4507852210916714. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.450785 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.22201246225002172, 'lr': 0.0018802322915298384, 'weight_decay': 0.04341402361540322, 'batch_size': 64} - Best Value (CSI): 0.450785 - Best Trial: 90 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.22201246225002172, 'lr': 0.0018802322915298384, 'weight_decay': 0.04341402361540322, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) -[I 2025-12-25 11:53:17,871] Trial 91 pruned. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.454705 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.22150801166759645, 'lr': 0.002528943557055791, 'weight_decay': 0.055791482949211296, 'batch_size': 64} - Best Value (CSI): 0.450785 - Best Trial: 90 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.22201246225002172, 'lr': 0.0018802322915298384, 'weight_decay': 0.04341402361540322, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:53:27,177] Trial 92 pruned. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.386196 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.22948320858546697, 'lr': 0.0017240121558497689, 'weight_decay': 0.044503674033275306, 'batch_size': 64} - Best Value (CSI): 0.450785 - Best Trial: 90 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.22201246225002172, 'lr': 0.0018802322915298384, 'weight_decay': 0.04341402361540322, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:53:43,074] Trial 93 pruned. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.410517 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.15634009853102326, 'lr': 0.0014046644618413544, 'weight_decay': 0.08647418720194373, 'batch_size': 64} - Best Value (CSI): 0.450785 - Best Trial: 90 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.22201246225002172, 'lr': 0.0018802322915298384, 'weight_decay': 0.04341402361540322, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:53:57,126] Trial 94 pruned. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.400327 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.23906008897590655, 'lr': 0.002003075396131143, 'weight_decay': 0.07118260123105781, 'batch_size': 64} - Best Value (CSI): 0.450785 - Best Trial: 90 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.22201246225002172, 'lr': 0.0018802322915298384, 'weight_decay': 0.04341402361540322, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:54:23,896] Trial 95 pruned. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.416132 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.2494608087881565, 'lr': 0.0023504036277887815, 'weight_decay': 0.06643059468252212, 'batch_size': 64} - Best Value (CSI): 0.450785 - Best Trial: 90 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.22201246225002172, 'lr': 0.0018802322915298384, 'weight_decay': 0.04341402361540322, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:54:29,998] Trial 96 pruned. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.384127 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.2109732898714899, 'lr': 0.001555665077346605, 'weight_decay': 0.029127147181912633, 'batch_size': 128} - Best Value (CSI): 0.450785 - Best Trial: 90 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.22201246225002172, 'lr': 0.0018802322915298384, 'weight_decay': 0.04341402361540322, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:54:54,060] Trial 97 pruned. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.401343 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.22379713830824427, 'lr': 0.0007159263881836746, 'weight_decay': 0.0217400530764778, 'batch_size': 32} - Best Value (CSI): 0.450785 - Best Trial: 90 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.22201246225002172, 'lr': 0.0018802322915298384, 'weight_decay': 0.04341402361540322, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:55:04,666] Trial 98 pruned. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.377544 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.14464214664366123, 'lr': 0.0032404425000478157, 'weight_decay': 0.052117313745577744, 'batch_size': 64} - Best Value (CSI): 0.450785 - Best Trial: 90 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.22201246225002172, 'lr': 0.0018802322915298384, 'weight_decay': 0.04341402361540322, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 11:55:16,884] Trial 99 pruned. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.405224 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1681937144413499, 'lr': 0.0018911448698917005, 'weight_decay': 0.09719063942739173, 'batch_size': 64} - Best Value (CSI): 0.450785 - Best Trial: 90 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.22201246225002172, 'lr': 0.0018802322915298384, 'weight_decay': 0.04341402361540322, 'batch_size': 64} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.4508 -Best Hyperparameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.22201246225002172, 'lr': 0.0018802322915298384, 'weight_decay': 0.04341402361540322, 'batch_size': 64} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.4439 - - 최종 CSI: 0.4052 - - 최고 CSI: 0.4630 - - 최저 CSI: 0.2168 - - 평균 CSI: 0.3897 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/deepgbm_pure_gwangju_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 40, Best CSI: 0.4107 - Fold 1 학습 완료 (검증 CSI: 0.4107) -Fold 2 학습 중... - Early stopping at epoch 25, Best CSI: 0.4538 - Fold 2 학습 완료 (검증 CSI: 0.4538) -Fold 3 학습 중... - Early stopping at epoch 50, Best CSI: 0.4745 - Fold 3 학습 완료 (검증 CSI: 0.4745) - -모든 모델 저장 완료: ../save_model/deepgbm_optima/deepgbm_pure_gwangju.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/deepgbm_optima/scaler/deepgbm_pure_gwangju_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: - - . - - . - - / - - s - - a - - v - - e - - _ - - m - - o - - d - - e - - l - - / - - d - - e - - e - - p - - g - - b - - m - - _ - - o - - p - - t - - i - - m - - a - - / - - d - - e - - e - - p - - g - - b - - m - - _ - - p - - u - - r - - e - - _ - - g - - w - - a - - n - - g - - j - - u - - . - - p - - k - - l - -✓ 완료: deepgbm_pure/deepgbm_pure_gwangju.py (소요 시간: 2269초) - ----------------------------------------- -실행 중: deepgbm_pure/deepgbm_pure_incheon.py -시작 시간: 2025-12-25 11:56:36 ----------------------------------------- -[I 2025-12-25 11:56:38,123] A new study created in memory with name: no-name-5e2f4300-3d89-448f-8882-bd45c56518ee - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 11:57:24,582] Trial 0 finished with value: 0.5398082319025785 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.12996023859177236, 'lr': 0.0021969486598842577, 'weight_decay': 0.000205272880210174, 'batch_size': 128}. Best is trial 0 with value: 0.5398082319025785. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.539808 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.12996023859177236, 'lr': 0.0021969486598842577, 'weight_decay': 0.000205272880210174, 'batch_size': 128} - Best Value (CSI): 0.539808 - Best Trial: 0 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.12996023859177236, 'lr': 0.0021969486598842577, 'weight_decay': 0.000205272880210174, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 11:57:53,039] Trial 1 finished with value: 0.5395801631203564 and parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2052099434358718, 'lr': 0.0011464238703545982, 'weight_decay': 0.00012036966491279877, 'batch_size': 256}. Best is trial 0 with value: 0.5398082319025785. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.539580 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2052099434358718, 'lr': 0.0011464238703545982, 'weight_decay': 0.00012036966491279877, 'batch_size': 256} - Best Value (CSI): 0.539808 - Best Trial: 0 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.12996023859177236, 'lr': 0.0021969486598842577, 'weight_decay': 0.000205272880210174, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 11:59:21,725] Trial 2 finished with value: 0.49210070434094105 and parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.1882258225722049, 'lr': 2.429769383072964e-05, 'weight_decay': 0.0009259880137543167, 'batch_size': 128}. Best is trial 0 with value: 0.5398082319025785. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.492101 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.1882258225722049, 'lr': 2.429769383072964e-05, 'weight_decay': 0.0009259880137543167, 'batch_size': 128} - Best Value (CSI): 0.539808 - Best Trial: 0 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.12996023859177236, 'lr': 0.0021969486598842577, 'weight_decay': 0.000205272880210174, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 12:00:02,492] Trial 3 finished with value: 0.5242816328503098 and parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.1715632804383884, 'lr': 0.0001304094615680662, 'weight_decay': 0.051851090376700305, 'batch_size': 256}. Best is trial 0 with value: 0.5398082319025785. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.524282 - Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.1715632804383884, 'lr': 0.0001304094615680662, 'weight_decay': 0.051851090376700305, 'batch_size': 256} - Best Value (CSI): 0.539808 - Best Trial: 0 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.12996023859177236, 'lr': 0.0021969486598842577, 'weight_decay': 0.000205272880210174, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 12:00:45,617] Trial 4 finished with value: 0.513217369005471 and parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.12641317740147245, 'lr': 8.744857172247754e-05, 'weight_decay': 0.015610127050355116, 'batch_size': 256}. Best is trial 0 with value: 0.5398082319025785. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.513217 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.12641317740147245, 'lr': 8.744857172247754e-05, 'weight_decay': 0.015610127050355116, 'batch_size': 256} - Best Value (CSI): 0.539808 - Best Trial: 0 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.12996023859177236, 'lr': 0.0021969486598842577, 'weight_decay': 0.000205272880210174, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 12:02:15,402] Trial 5 finished with value: 0.5454600742006473 and parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.35017034280008896, 'lr': 0.0029067910523158783, 'weight_decay': 0.015242123725854921, 'batch_size': 64}. Best is trial 5 with value: 0.5454600742006473. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.545460 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.35017034280008896, 'lr': 0.0029067910523158783, 'weight_decay': 0.015242123725854921, 'batch_size': 64} - Best Value (CSI): 0.545460 - Best Trial: 5 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.35017034280008896, 'lr': 0.0029067910523158783, 'weight_decay': 0.015242123725854921, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 12:02:46,981] Trial 6 finished with value: 0.528862945907989 and parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.1826314839022573, 'lr': 0.0005465079430385442, 'weight_decay': 0.0027607233242981765, 'batch_size': 256}. Best is trial 5 with value: 0.5454600742006473. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.528863 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.1826314839022573, 'lr': 0.0005465079430385442, 'weight_decay': 0.0027607233242981765, 'batch_size': 256} - Best Value (CSI): 0.545460 - Best Trial: 5 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.35017034280008896, 'lr': 0.0029067910523158783, 'weight_decay': 0.015242123725854921, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 12:02:59,404] Trial 7 pruned. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.464886 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.3341566760522341, 'lr': 4.47690194853178e-05, 'weight_decay': 0.0018581535695576727, 'batch_size': 32} - Best Value (CSI): 0.545460 - Best Trial: 5 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.35017034280008896, 'lr': 0.0029067910523158783, 'weight_decay': 0.015242123725854921, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 12:03:27,576] Trial 8 finished with value: 0.5442566525007488 and parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.332043912676258, 'lr': 0.0018575021744344784, 'weight_decay': 0.0005962299557826236, 'batch_size': 256}. Best is trial 5 with value: 0.5454600742006473. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.544257 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.332043912676258, 'lr': 0.0018575021744344784, 'weight_decay': 0.0005962299557826236, 'batch_size': 256} - Best Value (CSI): 0.545460 - Best Trial: 5 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.35017034280008896, 'lr': 0.0029067910523158783, 'weight_decay': 0.015242123725854921, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 12:03:32,462] Trial 9 pruned. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.440207 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2047505482743774, 'lr': 7.621075622055807e-05, 'weight_decay': 0.09258946050196508, 'batch_size': 128} - Best Value (CSI): 0.545460 - Best Trial: 5 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.35017034280008896, 'lr': 0.0029067910523158783, 'weight_decay': 0.015242123725854921, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 12:03:55,385] Trial 10 pruned. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.525675 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.39929711816369756, 'lr': 0.0065359619143552814, 'weight_decay': 0.009625507619840165, 'batch_size': 64} - Best Value (CSI): 0.545460 - Best Trial: 5 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.35017034280008896, 'lr': 0.0029067910523158783, 'weight_decay': 0.015242123725854921, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 12:04:04,128] Trial 11 pruned. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.473934 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.300406540882716, 'lr': 0.008331992883704125, 'weight_decay': 0.0007811179539310358, 'batch_size': 64} - Best Value (CSI): 0.545460 - Best Trial: 5 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.35017034280008896, 'lr': 0.0029067910523158783, 'weight_decay': 0.015242123725854921, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 12:05:30,836] Trial 12 finished with value: 0.5464892759220491 and parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2988189709838643, 'lr': 0.0030267822511870373, 'weight_decay': 0.007243505215929789, 'batch_size': 64}. Best is trial 12 with value: 0.5464892759220491. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.546489 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2988189709838643, 'lr': 0.0030267822511870373, 'weight_decay': 0.007243505215929789, 'batch_size': 64} - Best Value (CSI): 0.546489 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2988189709838643, 'lr': 0.0030267822511870373, 'weight_decay': 0.007243505215929789, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 12:05:48,476] Trial 13 pruned. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.528157 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.2664591689193297, 'lr': 0.00038795611970612984, 'weight_decay': 0.008947178339688068, 'batch_size': 64} - Best Value (CSI): 0.546489 - Best Trial: 12 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2988189709838643, 'lr': 0.0030267822511870373, 'weight_decay': 0.007243505215929789, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 12:07:28,359] Trial 14 finished with value: 0.5467131531844633 and parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.38205229621689274, 'lr': 0.003571562941991637, 'weight_decay': 0.020764067625062124, 'batch_size': 64}. Best is trial 14 with value: 0.5467131531844633. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.546713 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.38205229621689274, 'lr': 0.003571562941991637, 'weight_decay': 0.020764067625062124, 'batch_size': 64} - Best Value (CSI): 0.546713 - Best Trial: 14 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.38205229621689274, 'lr': 0.003571562941991637, 'weight_decay': 0.020764067625062124, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 12:07:37,085] Trial 15 pruned. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.480691 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.3972881186554469, 'lr': 0.009715969020030522, 'weight_decay': 0.005839213249086865, 'batch_size': 64} - Best Value (CSI): 0.546713 - Best Trial: 14 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.38205229621689274, 'lr': 0.003571562941991637, 'weight_decay': 0.020764067625062124, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 12:10:05,077] Trial 16 finished with value: 0.5402886615274647 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.2616310892061921, 'lr': 0.000953621064747484, 'weight_decay': 0.022106985649890432, 'batch_size': 32}. Best is trial 14 with value: 0.5467131531844633. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.540289 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.2616310892061921, 'lr': 0.000953621064747484, 'weight_decay': 0.022106985649890432, 'batch_size': 32} - Best Value (CSI): 0.546713 - Best Trial: 14 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.38205229621689274, 'lr': 0.003571562941991637, 'weight_decay': 0.020764067625062124, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 12:11:25,584] Trial 17 finished with value: 0.5551745085893142 and parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64}. Best is trial 17 with value: 0.5551745085893142. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.555175 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} - Best Value (CSI): 0.555175 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 12:11:41,725] Trial 18 pruned. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.531283 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.3649802225975902, 'lr': 0.00019383238020520723, 'weight_decay': 0.03222207064954482, 'batch_size': 64} - Best Value (CSI): 0.555175 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 12:11:48,969] Trial 19 pruned. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.492879 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.37060378694118423, 'lr': 0.003900159066503448, 'weight_decay': 0.003220565485471045, 'batch_size': 64} - Best Value (CSI): 0.555175 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 12:14:15,416] Trial 20 finished with value: 0.5509949086170853 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.30978036306203555, 'lr': 0.000662569855814936, 'weight_decay': 0.03440451386643154, 'batch_size': 32}. Best is trial 17 with value: 0.5551745085893142. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.550995 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.30978036306203555, 'lr': 0.000662569855814936, 'weight_decay': 0.03440451386643154, 'batch_size': 32} - Best Value (CSI): 0.555175 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 12:16:13,790] Trial 21 finished with value: 0.5503035073304142 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3737279443425529, 'lr': 0.0009829203668613913, 'weight_decay': 0.03482862768198801, 'batch_size': 32}. Best is trial 17 with value: 0.5551745085893142. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.550304 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3737279443425529, 'lr': 0.0009829203668613913, 'weight_decay': 0.03482862768198801, 'batch_size': 32} - Best Value (CSI): 0.555175 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 12:18:20,234] Trial 22 finished with value: 0.5544995398382262 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.34582683049988644, 'lr': 0.0008037683707713287, 'weight_decay': 0.04538167917082227, 'batch_size': 32}. Best is trial 17 with value: 0.5551745085893142. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.554500 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.34582683049988644, 'lr': 0.0008037683707713287, 'weight_decay': 0.04538167917082227, 'batch_size': 32} - Best Value (CSI): 0.555175 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 12:20:21,360] Trial 23 finished with value: 0.5507336578123873 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3184274547183536, 'lr': 0.0005157973070841742, 'weight_decay': 0.08913193129004947, 'batch_size': 32}. Best is trial 17 with value: 0.5551745085893142. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.550734 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3184274547183536, 'lr': 0.0005157973070841742, 'weight_decay': 0.08913193129004947, 'batch_size': 32} - Best Value (CSI): 0.555175 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 12:22:31,927] Trial 24 finished with value: 0.5368460689861969 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3513977640538311, 'lr': 0.00026859453689570436, 'weight_decay': 0.0554240131173391, 'batch_size': 32}. Best is trial 17 with value: 0.5551745085893142. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.536846 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3513977640538311, 'lr': 0.00026859453689570436, 'weight_decay': 0.0554240131173391, 'batch_size': 32} - Best Value (CSI): 0.555175 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 12:24:46,267] Trial 25 finished with value: 0.5423339072340276 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2955749788427757, 'lr': 0.0007383993500845118, 'weight_decay': 0.047109516572130986, 'batch_size': 32}. Best is trial 17 with value: 0.5551745085893142. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.542334 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2955749788427757, 'lr': 0.0007383993500845118, 'weight_decay': 0.047109516572130986, 'batch_size': 32} - Best Value (CSI): 0.555175 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 12:27:03,381] Trial 26 finished with value: 0.542890410622943 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.34024638433056775, 'lr': 0.0016051669076166523, 'weight_decay': 0.02960905459199312, 'batch_size': 32}. Best is trial 17 with value: 0.5551745085893142. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.542890 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.34024638433056775, 'lr': 0.0016051669076166523, 'weight_decay': 0.02960905459199312, 'batch_size': 32} - Best Value (CSI): 0.555175 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 12:29:06,883] Trial 27 finished with value: 0.5542068927610041 and parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3237995354077479, 'lr': 0.0014253433150785684, 'weight_decay': 0.015257328010990265, 'batch_size': 32}. Best is trial 17 with value: 0.5551745085893142. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.554207 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3237995354077479, 'lr': 0.0014253433150785684, 'weight_decay': 0.015257328010990265, 'batch_size': 32} - Best Value (CSI): 0.555175 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 12:29:35,388] Trial 28 pruned. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.526496 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.3576068424152014, 'lr': 0.0013560047218536613, 'weight_decay': 0.012527653261457291, 'batch_size': 32} - Best Value (CSI): 0.555175 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 12:30:13,152] Trial 29 finished with value: 0.5471204447023058 and parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3237988071223005, 'lr': 0.0020288907779185297, 'weight_decay': 0.0051484439506685525, 'batch_size': 128}. Best is trial 17 with value: 0.5551745085893142. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.547120 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3237988071223005, 'lr': 0.0020288907779185297, 'weight_decay': 0.0051484439506685525, 'batch_size': 128} - Best Value (CSI): 0.555175 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 12:30:25,632] Trial 30 pruned. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.521531 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.34596153622732934, 'lr': 0.00036393235865644425, 'weight_decay': 0.010496525112348028, 'batch_size': 32} - Best Value (CSI): 0.555175 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 12:32:00,047] Trial 31 finished with value: 0.5513227042901331 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.311972904416097, 'lr': 0.0007978829426222, 'weight_decay': 0.01875552948328875, 'batch_size': 32}. Best is trial 17 with value: 0.5551745085893142. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.551323 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.311972904416097, 'lr': 0.0007978829426222, 'weight_decay': 0.01875552948328875, 'batch_size': 32} - Best Value (CSI): 0.555175 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 12:33:39,261] Trial 32 finished with value: 0.5499185942379469 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.32036496103422396, 'lr': 0.0011574010777269119, 'weight_decay': 0.017409677232194325, 'batch_size': 32}. Best is trial 17 with value: 0.5551745085893142. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.549919 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.32036496103422396, 'lr': 0.0011574010777269119, 'weight_decay': 0.017409677232194325, 'batch_size': 32} - Best Value (CSI): 0.555175 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 12:35:08,768] Trial 33 finished with value: 0.547323522963601 and parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2811669900464092, 'lr': 0.0014892831131769766, 'weight_decay': 0.019421638433599595, 'batch_size': 32}. Best is trial 17 with value: 0.5551745085893142. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.547324 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2811669900464092, 'lr': 0.0014892831131769766, 'weight_decay': 0.019421638433599595, 'batch_size': 32} - Best Value (CSI): 0.555175 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 12:35:18,634] Trial 34 pruned. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.534286 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.278302000291648, 'lr': 0.0008561682867178119, 'weight_decay': 0.011990688677177256, 'batch_size': 128} - Best Value (CSI): 0.555175 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 12:35:47,688] Trial 35 pruned. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.531480 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.23854939709552206, 'lr': 0.0025203547030777334, 'weight_decay': 0.0072911803413375125, 'batch_size': 32} - Best Value (CSI): 0.555175 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 12:35:58,351] Trial 36 pruned. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.483594 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.3410147131150019, 'lr': 0.0052021732746065745, 'weight_decay': 0.024923183210486918, 'batch_size': 32} - Best Value (CSI): 0.555175 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 12:36:07,631] Trial 37 pruned. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.463934 - Parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.38275103694651424, 'lr': 0.002477285864588133, 'weight_decay': 0.015182424960103013, 'batch_size': 32} - Best Value (CSI): 0.555175 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 12:36:10,645] Trial 38 pruned. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.514599 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.3576928757428856, 'lr': 0.004926030571857137, 'weight_decay': 0.05458467365538982, 'batch_size': 256} - Best Value (CSI): 0.555175 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 12:36:17,294] Trial 39 pruned. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.538122 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.33086918701024143, 'lr': 0.0005746859277750123, 'weight_decay': 0.004605609904086216, 'batch_size': 128} - Best Value (CSI): 0.555175 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 12:36:20,115] Trial 40 pruned. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.518753 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.11002431937395546, 'lr': 0.0019040100392193374, 'weight_decay': 0.0017345271319941609, 'batch_size': 256} - Best Value (CSI): 0.555175 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 12:36:48,224] Trial 41 pruned. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.538375 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3109621736385688, 'lr': 0.0006813301822155025, 'weight_decay': 0.03941814772498077, 'batch_size': 32} - Best Value (CSI): 0.555175 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 12:38:09,480] Trial 42 finished with value: 0.5498997397794992 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3072890202822163, 'lr': 0.0011741282295039787, 'weight_decay': 0.025885387108790466, 'batch_size': 32}. Best is trial 17 with value: 0.5551745085893142. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.549900 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3072890202822163, 'lr': 0.0011741282295039787, 'weight_decay': 0.025885387108790466, 'batch_size': 32} - Best Value (CSI): 0.555175 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 12:39:40,973] Trial 43 finished with value: 0.5486451908796384 and parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3272321626231051, 'lr': 0.0007535720720547696, 'weight_decay': 0.0715844145351396, 'batch_size': 32}. Best is trial 17 with value: 0.5551745085893142. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.548645 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3272321626231051, 'lr': 0.0007535720720547696, 'weight_decay': 0.0715844145351396, 'batch_size': 32} - Best Value (CSI): 0.555175 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 12:41:16,123] Trial 44 finished with value: 0.5410827387925036 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.3487980724216529, 'lr': 0.0004741505333394171, 'weight_decay': 0.03566391039772591, 'batch_size': 32}. Best is trial 17 with value: 0.5551745085893142. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.541083 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.3487980724216529, 'lr': 0.0004741505333394171, 'weight_decay': 0.03566391039772591, 'batch_size': 32} - Best Value (CSI): 0.555175 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 12:42:29,985] Trial 45 finished with value: 0.5416175965281175 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.31244087679001586, 'lr': 0.0014705763513138534, 'weight_decay': 0.014182122548452598, 'batch_size': 32}. Best is trial 17 with value: 0.5551745085893142. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.541618 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.31244087679001586, 'lr': 0.0014705763513138534, 'weight_decay': 0.014182122548452598, 'batch_size': 32} - Best Value (CSI): 0.555175 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 12:42:32,723] Trial 46 pruned. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.529936 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.3379627888148658, 'lr': 0.0021350099228449274, 'weight_decay': 0.0430055533169051, 'batch_size': 256} - Best Value (CSI): 0.555175 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 12:42:40,526] Trial 47 pruned. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.527293 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.2920761111656685, 'lr': 0.00027225003394269797, 'weight_decay': 0.019537095386170093, 'batch_size': 64} - Best Value (CSI): 0.555175 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 12:44:42,045] Trial 48 finished with value: 0.5499254947854935 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.32979892400099775, 'lr': 0.0009395177300304981, 'weight_decay': 0.02794253459531498, 'batch_size': 32}. Best is trial 17 with value: 0.5551745085893142. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.549925 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.32979892400099775, 'lr': 0.0009395177300304981, 'weight_decay': 0.02794253459531498, 'batch_size': 32} - Best Value (CSI): 0.555175 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 12:44:46,141] Trial 49 pruned. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.526164 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3617864671363842, 'lr': 0.0031375575907209513, 'weight_decay': 0.01036012305178339, 'batch_size': 128} - Best Value (CSI): 0.555175 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 12:45:59,837] Trial 50 finished with value: 0.5458647895434502 and parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.30635845644966186, 'lr': 0.0006273966318632081, 'weight_decay': 0.06546873818692377, 'batch_size': 64}. Best is trial 17 with value: 0.5551745085893142. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.545865 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.30635845644966186, 'lr': 0.0006273966318632081, 'weight_decay': 0.06546873818692377, 'batch_size': 64} - Best Value (CSI): 0.555175 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 12:47:52,774] Trial 51 finished with value: 0.5495536455288512 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3163217386149727, 'lr': 0.0011331763424551782, 'weight_decay': 0.08431147365458909, 'batch_size': 32}. Best is trial 17 with value: 0.5551745085893142. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.549554 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3163217386149727, 'lr': 0.0011331763424551782, 'weight_decay': 0.08431147365458909, 'batch_size': 32} - Best Value (CSI): 0.555175 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 12:48:04,014] Trial 52 pruned. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.490991 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.321074885729257, 'lr': 0.000528756391770501, 'weight_decay': 0.09744899866325872, 'batch_size': 32} - Best Value (CSI): 0.555175 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 12:49:57,614] Trial 53 finished with value: 0.5501575240214502 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3431827703440595, 'lr': 0.0004471284155865241, 'weight_decay': 0.06404947684236742, 'batch_size': 32}. Best is trial 17 with value: 0.5551745085893142. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.550158 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3431827703440595, 'lr': 0.0004471284155865241, 'weight_decay': 0.06404947684236742, 'batch_size': 32} - Best Value (CSI): 0.555175 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 12:51:26,063] Trial 54 finished with value: 0.5490271137870021 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.28921111266247523, 'lr': 0.0003354735932875485, 'weight_decay': 0.048681016057827015, 'batch_size': 32}. Best is trial 17 with value: 0.5551745085893142. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.549027 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.28921111266247523, 'lr': 0.0003354735932875485, 'weight_decay': 0.048681016057827015, 'batch_size': 32} - Best Value (CSI): 0.555175 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 12:52:16,919] Trial 55 finished with value: 0.5390277969476309 and parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.30265866657178614, 'lr': 0.0007639330681487032, 'weight_decay': 0.03404460227041301, 'batch_size': 64}. Best is trial 17 with value: 0.5551745085893142. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.539028 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.30265866657178614, 'lr': 0.0007639330681487032, 'weight_decay': 0.03404460227041301, 'batch_size': 64} - Best Value (CSI): 0.555175 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 12:52:31,297] Trial 56 pruned. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.530096 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.3765374553244314, 'lr': 0.00042833984304671503, 'weight_decay': 0.023681195659712648, 'batch_size': 32} - Best Value (CSI): 0.555175 - Best Trial: 17 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36953990738060694, 'lr': 0.0036111741433088674, 'weight_decay': 0.004343119929398933, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 12:54:28,187] Trial 57 finished with value: 0.5622375492647842 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32}. Best is trial 57 with value: 0.5622375492647842. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.562238 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 12:54:45,194] Trial 58 pruned. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.549540 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3663640065939134, 'lr': 0.0018316592619218998, 'weight_decay': 0.014645344169739822, 'batch_size': 64} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 12:55:18,285] Trial 59 pruned. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.546218 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.3879305135389739, 'lr': 0.0012763954262866607, 'weight_decay': 0.04187688478887795, 'batch_size': 32} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 12:55:37,700] Trial 60 finished with value: 0.5431280789835105 and parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.35554976791745685, 'lr': 0.002614530298701318, 'weight_decay': 0.02041390215820383, 'batch_size': 256}. Best is trial 57 with value: 0.5622375492647842. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.543128 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.35554976791745685, 'lr': 0.002614530298701318, 'weight_decay': 0.02041390215820383, 'batch_size': 256} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 12:55:48,614] Trial 61 pruned. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.525263 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3360102546673934, 'lr': 0.0009252242433510833, 'weight_decay': 0.07589975808637867, 'batch_size': 32} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 12:55:59,772] Trial 62 pruned. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.526392 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3701512512029099, 'lr': 0.0005277049460772327, 'weight_decay': 0.052635225100636986, 'batch_size': 32} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 12:57:30,823] Trial 63 finished with value: 0.5539352973448302 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3181151394544893, 'lr': 0.0016405681844076506, 'weight_decay': 0.030654413218720013, 'batch_size': 32}. Best is trial 57 with value: 0.5622375492647842. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.553935 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3181151394544893, 'lr': 0.0016405681844076506, 'weight_decay': 0.030654413218720013, 'batch_size': 32} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 12:58:47,543] Trial 64 finished with value: 0.5557521602545893 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.35260687060739027, 'lr': 0.0016710657513766094, 'weight_decay': 0.02877905871688585, 'batch_size': 32}. Best is trial 57 with value: 0.5622375492647842. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.555752 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.35260687060739027, 'lr': 0.0016710657513766094, 'weight_decay': 0.02877905871688585, 'batch_size': 32} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 12:59:02,650] Trial 65 pruned. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.499528 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.35055647960182523, 'lr': 0.001770872181773667, 'weight_decay': 0.028938493529098448, 'batch_size': 32} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 12:59:14,088] Trial 66 pruned. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.494135 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.36435472918668044, 'lr': 0.0034727401622742615, 'weight_decay': 0.016890756202554896, 'batch_size': 32} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 12:59:21,105] Trial 67 pruned. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.520378 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.3327592048818807, 'lr': 0.002409334600902633, 'weight_decay': 0.023710380606181587, 'batch_size': 64} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 12:59:32,241] Trial 68 pruned. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.500000 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.34861888187898515, 'lr': 0.001551478315135587, 'weight_decay': 0.03966412791216449, 'batch_size': 32} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 12:59:43,119] Trial 69 pruned. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.474576 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.38919439960771524, 'lr': 0.0029002085671547715, 'weight_decay': 0.00872238306028511, 'batch_size': 32} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 12:59:47,785] Trial 70 pruned. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.514160 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.37229887524701416, 'lr': 0.0010424116998415077, 'weight_decay': 0.01789147885405447, 'batch_size': 128} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 13:01:12,037] Trial 71 finished with value: 0.5539588744732061 and parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.32435524737543703, 'lr': 0.0013726072937409676, 'weight_decay': 0.03429201136825487, 'batch_size': 32}. Best is trial 57 with value: 0.5622375492647842. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.553959 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.32435524737543703, 'lr': 0.0013726072937409676, 'weight_decay': 0.03429201136825487, 'batch_size': 32} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 13:01:39,911] Trial 72 pruned. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.542102 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.32537321478277587, 'lr': 0.001264184830591255, 'weight_decay': 0.03216566390788505, 'batch_size': 32} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 13:03:11,136] Trial 73 finished with value: 0.5512994332944948 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.33898797729135705, 'lr': 0.0021858054184698515, 'weight_decay': 0.021920041417213036, 'batch_size': 32}. Best is trial 57 with value: 0.5622375492647842. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.551299 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.33898797729135705, 'lr': 0.0021858054184698515, 'weight_decay': 0.021920041417213036, 'batch_size': 32} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 13:04:31,315] Trial 74 finished with value: 0.5576171711615054 and parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.31753257872429125, 'lr': 0.0018046667974695807, 'weight_decay': 0.028508253977462886, 'batch_size': 32}. Best is trial 57 with value: 0.5622375492647842. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.557617 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.31753257872429125, 'lr': 0.0018046667974695807, 'weight_decay': 0.028508253977462886, 'batch_size': 32} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 13:04:42,334] Trial 75 pruned. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.527967 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.35731718438182597, 'lr': 0.0016231247361438127, 'weight_decay': 0.058053551836962924, 'batch_size': 32} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 13:04:52,844] Trial 76 pruned. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.478039 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.3174372583193715, 'lr': 0.004143675415950162, 'weight_decay': 0.04444387698778899, 'batch_size': 32} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 13:06:25,385] Trial 77 finished with value: 0.5510367318749524 and parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3432096139747182, 'lr': 0.001349972325918033, 'weight_decay': 0.028527911585154022, 'batch_size': 32}. Best is trial 57 with value: 0.5622375492647842. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.551037 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3432096139747182, 'lr': 0.001349972325918033, 'weight_decay': 0.028527911585154022, 'batch_size': 32} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 13:07:15,135] Trial 78 finished with value: 0.5506433873800006 and parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.3535865604699027, 'lr': 0.002077968909215715, 'weight_decay': 0.03408538299486895, 'batch_size': 64}. Best is trial 57 with value: 0.5622375492647842. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.550643 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.3535865604699027, 'lr': 0.002077968909215715, 'weight_decay': 0.03408538299486895, 'batch_size': 64} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 13:07:26,230] Trial 79 pruned. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.515167 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3260558985990823, 'lr': 0.0028762548197660952, 'weight_decay': 0.04823652992667317, 'batch_size': 32} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 13:08:59,635] Trial 80 finished with value: 0.544878489962326 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3783306210266175, 'lr': 0.0017974384742427741, 'weight_decay': 0.027143162583010024, 'batch_size': 32}. Best is trial 57 with value: 0.5622375492647842. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.544878 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3783306210266175, 'lr': 0.0017974384742427741, 'weight_decay': 0.027143162583010024, 'batch_size': 32} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 13:10:06,275] Trial 81 finished with value: 0.5477478254836653 and parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.33346221580090457, 'lr': 0.0008825162642193032, 'weight_decay': 0.012421363329493703, 'batch_size': 32}. Best is trial 57 with value: 0.5622375492647842. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.547748 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.33346221580090457, 'lr': 0.0008825162642193032, 'weight_decay': 0.012421363329493703, 'batch_size': 32} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 13:11:19,469] Trial 82 pruned. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.521777 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3097915441734883, 'lr': 0.0010886098563170187, 'weight_decay': 0.021893070690878286, 'batch_size': 32} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 13:12:49,224] Trial 83 pruned. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.534725 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3028519103847426, 'lr': 0.001478901706212989, 'weight_decay': 0.03938398362077607, 'batch_size': 32} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 13:12:52,036] Trial 84 pruned. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.527282 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.31745247629019857, 'lr': 0.0023131890636881986, 'weight_decay': 0.015436812715398075, 'batch_size': 256} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 13:14:15,409] Trial 85 finished with value: 0.5557388961909923 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.36208970238831906, 'lr': 0.0008059990014923111, 'weight_decay': 0.018292902765348222, 'batch_size': 32}. Best is trial 57 with value: 0.5622375492647842. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.555739 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.36208970238831906, 'lr': 0.0008059990014923111, 'weight_decay': 0.018292902765348222, 'batch_size': 32} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 13:14:26,519] Trial 86 pruned. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.500474 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.36148326434398526, 'lr': 0.0012983075614718057, 'weight_decay': 0.031641278407837474, 'batch_size': 32} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) -[I 2025-12-25 13:14:45,299] Trial 87 pruned. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.547384 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.344724681529483, 'lr': 0.001672630443300514, 'weight_decay': 0.05702358568779882, 'batch_size': 128} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 13:16:12,106] Trial 88 finished with value: 0.554876529672856 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3694482233068902, 'lr': 0.0010505281360110661, 'weight_decay': 0.027370752836605502, 'batch_size': 32}. Best is trial 57 with value: 0.5622375492647842. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.554877 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3694482233068902, 'lr': 0.0010505281360110661, 'weight_decay': 0.027370752836605502, 'batch_size': 32} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 13:16:18,614] Trial 89 pruned. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.532301 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3717402997529454, 'lr': 0.0006632926936244838, 'weight_decay': 0.024807189908994, 'batch_size': 64} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 13:16:32,822] Trial 90 pruned. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.533265 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.36621400029766193, 'lr': 0.0008307785991559915, 'weight_decay': 0.017536994723021417, 'batch_size': 32} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 13:16:44,042] Trial 91 pruned. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.525558 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.35617613273745313, 'lr': 0.001056513740217729, 'weight_decay': 0.03834901822656005, 'batch_size': 32} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 13:16:55,443] Trial 92 pruned. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.513592 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3484197197003372, 'lr': 0.0019446450259542542, 'weight_decay': 0.030044583328576565, 'batch_size': 32} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 13:17:06,610] Trial 93 pruned. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.534180 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3835131127590826, 'lr': 0.001170222113278595, 'weight_decay': 0.020890637769647155, 'batch_size': 32} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 13:17:30,784] Trial 94 pruned. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.544728 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.33440991289422534, 'lr': 0.0014998866295702752, 'weight_decay': 0.04551806155946472, 'batch_size': 32} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 13:17:44,627] Trial 95 pruned. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.513598 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.3961264840810923, 'lr': 0.0009349614802098341, 'weight_decay': 0.013692037423928894, 'batch_size': 32} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 13:17:56,016] Trial 96 pruned. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.509284 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3604897963696044, 'lr': 0.0020867685509400775, 'weight_decay': 0.025623132769901476, 'batch_size': 32} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 13:18:07,146] Trial 97 pruned. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.509974 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3261004632013275, 'lr': 0.002646589655307092, 'weight_decay': 0.03635150165026664, 'batch_size': 32} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 13:18:18,155] Trial 98 pruned. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.537466 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.34235552737413705, 'lr': 0.0013596516998081044, 'weight_decay': 0.011544636065521908, 'batch_size': 32} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 13:18:24,507] Trial 99 pruned. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.533965 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3504310077859415, 'lr': 0.0008184057704509884, 'weight_decay': 0.05095561734194177, 'batch_size': 64} - Best Value (CSI): 0.562238 - Best Trial: 57 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.5622 -Best Hyperparameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3553750103803738, 'lr': 0.0017038392317957017, 'weight_decay': 0.04010324241876258, 'batch_size': 32} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.5398 - - 최종 CSI: 0.5340 - - 최고 CSI: 0.5622 - - 최저 CSI: 0.4402 - - 평균 CSI: 0.5299 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/deepgbm_pure_incheon_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 38, Best CSI: 0.5698 - Fold 1 학습 완료 (검증 CSI: 0.5698) -Fold 2 학습 중... - Early stopping at epoch 36, Best CSI: 0.5718 - Fold 2 학습 완료 (검증 CSI: 0.5718) -Fold 3 학습 중... - Early stopping at epoch 54, Best CSI: 0.5262 - Fold 3 학습 완료 (검증 CSI: 0.5262) - -모든 모델 저장 완료: ../save_model/deepgbm_optima/deepgbm_pure_incheon.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/deepgbm_optima/scaler/deepgbm_pure_incheon_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: - - . - - . - - / - - s - - a - - v - - e - - _ - - m - - o - - d - - e - - l - - / - - d - - e - - e - - p - - g - - b - - m - - _ - - o - - p - - t - - i - - m - - a - - / - - d - - e - - e - - p - - g - - b - - m - - _ - - p - - u - - r - - e - - _ - - i - - n - - c - - h - - e - - o - - n - - . - - p - - k - - l - -✓ 완료: deepgbm_pure/deepgbm_pure_incheon.py (소요 시간: 5015초) - ----------------------------------------- -실행 중: deepgbm_pure/deepgbm_pure_seoul.py -시작 시간: 2025-12-25 13:20:11 ----------------------------------------- -[I 2025-12-25 13:20:13,013] A new study created in memory with name: no-name-07f43e77-e098-449f-b993-9405f1219c23 - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 13:21:31,484] Trial 0 finished with value: 0.4257937191690074 and parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.24533239114869734, 'lr': 1.3834131192346413e-05, 'weight_decay': 0.006886966554932495, 'batch_size': 128}. Best is trial 0 with value: 0.4257937191690074. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.425794 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.24533239114869734, 'lr': 1.3834131192346413e-05, 'weight_decay': 0.006886966554932495, 'batch_size': 128} - Best Value (CSI): 0.425794 - Best Trial: 0 - Best Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.24533239114869734, 'lr': 1.3834131192346413e-05, 'weight_decay': 0.006886966554932495, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 13:23:32,290] Trial 1 finished with value: 0.5217902349231974 and parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.3329283403125648, 'lr': 0.008460577568852379, 'weight_decay': 0.0005221386819991609, 'batch_size': 32}. Best is trial 1 with value: 0.5217902349231974. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.521790 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.3329283403125648, 'lr': 0.008460577568852379, 'weight_decay': 0.0005221386819991609, 'batch_size': 32} - Best Value (CSI): 0.521790 - Best Trial: 1 - Best Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.3329283403125648, 'lr': 0.008460577568852379, 'weight_decay': 0.0005221386819991609, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 13:25:05,819] Trial 2 finished with value: 0.4776861542911755 and parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.13249850322742868, 'lr': 1.590501934852864e-05, 'weight_decay': 0.015109012194703939, 'batch_size': 64}. Best is trial 1 with value: 0.5217902349231974. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.477686 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.13249850322742868, 'lr': 1.590501934852864e-05, 'weight_decay': 0.015109012194703939, 'batch_size': 64} - Best Value (CSI): 0.521790 - Best Trial: 1 - Best Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.3329283403125648, 'lr': 0.008460577568852379, 'weight_decay': 0.0005221386819991609, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 13:25:58,542] Trial 3 finished with value: 0.5265813362473614 and parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.38915968797450695, 'lr': 0.002206237271158953, 'weight_decay': 0.002856471203543811, 'batch_size': 128}. Best is trial 3 with value: 0.5265813362473614. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.526581 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.38915968797450695, 'lr': 0.002206237271158953, 'weight_decay': 0.002856471203543811, 'batch_size': 128} - Best Value (CSI): 0.526581 - Best Trial: 3 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.38915968797450695, 'lr': 0.002206237271158953, 'weight_decay': 0.002856471203543811, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 13:26:41,520] Trial 4 finished with value: 0.5232331396936433 and parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.36916759307006974, 'lr': 0.00027492710838838074, 'weight_decay': 0.00030969873026156163, 'batch_size': 128}. Best is trial 3 with value: 0.5265813362473614. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.523233 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.36916759307006974, 'lr': 0.00027492710838838074, 'weight_decay': 0.00030969873026156163, 'batch_size': 128} - Best Value (CSI): 0.526581 - Best Trial: 3 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.38915968797450695, 'lr': 0.002206237271158953, 'weight_decay': 0.002856471203543811, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 13:27:34,418] Trial 5 finished with value: 0.5259974241657493 and parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2519433809120093, 'lr': 0.006607593409392719, 'weight_decay': 0.009875138243321667, 'batch_size': 64}. Best is trial 3 with value: 0.5265813362473614. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.525997 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2519433809120093, 'lr': 0.006607593409392719, 'weight_decay': 0.009875138243321667, 'batch_size': 64} - Best Value (CSI): 0.526581 - Best Trial: 3 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.38915968797450695, 'lr': 0.002206237271158953, 'weight_decay': 0.002856471203543811, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:27:40,608] Trial 6 pruned. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.398383 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.18826206529203332, 'lr': 0.0003857347399967069, 'weight_decay': 0.003276996041484107, 'batch_size': 256} - Best Value (CSI): 0.526581 - Best Trial: 3 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.38915968797450695, 'lr': 0.002206237271158953, 'weight_decay': 0.002856471203543811, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:27:44,531] Trial 7 pruned. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.186809 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3374661572117743, 'lr': 1.1507176143400515e-05, 'weight_decay': 0.0007461883525425925, 'batch_size': 128} - Best Value (CSI): 0.526581 - Best Trial: 3 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.38915968797450695, 'lr': 0.002206237271158953, 'weight_decay': 0.002856471203543811, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:28:19,004] Trial 8 pruned. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.403846 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3363138836670656, 'lr': 4.762517027847149e-05, 'weight_decay': 0.000851460560120491, 'batch_size': 32} - Best Value (CSI): 0.526581 - Best Trial: 3 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.38915968797450695, 'lr': 0.002206237271158953, 'weight_decay': 0.002856471203543811, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:28:21,449] Trial 9 pruned. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.142247 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2658526999592039, 'lr': 1.9119414415742538e-05, 'weight_decay': 0.00015159440958890412, 'batch_size': 256} - Best Value (CSI): 0.526581 - Best Trial: 3 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.38915968797450695, 'lr': 0.002206237271158953, 'weight_decay': 0.002856471203543811, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:28:25,609] Trial 10 pruned. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.356707 - Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.39980645815585986, 'lr': 0.002268670414758156, 'weight_decay': 0.06589901256066216, 'batch_size': 128} - Best Value (CSI): 0.526581 - Best Trial: 3 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.38915968797450695, 'lr': 0.002206237271158953, 'weight_decay': 0.002856471203543811, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 13:29:06,734] Trial 11 finished with value: 0.5136619825533483 and parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.272877246131759, 'lr': 0.008969645570237288, 'weight_decay': 0.0025708521254366795, 'batch_size': 64}. Best is trial 3 with value: 0.5265813362473614. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.513662 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.272877246131759, 'lr': 0.008969645570237288, 'weight_decay': 0.0025708521254366795, 'batch_size': 64} - Best Value (CSI): 0.526581 - Best Trial: 3 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.38915968797450695, 'lr': 0.002206237271158953, 'weight_decay': 0.002856471203543811, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:29:19,241] Trial 12 pruned. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.394030 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.21128949147568887, 'lr': 0.0023081707056596657, 'weight_decay': 0.01153943121395969, 'batch_size': 64} - Best Value (CSI): 0.526581 - Best Trial: 3 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.38915968797450695, 'lr': 0.002206237271158953, 'weight_decay': 0.002856471203543811, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:29:34,856] Trial 13 pruned. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.419257 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.2951170641941568, 'lr': 0.0021921511794306676, 'weight_decay': 0.0026244181787671073, 'batch_size': 64} - Best Value (CSI): 0.526581 - Best Trial: 3 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.38915968797450695, 'lr': 0.002206237271158953, 'weight_decay': 0.002856471203543811, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:29:43,635] Trial 14 pruned. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.396780 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.38349779067315165, 'lr': 0.004216956688762611, 'weight_decay': 0.03579711342954294, 'batch_size': 128} - Best Value (CSI): 0.526581 - Best Trial: 3 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.38915968797450695, 'lr': 0.002206237271158953, 'weight_decay': 0.002856471203543811, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:29:56,751] Trial 15 pruned. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.421323 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3048994156001041, 'lr': 0.0008839252271513052, 'weight_decay': 0.03082100394093231, 'batch_size': 64} - Best Value (CSI): 0.526581 - Best Trial: 3 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.38915968797450695, 'lr': 0.002206237271158953, 'weight_decay': 0.002856471203543811, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 13:31:19,969] Trial 16 finished with value: 0.5130527730041567 and parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.22686386336117725, 'lr': 0.009989725678278109, 'weight_decay': 0.0057397826952661855, 'batch_size': 32}. Best is trial 3 with value: 0.5265813362473614. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.513053 - Parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.22686386336117725, 'lr': 0.009989725678278109, 'weight_decay': 0.0057397826952661855, 'batch_size': 32} - Best Value (CSI): 0.526581 - Best Trial: 3 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.38915968797450695, 'lr': 0.002206237271158953, 'weight_decay': 0.002856471203543811, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:31:25,549] Trial 17 pruned. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.365655 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10212372893850391, 'lr': 0.0038731937740659377, 'weight_decay': 0.0015634351927414293, 'batch_size': 256} - Best Value (CSI): 0.526581 - Best Trial: 3 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.38915968797450695, 'lr': 0.002206237271158953, 'weight_decay': 0.002856471203543811, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:31:39,287] Trial 18 pruned. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.391451 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3642350209271259, 'lr': 0.001011965722445585, 'weight_decay': 0.0064774300427520946, 'batch_size': 64} - Best Value (CSI): 0.526581 - Best Trial: 3 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.38915968797450695, 'lr': 0.002206237271158953, 'weight_decay': 0.002856471203543811, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:31:46,484] Trial 19 pruned. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.370810 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3063538515751695, 'lr': 0.004602423828782875, 'weight_decay': 0.08942357391272167, 'batch_size': 128} - Best Value (CSI): 0.526581 - Best Trial: 3 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.38915968797450695, 'lr': 0.002206237271158953, 'weight_decay': 0.002856471203543811, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:31:59,314] Trial 20 pruned. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.388360 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.39789626668021333, 'lr': 0.0013594764302116335, 'weight_decay': 0.001330978667203392, 'batch_size': 64} - Best Value (CSI): 0.526581 - Best Trial: 3 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.38915968797450695, 'lr': 0.002206237271158953, 'weight_decay': 0.002856471203543811, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:32:07,309] Trial 21 pruned. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.363126 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.3709186372452401, 'lr': 0.00022299337000533114, 'weight_decay': 0.0002839863109594537, 'batch_size': 128} - Best Value (CSI): 0.526581 - Best Trial: 3 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.38915968797450695, 'lr': 0.002206237271158953, 'weight_decay': 0.002856471203543811, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:32:14,945] Trial 22 pruned. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.366393 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.35723433774945695, 'lr': 0.00047698065015298885, 'weight_decay': 0.00011438128742236901, 'batch_size': 128} - Best Value (CSI): 0.526581 - Best Trial: 3 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.38915968797450695, 'lr': 0.002206237271158953, 'weight_decay': 0.002856471203543811, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:32:21,329] Trial 23 pruned. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.338491 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.35813244748258455, 'lr': 0.00021346071592888446, 'weight_decay': 0.0003782297028110424, 'batch_size': 128} - Best Value (CSI): 0.526581 - Best Trial: 3 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.38915968797450695, 'lr': 0.002206237271158953, 'weight_decay': 0.002856471203543811, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:32:29,334] Trial 24 pruned. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.374176 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.32294167741689767, 'lr': 0.00012020083537808011, 'weight_decay': 0.0002702149732287292, 'batch_size': 128} - Best Value (CSI): 0.526581 - Best Trial: 3 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.38915968797450695, 'lr': 0.002206237271158953, 'weight_decay': 0.002856471203543811, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:32:36,831] Trial 25 pruned. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.388002 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.38179877195394873, 'lr': 0.0006063353967799699, 'weight_decay': 0.00018019592094984649, 'batch_size': 128} - Best Value (CSI): 0.526581 - Best Trial: 3 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.38915968797450695, 'lr': 0.002206237271158953, 'weight_decay': 0.002856471203543811, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:32:56,078] Trial 26 pruned. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.402129 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.2840639484621873, 'lr': 0.0007073926017645721, 'weight_decay': 0.000506847054545457, 'batch_size': 32} - Best Value (CSI): 0.526581 - Best Trial: 3 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.38915968797450695, 'lr': 0.002206237271158953, 'weight_decay': 0.002856471203543811, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:33:04,473] Trial 27 pruned. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.344214 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.34848665237836135, 'lr': 0.0011783125670281876, 'weight_decay': 0.00010338911849833163, 'batch_size': 128} - Best Value (CSI): 0.526581 - Best Trial: 3 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.38915968797450695, 'lr': 0.002206237271158953, 'weight_decay': 0.002856471203543811, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:33:10,700] Trial 28 pruned. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.396226 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.3225431361734203, 'lr': 0.0003209992376974646, 'weight_decay': 0.0017705915447214086, 'batch_size': 256} - Best Value (CSI): 0.526581 - Best Trial: 3 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.38915968797450695, 'lr': 0.002206237271158953, 'weight_decay': 0.002856471203543811, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:33:18,555] Trial 29 pruned. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.384406 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2494359506395347, 'lr': 0.0015163881508858644, 'weight_decay': 0.004152596201816479, 'batch_size': 128} - Best Value (CSI): 0.526581 - Best Trial: 3 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.38915968797450695, 'lr': 0.002206237271158953, 'weight_decay': 0.002856471203543811, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:33:25,458] Trial 30 pruned. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.323448 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.37458466696555887, 'lr': 0.00011029244400696151, 'weight_decay': 0.010157243274653723, 'batch_size': 64} - Best Value (CSI): 0.526581 - Best Trial: 3 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.38915968797450695, 'lr': 0.002206237271158953, 'weight_decay': 0.002856471203543811, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) -[I 2025-12-25 13:34:23,622] Trial 31 pruned. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.579710 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.3453985874591653, 'lr': 0.007196211758982616, 'weight_decay': 0.000603684027598055, 'batch_size': 32} - Best Value (CSI): 0.526581 - Best Trial: 3 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.38915968797450695, 'lr': 0.002206237271158953, 'weight_decay': 0.002856471203543811, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 13:35:43,867] Trial 32 finished with value: 0.5182845445415168 and parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.322352471871049, 'lr': 0.005762308799319182, 'weight_decay': 0.001023691861547231, 'batch_size': 32}. Best is trial 3 with value: 0.5265813362473614. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.518285 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.322352471871049, 'lr': 0.005762308799319182, 'weight_decay': 0.001023691861547231, 'batch_size': 32} - Best Value (CSI): 0.526581 - Best Trial: 3 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.38915968797450695, 'lr': 0.002206237271158953, 'weight_decay': 0.002856471203543811, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) -[I 2025-12-25 13:36:32,959] Trial 33 pruned. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.560193 - Parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.38551627155299417, 'lr': 0.0067740915716981145, 'weight_decay': 0.0005235446959190094, 'batch_size': 32} - Best Value (CSI): 0.526581 - Best Trial: 3 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.38915968797450695, 'lr': 0.002206237271158953, 'weight_decay': 0.002856471203543811, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 13:37:58,477] Trial 34 finished with value: 0.5327039098747891 and parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.36256869173628287, 'lr': 0.0031459785086856472, 'weight_decay': 0.001019078421472157, 'batch_size': 32}. Best is trial 34 with value: 0.5327039098747891. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.532704 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.36256869173628287, 'lr': 0.0031459785086856472, 'weight_decay': 0.001019078421472157, 'batch_size': 32} - Best Value (CSI): 0.532704 - Best Trial: 34 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.36256869173628287, 'lr': 0.0031459785086856472, 'weight_decay': 0.001019078421472157, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:38:20,264] Trial 35 pruned. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.377121 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.35602094116311467, 'lr': 0.0031515165320641038, 'weight_decay': 0.0043432073295441125, 'batch_size': 32} - Best Value (CSI): 0.532704 - Best Trial: 34 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.36256869173628287, 'lr': 0.0031459785086856472, 'weight_decay': 0.001019078421472157, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:38:42,715] Trial 36 pruned. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.311209 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3378610904143791, 'lr': 0.005518149038627045, 'weight_decay': 0.0021092442879812622, 'batch_size': 32} - Best Value (CSI): 0.532704 - Best Trial: 34 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.36256869173628287, 'lr': 0.0031459785086856472, 'weight_decay': 0.001019078421472157, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 13:39:07,189] Trial 37 finished with value: 0.5258987348114557 and parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.16823769493210755, 'lr': 0.00340669549778494, 'weight_decay': 0.003052376954178058, 'batch_size': 256}. Best is trial 34 with value: 0.5327039098747891. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.525899 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.16823769493210755, 'lr': 0.00340669549778494, 'weight_decay': 0.003052376954178058, 'batch_size': 256} - Best Value (CSI): 0.532704 - Best Trial: 34 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.36256869173628287, 'lr': 0.0031459785086856472, 'weight_decay': 0.001019078421472157, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:39:12,742] Trial 38 pruned. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.410634 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.17576213280578845, 'lr': 0.0030461945211193355, 'weight_decay': 0.003450036500483126, 'batch_size': 256} - Best Value (CSI): 0.532704 - Best Trial: 34 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.36256869173628287, 'lr': 0.0031459785086856472, 'weight_decay': 0.001019078421472157, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:39:18,700] Trial 39 pruned. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.424282 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.16237597302949805, 'lr': 0.0016862292746772259, 'weight_decay': 0.0011832260192519669, 'batch_size': 256} - Best Value (CSI): 0.532704 - Best Trial: 34 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.36256869173628287, 'lr': 0.0031459785086856472, 'weight_decay': 0.001019078421472157, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:39:24,155] Trial 40 pruned. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.377093 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.26217554327757475, 'lr': 0.00328255537661049, 'weight_decay': 0.0021467968668157944, 'batch_size': 256} - Best Value (CSI): 0.532704 - Best Trial: 34 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.36256869173628287, 'lr': 0.0031459785086856472, 'weight_decay': 0.001019078421472157, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:39:29,656] Trial 41 pruned. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.377970 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.23394490975108634, 'lr': 0.005167693140048367, 'weight_decay': 0.0008946674079135073, 'batch_size': 256} - Best Value (CSI): 0.532704 - Best Trial: 34 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.36256869173628287, 'lr': 0.0031459785086856472, 'weight_decay': 0.001019078421472157, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:39:37,115] Trial 42 pruned. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.421717 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.2035783531844373, 'lr': 0.0021629427970970084, 'weight_decay': 0.0032722024858649434, 'batch_size': 128} - Best Value (CSI): 0.532704 - Best Trial: 34 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.36256869173628287, 'lr': 0.0031459785086856472, 'weight_decay': 0.001019078421472157, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) -[I 2025-12-25 13:40:02,828] Trial 43 pruned. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.575251 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3699380649940796, 'lr': 0.007320561134568392, 'weight_decay': 0.0016215069666944534, 'batch_size': 64} - Best Value (CSI): 0.532704 - Best Trial: 34 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.36256869173628287, 'lr': 0.0031459785086856472, 'weight_decay': 0.001019078421472157, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:40:08,132] Trial 44 pruned. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.350688 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.39712718493406857, 'lr': 0.002867455735998788, 'weight_decay': 0.0007385220790150335, 'batch_size': 256} - Best Value (CSI): 0.532704 - Best Trial: 34 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.36256869173628287, 'lr': 0.0031459785086856472, 'weight_decay': 0.001019078421472157, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) -[I 2025-12-25 13:40:31,708] Trial 45 pruned. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.565880 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.28284815643563466, 'lr': 0.009625272189340147, 'weight_decay': 0.002411559996053079, 'batch_size': 64} - Best Value (CSI): 0.532704 - Best Trial: 34 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.36256869173628287, 'lr': 0.0031459785086856472, 'weight_decay': 0.001019078421472157, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:40:36,063] Trial 46 pruned. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.320755 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.2548719157226795, 'lr': 0.00418095250613359, 'weight_decay': 0.00882826278366247, 'batch_size': 128} - Best Value (CSI): 0.532704 - Best Trial: 34 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.36256869173628287, 'lr': 0.0031459785086856472, 'weight_decay': 0.001019078421472157, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:40:40,675] Trial 47 pruned. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.414482 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.14784332607738693, 'lr': 0.0018457091247414978, 'weight_decay': 0.004838857981408515, 'batch_size': 256} - Best Value (CSI): 0.532704 - Best Trial: 34 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.36256869173628287, 'lr': 0.0031459785086856472, 'weight_decay': 0.001019078421472157, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:41:05,059] Trial 48 pruned. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.360731 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.20684001105033029, 'lr': 0.002508117462266513, 'weight_decay': 0.014960378957622481, 'batch_size': 32} - Best Value (CSI): 0.532704 - Best Trial: 34 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.36256869173628287, 'lr': 0.0031459785086856472, 'weight_decay': 0.001019078421472157, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:41:17,453] Trial 49 pruned. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.420615 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.18853045054490844, 'lr': 0.001075241812418215, 'weight_decay': 0.006409240196040836, 'batch_size': 64} - Best Value (CSI): 0.532704 - Best Trial: 34 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.36256869173628287, 'lr': 0.0031459785086856472, 'weight_decay': 0.001019078421472157, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:41:25,385] Trial 50 pruned. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.385177 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.23057029803789347, 'lr': 0.004322427429843228, 'weight_decay': 0.0034469084125107684, 'batch_size': 128} - Best Value (CSI): 0.532704 - Best Trial: 34 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.36256869173628287, 'lr': 0.0031459785086856472, 'weight_decay': 0.001019078421472157, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:41:40,436] Trial 51 pruned. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.364699 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.3842270801262768, 'lr': 0.007100852061550358, 'weight_decay': 0.001029713683940837, 'batch_size': 32} - Best Value (CSI): 0.532704 - Best Trial: 34 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.36256869173628287, 'lr': 0.0031459785086856472, 'weight_decay': 0.001019078421472157, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:41:59,820] Trial 52 pruned. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.314362 - Parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.36244244370315915, 'lr': 0.0038123454866597515, 'weight_decay': 0.0013783590993703301, 'batch_size': 32} - Best Value (CSI): 0.532704 - Best Trial: 34 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.36256869173628287, 'lr': 0.0031459785086856472, 'weight_decay': 0.001019078421472157, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:42:23,504] Trial 53 pruned. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.281950 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.34095276257195767, 'lr': 0.005509401795015204, 'weight_decay': 0.0007275318261210044, 'batch_size': 32} - Best Value (CSI): 0.532704 - Best Trial: 34 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.36256869173628287, 'lr': 0.0031459785086856472, 'weight_decay': 0.001019078421472157, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:42:33,421] Trial 54 pruned. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.371697 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.33017310352064017, 'lr': 0.009641448443541147, 'weight_decay': 0.006985626311108936, 'batch_size': 64} - Best Value (CSI): 0.532704 - Best Trial: 34 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.36256869173628287, 'lr': 0.0031459785086856472, 'weight_decay': 0.001019078421472157, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:42:55,665] Trial 55 pruned. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.392347 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.30882896588722286, 'lr': 0.0022518067621091816, 'weight_decay': 0.0027194331206095395, 'batch_size': 32} - Best Value (CSI): 0.532704 - Best Trial: 34 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.36256869173628287, 'lr': 0.0031459785086856472, 'weight_decay': 0.001019078421472157, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:42:59,461] Trial 56 pruned. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.311718 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3533606123085212, 'lr': 0.003573577586473713, 'weight_decay': 0.0003904483498121975, 'batch_size': 128} - Best Value (CSI): 0.532704 - Best Trial: 34 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.36256869173628287, 'lr': 0.0031459785086856472, 'weight_decay': 0.001019078421472157, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:43:07,290] Trial 57 pruned. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.353002 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3690334114614377, 'lr': 0.004881269463971595, 'weight_decay': 0.0016147737166172062, 'batch_size': 128} - Best Value (CSI): 0.532704 - Best Trial: 34 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.36256869173628287, 'lr': 0.0031459785086856472, 'weight_decay': 0.001019078421472157, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:43:14,053] Trial 58 pruned. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.332865 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.39244811349331055, 'lr': 0.0014132263060035078, 'weight_decay': 0.0011652663457776989, 'batch_size': 64} - Best Value (CSI): 0.532704 - Best Trial: 34 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.36256869173628287, 'lr': 0.0031459785086856472, 'weight_decay': 0.001019078421472157, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 13:44:19,463] Trial 59 finished with value: 0.5325254967062022 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.3775866167118096, 'lr': 0.0027056153896556296, 'weight_decay': 0.0008716493551503847, 'batch_size': 32}. Best is trial 34 with value: 0.5327039098747891. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.532525 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.3775866167118096, 'lr': 0.0027056153896556296, 'weight_decay': 0.0008716493551503847, 'batch_size': 32} - Best Value (CSI): 0.532704 - Best Trial: 34 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.36256869173628287, 'lr': 0.0031459785086856472, 'weight_decay': 0.001019078421472157, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 13:45:35,611] Trial 60 finished with value: 0.5382307883651579 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39995741419293035, 'lr': 0.0008596009108018591, 'weight_decay': 0.0019683288071159, 'batch_size': 32}. Best is trial 60 with value: 0.5382307883651579. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.538231 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39995741419293035, 'lr': 0.0008596009108018591, 'weight_decay': 0.0019683288071159, 'batch_size': 32} - Best Value (CSI): 0.538231 - Best Trial: 60 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39995741419293035, 'lr': 0.0008596009108018591, 'weight_decay': 0.0019683288071159, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 13:47:02,678] Trial 61 finished with value: 0.5344098660307736 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3807606029091518, 'lr': 0.0008837300172149344, 'weight_decay': 0.001995360877096483, 'batch_size': 32}. Best is trial 60 with value: 0.5382307883651579. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.534410 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3807606029091518, 'lr': 0.0008837300172149344, 'weight_decay': 0.001995360877096483, 'batch_size': 32} - Best Value (CSI): 0.538231 - Best Trial: 60 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39995741419293035, 'lr': 0.0008596009108018591, 'weight_decay': 0.0019683288071159, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 13:48:17,452] Trial 62 finished with value: 0.526553959349716 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3905406867876245, 'lr': 0.0008419844050233724, 'weight_decay': 0.0019017839502972276, 'batch_size': 32}. Best is trial 60 with value: 0.5382307883651579. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.526554 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3905406867876245, 'lr': 0.0008419844050233724, 'weight_decay': 0.0019017839502972276, 'batch_size': 32} - Best Value (CSI): 0.538231 - Best Trial: 60 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39995741419293035, 'lr': 0.0008596009108018591, 'weight_decay': 0.0019683288071159, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 13:49:26,438] Trial 63 finished with value: 0.5345969256568647 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.38201019377313766, 'lr': 0.000791573015600074, 'weight_decay': 0.002006341930460683, 'batch_size': 32}. Best is trial 60 with value: 0.5382307883651579. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.534597 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.38201019377313766, 'lr': 0.000791573015600074, 'weight_decay': 0.002006341930460683, 'batch_size': 32} - Best Value (CSI): 0.538231 - Best Trial: 60 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39995741419293035, 'lr': 0.0008596009108018591, 'weight_decay': 0.0019683288071159, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:49:46,027] Trial 64 pruned. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.394963 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3775526559513589, 'lr': 0.0008251589882571121, 'weight_decay': 0.0018050904270789745, 'batch_size': 32} - Best Value (CSI): 0.538231 - Best Trial: 60 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39995741419293035, 'lr': 0.0008596009108018591, 'weight_decay': 0.0019683288071159, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:50:00,459] Trial 65 pruned. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.389208 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3998445866172021, 'lr': 0.0012957632779441897, 'weight_decay': 0.001976776511261475, 'batch_size': 32} - Best Value (CSI): 0.538231 - Best Trial: 60 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39995741419293035, 'lr': 0.0008596009108018591, 'weight_decay': 0.0019683288071159, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:50:19,980] Trial 66 pruned. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.395989 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3890169099181452, 'lr': 0.000902858163866817, 'weight_decay': 0.001511558224942256, 'batch_size': 32} - Best Value (CSI): 0.538231 - Best Trial: 60 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39995741419293035, 'lr': 0.0008596009108018591, 'weight_decay': 0.0019683288071159, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:50:39,151] Trial 67 pruned. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.405771 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3799706748630615, 'lr': 0.0006191985858530829, 'weight_decay': 0.0024550907044714214, 'batch_size': 32} - Best Value (CSI): 0.538231 - Best Trial: 60 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39995741419293035, 'lr': 0.0008596009108018591, 'weight_decay': 0.0019683288071159, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:50:58,576] Trial 68 pruned. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.392334 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39087598404238166, 'lr': 0.0004911598719006123, 'weight_decay': 0.0013157009928850254, 'batch_size': 32} - Best Value (CSI): 0.538231 - Best Trial: 60 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39995741419293035, 'lr': 0.0008596009108018591, 'weight_decay': 0.0019683288071159, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:51:18,134] Trial 69 pruned. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.364252 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.37623495014430325, 'lr': 0.001075010669551354, 'weight_decay': 0.0022070918528649904, 'batch_size': 32} - Best Value (CSI): 0.538231 - Best Trial: 60 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39995741419293035, 'lr': 0.0008596009108018591, 'weight_decay': 0.0019683288071159, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 13:52:23,340] Trial 70 finished with value: 0.5255450538411197 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.36381421604592357, 'lr': 0.0017046478348638765, 'weight_decay': 0.0008951359594464586, 'batch_size': 32}. Best is trial 60 with value: 0.5382307883651579. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.525545 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.36381421604592357, 'lr': 0.0017046478348638765, 'weight_decay': 0.0008951359594464586, 'batch_size': 32} - Best Value (CSI): 0.538231 - Best Trial: 60 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39995741419293035, 'lr': 0.0008596009108018591, 'weight_decay': 0.0019683288071159, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 13:53:20,982] Trial 71 finished with value: 0.5295993787850383 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39304874309946425, 'lr': 0.0008197444942849649, 'weight_decay': 0.0018221540203865398, 'batch_size': 32}. Best is trial 60 with value: 0.5382307883651579. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.529599 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39304874309946425, 'lr': 0.0008197444942849649, 'weight_decay': 0.0018221540203865398, 'batch_size': 32} - Best Value (CSI): 0.538231 - Best Trial: 60 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39995741419293035, 'lr': 0.0008596009108018591, 'weight_decay': 0.0019683288071159, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:53:40,439] Trial 72 pruned. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.392201 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3880474848623916, 'lr': 0.0007946878848175573, 'weight_decay': 0.0016887233874288868, 'batch_size': 32} - Best Value (CSI): 0.538231 - Best Trial: 60 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39995741419293035, 'lr': 0.0008596009108018591, 'weight_decay': 0.0019683288071159, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 13:54:58,004] Trial 73 finished with value: 0.5365783664742453 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3727845257499506, 'lr': 0.00123747925778372, 'weight_decay': 0.002716965045577952, 'batch_size': 32}. Best is trial 60 with value: 0.5382307883651579. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.536578 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3727845257499506, 'lr': 0.00123747925778372, 'weight_decay': 0.002716965045577952, 'batch_size': 32} - Best Value (CSI): 0.538231 - Best Trial: 60 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39995741419293035, 'lr': 0.0008596009108018591, 'weight_decay': 0.0019683288071159, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:55:17,670] Trial 74 pruned. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.377944 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3765405616196625, 'lr': 0.0012212795970882207, 'weight_decay': 0.0012018095894975247, 'batch_size': 32} - Best Value (CSI): 0.538231 - Best Trial: 60 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39995741419293035, 'lr': 0.0008596009108018591, 'weight_decay': 0.0019683288071159, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:55:43,371] Trial 75 pruned. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.406028 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3997927148271429, 'lr': 0.0018228692864038626, 'weight_decay': 0.0025002270988140726, 'batch_size': 32} - Best Value (CSI): 0.538231 - Best Trial: 60 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39995741419293035, 'lr': 0.0008596009108018591, 'weight_decay': 0.0019683288071159, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:56:02,659] Trial 76 pruned. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.409768 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3681331957200844, 'lr': 0.001402619060234926, 'weight_decay': 0.003969840523803311, 'batch_size': 32} - Best Value (CSI): 0.538231 - Best Trial: 60 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39995741419293035, 'lr': 0.0008596009108018591, 'weight_decay': 0.0019683288071159, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:56:21,628] Trial 77 pruned. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.384574 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.35259219230250877, 'lr': 0.0006346170931794358, 'weight_decay': 0.0020545341979007663, 'batch_size': 32} - Best Value (CSI): 0.538231 - Best Trial: 60 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39995741419293035, 'lr': 0.0008596009108018591, 'weight_decay': 0.0019683288071159, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 13:57:38,196] Trial 78 finished with value: 0.5321672379175697 and parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3636578680891997, 'lr': 0.002675760352345131, 'weight_decay': 0.002683076356227441, 'batch_size': 32}. Best is trial 60 with value: 0.5382307883651579. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.532167 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3636578680891997, 'lr': 0.002675760352345131, 'weight_decay': 0.002683076356227441, 'batch_size': 32} - Best Value (CSI): 0.538231 - Best Trial: 60 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39995741419293035, 'lr': 0.0008596009108018591, 'weight_decay': 0.0019683288071159, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 13:59:16,780] Trial 79 finished with value: 0.5311776261856653 and parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.36239021013248446, 'lr': 0.0010126383424296603, 'weight_decay': 0.0028664780459203686, 'batch_size': 32}. Best is trial 60 with value: 0.5382307883651579. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.531178 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.36239021013248446, 'lr': 0.0010126383424296603, 'weight_decay': 0.0028664780459203686, 'batch_size': 32} - Best Value (CSI): 0.538231 - Best Trial: 60 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39995741419293035, 'lr': 0.0008596009108018591, 'weight_decay': 0.0019683288071159, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 13:59:41,403] Trial 80 pruned. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.423975 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.34257270499656395, 'lr': 0.0010785015729520857, 'weight_decay': 0.0032454677125051488, 'batch_size': 32} - Best Value (CSI): 0.538231 - Best Trial: 60 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39995741419293035, 'lr': 0.0008596009108018591, 'weight_decay': 0.0019683288071159, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 14:00:05,092] Trial 81 pruned. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.380235 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.36068797860383767, 'lr': 0.000996457924104477, 'weight_decay': 0.002912873917108787, 'batch_size': 32} - Best Value (CSI): 0.538231 - Best Trial: 60 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39995741419293035, 'lr': 0.0008596009108018591, 'weight_decay': 0.0019683288071159, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 14:01:24,599] Trial 82 finished with value: 0.5338810700775435 and parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3728886913968898, 'lr': 0.0005186702986774498, 'weight_decay': 0.0014732006995825824, 'batch_size': 32}. Best is trial 60 with value: 0.5382307883651579. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.533881 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3728886913968898, 'lr': 0.0005186702986774498, 'weight_decay': 0.0014732006995825824, 'batch_size': 32} - Best Value (CSI): 0.538231 - Best Trial: 60 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39995741419293035, 'lr': 0.0008596009108018591, 'weight_decay': 0.0019683288071159, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 14:01:48,307] Trial 83 pruned. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.423007 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3487650888309293, 'lr': 0.0004983582006048978, 'weight_decay': 0.0015165214315700907, 'batch_size': 32} - Best Value (CSI): 0.538231 - Best Trial: 60 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39995741419293035, 'lr': 0.0008596009108018591, 'weight_decay': 0.0019683288071159, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 14:03:33,144] Trial 84 finished with value: 0.5318115905774204 and parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.37273200184438604, 'lr': 0.002582017479681566, 'weight_decay': 0.002712147716067108, 'batch_size': 32}. Best is trial 60 with value: 0.5382307883651579. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.531812 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.37273200184438604, 'lr': 0.002582017479681566, 'weight_decay': 0.002712147716067108, 'batch_size': 32} - Best Value (CSI): 0.538231 - Best Trial: 60 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39995741419293035, 'lr': 0.0008596009108018591, 'weight_decay': 0.0019683288071159, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 14:03:51,514] Trial 85 pruned. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.389879 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.38068359590254974, 'lr': 0.0028152341182445142, 'weight_decay': 0.0010477529855403018, 'batch_size': 32} - Best Value (CSI): 0.538231 - Best Trial: 60 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39995741419293035, 'lr': 0.0008596009108018591, 'weight_decay': 0.0019683288071159, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 14:04:09,807] Trial 86 pruned. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.404508 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3705637020780281, 'lr': 0.0019527253774106294, 'weight_decay': 0.002249550821959253, 'batch_size': 32} - Best Value (CSI): 0.538231 - Best Trial: 60 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39995741419293035, 'lr': 0.0008596009108018591, 'weight_decay': 0.0019683288071159, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 14:05:15,831] Trial 87 finished with value: 0.5230164701895487 and parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3827170665655009, 'lr': 0.001599145792255847, 'weight_decay': 0.0014024534851214746, 'batch_size': 32}. Best is trial 60 with value: 0.5382307883651579. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.523016 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3827170665655009, 'lr': 0.001599145792255847, 'weight_decay': 0.0014024534851214746, 'batch_size': 32} - Best Value (CSI): 0.538231 - Best Trial: 60 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39995741419293035, 'lr': 0.0008596009108018591, 'weight_decay': 0.0019683288071159, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 14:05:34,626] Trial 88 pruned. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.422007 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3749907855066262, 'lr': 0.0024748874508626396, 'weight_decay': 0.003990337728479581, 'batch_size': 32} - Best Value (CSI): 0.538231 - Best Trial: 60 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39995741419293035, 'lr': 0.0008596009108018591, 'weight_decay': 0.0019683288071159, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 14:06:46,546] Trial 89 finished with value: 0.5318232308317515 and parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3565502593538942, 'lr': 0.0026949755646054406, 'weight_decay': 0.0025147223216072778, 'batch_size': 32}. Best is trial 60 with value: 0.5382307883651579. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.531823 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3565502593538942, 'lr': 0.0026949755646054406, 'weight_decay': 0.0025147223216072778, 'batch_size': 32} - Best Value (CSI): 0.538231 - Best Trial: 60 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39995741419293035, 'lr': 0.0008596009108018591, 'weight_decay': 0.0019683288071159, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) -[I 2025-12-25 14:07:22,474] Trial 90 pruned. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.556895 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.35877361545305386, 'lr': 0.0021251828351077904, 'weight_decay': 0.0013356474879583663, 'batch_size': 32} - Best Value (CSI): 0.538231 - Best Trial: 60 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39995741419293035, 'lr': 0.0008596009108018591, 'weight_decay': 0.0019683288071159, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 14:07:35,364] Trial 91 pruned. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.393811 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.36894009420187945, 'lr': 0.002651833003509981, 'weight_decay': 0.002650289012354075, 'batch_size': 32} - Best Value (CSI): 0.538231 - Best Trial: 60 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39995741419293035, 'lr': 0.0008596009108018591, 'weight_decay': 0.0019683288071159, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 14:07:52,491] Trial 92 pruned. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.358718 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.35415240401941045, 'lr': 0.0031372051018667517, 'weight_decay': 0.0020991315743877238, 'batch_size': 32} - Best Value (CSI): 0.538231 - Best Trial: 60 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39995741419293035, 'lr': 0.0008596009108018591, 'weight_decay': 0.0019683288071159, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 14:08:54,991] Trial 93 finished with value: 0.5441091848294762 and parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.38755576686685356, 'lr': 0.001481020211477321, 'weight_decay': 0.0036076992783665223, 'batch_size': 32}. Best is trial 93 with value: 0.5441091848294762. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.544109 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.38755576686685356, 'lr': 0.001481020211477321, 'weight_decay': 0.0036076992783665223, 'batch_size': 32} - Best Value (CSI): 0.544109 - Best Trial: 93 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.38755576686685356, 'lr': 0.001481020211477321, 'weight_decay': 0.0036076992783665223, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) -[I 2025-12-25 14:09:30,169] Trial 94 pruned. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.554364 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3852106274378048, 'lr': 0.0014344407987021027, 'weight_decay': 0.0033959435739903156, 'batch_size': 32} - Best Value (CSI): 0.544109 - Best Trial: 93 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.38755576686685356, 'lr': 0.001481020211477321, 'weight_decay': 0.0036076992783665223, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 14:09:48,980] Trial 95 pruned. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.398148 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3467193426661372, 'lr': 0.0007038616319449727, 'weight_decay': 0.0048507974462529135, 'batch_size': 32} - Best Value (CSI): 0.544109 - Best Trial: 93 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.38755576686685356, 'lr': 0.001481020211477321, 'weight_decay': 0.0036076992783665223, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 14:10:06,288] Trial 96 pruned. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.371983 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3839645842048834, 'lr': 0.001246811658403023, 'weight_decay': 0.0016668191042614685, 'batch_size': 32} - Best Value (CSI): 0.544109 - Best Trial: 93 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.38755576686685356, 'lr': 0.001481020211477321, 'weight_decay': 0.0036076992783665223, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 14:10:18,414] Trial 97 pruned. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.379370 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.39505839921902436, 'lr': 0.0019905245268807595, 'weight_decay': 0.0037390974393638073, 'batch_size': 32} - Best Value (CSI): 0.544109 - Best Trial: 93 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.38755576686685356, 'lr': 0.001481020211477321, 'weight_decay': 0.0036076992783665223, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 14:10:38,735] Trial 98 pruned. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.381522 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.36504354684948637, 'lr': 0.0015237952721035132, 'weight_decay': 0.002358565110645337, 'batch_size': 32} - Best Value (CSI): 0.544109 - Best Trial: 93 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.38755576686685356, 'lr': 0.001481020211477321, 'weight_decay': 0.0036076992783665223, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 14:10:52,058] Trial 99 pruned. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.395952 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3798891488946167, 'lr': 0.0036759618041821798, 'weight_decay': 0.00191325628922971, 'batch_size': 32} - Best Value (CSI): 0.544109 - Best Trial: 93 - Best Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.38755576686685356, 'lr': 0.001481020211477321, 'weight_decay': 0.0036076992783665223, 'batch_size': 32} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.5441 -Best Hyperparameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.38755576686685356, 'lr': 0.001481020211477321, 'weight_decay': 0.0036076992783665223, 'batch_size': 32} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.4258 - - 최종 CSI: 0.3960 - - 최고 CSI: 0.5797 - - 최저 CSI: 0.1422 - - 평균 CSI: 0.4241 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/deepgbm_pure_seoul_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 28, Best CSI: 0.4233 - Fold 1 학습 완료 (검증 CSI: 0.4233) -Fold 2 학습 중... - Early stopping at epoch 30, Best CSI: 0.6003 - Fold 2 학습 완료 (검증 CSI: 0.6003) -Fold 3 학습 중... - Early stopping at epoch 33, Best CSI: 0.5669 - Fold 3 학습 완료 (검증 CSI: 0.5669) - -모든 모델 저장 완료: ../save_model/deepgbm_optima/deepgbm_pure_seoul.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/deepgbm_optima/scaler/deepgbm_pure_seoul_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: - - . - - . - - / - - s - - a - - v - - e - - _ - - m - - o - - d - - e - - l - - / - - d - - e - - e - - p - - g - - b - - m - - _ - - o - - p - - t - - i - - m - - a - - / - - d - - e - - e - - p - - g - - b - - m - - _ - - p - - u - - r - - e - - _ - - s - - e - - o - - u - - l - - . - - p - - k - - l - -✓ 완료: deepgbm_pure/deepgbm_pure_seoul.py (소요 시간: 3111초) - -========================================== -DeepGBM Pure 파일 실행 완료 -종료 시간: 2025-12-25 14:12:02 -총 소요 시간: 6시간 59분 15초 -성공: 6개 -실패: 0개 -========================================== diff --git a/Analysis_code/5.optima/run_bash/deepgbm/deepgbm_smote.log b/Analysis_code/5.optima/run_bash/deepgbm/deepgbm_smote.log deleted file mode 100644 index 0dff19c78803dcd96f6bb75feb8bd395a4a5eff7..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/run_bash/deepgbm/deepgbm_smote.log +++ /dev/null @@ -1,8014 +0,0 @@ -nohup: ignoring input -/bin/bash: /opt/conda/lib/libtinfo.so.6: no version information available (required by /bin/bash) -========================================== -DeepGBM SMOTE 파일 실행 시작 -시작 시간: 2025-12-25 07:12:19 -GPU: 1번 (CUDA_VISIBLE_DEVICES=1) -========================================== - ----------------------------------------- -실행 중: deepgbm_smote/deepgbm_smote_busan.py -시작 시간: 2025-12-25 07:12:19 ----------------------------------------- -[I 2025-12-25 07:12:20,454] A new study created in memory with name: no-name-c9842cd7-6593-403d-8273-208f6c867f45 - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 07:14:40,285] Trial 0 finished with value: 0.4078744619513655 and parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.2537666397006374, 'lr': 6.855147896820647e-05, 'weight_decay': 0.00015935372159435351, 'batch_size': 64}. Best is trial 0 with value: 0.4078744619513655. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.407874 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.2537666397006374, 'lr': 6.855147896820647e-05, 'weight_decay': 0.00015935372159435351, 'batch_size': 64} - Best Value (CSI): 0.407874 - Best Trial: 0 - Best Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.2537666397006374, 'lr': 6.855147896820647e-05, 'weight_decay': 0.00015935372159435351, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 07:15:22,487] Trial 1 finished with value: 0.40564449370505945 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.26910036962813694, 'lr': 0.0028187224808550637, 'weight_decay': 0.00046794114309403053, 'batch_size': 256}. Best is trial 0 with value: 0.4078744619513655. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.405644 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.26910036962813694, 'lr': 0.0028187224808550637, 'weight_decay': 0.00046794114309403053, 'batch_size': 256} - Best Value (CSI): 0.407874 - Best Trial: 0 - Best Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.2537666397006374, 'lr': 6.855147896820647e-05, 'weight_decay': 0.00015935372159435351, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 07:17:39,493] Trial 2 finished with value: 0.4132252365368669 and parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.28109998916034445, 'lr': 0.0012529398844222108, 'weight_decay': 0.0005825996067223634, 'batch_size': 32}. Best is trial 2 with value: 0.4132252365368669. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.413225 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.28109998916034445, 'lr': 0.0012529398844222108, 'weight_decay': 0.0005825996067223634, 'batch_size': 32} - Best Value (CSI): 0.413225 - Best Trial: 2 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.28109998916034445, 'lr': 0.0012529398844222108, 'weight_decay': 0.0005825996067223634, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 07:18:26,298] Trial 3 finished with value: 0.3979947576260899 and parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.39325526241135966, 'lr': 7.717763451728409e-05, 'weight_decay': 0.00441652459680916, 'batch_size': 256}. Best is trial 2 with value: 0.4132252365368669. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.397995 - Parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.39325526241135966, 'lr': 7.717763451728409e-05, 'weight_decay': 0.00441652459680916, 'batch_size': 256} - Best Value (CSI): 0.413225 - Best Trial: 2 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.28109998916034445, 'lr': 0.0012529398844222108, 'weight_decay': 0.0005825996067223634, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 07:19:03,097] Trial 4 finished with value: 0.40265877820632595 and parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.34753031094264364, 'lr': 0.00025774388069870293, 'weight_decay': 0.014654299385095106, 'batch_size': 256}. Best is trial 2 with value: 0.4132252365368669. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.402659 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.34753031094264364, 'lr': 0.00025774388069870293, 'weight_decay': 0.014654299385095106, 'batch_size': 256} - Best Value (CSI): 0.413225 - Best Trial: 2 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.28109998916034445, 'lr': 0.0012529398844222108, 'weight_decay': 0.0005825996067223634, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 07:19:53,143] Trial 5 finished with value: 0.4119720765966437 and parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.22424849929594748, 'lr': 0.003446334047434366, 'weight_decay': 0.0013377983737562404, 'batch_size': 128}. Best is trial 2 with value: 0.4132252365368669. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.411972 - Parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.22424849929594748, 'lr': 0.003446334047434366, 'weight_decay': 0.0013377983737562404, 'batch_size': 128} - Best Value (CSI): 0.413225 - Best Trial: 2 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.28109998916034445, 'lr': 0.0012529398844222108, 'weight_decay': 0.0005825996067223634, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 07:21:18,848] Trial 6 finished with value: 0.41987261032651624 and parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.2857298117939696, 'lr': 0.0026345595044368134, 'weight_decay': 0.009519191260865579, 'batch_size': 64}. Best is trial 6 with value: 0.41987261032651624. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.419873 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.2857298117939696, 'lr': 0.0026345595044368134, 'weight_decay': 0.009519191260865579, 'batch_size': 64} - Best Value (CSI): 0.419873 - Best Trial: 6 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.2857298117939696, 'lr': 0.0026345595044368134, 'weight_decay': 0.009519191260865579, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-25 07:21:22,859] Trial 7 pruned. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.305120 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.26179021642395506, 'lr': 4.708202128011251e-05, 'weight_decay': 0.00038316060207813253, 'batch_size': 256} - Best Value (CSI): 0.419873 - Best Trial: 6 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.2857298117939696, 'lr': 0.0026345595044368134, 'weight_decay': 0.009519191260865579, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 07:23:15,962] Trial 8 finished with value: 0.41900785780300304 and parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.2791455714307445, 'lr': 0.007151351707977939, 'weight_decay': 0.002718216624873902, 'batch_size': 64}. Best is trial 6 with value: 0.41987261032651624. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.419008 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.2791455714307445, 'lr': 0.007151351707977939, 'weight_decay': 0.002718216624873902, 'batch_size': 64} - Best Value (CSI): 0.419873 - Best Trial: 6 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.2857298117939696, 'lr': 0.0026345595044368134, 'weight_decay': 0.009519191260865579, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 07:25:49,709] Trial 9 finished with value: 0.4064930534935094 and parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.16273324544601725, 'lr': 0.0034045503489501384, 'weight_decay': 0.00022026365275125702, 'batch_size': 32}. Best is trial 6 with value: 0.41987261032651624. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.406493 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.16273324544601725, 'lr': 0.0034045503489501384, 'weight_decay': 0.00022026365275125702, 'batch_size': 32} - Best Value (CSI): 0.419873 - Best Trial: 6 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.2857298117939696, 'lr': 0.0026345595044368134, 'weight_decay': 0.009519191260865579, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-25 07:26:02,124] Trial 10 pruned. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.260536 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.10256243409253474, 'lr': 1.1300847788000762e-05, 'weight_decay': 0.06432508570541524, 'batch_size': 64} - Best Value (CSI): 0.419873 - Best Trial: 6 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.2857298117939696, 'lr': 0.0026345595044368134, 'weight_decay': 0.009519191260865579, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-25 07:26:14,318] Trial 11 pruned. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.382784 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.32059134106723475, 'lr': 0.009692223378075014, 'weight_decay': 0.004434727662792031, 'batch_size': 64} - Best Value (CSI): 0.419873 - Best Trial: 6 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.2857298117939696, 'lr': 0.0026345595044368134, 'weight_decay': 0.009519191260865579, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-25 07:26:30,350] Trial 12 pruned. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.385204 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.21637765278996401, 'lr': 0.0008313068194018554, 'weight_decay': 0.01345223749571734, 'batch_size': 64} - Best Value (CSI): 0.419873 - Best Trial: 6 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.2857298117939696, 'lr': 0.0026345595044368134, 'weight_decay': 0.009519191260865579, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-25 07:26:45,364] Trial 13 pruned. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.391121 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3152036482990691, 'lr': 0.008279372910796789, 'weight_decay': 0.0016033353354925914, 'batch_size': 64} - Best Value (CSI): 0.419873 - Best Trial: 6 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.2857298117939696, 'lr': 0.0026345595044368134, 'weight_decay': 0.009519191260865579, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-25 07:26:54,286] Trial 14 pruned. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.387013 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.3120186555309397, 'lr': 0.0009323836222617935, 'weight_decay': 0.01014956637999636, 'batch_size': 128} - Best Value (CSI): 0.419873 - Best Trial: 6 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.2857298117939696, 'lr': 0.0026345595044368134, 'weight_decay': 0.009519191260865579, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-25 07:27:04,700] Trial 15 pruned. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.368351 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.3625806955193889, 'lr': 0.009049457580712409, 'weight_decay': 0.0016188728466125682, 'batch_size': 64} - Best Value (CSI): 0.419873 - Best Trial: 6 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.2857298117939696, 'lr': 0.0026345595044368134, 'weight_decay': 0.009519191260865579, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 07:28:37,698] Trial 16 finished with value: 0.4186013518663369 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.28996331018947785, 'lr': 0.0018664614051562148, 'weight_decay': 0.03816023795703487, 'batch_size': 64}. Best is trial 6 with value: 0.41987261032651624. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.418601 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.28996331018947785, 'lr': 0.0018664614051562148, 'weight_decay': 0.03816023795703487, 'batch_size': 64} - Best Value (CSI): 0.419873 - Best Trial: 6 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.2857298117939696, 'lr': 0.0026345595044368134, 'weight_decay': 0.009519191260865579, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 07:29:47,364] Trial 17 finished with value: 0.4096437963594779 and parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23508015932006845, 'lr': 0.004074693080473773, 'weight_decay': 0.006590435893058194, 'batch_size': 64}. Best is trial 6 with value: 0.41987261032651624. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.409644 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23508015932006845, 'lr': 0.004074693080473773, 'weight_decay': 0.006590435893058194, 'batch_size': 64} - Best Value (CSI): 0.419873 - Best Trial: 6 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.2857298117939696, 'lr': 0.0026345595044368134, 'weight_decay': 0.009519191260865579, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 07:30:48,545] Trial 18 finished with value: 0.40778164483980756 and parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.19947983138304992, 'lr': 0.0005637282267743489, 'weight_decay': 0.025887957435872973, 'batch_size': 128}. Best is trial 6 with value: 0.41987261032651624. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.407782 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.19947983138304992, 'lr': 0.0005637282267743489, 'weight_decay': 0.025887957435872973, 'batch_size': 128} - Best Value (CSI): 0.419873 - Best Trial: 6 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.2857298117939696, 'lr': 0.0026345595044368134, 'weight_decay': 0.009519191260865579, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 07:33:19,457] Trial 19 finished with value: 0.41553669552186573 and parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.28974471025402826, 'lr': 0.0018773263654836595, 'weight_decay': 0.002655602108958871, 'batch_size': 32}. Best is trial 6 with value: 0.41987261032651624. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.415537 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.28974471025402826, 'lr': 0.0018773263654836595, 'weight_decay': 0.002655602108958871, 'batch_size': 32} - Best Value (CSI): 0.419873 - Best Trial: 6 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.2857298117939696, 'lr': 0.0026345595044368134, 'weight_decay': 0.009519191260865579, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 07:35:02,910] Trial 20 finished with value: 0.4229700653400353 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.34476861590539, 'lr': 0.00456136044801199, 'weight_decay': 0.007848835724922575, 'batch_size': 64}. Best is trial 20 with value: 0.4229700653400353. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.422970 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.34476861590539, 'lr': 0.00456136044801199, 'weight_decay': 0.007848835724922575, 'batch_size': 64} - Best Value (CSI): 0.422970 - Best Trial: 20 - Best Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.34476861590539, 'lr': 0.00456136044801199, 'weight_decay': 0.007848835724922575, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 07:36:33,642] Trial 21 finished with value: 0.42499984312808053 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3598265536419826, 'lr': 0.0058692232154894984, 'weight_decay': 0.008563601924292032, 'batch_size': 64}. Best is trial 21 with value: 0.42499984312808053. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.425000 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3598265536419826, 'lr': 0.0058692232154894984, 'weight_decay': 0.008563601924292032, 'batch_size': 64} - Best Value (CSI): 0.425000 - Best Trial: 21 - Best Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3598265536419826, 'lr': 0.0058692232154894984, 'weight_decay': 0.008563601924292032, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 07:38:32,779] Trial 22 finished with value: 0.4149038309402049 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3998459206757026, 'lr': 0.005320935245913582, 'weight_decay': 0.009680562092821697, 'batch_size': 64}. Best is trial 21 with value: 0.42499984312808053. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.414904 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3998459206757026, 'lr': 0.005320935245913582, 'weight_decay': 0.009680562092821697, 'batch_size': 64} - Best Value (CSI): 0.425000 - Best Trial: 21 - Best Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3598265536419826, 'lr': 0.0058692232154894984, 'weight_decay': 0.008563601924292032, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 07:39:47,311] Trial 23 finished with value: 0.42641925885433235 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3463819832745381, 'lr': 0.0020350649229428277, 'weight_decay': 0.02235490145501715, 'batch_size': 64}. Best is trial 23 with value: 0.42641925885433235. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.426419 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3463819832745381, 'lr': 0.0020350649229428277, 'weight_decay': 0.02235490145501715, 'batch_size': 64} - Best Value (CSI): 0.426419 - Best Trial: 23 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3463819832745381, 'lr': 0.0020350649229428277, 'weight_decay': 0.02235490145501715, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 07:41:13,272] Trial 24 finished with value: 0.4292917267691137 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3621538746283491, 'lr': 0.004731509312406335, 'weight_decay': 0.02761771859966573, 'batch_size': 64}. Best is trial 24 with value: 0.4292917267691137. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.429292 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3621538746283491, 'lr': 0.004731509312406335, 'weight_decay': 0.02761771859966573, 'batch_size': 64} - Best Value (CSI): 0.429292 - Best Trial: 24 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3621538746283491, 'lr': 0.004731509312406335, 'weight_decay': 0.02761771859966573, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 07:42:56,812] Trial 25 finished with value: 0.4426438646716793 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.37614451323155623, 'lr': 0.005171352248249976, 'weight_decay': 0.08533193242553579, 'batch_size': 64}. Best is trial 25 with value: 0.4426438646716793. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.442644 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.37614451323155623, 'lr': 0.005171352248249976, 'weight_decay': 0.08533193242553579, 'batch_size': 64} - Best Value (CSI): 0.442644 - Best Trial: 25 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.37614451323155623, 'lr': 0.005171352248249976, 'weight_decay': 0.08533193242553579, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 07:44:11,784] Trial 26 finished with value: 0.43001436124513553 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.38157469795226523, 'lr': 0.0020253232084036146, 'weight_decay': 0.07434760381236132, 'batch_size': 64}. Best is trial 25 with value: 0.4426438646716793. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.430014 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.38157469795226523, 'lr': 0.0020253232084036146, 'weight_decay': 0.07434760381236132, 'batch_size': 64} - Best Value (CSI): 0.442644 - Best Trial: 25 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.37614451323155623, 'lr': 0.005171352248249976, 'weight_decay': 0.08533193242553579, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 07:45:08,732] Trial 27 finished with value: 0.422718438436901 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3831352743345396, 'lr': 0.0015078538704023188, 'weight_decay': 0.09696843630266386, 'batch_size': 128}. Best is trial 25 with value: 0.4426438646716793. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.422718 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3831352743345396, 'lr': 0.0015078538704023188, 'weight_decay': 0.09696843630266386, 'batch_size': 128} - Best Value (CSI): 0.442644 - Best Trial: 25 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.37614451323155623, 'lr': 0.005171352248249976, 'weight_decay': 0.08533193242553579, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 07:48:35,503] Trial 28 finished with value: 0.44276076380851953 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.442761 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 07:50:49,439] Trial 29 finished with value: 0.4287236759825297 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.38628087706808634, 'lr': 0.0026875731600561827, 'weight_decay': 0.04566861243877897, 'batch_size': 32}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.428724 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.38628087706808634, 'lr': 0.0026875731600561827, 'weight_decay': 0.04566861243877897, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 07:54:39,078] Trial 30 finished with value: 0.4383084314039303 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3819141494353552, 'lr': 0.005870859116420869, 'weight_decay': 0.09552495030713583, 'batch_size': 32}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.438308 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3819141494353552, 'lr': 0.005870859116420869, 'weight_decay': 0.09552495030713583, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-25 07:54:57,709] Trial 31 pruned. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.401998 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3758331126393262, 'lr': 0.006076482252297541, 'weight_decay': 0.09739364618228472, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 07:58:46,361] Trial 32 finished with value: 0.43541147047529943 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.399422150815644, 'lr': 0.003232282792702033, 'weight_decay': 0.05764995180189082, 'batch_size': 32}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.435411 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.399422150815644, 'lr': 0.003232282792702033, 'weight_decay': 0.05764995180189082, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 08:01:07,903] Trial 33 finished with value: 0.42838402886009147 and parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.39661600162914323, 'lr': 0.003608811344093132, 'weight_decay': 0.055634862281129245, 'batch_size': 32}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.428384 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.39661600162914323, 'lr': 0.003608811344093132, 'weight_decay': 0.055634862281129245, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-25 08:01:25,433] Trial 34 pruned. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.400978 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39882064178578014, 'lr': 0.009258784955223457, 'weight_decay': 0.04288426357196215, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 08:03:59,679] Trial 35 finished with value: 0.43542991491965144 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.37613034315743243, 'lr': 0.005571364599902523, 'weight_decay': 0.06634044497962055, 'batch_size': 32}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.435430 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.37613034315743243, 'lr': 0.005571364599902523, 'weight_decay': 0.06634044497962055, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 08:07:32,055] Trial 36 finished with value: 0.4344778902892066 and parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.3334344122713491, 'lr': 0.005953760896950202, 'weight_decay': 0.09644667220112411, 'batch_size': 32}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.434478 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.3334344122713491, 'lr': 0.005953760896950202, 'weight_decay': 0.09644667220112411, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-25 08:07:49,709] Trial 37 pruned. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.333333 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.36469756868313413, 'lr': 0.006450797787690603, 'weight_decay': 0.036428992235199846, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 08:09:57,662] Trial 38 finished with value: 0.4291394157432447 and parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.37715053236140245, 'lr': 0.0012010480077969926, 'weight_decay': 0.06594607241040679, 'batch_size': 32}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.429139 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.37715053236140245, 'lr': 0.0012010480077969926, 'weight_decay': 0.06594607241040679, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 08:10:37,460] Trial 39 finished with value: 0.4219683916352756 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.338465381710154, 'lr': 0.00432633969349526, 'weight_decay': 0.02196619280932337, 'batch_size': 256}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.421968 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.338465381710154, 'lr': 0.00432633969349526, 'weight_decay': 0.02196619280932337, 'batch_size': 256} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 08:13:45,738] Trial 40 finished with value: 0.42416668025060195 and parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3708039610820247, 'lr': 0.0027419792369027334, 'weight_decay': 0.036693825651704315, 'batch_size': 32}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.424167 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3708039610820247, 'lr': 0.0027419792369027334, 'weight_decay': 0.036693825651704315, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-25 08:14:08,995] Trial 41 pruned. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.404915 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.38513567636244467, 'lr': 0.0033757676876511747, 'weight_decay': 0.05622976403393539, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 08:17:45,812] Trial 42 finished with value: 0.4418058413221259 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3525483709797552, 'lr': 0.006482519791778859, 'weight_decay': 0.06474211872533037, 'batch_size': 32}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.441806 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3525483709797552, 'lr': 0.006482519791778859, 'weight_decay': 0.06474211872533037, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 08:21:08,578] Trial 43 finished with value: 0.434006611084962 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3546752166888072, 'lr': 0.008078692177606612, 'weight_decay': 0.06772624569460033, 'batch_size': 32}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.434007 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3546752166888072, 'lr': 0.008078692177606612, 'weight_decay': 0.06772624569460033, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-25 08:21:12,962] Trial 44 pruned. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.387441 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.33242120632904093, 'lr': 0.006390416282628266, 'weight_decay': 0.018499151241463084, 'batch_size': 256} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 08:24:35,876] Trial 45 finished with value: 0.4328911597365824 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3541411302655004, 'lr': 0.004361277389375321, 'weight_decay': 0.0310942174421319, 'batch_size': 32}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.432891 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3541411302655004, 'lr': 0.004361277389375321, 'weight_decay': 0.0310942174421319, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-25 08:24:52,502] Trial 46 pruned. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.385987 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3684479784910826, 'lr': 0.00987274724654166, 'weight_decay': 0.04877497466065724, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 08:28:41,501] Trial 47 finished with value: 0.43748518059903524 and parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.37226062348503974, 'lr': 0.0026221085887409047, 'weight_decay': 0.07714066787961482, 'batch_size': 32}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.437485 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.37226062348503974, 'lr': 0.0026221085887409047, 'weight_decay': 0.07714066787961482, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 08:31:18,827] Trial 48 finished with value: 0.4309640940602453 and parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.34951328656179387, 'lr': 0.0030883616656939266, 'weight_decay': 0.08426951786029306, 'batch_size': 32}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.430964 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.34951328656179387, 'lr': 0.0030883616656939266, 'weight_decay': 0.08426951786029306, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 08:31:58,250] Trial 49 finished with value: 0.42792317557435494 and parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.32726311768049343, 'lr': 0.007721105830507379, 'weight_decay': 0.046424793978988646, 'batch_size': 256}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.427923 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.32726311768049343, 'lr': 0.007721105830507379, 'weight_decay': 0.046424793978988646, 'batch_size': 256} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-25 08:32:04,390] Trial 50 pruned. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.404669 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.3046255172243599, 'lr': 0.002398728968962199, 'weight_decay': 0.08131564678612604, 'batch_size': 128} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 08:35:05,791] Trial 51 finished with value: 0.4335312227141816 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.37168225483435563, 'lr': 0.004987328488461577, 'weight_decay': 0.07202480689896357, 'batch_size': 32}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.433531 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.37168225483435563, 'lr': 0.004987328488461577, 'weight_decay': 0.07202480689896357, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 08:38:06,235] Trial 52 finished with value: 0.4322331573640996 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3871597535213145, 'lr': 0.006913919073344203, 'weight_decay': 0.05748508675597505, 'batch_size': 32}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.432233 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3871597535213145, 'lr': 0.006913919073344203, 'weight_decay': 0.05748508675597505, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 08:41:30,157] Trial 53 finished with value: 0.42867022034956187 and parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3425024263370022, 'lr': 0.003941754767765407, 'weight_decay': 0.03506863504386928, 'batch_size': 32}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.428670 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3425024263370022, 'lr': 0.003941754767765407, 'weight_decay': 0.03506863504386928, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-25 08:41:48,328] Trial 54 pruned. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.405637 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.3723057546422501, 'lr': 0.009906664411190902, 'weight_decay': 0.0992815896868623, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 08:45:33,067] Trial 55 finished with value: 0.44198060611780043 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3548609770444313, 'lr': 0.004772287245178301, 'weight_decay': 0.07431485260937054, 'batch_size': 32}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.441981 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3548609770444313, 'lr': 0.004772287245178301, 'weight_decay': 0.07431485260937054, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 08:48:44,592] Trial 56 finished with value: 0.4330834378297727 and parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3562086125969326, 'lr': 0.0026282896329378694, 'weight_decay': 0.04492595669313181, 'batch_size': 32}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.433083 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3562086125969326, 'lr': 0.0026282896329378694, 'weight_decay': 0.04492595669313181, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 08:52:05,185] Trial 57 finished with value: 0.42093308066262 and parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.32166876844272685, 'lr': 0.0036186646774992617, 'weight_decay': 0.032851955741950864, 'batch_size': 32}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.420933 - Parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.32166876844272685, 'lr': 0.0036186646774992617, 'weight_decay': 0.032851955741950864, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 08:53:01,010] Trial 58 finished with value: 0.4303641783294103 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3410535792361091, 'lr': 0.007595740994424047, 'weight_decay': 0.0758603102057132, 'batch_size': 128}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.430364 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3410535792361091, 'lr': 0.007595740994424047, 'weight_decay': 0.0758603102057132, 'batch_size': 128} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-25 08:53:05,632] Trial 59 pruned. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.393120 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3870914809694128, 'lr': 0.004580615286128826, 'weight_decay': 0.02888965128912849, 'batch_size': 256} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-25 08:53:28,859] Trial 60 pruned. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.365229 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.3515699441979157, 'lr': 0.0015068182469473975, 'weight_decay': 0.018363470187339928, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-25 08:53:47,454] Trial 61 pruned. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.407134 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.36706047746968157, 'lr': 0.005508119117433485, 'weight_decay': 0.06621951432080188, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 08:57:05,998] Trial 62 finished with value: 0.43032574505853805 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3892564320843488, 'lr': 0.007214234407084324, 'weight_decay': 0.05177799735130411, 'batch_size': 32}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.430326 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3892564320843488, 'lr': 0.007214234407084324, 'weight_decay': 0.05177799735130411, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 08:59:50,636] Trial 63 finished with value: 0.43342993067010366 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3773160953077685, 'lr': 0.005474325345182978, 'weight_decay': 0.07949441907331403, 'batch_size': 32}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.433430 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3773160953077685, 'lr': 0.005474325345182978, 'weight_decay': 0.07949441907331403, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 09:03:00,816] Trial 64 finished with value: 0.44040042816128716 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.36037655513594746, 'lr': 0.003838150334960364, 'weight_decay': 0.04084151208216666, 'batch_size': 32}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.440400 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.36037655513594746, 'lr': 0.003838150334960364, 'weight_decay': 0.04084151208216666, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 09:06:00,670] Trial 65 finished with value: 0.42917475530991817 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.35723139086889033, 'lr': 0.0023535831348208067, 'weight_decay': 0.04487131442914227, 'batch_size': 32}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.429175 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.35723139086889033, 'lr': 0.0023535831348208067, 'weight_decay': 0.04487131442914227, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 09:09:23,913] Trial 66 finished with value: 0.4309938681187342 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.36503185557467877, 'lr': 0.0038576854251769223, 'weight_decay': 0.08311360875827824, 'batch_size': 32}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.430994 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.36503185557467877, 'lr': 0.0038576854251769223, 'weight_decay': 0.08311360875827824, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 09:10:29,812] Trial 67 finished with value: 0.43062741181967196 and parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3916990377032639, 'lr': 0.002987024090187709, 'weight_decay': 0.09976465725286458, 'batch_size': 64}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.430627 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3916990377032639, 'lr': 0.002987024090187709, 'weight_decay': 0.09976465725286458, 'batch_size': 64} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 09:11:25,619] Trial 68 finished with value: 0.42958518520267885 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.342848455151024, 'lr': 0.004770310833468034, 'weight_decay': 0.0594664080887527, 'batch_size': 128}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.429585 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.342848455151024, 'lr': 0.004770310833468034, 'weight_decay': 0.0594664080887527, 'batch_size': 128} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 09:15:03,498] Trial 69 finished with value: 0.4237286620526743 and parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.36220531240024484, 'lr': 0.007811662644415548, 'weight_decay': 0.036405719008048225, 'batch_size': 32}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.423729 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.36220531240024484, 'lr': 0.007811662644415548, 'weight_decay': 0.036405719008048225, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 09:16:22,360] Trial 70 finished with value: 0.4338468546714666 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.33063700575093646, 'lr': 0.0036895806085626742, 'weight_decay': 0.05287383236622923, 'batch_size': 64}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.433847 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.33063700575093646, 'lr': 0.0036895806085626742, 'weight_decay': 0.05287383236622923, 'batch_size': 64} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 09:19:54,365] Trial 71 finished with value: 0.43874925307127866 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.3778273207818534, 'lr': 0.005242586274916353, 'weight_decay': 0.06633213192626904, 'batch_size': 32}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.438749 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.3778273207818534, 'lr': 0.005242586274916353, 'weight_decay': 0.06633213192626904, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 09:23:22,954] Trial 72 finished with value: 0.43056932254494645 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.37902973790933575, 'lr': 0.006726735417270347, 'weight_decay': 0.0785495957829436, 'batch_size': 32}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.430569 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.37902973790933575, 'lr': 0.006726735417270347, 'weight_decay': 0.0785495957829436, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 09:27:15,990] Trial 73 finished with value: 0.43668668822988194 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.39274665266093595, 'lr': 0.004982119803401997, 'weight_decay': 0.04152762132722463, 'batch_size': 32}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.436687 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.39274665266093595, 'lr': 0.004982119803401997, 'weight_decay': 0.04152762132722463, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 09:29:50,880] Trial 74 finished with value: 0.43415434679144077 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.35001564793088136, 'lr': 0.0030951709454712538, 'weight_decay': 0.06285339715307228, 'batch_size': 32}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.434154 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.35001564793088136, 'lr': 0.0030951709454712538, 'weight_decay': 0.06285339715307228, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-25 09:30:09,451] Trial 75 pruned. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.380531 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.37982402458883635, 'lr': 0.008237765258950178, 'weight_decay': 0.0525666170194673, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-25 09:30:28,346] Trial 76 pruned. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.409488 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3664525826531577, 'lr': 0.006230577001515142, 'weight_decay': 0.08557913694923001, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 09:33:06,782] Trial 77 finished with value: 0.4349047275907474 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3584665074698671, 'lr': 0.002211456516132352, 'weight_decay': 0.06788899015807041, 'batch_size': 32}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.434905 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3584665074698671, 'lr': 0.002211456516132352, 'weight_decay': 0.06788899015807041, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 09:35:03,815] Trial 78 finished with value: 0.42304495946959236 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.39154349710854414, 'lr': 0.0043334535881214865, 'weight_decay': 0.04108238306094363, 'batch_size': 32}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.423045 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.39154349710854414, 'lr': 0.0043334535881214865, 'weight_decay': 0.04108238306094363, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 09:36:32,707] Trial 79 finished with value: 0.4275010679989079 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.39981206573656375, 'lr': 0.0027244711858706193, 'weight_decay': 0.028291942507204206, 'batch_size': 64}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.427501 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.39981206573656375, 'lr': 0.0027244711858706193, 'weight_decay': 0.028291942507204206, 'batch_size': 64} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-25 09:36:37,446] Trial 80 pruned. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.399067 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.37304510499359284, 'lr': 0.0017939304585236767, 'weight_decay': 0.06112859851710679, 'batch_size': 256} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 09:39:47,963] Trial 81 finished with value: 0.43380402853322325 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.3848460112008122, 'lr': 0.00505455464781989, 'weight_decay': 0.04100953279229212, 'batch_size': 32}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.433804 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.3848460112008122, 'lr': 0.00505455464781989, 'weight_decay': 0.04100953279229212, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-25 09:40:07,269] Trial 82 pruned. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.397216 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.3943966056793682, 'lr': 0.00572882708935938, 'weight_decay': 0.049586709393817444, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 09:43:57,848] Trial 83 finished with value: 0.4410103789160947 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.3611661148695177, 'lr': 0.003846963661620498, 'weight_decay': 0.08738778891664734, 'batch_size': 32}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.441010 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.3611661148695177, 'lr': 0.003846963661620498, 'weight_decay': 0.08738778891664734, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 09:46:52,400] Trial 84 finished with value: 0.42979542316365876 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.34903561683773676, 'lr': 0.0035111121635313216, 'weight_decay': 0.0890711127722488, 'batch_size': 32}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.429795 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.34903561683773676, 'lr': 0.0035111121635313216, 'weight_decay': 0.0890711127722488, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 09:50:18,462] Trial 85 finished with value: 0.4410166159579519 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.3596186411776026, 'lr': 0.004030165803158148, 'weight_decay': 0.07919363982374236, 'batch_size': 32}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.441017 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.3596186411776026, 'lr': 0.004030165803158148, 'weight_decay': 0.07919363982374236, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 09:53:55,356] Trial 86 finished with value: 0.42615088175633326 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.36089419325176314, 'lr': 0.008603128117309523, 'weight_decay': 0.09954750830025873, 'batch_size': 32}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.426151 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.36089419325176314, 'lr': 0.008603128117309523, 'weight_decay': 0.09954750830025873, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 09:55:43,154] Trial 87 finished with value: 0.43914853181984004 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.33589126513240236, 'lr': 0.0042101395761540965, 'weight_decay': 0.07094468689074228, 'batch_size': 64}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.439149 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.33589126513240236, 'lr': 0.0042101395761540965, 'weight_decay': 0.07094468689074228, 'batch_size': 64} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 09:57:01,957] Trial 88 finished with value: 0.43246858024747725 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3364482672111648, 'lr': 0.0038698894733847303, 'weight_decay': 0.06850443500181619, 'batch_size': 64}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.432469 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3364482672111648, 'lr': 0.0038698894733847303, 'weight_decay': 0.06850443500181619, 'batch_size': 64} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 09:58:28,486] Trial 89 finished with value: 0.42742917169122263 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3422521665886178, 'lr': 0.004344180837458457, 'weight_decay': 0.05856566071589265, 'batch_size': 64}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.427429 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3422521665886178, 'lr': 0.004344180837458457, 'weight_decay': 0.05856566071589265, 'batch_size': 64} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 09:59:34,075] Trial 90 finished with value: 0.4319723272172713 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.35392743436905894, 'lr': 0.0031784384607110765, 'weight_decay': 0.07434354464171276, 'batch_size': 64}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.431972 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.35392743436905894, 'lr': 0.0031784384607110765, 'weight_decay': 0.07434354464171276, 'batch_size': 64} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 10:01:07,984] Trial 91 finished with value: 0.4231064401566607 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.36535083548241326, 'lr': 0.006545489640197504, 'weight_decay': 0.0857094924336036, 'batch_size': 64}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.423106 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.36535083548241326, 'lr': 0.006545489640197504, 'weight_decay': 0.0857094924336036, 'batch_size': 64} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 10:04:36,248] Trial 92 finished with value: 0.4270722364934815 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3817011867082615, 'lr': 0.005903956717040021, 'weight_decay': 0.06897688226450807, 'batch_size': 32}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.427072 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3817011867082615, 'lr': 0.005903956717040021, 'weight_decay': 0.06897688226450807, 'batch_size': 32} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 10:05:53,065] Trial 93 finished with value: 0.4386609989907346 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3494702326942578, 'lr': 0.0052097571460931035, 'weight_decay': 0.0501444167014133, 'batch_size': 64}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.438661 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3494702326942578, 'lr': 0.0052097571460931035, 'weight_decay': 0.0501444167014133, 'batch_size': 64} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 10:07:12,719] Trial 94 finished with value: 0.42648689346964036 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3491298048417893, 'lr': 0.004220014004795823, 'weight_decay': 0.04907414384042496, 'batch_size': 64}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.426487 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3491298048417893, 'lr': 0.004220014004795823, 'weight_decay': 0.04907414384042496, 'batch_size': 64} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 10:09:09,113] Trial 95 finished with value: 0.4335223335222825 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.33494179643396405, 'lr': 0.005038316694356064, 'weight_decay': 0.03797464449585985, 'batch_size': 64}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.433522 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.33494179643396405, 'lr': 0.005038316694356064, 'weight_decay': 0.03797464449585985, 'batch_size': 64} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 10:10:13,648] Trial 96 finished with value: 0.42884533156428795 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3243142086963741, 'lr': 0.00328580215706643, 'weight_decay': 0.03351377477957235, 'batch_size': 64}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.428845 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3243142086963741, 'lr': 0.00328580215706643, 'weight_decay': 0.03351377477957235, 'batch_size': 64} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 10:11:46,473] Trial 97 finished with value: 0.43414120587760757 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.3588675874879524, 'lr': 0.00710004308022971, 'weight_decay': 0.04863246086507264, 'batch_size': 64}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.434141 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.3588675874879524, 'lr': 0.00710004308022971, 'weight_decay': 0.04863246086507264, 'batch_size': 64} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 10:12:40,663] Trial 98 finished with value: 0.42500405850084616 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.3456535291700908, 'lr': 0.009132581554756537, 'weight_decay': 0.05700512594159186, 'batch_size': 128}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.425004 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.3456535291700908, 'lr': 0.009132581554756537, 'weight_decay': 0.05700512594159186, 'batch_size': 128} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 10:14:26,836] Trial 99 finished with value: 0.4241233153005788 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.31533657045523833, 'lr': 0.003939995491006706, 'weight_decay': 0.025564256325468267, 'batch_size': 64}. Best is trial 28 with value: 0.44276076380851953. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.424123 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.31533657045523833, 'lr': 0.003939995491006706, 'weight_decay': 0.025564256325468267, 'batch_size': 64} - Best Value (CSI): 0.442761 - Best Trial: 28 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.4428 -Best Hyperparameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3745726718399158, 'lr': 0.005338808759265471, 'weight_decay': 0.06558728678415406, 'batch_size': 32} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.4079 - - 최종 CSI: 0.4241 - - 최고 CSI: 0.4428 - - 최저 CSI: 0.2605 - - 평균 CSI: 0.4172 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/deepgbm_smote_busan_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 37, Best CSI: 0.4532 - Fold 1 학습 완료 (검증 CSI: 0.4532) -Fold 2 학습 중... - Early stopping at epoch 42, Best CSI: 0.4367 - Fold 2 학습 완료 (검증 CSI: 0.4367) -Fold 3 학습 중... - Early stopping at epoch 47, Best CSI: 0.4136 - Fold 3 학습 완료 (검증 CSI: 0.4136) - -모든 모델 저장 완료: ../save_model/deepgbm_optima/deepgbm_smote_busan.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/deepgbm_optima/scaler/deepgbm_smote_busan_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: ../save_model/deepgbm_optima/deepgbm_smote_busan.pkl - -✓ 완료: deepgbm_smote/deepgbm_smote_busan.py (소요 시간: 11142초) - ----------------------------------------- -실행 중: deepgbm_smote/deepgbm_smote_daegu.py -시작 시간: 2025-12-25 10:18:01 ----------------------------------------- -[I 2025-12-25 10:18:02,945] A new study created in memory with name: no-name-1cc174e2-978c-434f-abfd-727c71304e00 - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 10:20:03,466] Trial 0 finished with value: 0.3799639966852475 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.2666208123916278, 'lr': 0.0005465294667727818, 'weight_decay': 0.002745736481011257, 'batch_size': 64}. Best is trial 0 with value: 0.3799639966852475. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.379964 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.2666208123916278, 'lr': 0.0005465294667727818, 'weight_decay': 0.002745736481011257, 'batch_size': 64} - Best Value (CSI): 0.379964 - Best Trial: 0 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.2666208123916278, 'lr': 0.0005465294667727818, 'weight_decay': 0.002745736481011257, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 10:20:35,314] Trial 1 finished with value: 0.3668198304803291 and parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.21627770244910025, 'lr': 0.0016125629810288344, 'weight_decay': 0.013038684867465433, 'batch_size': 256}. Best is trial 0 with value: 0.3799639966852475. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.366820 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.21627770244910025, 'lr': 0.0016125629810288344, 'weight_decay': 0.013038684867465433, 'batch_size': 256} - Best Value (CSI): 0.379964 - Best Trial: 0 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.2666208123916278, 'lr': 0.0005465294667727818, 'weight_decay': 0.002745736481011257, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 10:21:10,264] Trial 2 finished with value: 0.38648608802453116 and parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.12470803129977624, 'lr': 0.0022650531347891455, 'weight_decay': 0.08639331906164949, 'batch_size': 256}. Best is trial 2 with value: 0.38648608802453116. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.386486 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.12470803129977624, 'lr': 0.0022650531347891455, 'weight_decay': 0.08639331906164949, 'batch_size': 256} - Best Value (CSI): 0.386486 - Best Trial: 2 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.12470803129977624, 'lr': 0.0022650531347891455, 'weight_decay': 0.08639331906164949, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 10:23:44,943] Trial 3 finished with value: 0.38922193462353977 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.20876216806444886, 'lr': 0.0005164464819057032, 'weight_decay': 0.09576317801475862, 'batch_size': 32}. Best is trial 3 with value: 0.38922193462353977. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.389222 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.20876216806444886, 'lr': 0.0005164464819057032, 'weight_decay': 0.09576317801475862, 'batch_size': 32} - Best Value (CSI): 0.389222 - Best Trial: 3 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.20876216806444886, 'lr': 0.0005164464819057032, 'weight_decay': 0.09576317801475862, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 10:24:41,038] Trial 4 finished with value: 0.3804818142573793 and parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.10444626075825428, 'lr': 0.0030476989826526226, 'weight_decay': 0.003205964452783614, 'batch_size': 128}. Best is trial 3 with value: 0.38922193462353977. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.380482 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.10444626075825428, 'lr': 0.0030476989826526226, 'weight_decay': 0.003205964452783614, 'batch_size': 128} - Best Value (CSI): 0.389222 - Best Trial: 3 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.20876216806444886, 'lr': 0.0005164464819057032, 'weight_decay': 0.09576317801475862, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:25:04,367] Trial 5 pruned. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.207197 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.3691996961773035, 'lr': 1.527611225423362e-05, 'weight_decay': 0.0009546613111577258, 'batch_size': 32} - Best Value (CSI): 0.389222 - Best Trial: 3 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.20876216806444886, 'lr': 0.0005164464819057032, 'weight_decay': 0.09576317801475862, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:25:08,691] Trial 6 pruned. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.281538 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39996451185090576, 'lr': 0.007394348851163182, 'weight_decay': 0.010376776259149609, 'batch_size': 256} - Best Value (CSI): 0.389222 - Best Trial: 3 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.20876216806444886, 'lr': 0.0005164464819057032, 'weight_decay': 0.09576317801475862, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 10:25:42,179] Trial 7 finished with value: 0.38682311328959723 and parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3926205073804223, 'lr': 0.00120757270928109, 'weight_decay': 0.00127873127599199, 'batch_size': 256}. Best is trial 3 with value: 0.38922193462353977. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.386823 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3926205073804223, 'lr': 0.00120757270928109, 'weight_decay': 0.00127873127599199, 'batch_size': 256} - Best Value (CSI): 0.389222 - Best Trial: 3 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.20876216806444886, 'lr': 0.0005164464819057032, 'weight_decay': 0.09576317801475862, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:26:07,738] Trial 8 pruned. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.226667 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.3900236495958841, 'lr': 0.006392038667949501, 'weight_decay': 0.007727494024312039, 'batch_size': 32} - Best Value (CSI): 0.389222 - Best Trial: 3 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.20876216806444886, 'lr': 0.0005164464819057032, 'weight_decay': 0.09576317801475862, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:26:31,290] Trial 9 pruned. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.219753 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.1062755482090099, 'lr': 1.022975625088184e-05, 'weight_decay': 0.03294018209881079, 'batch_size': 32} - Best Value (CSI): 0.389222 - Best Trial: 3 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.20876216806444886, 'lr': 0.0005164464819057032, 'weight_decay': 0.09576317801475862, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:26:42,920] Trial 10 pruned. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.287714 - Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.19738465623135423, 'lr': 0.00015442999628122322, 'weight_decay': 0.00013894352784525436, 'batch_size': 64} - Best Value (CSI): 0.389222 - Best Trial: 3 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.20876216806444886, 'lr': 0.0005164464819057032, 'weight_decay': 0.09576317801475862, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:26:48,963] Trial 11 pruned. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.305800 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.312415525209189, 'lr': 0.00046125491401768535, 'weight_decay': 0.0556206655132464, 'batch_size': 128} - Best Value (CSI): 0.389222 - Best Trial: 3 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.20876216806444886, 'lr': 0.0005164464819057032, 'weight_decay': 0.09576317801475862, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 10:28:50,242] Trial 12 finished with value: 0.36798766757477086 and parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.3268336593966905, 'lr': 0.0001703858253349612, 'weight_decay': 0.0006930684998292664, 'batch_size': 32}. Best is trial 3 with value: 0.38922193462353977. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.367988 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.3268336593966905, 'lr': 0.0001703858253349612, 'weight_decay': 0.0006930684998292664, 'batch_size': 32} - Best Value (CSI): 0.389222 - Best Trial: 3 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.20876216806444886, 'lr': 0.0005164464819057032, 'weight_decay': 0.09576317801475862, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 10:29:22,484] Trial 13 finished with value: 0.3663582344792926 and parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.2724989136238676, 'lr': 0.0010932383377381, 'weight_decay': 0.09671928259013905, 'batch_size': 256}. Best is trial 3 with value: 0.38922193462353977. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.366358 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.2724989136238676, 'lr': 0.0010932383377381, 'weight_decay': 0.09671928259013905, 'batch_size': 256} - Best Value (CSI): 0.389222 - Best Trial: 3 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.20876216806444886, 'lr': 0.0005164464819057032, 'weight_decay': 0.09576317801475862, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:29:42,291] Trial 14 pruned. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.300169 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.3470774934959984, 'lr': 0.0007479480013098135, 'weight_decay': 0.030440322441674328, 'batch_size': 32} - Best Value (CSI): 0.389222 - Best Trial: 3 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.20876216806444886, 'lr': 0.0005164464819057032, 'weight_decay': 0.09576317801475862, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:29:47,418] Trial 15 pruned. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.299509 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.3014471739699389, 'lr': 0.0003652190060532535, 'weight_decay': 0.01899680381137632, 'batch_size': 256} - Best Value (CSI): 0.389222 - Best Trial: 3 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.20876216806444886, 'lr': 0.0005164464819057032, 'weight_decay': 0.09576317801475862, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:29:53,476] Trial 16 pruned. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.252996 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.22850486598383826, 'lr': 0.00019263153301960474, 'weight_decay': 0.005270641562371327, 'batch_size': 128} - Best Value (CSI): 0.389222 - Best Trial: 3 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.20876216806444886, 'lr': 0.0005164464819057032, 'weight_decay': 0.09576317801475862, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:30:06,800] Trial 17 pruned. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.312734 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.3552528318586833, 'lr': 0.0011033090859263656, 'weight_decay': 0.032386835555271026, 'batch_size': 64} - Best Value (CSI): 0.389222 - Best Trial: 3 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.20876216806444886, 'lr': 0.0005164464819057032, 'weight_decay': 0.09576317801475862, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 10:30:32,998] Trial 18 finished with value: 0.38616116116110305 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.17924462033357003, 'lr': 0.003558380504467277, 'weight_decay': 0.0015922627694553784, 'batch_size': 256}. Best is trial 3 with value: 0.38922193462353977. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.386161 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.17924462033357003, 'lr': 0.003558380504467277, 'weight_decay': 0.0015922627694553784, 'batch_size': 256} - Best Value (CSI): 0.389222 - Best Trial: 3 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.20876216806444886, 'lr': 0.0005164464819057032, 'weight_decay': 0.09576317801475862, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:30:53,286] Trial 19 pruned. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.260870 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2874238221222528, 'lr': 7.506660767273947e-05, 'weight_decay': 0.005513325362098484, 'batch_size': 32} - Best Value (CSI): 0.389222 - Best Trial: 3 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.20876216806444886, 'lr': 0.0005164464819057032, 'weight_decay': 0.09576317801475862, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:31:14,353] Trial 20 pruned. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.297445 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.2491214999890637, 'lr': 0.000910320349223202, 'weight_decay': 0.016188693268940423, 'batch_size': 32} - Best Value (CSI): 0.389222 - Best Trial: 3 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.20876216806444886, 'lr': 0.0005164464819057032, 'weight_decay': 0.09576317801475862, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 10:31:38,871] Trial 21 finished with value: 0.37905684397783507 and parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.1584681308197271, 'lr': 0.0022319525950319375, 'weight_decay': 0.07526412812680121, 'batch_size': 256}. Best is trial 3 with value: 0.38922193462353977. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.379057 - Parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.1584681308197271, 'lr': 0.0022319525950319375, 'weight_decay': 0.07526412812680121, 'batch_size': 256} - Best Value (CSI): 0.389222 - Best Trial: 3 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.20876216806444886, 'lr': 0.0005164464819057032, 'weight_decay': 0.09576317801475862, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 10:32:01,522] Trial 22 finished with value: 0.3742013711795391 and parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.14898293846393393, 'lr': 0.0016191964550202153, 'weight_decay': 0.09960795955316919, 'batch_size': 256}. Best is trial 3 with value: 0.38922193462353977. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.374201 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.14898293846393393, 'lr': 0.0016191964550202153, 'weight_decay': 0.09960795955316919, 'batch_size': 256} - Best Value (CSI): 0.389222 - Best Trial: 3 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.20876216806444886, 'lr': 0.0005164464819057032, 'weight_decay': 0.09576317801475862, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 10:32:31,613] Trial 23 finished with value: 0.38403288729251644 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.23982051867352228, 'lr': 0.0022535978739877355, 'weight_decay': 0.04390560086034278, 'batch_size': 256}. Best is trial 3 with value: 0.38922193462353977. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.384033 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.23982051867352228, 'lr': 0.0022535978739877355, 'weight_decay': 0.04390560086034278, 'batch_size': 256} - Best Value (CSI): 0.389222 - Best Trial: 3 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.20876216806444886, 'lr': 0.0005164464819057032, 'weight_decay': 0.09576317801475862, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 10:32:51,735] Trial 24 finished with value: 0.3837739538797326 and parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20330088090912773, 'lr': 0.004139025247752964, 'weight_decay': 0.05826927057608679, 'batch_size': 256}. Best is trial 3 with value: 0.38922193462353977. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.383774 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20330088090912773, 'lr': 0.004139025247752964, 'weight_decay': 0.05826927057608679, 'batch_size': 256} - Best Value (CSI): 0.389222 - Best Trial: 3 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.20876216806444886, 'lr': 0.0005164464819057032, 'weight_decay': 0.09576317801475862, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:32:56,685] Trial 25 pruned. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.288217 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.2580218913575311, 'lr': 0.009475485208519449, 'weight_decay': 0.0291598400017154, 'batch_size': 256} - Best Value (CSI): 0.389222 - Best Trial: 3 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.20876216806444886, 'lr': 0.0005164464819057032, 'weight_decay': 0.09576317801475862, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 10:33:44,635] Trial 26 finished with value: 0.3809354826795412 and parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.22867571820434696, 'lr': 0.0005586689111890366, 'weight_decay': 0.05725685456891913, 'batch_size': 128}. Best is trial 3 with value: 0.38922193462353977. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.380935 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.22867571820434696, 'lr': 0.0005586689111890366, 'weight_decay': 0.05725685456891913, 'batch_size': 128} - Best Value (CSI): 0.389222 - Best Trial: 3 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.20876216806444886, 'lr': 0.0005164464819057032, 'weight_decay': 0.09576317801475862, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:33:57,974] Trial 27 pruned. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.254573 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.28090636483273385, 'lr': 0.004894773731191438, 'weight_decay': 0.020350960751609394, 'batch_size': 64} - Best Value (CSI): 0.389222 - Best Trial: 3 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.20876216806444886, 'lr': 0.0005164464819057032, 'weight_decay': 0.09576317801475862, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 10:34:26,482] Trial 28 finished with value: 0.38223146891066967 and parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.12697402385290293, 'lr': 0.0015461056255990121, 'weight_decay': 0.09287102233783434, 'batch_size': 256}. Best is trial 3 with value: 0.38922193462353977. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.382231 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.12697402385290293, 'lr': 0.0015461056255990121, 'weight_decay': 0.09287102233783434, 'batch_size': 256} - Best Value (CSI): 0.389222 - Best Trial: 3 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.20876216806444886, 'lr': 0.0005164464819057032, 'weight_decay': 0.09576317801475862, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:34:38,780] Trial 29 pruned. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.299130 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.17862932485904334, 'lr': 0.0007857023496361708, 'weight_decay': 0.010737656528277547, 'batch_size': 64} - Best Value (CSI): 0.389222 - Best Trial: 3 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.20876216806444886, 'lr': 0.0005164464819057032, 'weight_decay': 0.09576317801475862, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:35:17,121] Trial 30 pruned. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.303085 - Parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.25736910493793136, 'lr': 0.000563167652025217, 'weight_decay': 0.0459745860291337, 'batch_size': 32} - Best Value (CSI): 0.389222 - Best Trial: 3 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.20876216806444886, 'lr': 0.0005164464819057032, 'weight_decay': 0.09576317801475862, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 10:35:46,074] Trial 31 finished with value: 0.3945678027386506 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.18096543107822097, 'lr': 0.004134975087810065, 'weight_decay': 0.0017321528616573878, 'batch_size': 256}. Best is trial 31 with value: 0.3945678027386506. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.394568 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.18096543107822097, 'lr': 0.004134975087810065, 'weight_decay': 0.0017321528616573878, 'batch_size': 256} - Best Value (CSI): 0.394568 - Best Trial: 31 - Best Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.18096543107822097, 'lr': 0.004134975087810065, 'weight_decay': 0.0017321528616573878, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) -[I 2025-12-25 10:36:04,683] Trial 32 pruned. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.400000 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.20352501308065996, 'lr': 0.002662279592334002, 'weight_decay': 0.0018810916350173624, 'batch_size': 256} - Best Value (CSI): 0.394568 - Best Trial: 31 - Best Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.18096543107822097, 'lr': 0.004134975087810065, 'weight_decay': 0.0017321528616573878, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) -[I 2025-12-25 10:36:22,987] Trial 33 pruned. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.398754 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.1444354968536202, 'lr': 0.004743055901059185, 'weight_decay': 0.003271598013705027, 'batch_size': 256} - Best Value (CSI): 0.394568 - Best Trial: 31 - Best Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.18096543107822097, 'lr': 0.004134975087810065, 'weight_decay': 0.0017321528616573878, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 10:36:53,572] Trial 34 finished with value: 0.38036898508488215 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.17277097347425946, 'lr': 0.0017829705353806, 'weight_decay': 0.0008289928622124768, 'batch_size': 256}. Best is trial 31 with value: 0.3945678027386506. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.380369 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.17277097347425946, 'lr': 0.0017829705353806, 'weight_decay': 0.0008289928622124768, 'batch_size': 256} - Best Value (CSI): 0.394568 - Best Trial: 31 - Best Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.18096543107822097, 'lr': 0.004134975087810065, 'weight_decay': 0.0017321528616573878, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:36:58,383] Trial 35 pruned. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.283850 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.21833079848169135, 'lr': 0.002765528594744245, 'weight_decay': 0.0005168248054815874, 'batch_size': 256} - Best Value (CSI): 0.394568 - Best Trial: 31 - Best Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.18096543107822097, 'lr': 0.004134975087810065, 'weight_decay': 0.0017321528616573878, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:37:03,144] Trial 36 pruned. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.310160 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.12804284580292918, 'lr': 0.0013433677312922113, 'weight_decay': 0.002207397849586159, 'batch_size': 256} - Best Value (CSI): 0.394568 - Best Trial: 31 - Best Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.18096543107822097, 'lr': 0.004134975087810065, 'weight_decay': 0.0017321528616573878, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:37:11,934] Trial 37 pruned. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.298658 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.1923981866116894, 'lr': 0.006623194051101409, 'weight_decay': 0.0012923589894526329, 'batch_size': 128} - Best Value (CSI): 0.394568 - Best Trial: 31 - Best Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.18096543107822097, 'lr': 0.004134975087810065, 'weight_decay': 0.0017321528616573878, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:37:31,024] Trial 38 pruned. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.273450 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3903551807268393, 'lr': 0.003191233881524633, 'weight_decay': 0.0032358216083234618, 'batch_size': 32} - Best Value (CSI): 0.394568 - Best Trial: 31 - Best Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.18096543107822097, 'lr': 0.004134975087810065, 'weight_decay': 0.0017321528616573878, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:37:36,204] Trial 39 pruned. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.290429 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.21689705040199428, 'lr': 0.0021204471040659526, 'weight_decay': 0.012739679600043696, 'batch_size': 256} - Best Value (CSI): 0.394568 - Best Trial: 31 - Best Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.18096543107822097, 'lr': 0.004134975087810065, 'weight_decay': 0.0017321528616573878, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:37:56,893] Trial 40 pruned. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.284810 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.16384073992467782, 'lr': 0.0012741320589864866, 'weight_decay': 0.0071008607514074125, 'batch_size': 32} - Best Value (CSI): 0.394568 - Best Trial: 31 - Best Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.18096543107822097, 'lr': 0.004134975087810065, 'weight_decay': 0.0017321528616573878, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:38:01,791] Trial 41 pruned. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.285950 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.18757987578375068, 'lr': 0.003724865578920741, 'weight_decay': 0.0014697437121471359, 'batch_size': 256} - Best Value (CSI): 0.394568 - Best Trial: 31 - Best Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.18096543107822097, 'lr': 0.004134975087810065, 'weight_decay': 0.0017321528616573878, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:38:11,830] Trial 42 pruned. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.310409 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.18044460297307663, 'lr': 0.0051993715252157055, 'weight_decay': 0.0013019159560897495, 'batch_size': 256} - Best Value (CSI): 0.394568 - Best Trial: 31 - Best Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.18096543107822097, 'lr': 0.004134975087810065, 'weight_decay': 0.0017321528616573878, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:38:16,727] Trial 43 pruned. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.294976 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.20325532877225683, 'lr': 0.0034700593375179547, 'weight_decay': 0.0005309524248500822, 'batch_size': 256} - Best Value (CSI): 0.394568 - Best Trial: 31 - Best Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.18096543107822097, 'lr': 0.004134975087810065, 'weight_decay': 0.0017321528616573878, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:38:21,818] Trial 44 pruned. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.282371 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.16694605614749716, 'lr': 0.009212863032541391, 'weight_decay': 0.0025536274259801723, 'batch_size': 256} - Best Value (CSI): 0.394568 - Best Trial: 31 - Best Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.18096543107822097, 'lr': 0.004134975087810065, 'weight_decay': 0.0017321528616573878, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:38:26,719] Trial 45 pruned. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.288194 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.10021827439209874, 'lr': 0.006262268647582937, 'weight_decay': 0.004298657025019462, 'batch_size': 256} - Best Value (CSI): 0.394568 - Best Trial: 31 - Best Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.18096543107822097, 'lr': 0.004134975087810065, 'weight_decay': 0.0017321528616573878, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:38:34,552] Trial 46 pruned. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.292894 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.18921820659243188, 'lr': 0.0017797834129898453, 'weight_decay': 0.0016565956048746635, 'batch_size': 128} - Best Value (CSI): 0.394568 - Best Trial: 31 - Best Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.18096543107822097, 'lr': 0.004134975087810065, 'weight_decay': 0.0017321528616573878, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 10:39:51,046] Trial 47 finished with value: 0.3839967601629691 and parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.36990152674958987, 'lr': 0.0009949492369743284, 'weight_decay': 0.0011293827212123183, 'batch_size': 64}. Best is trial 31 with value: 0.3945678027386506. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.383997 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.36990152674958987, 'lr': 0.0009949492369743284, 'weight_decay': 0.0011293827212123183, 'batch_size': 64} - Best Value (CSI): 0.394568 - Best Trial: 31 - Best Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.18096543107822097, 'lr': 0.004134975087810065, 'weight_decay': 0.0017321528616573878, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:40:17,040] Trial 48 pruned. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.313356 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.1752576140227033, 'lr': 0.003045224931120496, 'weight_decay': 0.002279787526354897, 'batch_size': 32} - Best Value (CSI): 0.394568 - Best Trial: 31 - Best Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.18096543107822097, 'lr': 0.004134975087810065, 'weight_decay': 0.0017321528616573878, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:40:21,528] Trial 49 pruned. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.290679 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.3259028893874871, 'lr': 0.0012404833197619545, 'weight_decay': 0.003888299502918717, 'batch_size': 256} - Best Value (CSI): 0.394568 - Best Trial: 31 - Best Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.18096543107822097, 'lr': 0.004134975087810065, 'weight_decay': 0.0017321528616573878, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 10:42:50,272] Trial 50 finished with value: 0.3991148650568916 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32}. Best is trial 50 with value: 0.3991148650568916. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.399115 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:43:13,733] Trial 51 pruned. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.278689 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15026730144945138, 'lr': 0.0021222573817092174, 'weight_decay': 0.06856894850149621, 'batch_size': 32} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:43:35,070] Trial 52 pruned. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.284418 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.16158278366973722, 'lr': 0.0037957240267297975, 'weight_decay': 0.07548485212271465, 'batch_size': 32} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:44:00,931] Trial 53 pruned. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.304348 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.13977897970614214, 'lr': 0.0007794448426705132, 'weight_decay': 0.04115632604305206, 'batch_size': 32} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:44:49,834] Trial 54 pruned. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.311037 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.11799714271011041, 'lr': 0.0023913448784310307, 'weight_decay': 0.09701227598373802, 'batch_size': 32} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:45:36,044] Trial 55 pruned. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.310476 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.15819306010382994, 'lr': 0.0015188961842522316, 'weight_decay': 0.023414744848961423, 'batch_size': 32} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 10:46:04,230] Trial 56 finished with value: 0.37146497373951365 and parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.1332182868638302, 'lr': 0.0010104177071028253, 'weight_decay': 0.0698148511904944, 'batch_size': 256}. Best is trial 50 with value: 0.3991148650568916. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.371465 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.1332182868638302, 'lr': 0.0010104177071028253, 'weight_decay': 0.0698148511904944, 'batch_size': 256} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 10:46:40,598] Trial 57 finished with value: 0.38120720064377095 and parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.11712804540334501, 'lr': 0.0030187048701160986, 'weight_decay': 0.04396549278199766, 'batch_size': 256}. Best is trial 50 with value: 0.3991148650568916. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.381207 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.11712804540334501, 'lr': 0.0030187048701160986, 'weight_decay': 0.04396549278199766, 'batch_size': 256} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:46:53,893] Trial 58 pruned. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.259644 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.15582012062111483, 'lr': 0.0050824239734123585, 'weight_decay': 0.001852710524566254, 'batch_size': 64} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:47:07,075] Trial 59 pruned. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.320789 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.13936790533204063, 'lr': 0.0003609735140570261, 'weight_decay': 0.026421674665346548, 'batch_size': 128} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:47:32,601] Trial 60 pruned. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.291379 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.18356632922074298, 'lr': 0.0017478760653826847, 'weight_decay': 0.035605492114935085, 'batch_size': 32} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:47:40,447] Trial 61 pruned. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.315141 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.23934231110440768, 'lr': 0.0024629031412798895, 'weight_decay': 0.06763189339518477, 'batch_size': 256} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:47:48,947] Trial 62 pruned. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.299652 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19923734582816371, 'lr': 0.0020868444234223836, 'weight_decay': 0.05235173976486803, 'batch_size': 256} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:47:56,869] Trial 63 pruned. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.314079 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.21082963872016686, 'lr': 0.0044031147291905244, 'weight_decay': 0.03668958285488595, 'batch_size': 256} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:48:01,820] Trial 64 pruned. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.263464 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.2291651535923204, 'lr': 0.0006256996471644392, 'weight_decay': 0.049939044301450644, 'batch_size': 256} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:48:10,598] Trial 65 pruned. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.315141 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.1740386597875413, 'lr': 0.0013572853802497017, 'weight_decay': 0.0824185461309748, 'batch_size': 256} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:48:14,972] Trial 66 pruned. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.249311 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2972500723148835, 'lr': 0.0004545162456076582, 'weight_decay': 0.05702822937299325, 'batch_size': 256} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:48:23,095] Trial 67 pruned. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.314991 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.27362874380623387, 'lr': 0.0038103988419880613, 'weight_decay': 0.09788896286805923, 'batch_size': 256} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:48:44,812] Trial 68 pruned. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.270270 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.19437862251476629, 'lr': 0.002555513736898342, 'weight_decay': 0.05940725010140362, 'batch_size': 32} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:48:52,573] Trial 69 pruned. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.302536 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.25091380422037446, 'lr': 0.001836268500181193, 'weight_decay': 0.07960486618535044, 'batch_size': 256} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:49:04,882] Trial 70 pruned. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.295000 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.21066982926244077, 'lr': 0.001148257627887433, 'weight_decay': 0.04261314365207434, 'batch_size': 64} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:49:17,153] Trial 71 pruned. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.302926 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.393440851831177, 'lr': 0.0009251539187595495, 'weight_decay': 0.00104863783214552, 'batch_size': 64} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:49:29,726] Trial 72 pruned. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.303136 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3715916802254118, 'lr': 0.0009211859480386593, 'weight_decay': 0.0009736160671407746, 'batch_size': 64} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:49:42,852] Trial 73 pruned. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.302876 - Parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3993920593294619, 'lr': 0.0030760058375423, 'weight_decay': 0.0019876925560191124, 'batch_size': 64} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:49:55,755] Trial 74 pruned. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.281056 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3687502266813523, 'lr': 0.0014705473249239482, 'weight_decay': 0.002683436641443877, 'batch_size': 64} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 10:50:27,527] Trial 75 finished with value: 0.37373360227220814 and parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.16852036699010972, 'lr': 0.0007412789666526645, 'weight_decay': 0.032942877994157904, 'batch_size': 256}. Best is trial 50 with value: 0.3991148650568916. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.373734 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.16852036699010972, 'lr': 0.0007412789666526645, 'weight_decay': 0.032942877994157904, 'batch_size': 256} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:50:39,120] Trial 76 pruned. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.303136 - Parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.3762164375802858, 'lr': 0.0011638032515101202, 'weight_decay': 0.016029964840315068, 'batch_size': 128} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) -[I 2025-12-25 10:51:23,921] Trial 77 pruned. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.384717 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.18673392023736332, 'lr': 0.0019509772169473525, 'weight_decay': 0.08237453773626051, 'batch_size': 64} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 10:51:49,062] Trial 78 pruned. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.339367 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.14980011794738504, 'lr': 0.002616318753905241, 'weight_decay': 0.0011790209865310485, 'batch_size': 256} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:52:27,009] Trial 79 pruned. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.314629 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3482998372950359, 'lr': 0.0016101741780071962, 'weight_decay': 0.0015529658811561917, 'batch_size': 32} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:52:35,178] Trial 80 pruned. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.308958 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.2636590728798877, 'lr': 0.0022588713283375906, 'weight_decay': 0.0007416673190366454, 'batch_size': 256} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:52:43,128] Trial 81 pruned. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.302655 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.19901938896629273, 'lr': 0.004309866678878766, 'weight_decay': 0.062170482421782663, 'batch_size': 256} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:52:50,897] Trial 82 pruned. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.309783 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.22333499043430177, 'lr': 0.005755188918155663, 'weight_decay': 0.06212492182390605, 'batch_size': 256} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:52:55,451] Trial 83 pruned. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.265879 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.23573420973903098, 'lr': 0.0040309057249031, 'weight_decay': 0.0486525925808665, 'batch_size': 256} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:53:03,554] Trial 84 pruned. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.288815 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.17951721468093498, 'lr': 0.003504755677581347, 'weight_decay': 0.07694261852754754, 'batch_size': 256} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:53:20,855] Trial 85 pruned. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.245333 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.21049379750365418, 'lr': 0.007315461619132211, 'weight_decay': 0.09686950381148796, 'batch_size': 32} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:53:25,995] Trial 86 pruned. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.298951 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.1665783224164815, 'lr': 0.002818071068346511, 'weight_decay': 0.05342759307463519, 'batch_size': 256} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 10:53:55,747] Trial 87 finished with value: 0.38622992514289 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.19380734004419836, 'lr': 0.0034286714602493828, 'weight_decay': 0.03870477819428157, 'batch_size': 256}. Best is trial 50 with value: 0.3991148650568916. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.386230 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.19380734004419836, 'lr': 0.0034286714602493828, 'weight_decay': 0.03870477819428157, 'batch_size': 256} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 10:54:23,905] Trial 88 finished with value: 0.38205031167480646 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.19218872516115634, 'lr': 0.0034292892542343513, 'weight_decay': 0.03731215718685484, 'batch_size': 256}. Best is trial 50 with value: 0.3991148650568916. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.382050 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.19218872516115634, 'lr': 0.0034292892542343513, 'weight_decay': 0.03731215718685484, 'batch_size': 256} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:54:45,466] Trial 89 pruned. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.298246 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3826550935165921, 'lr': 0.0020387742568004578, 'weight_decay': 0.0301858375267081, 'batch_size': 32} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:54:59,393] Trial 90 pruned. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.304598 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.17956484157307714, 'lr': 0.0014234776430758133, 'weight_decay': 0.0012686179044465494, 'batch_size': 128} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:55:07,151] Trial 91 pruned. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.312950 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.20550749976286584, 'lr': 0.004990187463361563, 'weight_decay': 0.04446944724854915, 'batch_size': 256} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 10:55:33,964] Trial 92 finished with value: 0.3861654299300438 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.18752509238060627, 'lr': 0.003225365758804971, 'weight_decay': 0.06434288907545135, 'batch_size': 256}. Best is trial 50 with value: 0.3991148650568916. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.386165 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.18752509238060627, 'lr': 0.003225365758804971, 'weight_decay': 0.06434288907545135, 'batch_size': 256} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:55:42,826] Trial 93 pruned. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.307971 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.18941975048782195, 'lr': 0.002405507961164702, 'weight_decay': 0.06869273768857732, 'batch_size': 256} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:55:51,602] Trial 94 pruned. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.334646 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.19838281628438045, 'lr': 0.0028996894330121275, 'weight_decay': 0.07854350000952375, 'batch_size': 256} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) -[I 2025-12-25 10:56:09,601] Trial 95 pruned. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.400657 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.17189500140845693, 'lr': 0.0017296632236915236, 'weight_decay': 0.08679290883377223, 'batch_size': 256} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 10:56:34,441] Trial 96 finished with value: 0.3925027975323269 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.1583979593886063, 'lr': 0.004314228713221431, 'weight_decay': 0.05461399292125453, 'batch_size': 256}. Best is trial 50 with value: 0.3991148650568916. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.392503 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.1583979593886063, 'lr': 0.004314228713221431, 'weight_decay': 0.05461399292125453, 'batch_size': 256} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:56:43,256] Trial 97 pruned. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.286432 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.1531563160633173, 'lr': 0.005815901514299003, 'weight_decay': 0.051293196906924694, 'batch_size': 256} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 10:56:52,103] Trial 98 pruned. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.321012 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.15676460066833806, 'lr': 0.0033570333619670186, 'weight_decay': 0.06475500413231854, 'batch_size': 256} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 10:57:21,754] Trial 99 finished with value: 0.38388991661254934 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.1628794523741427, 'lr': 0.004630818769419554, 'weight_decay': 0.026322383541567407, 'batch_size': 256}. Best is trial 50 with value: 0.3991148650568916. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.383890 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.1628794523741427, 'lr': 0.004630818769419554, 'weight_decay': 0.026322383541567407, 'batch_size': 256} - Best Value (CSI): 0.399115 - Best Trial: 50 - Best Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.3991 -Best Hyperparameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15327234825163508, 'lr': 0.0021257323880618864, 'weight_decay': 0.06824750948093047, 'batch_size': 32} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.3800 - - 최종 CSI: 0.3839 - - 최고 CSI: 0.4007 - - 최저 CSI: 0.2072 - - 평균 CSI: 0.3203 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/deepgbm_smote_daegu_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 23, Best CSI: 0.3176 - Fold 1 학습 완료 (검증 CSI: 0.3176) -Fold 2 학습 중... - Early stopping at epoch 26, Best CSI: 0.4231 - Fold 2 학습 완료 (검증 CSI: 0.4231) -Fold 3 학습 중... - Early stopping at epoch 18, Best CSI: 0.4168 - Fold 3 학습 완료 (검증 CSI: 0.4168) - -모든 모델 저장 완료: ../save_model/deepgbm_optima/deepgbm_smote_daegu.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/deepgbm_optima/scaler/deepgbm_smote_daegu_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: ../save_model/deepgbm_optima/deepgbm_smote_daegu.pkl - -✓ 완료: deepgbm_smote/deepgbm_smote_daegu.py (소요 시간: 2496초) - ----------------------------------------- -실행 중: deepgbm_smote/deepgbm_smote_daejeon.py -시작 시간: 2025-12-25 10:59:37 ----------------------------------------- -[I 2025-12-25 10:59:38,660] A new study created in memory with name: no-name-22bba392-197f-4a3e-af31-8eebaa82803a - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.3215416666666666, 1: 1.3215416666666666, 2: 0.6726686602617123} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.3243333333333334, 1: 1.3243333333333334, 2: 0.6712282480148674} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15784}) -[I 2025-12-25 11:00:48,730] Trial 0 finished with value: 0.4287732599473563 and parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16464401777790397, 'lr': 5.3782695067300876e-05, 'weight_decay': 0.0234130008776593, 'batch_size': 256}. Best is trial 0 with value: 0.4287732599473563. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.428773 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16464401777790397, 'lr': 5.3782695067300876e-05, 'weight_decay': 0.0234130008776593, 'batch_size': 256} - Best Value (CSI): 0.428773 - Best Trial: 0 - Best Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.16464401777790397, 'lr': 5.3782695067300876e-05, 'weight_decay': 0.0234130008776593, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.3215416666666666, 1: 1.3215416666666666, 2: 0.6726686602617123} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.3243333333333334, 1: 1.3243333333333334, 2: 0.6712282480148674} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15784}) -[I 2025-12-25 11:01:33,375] Trial 1 finished with value: 0.43942802503868333 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3662705454238786, 'lr': 0.00043748998546167114, 'weight_decay': 0.0004612836663478313, 'batch_size': 256}. Best is trial 1 with value: 0.43942802503868333. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.439428 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3662705454238786, 'lr': 0.00043748998546167114, 'weight_decay': 0.0004612836663478313, 'batch_size': 256} - Best Value (CSI): 0.439428 - Best Trial: 1 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3662705454238786, 'lr': 0.00043748998546167114, 'weight_decay': 0.0004612836663478313, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.3215416666666666, 1: 1.3215416666666666, 2: 0.6726686602617123} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.3243333333333334, 1: 1.3243333333333334, 2: 0.6712282480148674} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15784}) -[I 2025-12-25 11:02:33,667] Trial 2 finished with value: 0.4372761639284977 and parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.35901159939108807, 'lr': 0.00014768331556955659, 'weight_decay': 0.00012548650420212836, 'batch_size': 128}. Best is trial 1 with value: 0.43942802503868333. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.437276 - Parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.35901159939108807, 'lr': 0.00014768331556955659, 'weight_decay': 0.00012548650420212836, 'batch_size': 128} - Best Value (CSI): 0.439428 - Best Trial: 1 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3662705454238786, 'lr': 0.00043748998546167114, 'weight_decay': 0.0004612836663478313, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.3215416666666666, 1: 1.3215416666666666, 2: 0.6726686602617123} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.3243333333333334, 1: 1.3243333333333334, 2: 0.6712282480148674} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15784}) -[I 2025-12-25 11:03:02,020] Trial 3 finished with value: 0.4389940470777424 and parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.18788681175636734, 'lr': 0.008993364380459518, 'weight_decay': 0.0002874106814724655, 'batch_size': 256}. Best is trial 1 with value: 0.43942802503868333. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.438994 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.18788681175636734, 'lr': 0.008993364380459518, 'weight_decay': 0.0002874106814724655, 'batch_size': 256} - Best Value (CSI): 0.439428 - Best Trial: 1 - Best Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3662705454238786, 'lr': 0.00043748998546167114, 'weight_decay': 0.0004612836663478313, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.3215416666666666, 1: 1.3215416666666666, 2: 0.6726686602617123} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.3243333333333334, 1: 1.3243333333333334, 2: 0.6712282480148674} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15784}) -[I 2025-12-25 11:04:03,369] Trial 4 finished with value: 0.4464527362467254 and parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3778682430348451, 'lr': 0.0005233088132224274, 'weight_decay': 0.0005012485686439388, 'batch_size': 128}. Best is trial 4 with value: 0.4464527362467254. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.446453 - Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3778682430348451, 'lr': 0.0005233088132224274, 'weight_decay': 0.0005012485686439388, 'batch_size': 128} - Best Value (CSI): 0.446453 - Best Trial: 4 - Best Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3778682430348451, 'lr': 0.0005233088132224274, 'weight_decay': 0.0005012485686439388, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.3215416666666666, 1: 1.3215416666666666, 2: 0.6726686602617123} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.3243333333333334, 1: 1.3243333333333334, 2: 0.6712282480148674} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15784}) -[I 2025-12-25 11:07:49,679] Trial 5 finished with value: 0.46415327690903346 and parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32}. Best is trial 5 with value: 0.46415327690903346. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.464153 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:08:11,159] Trial 6 pruned. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.341860 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.21951229831134825, 'lr': 0.00026813258895535256, 'weight_decay': 0.008924049742627492, 'batch_size': 64} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:08:22,388] Trial 7 pruned. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.357364 - Parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.29853695731466656, 'lr': 0.0007389119172172103, 'weight_decay': 0.01498410948030983, 'batch_size': 256} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:08:33,447] Trial 8 pruned. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.353016 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.39177796885911254, 'lr': 0.008851023444534076, 'weight_decay': 0.032144744161495035, 'batch_size': 128} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.3215416666666666, 1: 1.3215416666666666, 2: 0.6726686602617123} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.3243333333333334, 1: 1.3243333333333334, 2: 0.6712282480148674} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15784}) -[I 2025-12-25 11:09:12,780] Trial 9 finished with value: 0.42478663205665873 and parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.1146631594730683, 'lr': 0.0004080170931844666, 'weight_decay': 0.001780418371684631, 'batch_size': 256}. Best is trial 5 with value: 0.46415327690903346. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.424787 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.1146631594730683, 'lr': 0.0004080170931844666, 'weight_decay': 0.001780418371684631, 'batch_size': 256} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:09:34,665] Trial 10 pruned. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.266585 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.26430770302866413, 'lr': 1.1722848936261475e-05, 'weight_decay': 0.06683391808636456, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.3215416666666666, 1: 1.3215416666666666, 2: 0.6726686602617123} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.3243333333333334, 1: 1.3243333333333334, 2: 0.6712282480148674} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15784}) -[I 2025-12-25 11:12:16,225] Trial 11 finished with value: 0.44932048628614457 and parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.29953132854656955, 'lr': 0.002192489709688562, 'weight_decay': 0.0021768122857367925, 'batch_size': 32}. Best is trial 5 with value: 0.46415327690903346. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.449320 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.29953132854656955, 'lr': 0.002192489709688562, 'weight_decay': 0.0021768122857367925, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.3215416666666666, 1: 1.3215416666666666, 2: 0.6726686602617123} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.3243333333333334, 1: 1.3243333333333334, 2: 0.6712282480148674} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15784}) -[I 2025-12-25 11:15:43,854] Trial 12 finished with value: 0.4558921609385491 and parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.2883440169162035, 'lr': 0.0024078560125422328, 'weight_decay': 0.002100644058644268, 'batch_size': 32}. Best is trial 5 with value: 0.46415327690903346. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.455892 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.2883440169162035, 'lr': 0.0024078560125422328, 'weight_decay': 0.002100644058644268, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.3215416666666666, 1: 1.3215416666666666, 2: 0.6726686602617123} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.3243333333333334, 1: 1.3243333333333334, 2: 0.6712282480148674} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15784}) -[I 2025-12-25 11:18:06,924] Trial 13 finished with value: 0.4590607939093762 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.24029644774353975, 'lr': 0.0027238994605550512, 'weight_decay': 0.006704529092413096, 'batch_size': 32}. Best is trial 5 with value: 0.46415327690903346. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.459061 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.24029644774353975, 'lr': 0.0027238994605550512, 'weight_decay': 0.006704529092413096, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.3215416666666666, 1: 1.3215416666666666, 2: 0.6726686602617123} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.3243333333333334, 1: 1.3243333333333334, 2: 0.6712282480148674} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15784}) -[I 2025-12-25 11:19:50,969] Trial 14 finished with value: 0.45021770249691623 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.22716904696819115, 'lr': 0.0021981559261548093, 'weight_decay': 0.006159398421888917, 'batch_size': 32}. Best is trial 5 with value: 0.46415327690903346. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.450218 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.22716904696819115, 'lr': 0.0021981559261548093, 'weight_decay': 0.006159398421888917, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.3215416666666666, 1: 1.3215416666666666, 2: 0.6726686602617123} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.3243333333333334, 1: 1.3243333333333334, 2: 0.6712282480148674} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15784}) -[I 2025-12-25 11:22:46,204] Trial 15 finished with value: 0.45521765457767643 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.17040805834369976, 'lr': 0.004799765053470751, 'weight_decay': 0.004525435340301081, 'batch_size': 32}. Best is trial 5 with value: 0.46415327690903346. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.455218 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.17040805834369976, 'lr': 0.004799765053470751, 'weight_decay': 0.004525435340301081, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.3215416666666666, 1: 1.3215416666666666, 2: 0.6726686602617123} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.3243333333333334, 1: 1.3243333333333334, 2: 0.6712282480148674} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15784}) -[I 2025-12-25 11:24:12,306] Trial 16 finished with value: 0.450080160036941 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.238832754725644, 'lr': 0.0012632778584606111, 'weight_decay': 0.010263032550019528, 'batch_size': 64}. Best is trial 5 with value: 0.46415327690903346. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.450080 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.238832754725644, 'lr': 0.0012632778584606111, 'weight_decay': 0.010263032550019528, 'batch_size': 64} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:24:41,402] Trial 17 pruned. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.332324 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.19890008968125483, 'lr': 0.004456652058705178, 'weight_decay': 0.004169618999154077, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:25:26,590] Trial 18 pruned. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.361045 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.13482671764257276, 'lr': 0.0011602292113980582, 'weight_decay': 0.0011256771541441183, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:25:52,502] Trial 19 pruned. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.329593 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.14591536893010745, 'lr': 0.004770045944671216, 'weight_decay': 0.00465997282724911, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:26:13,382] Trial 20 pruned. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.320896 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.19042121521325517, 'lr': 0.009616778726178398, 'weight_decay': 0.013895928020587088, 'batch_size': 64} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:26:39,883] Trial 21 pruned. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.329193 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.26501344565236834, 'lr': 0.002503693082844455, 'weight_decay': 0.0027450172833413233, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.3215416666666666, 1: 1.3215416666666666, 2: 0.6726686602617123} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.3243333333333334, 1: 1.3243333333333334, 2: 0.6712282480148674} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15784}) -[I 2025-12-25 11:29:12,222] Trial 22 finished with value: 0.44548846075424064 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.25988553510772683, 'lr': 0.0011458609033561087, 'weight_decay': 0.0014977892689250762, 'batch_size': 32}. Best is trial 5 with value: 0.46415327690903346. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.445488 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.25988553510772683, 'lr': 0.0011458609033561087, 'weight_decay': 0.0014977892689250762, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:29:35,681] Trial 23 pruned. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.335522 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2146698513866834, 'lr': 0.003898799612948572, 'weight_decay': 0.0030351850585981924, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:30:25,903] Trial 24 pruned. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.358590 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2837194030872841, 'lr': 0.0025624004315054046, 'weight_decay': 0.000939462763311808, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:31:17,217] Trial 25 pruned. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.361702 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.2369603115227768, 'lr': 0.0015004466317156111, 'weight_decay': 0.005684584203533478, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:31:42,409] Trial 26 pruned. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.335349 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.3281919193754264, 'lr': 0.003653084787960292, 'weight_decay': 0.002593753982817319, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:32:10,335] Trial 27 pruned. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.339498 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.24238681164453107, 'lr': 0.006222971843370453, 'weight_decay': 0.007060284530140196, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.3215416666666666, 1: 1.3215416666666666, 2: 0.6726686602617123} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.3243333333333334, 1: 1.3243333333333334, 2: 0.6712282480148674} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15784}) -[I 2025-12-25 11:33:06,088] Trial 28 finished with value: 0.45695609299860057 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20752713665735453, 'lr': 0.006648083425661159, 'weight_decay': 0.0036996148116303145, 'batch_size': 128}. Best is trial 5 with value: 0.46415327690903346. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.456956 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20752713665735453, 'lr': 0.006648083425661159, 'weight_decay': 0.0036996148116303145, 'batch_size': 128} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:33:24,872] Trial 29 pruned. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.365926 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.17500847616967957, 'lr': 0.0064828596420271525, 'weight_decay': 0.021483667146751494, 'batch_size': 128} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.3215416666666666, 1: 1.3215416666666666, 2: 0.6726686602617123} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.3243333333333334, 1: 1.3243333333333334, 2: 0.6712282480148674} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15784}) -[I 2025-12-25 11:34:07,378] Trial 30 finished with value: 0.4576487043782602 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20847655448123484, 'lr': 0.0064290897331499425, 'weight_decay': 0.011555372169890296, 'batch_size': 128}. Best is trial 5 with value: 0.46415327690903346. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.457649 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20847655448123484, 'lr': 0.0064290897331499425, 'weight_decay': 0.011555372169890296, 'batch_size': 128} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:34:14,485] Trial 31 pruned. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.325243 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2144761396440545, 'lr': 0.009869734354514928, 'weight_decay': 0.008767107652312225, 'batch_size': 128} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:34:21,456] Trial 32 pruned. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.342249 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20540971482821843, 'lr': 0.006254686839228225, 'weight_decay': 0.003624028731083136, 'batch_size': 128} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:34:39,695] Trial 33 pruned. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.363290 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.1630728535843246, 'lr': 0.003392239594994088, 'weight_decay': 0.006853525517551923, 'batch_size': 128} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.3215416666666666, 1: 1.3215416666666666, 2: 0.6726686602617123} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.3243333333333334, 1: 1.3243333333333334, 2: 0.6712282480148674} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15784}) -[I 2025-12-25 11:35:39,061] Trial 34 finished with value: 0.4546940689347913 and parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.1854106130576178, 'lr': 0.005944171350580241, 'weight_decay': 0.012324520059844184, 'batch_size': 128}. Best is trial 5 with value: 0.46415327690903346. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.454694 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.1854106130576178, 'lr': 0.005944171350580241, 'weight_decay': 0.012324520059844184, 'batch_size': 128} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:35:51,318] Trial 35 pruned. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.359769 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20791294064872518, 'lr': 0.00359180464405028, 'weight_decay': 0.005002850528828287, 'batch_size': 128} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:35:58,260] Trial 36 pruned. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.301266 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.23408406089299583, 'lr': 0.007013687675567585, 'weight_decay': 0.02085664152593502, 'batch_size': 128} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:36:02,897] Trial 37 pruned. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.331176 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.1962358753441096, 'lr': 0.0008154462754522754, 'weight_decay': 0.003353684673968479, 'batch_size': 256} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:36:15,088] Trial 38 pruned. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.339860 - Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.22301188011372783, 'lr': 0.0018537431023315574, 'weight_decay': 0.010952343895864471, 'batch_size': 64} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:36:22,355] Trial 39 pruned. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.352787 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.2530331080654246, 'lr': 0.009554565587104914, 'weight_decay': 0.00800069385201141, 'batch_size': 128} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:36:27,262] Trial 40 pruned. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.347458 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.18181692798021262, 'lr': 0.0030272837497173563, 'weight_decay': 0.030001565866496334, 'batch_size': 256} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.3215416666666666, 1: 1.3215416666666666, 2: 0.6726686602617123} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.3243333333333334, 1: 1.3243333333333334, 2: 0.6712282480148674} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15784}) -[I 2025-12-25 11:37:37,515] Trial 41 finished with value: 0.443036958131292 and parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.20313276033881345, 'lr': 0.0017909733652901674, 'weight_decay': 0.001947621770568733, 'batch_size': 128}. Best is trial 5 with value: 0.46415327690903346. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.443037 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.20313276033881345, 'lr': 0.0017909733652901674, 'weight_decay': 0.001947621770568733, 'batch_size': 128} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:37:51,161] Trial 42 pruned. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.352985 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.22530020228353814, 'lr': 0.002872181716308711, 'weight_decay': 0.0030965078610407813, 'batch_size': 128} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:38:15,944] Trial 43 pruned. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.333809 - Parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.2470934028182155, 'lr': 0.005100973575190262, 'weight_decay': 0.006036122928405448, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:38:28,936] Trial 44 pruned. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.352209 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.21970754113779406, 'lr': 0.006760236768559722, 'weight_decay': 0.016092669452126115, 'batch_size': 64} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:38:48,542] Trial 45 pruned. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.345015 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2709966629780014, 'lr': 0.0044831705807178495, 'weight_decay': 0.0023482843196448015, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.3215416666666666, 1: 1.3215416666666666, 2: 0.6726686602617123} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.3243333333333334, 1: 1.3243333333333334, 2: 0.6712282480148674} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15784}) -[I 2025-12-25 11:39:13,152] Trial 46 finished with value: 0.4330390639403226 and parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.24941063176146577, 'lr': 0.002450335495027332, 'weight_decay': 0.004012034828780417, 'batch_size': 256}. Best is trial 5 with value: 0.46415327690903346. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.433039 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.24941063176146577, 'lr': 0.002450335495027332, 'weight_decay': 0.004012034828780417, 'batch_size': 256} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:39:36,714] Trial 47 pruned. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.352941 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.19158419250585093, 'lr': 0.0017537510132058962, 'weight_decay': 0.008915809048351384, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:39:48,079] Trial 48 pruned. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.350453 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.16456425784858197, 'lr': 0.007304822933018429, 'weight_decay': 0.0017434226207284598, 'batch_size': 128} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:40:15,502] Trial 49 pruned. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.345966 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.22935504589674793, 'lr': 0.004469269310128671, 'weight_decay': 0.005358166891792854, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:41:10,878] Trial 50 pruned. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.367534 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2790091485122156, 'lr': 0.0031747912755973073, 'weight_decay': 0.0007131009578992205, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:41:38,294] Trial 51 pruned. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.338731 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.1738458116064515, 'lr': 0.004661870352050287, 'weight_decay': 0.004258755018686358, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:42:05,151] Trial 52 pruned. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.317479 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.15155836157132863, 'lr': 0.00786786521682219, 'weight_decay': 0.002254732141895047, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:42:33,318] Trial 53 pruned. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.350136 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2012592864399289, 'lr': 0.005354897885305355, 'weight_decay': 0.00376099327801976, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:43:26,873] Trial 54 pruned. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.339190 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.21055821430788133, 'lr': 0.002291031858456491, 'weight_decay': 0.006278448060485363, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:43:52,366] Trial 55 pruned. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.329268 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.1732185532873094, 'lr': 0.007979696891563215, 'weight_decay': 0.001418995098208098, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:44:05,192] Trial 56 pruned. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.325255 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.23343600736047893, 'lr': 0.0038169882874503, 'weight_decay': 0.010267663720787495, 'batch_size': 64} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.3215416666666666, 1: 1.3215416666666666, 2: 0.6726686602617123} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.3243333333333334, 1: 1.3243333333333334, 2: 0.6712282480148674} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15784}) -[I 2025-12-25 11:46:55,831] Trial 57 finished with value: 0.45552788001050887 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.1890947598044475, 'lr': 0.002800512833212468, 'weight_decay': 0.004146883806976406, 'batch_size': 32}. Best is trial 5 with value: 0.46415327690903346. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.455528 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.1890947598044475, 'lr': 0.002800512833212468, 'weight_decay': 0.004146883806976406, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.3215416666666666, 1: 1.3215416666666666, 2: 0.6726686602617123} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.3243333333333334, 1: 1.3243333333333334, 2: 0.6712282480148674} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15784}) -[I 2025-12-25 11:47:32,172] Trial 58 finished with value: 0.4470015495134916 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.21870407910281478, 'lr': 0.002829387947576689, 'weight_decay': 0.0026736144020761826, 'batch_size': 256}. Best is trial 5 with value: 0.46415327690903346. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.447002 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.21870407910281478, 'lr': 0.002829387947576689, 'weight_decay': 0.0026736144020761826, 'batch_size': 256} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:48:00,471] Trial 59 pruned. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.337569 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.19326120920997386, 'lr': 0.0002941093342961994, 'weight_decay': 0.007459303152888276, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:48:14,329] Trial 60 pruned. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.351824 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.18302293346770607, 'lr': 0.0013892957753101677, 'weight_decay': 0.005308267424195553, 'batch_size': 128} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:48:55,341] Trial 61 pruned. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.337093 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.19978358570179253, 'lr': 0.005320679563522986, 'weight_decay': 0.004657898219946525, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:49:22,352] Trial 62 pruned. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.335719 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.21572356050889546, 'lr': 0.003982246201964759, 'weight_decay': 0.003143982132961233, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:49:48,798] Trial 63 pruned. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.348539 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.15738597168003315, 'lr': 0.008561903314313035, 'weight_decay': 0.004176031834527413, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.3215416666666666, 1: 1.3215416666666666, 2: 0.6726686602617123} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.3243333333333334, 1: 1.3243333333333334, 2: 0.6712282480148674} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15784}) -[I 2025-12-25 11:53:25,033] Trial 64 finished with value: 0.4482118702368421 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.17678192143218122, 'lr': 0.0022176080675088954, 'weight_decay': 0.0078111186836251345, 'batch_size': 32}. Best is trial 5 with value: 0.46415327690903346. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.448212 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.17678192143218122, 'lr': 0.0022176080675088954, 'weight_decay': 0.0078111186836251345, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:53:47,954] Trial 65 pruned. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.354098 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.19058249322876564, 'lr': 0.0035050284517651785, 'weight_decay': 0.002374798499092826, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:53:57,005] Trial 66 pruned. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.341033 - Parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.1366424458797351, 'lr': 0.005716132836874952, 'weight_decay': 0.003356258347098875, 'batch_size': 128} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:54:19,272] Trial 67 pruned. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.260606 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2414531781231318, 'lr': 0.009842510675304493, 'weight_decay': 0.006302270537569458, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:54:44,075] Trial 68 pruned. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.334223 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.20568725178632613, 'lr': 0.0029490630309926555, 'weight_decay': 0.013192103437245917, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:55:07,800] Trial 69 pruned. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.350384 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.16764956155777316, 'lr': 0.0009833878522420164, 'weight_decay': 0.004723031273642582, 'batch_size': 64} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:55:35,106] Trial 70 pruned. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.373441 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.2594181600680446, 'lr': 0.00415797873685806, 'weight_decay': 0.010626535689528652, 'batch_size': 128} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:55:41,682] Trial 71 pruned. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.354037 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.18639269227142652, 'lr': 0.005552836755870471, 'weight_decay': 0.011791491862484753, 'batch_size': 128} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.3215416666666666, 1: 1.3215416666666666, 2: 0.6726686602617123} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.3243333333333334, 1: 1.3243333333333334, 2: 0.6712282480148674} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15784}) -[I 2025-12-25 11:56:36,858] Trial 72 finished with value: 0.4498004002076441 and parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.182080509484167, 'lr': 0.006324992275277196, 'weight_decay': 0.008340269604431572, 'batch_size': 128}. Best is trial 5 with value: 0.46415327690903346. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.449800 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.182080509484167, 'lr': 0.006324992275277196, 'weight_decay': 0.008340269604431572, 'batch_size': 128} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.3215416666666666, 1: 1.3215416666666666, 2: 0.6726686602617123} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.3243333333333334, 1: 1.3243333333333334, 2: 0.6712282480148674} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15784}) -[I 2025-12-25 11:57:27,958] Trial 73 finished with value: 0.45814751492735084 and parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.1964230067052286, 'lr': 0.007531173473681538, 'weight_decay': 0.016414646949729786, 'batch_size': 128}. Best is trial 5 with value: 0.46415327690903346. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.458148 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.1964230067052286, 'lr': 0.007531173473681538, 'weight_decay': 0.016414646949729786, 'batch_size': 128} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:57:34,503] Trial 74 pruned. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.353119 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.22845477905884504, 'lr': 0.0077074987340415, 'weight_decay': 0.016380702397955277, 'batch_size': 128} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:58:02,855] Trial 75 pruned. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.371253 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.1973827827381889, 'lr': 0.004793715972101929, 'weight_decay': 0.002829405483209596, 'batch_size': 128} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 11:58:24,971] Trial 76 pruned. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.278278 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.20971550373485742, 'lr': 0.007028727463383145, 'weight_decay': 0.0036265829279168186, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.3215416666666666, 1: 1.3215416666666666, 2: 0.6726686602617123} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.3243333333333334, 1: 1.3243333333333334, 2: 0.6712282480148674} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15784}) -[I 2025-12-25 11:59:20,481] Trial 77 finished with value: 0.44899634001890026 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.22375199904803117, 'lr': 0.003700404292216207, 'weight_decay': 0.006255204856161227, 'batch_size': 128}. Best is trial 5 with value: 0.46415327690903346. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.448996 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.22375199904803117, 'lr': 0.003700404292216207, 'weight_decay': 0.006255204856161227, 'batch_size': 128} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.3215416666666666, 1: 1.3215416666666666, 2: 0.6726686602617123} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.3243333333333334, 1: 1.3243333333333334, 2: 0.6712282480148674} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15784}) -[I 2025-12-25 11:59:53,251] Trial 78 finished with value: 0.4418361120969623 and parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.21136184090995408, 'lr': 0.001980360107396802, 'weight_decay': 0.009362751757232907, 'batch_size': 256}. Best is trial 5 with value: 0.46415327690903346. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.441836 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.21136184090995408, 'lr': 0.001980360107396802, 'weight_decay': 0.009362751757232907, 'batch_size': 256} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 12:00:15,000] Trial 79 pruned. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.333333 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.19191890280626206, 'lr': 0.001602764832593769, 'weight_decay': 0.004876867367354813, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 12:00:25,337] Trial 80 pruned. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.362810 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.23662650318562192, 'lr': 0.003030007584684654, 'weight_decay': 0.0019446964292920308, 'batch_size': 128} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 12:00:32,484] Trial 81 pruned. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.356183 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.17713196668865303, 'lr': 0.005924189291163754, 'weight_decay': 0.01362333111677131, 'batch_size': 128} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 12:00:39,041] Trial 82 pruned. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.345164 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.1853404265408541, 'lr': 0.00840328237817287, 'weight_decay': 0.016184733774346035, 'batch_size': 128} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 12:00:45,993] Trial 83 pruned. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.345752 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20092416197218269, 'lr': 0.0047954688515489735, 'weight_decay': 0.005369326006888547, 'batch_size': 128} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 12:00:52,948] Trial 84 pruned. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.348958 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.16248448474713734, 'lr': 0.00562578861307767, 'weight_decay': 0.007267009986342066, 'batch_size': 128} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 12:01:16,311] Trial 85 pruned. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.332677 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2146430825350196, 'lr': 0.006471457422795512, 'weight_decay': 0.009543411671566011, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 12:01:27,019] Trial 86 pruned. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.341772 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.19792032858341166, 'lr': 0.00252938785707992, 'weight_decay': 0.004001573498499421, 'batch_size': 128} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 12:01:41,719] Trial 87 pruned. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.354344 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.20593001842542305, 'lr': 0.004210621317758699, 'weight_decay': 0.0028008873466056714, 'batch_size': 64} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.3215416666666666, 1: 1.3215416666666666, 2: 0.6726686602617123} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.3243333333333334, 1: 1.3243333333333334, 2: 0.6712282480148674} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15784}) -[I 2025-12-25 12:05:05,367] Trial 88 finished with value: 0.46119960988324543 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.17105717985983282, 'lr': 0.007226644578533335, 'weight_decay': 0.007070930382314022, 'batch_size': 32}. Best is trial 5 with value: 0.46415327690903346. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.461200 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.17105717985983282, 'lr': 0.007226644578533335, 'weight_decay': 0.007070930382314022, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 12:05:28,187] Trial 89 pruned. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.330195 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.22050772997154244, 'lr': 0.00852303376220635, 'weight_decay': 0.007158189696259026, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 12:05:55,740] Trial 90 pruned. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.312576 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.14973733932025876, 'lr': 0.009855836603599998, 'weight_decay': 0.005589509162587524, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 12:06:16,570] Trial 91 pruned. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.339635 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.1673948542392079, 'lr': 0.0072624705065743155, 'weight_decay': 0.01182054162556331, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 12:06:36,793] Trial 92 pruned. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.343313 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.188002506013144, 'lr': 0.004975098178220747, 'weight_decay': 0.019870892589361668, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.3215416666666666, 1: 1.3215416666666666, 2: 0.6726686602617123} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.3243333333333334, 1: 1.3243333333333334, 2: 0.6712282480148674} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15784}) -[I 2025-12-25 12:10:08,003] Trial 93 finished with value: 0.4603462838521056 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.17960496871610754, 'lr': 0.0065183527010523, 'weight_decay': 0.008796525765394041, 'batch_size': 32}. Best is trial 5 with value: 0.46415327690903346. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.460346 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.17960496871610754, 'lr': 0.0065183527010523, 'weight_decay': 0.008796525765394041, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.3215416666666666, 1: 1.3215416666666666, 2: 0.6726686602617123} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.3243333333333334, 1: 1.3243333333333334, 2: 0.6712282480148674} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15784}) -[I 2025-12-25 12:12:59,032] Trial 94 finished with value: 0.45546321227986236 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.17239987866417447, 'lr': 0.003443645285752852, 'weight_decay': 0.0042998443856354564, 'batch_size': 32}. Best is trial 5 with value: 0.46415327690903346. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.455463 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.17239987866417447, 'lr': 0.003443645285752852, 'weight_decay': 0.0042998443856354564, 'batch_size': 32} - Best Value (CSI): 0.464153 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1930496093640372, 'lr': 0.0061014661404076125, 'weight_decay': 0.004528050765843693, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.3215416666666666, 1: 1.3215416666666666, 2: 0.6726686602617123} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.3243333333333334, 1: 1.3243333333333334, 2: 0.6712282480148674} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15784}) -[I 2025-12-25 12:15:24,853] Trial 95 finished with value: 0.4669846754411795 and parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.17471030464369763, 'lr': 0.0034006630423833845, 'weight_decay': 0.008657423885357477, 'batch_size': 32}. Best is trial 95 with value: 0.4669846754411795. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.466985 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.17471030464369763, 'lr': 0.0034006630423833845, 'weight_decay': 0.008657423885357477, 'batch_size': 32} - Best Value (CSI): 0.466985 - Best Trial: 95 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.17471030464369763, 'lr': 0.0034006630423833845, 'weight_decay': 0.008657423885357477, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 12:15:46,040] Trial 96 pruned. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.323333 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.19461520314981415, 'lr': 0.007371849161676959, 'weight_decay': 0.00877978892157631, 'batch_size': 32} - Best Value (CSI): 0.466985 - Best Trial: 95 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.17471030464369763, 'lr': 0.0034006630423833845, 'weight_decay': 0.008657423885357477, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 12:16:25,693] Trial 97 pruned. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.359630 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.18049856378608434, 'lr': 0.004174085995783068, 'weight_decay': 0.006593902148589155, 'batch_size': 32} - Best Value (CSI): 0.466985 - Best Trial: 95 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.17471030464369763, 'lr': 0.0034006630423833845, 'weight_decay': 0.008657423885357477, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 12:16:46,807] Trial 98 pruned. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.332163 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.15881131999315357, 'lr': 0.006112260286283692, 'weight_decay': 0.010468592539733972, 'batch_size': 32} - Best Value (CSI): 0.466985 - Best Trial: 95 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.17471030464369763, 'lr': 0.0034006630423833845, 'weight_decay': 0.008657423885357477, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 12:17:17,944] Trial 99 pruned. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.357030 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.1788120081388533, 'lr': 0.0026368736089580763, 'weight_decay': 0.008502286246445091, 'batch_size': 32} - Best Value (CSI): 0.466985 - Best Trial: 95 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.17471030464369763, 'lr': 0.0034006630423833845, 'weight_decay': 0.008657423885357477, 'batch_size': 32} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.4670 -Best Hyperparameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.17471030464369763, 'lr': 0.0034006630423833845, 'weight_decay': 0.008657423885357477, 'batch_size': 32} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.4288 - - 최종 CSI: 0.3570 - - 최고 CSI: 0.4670 - - 최저 CSI: 0.2606 - - 평균 CSI: 0.3734 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/deepgbm_smote_daejeon_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 50, Best CSI: 0.3871 - Fold 1 학습 완료 (검증 CSI: 0.3871) -Fold 2 학습 중... - Early stopping at epoch 31, Best CSI: 0.4808 - Fold 2 학습 완료 (검증 CSI: 0.4808) -Fold 3 학습 중... - Early stopping at epoch 30, Best CSI: 0.4924 - Fold 3 학습 완료 (검증 CSI: 0.4924) - -모든 모델 저장 완료: ../save_model/deepgbm_optima/deepgbm_smote_daejeon.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/deepgbm_optima/scaler/deepgbm_smote_daejeon_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: ../save_model/deepgbm_optima/deepgbm_smote_daejeon.pkl - -✓ 완료: deepgbm_smote/deepgbm_smote_daejeon.py (소요 시간: 4870초) - ----------------------------------------- -실행 중: deepgbm_smote/deepgbm_smote_gwangju.py -시작 시간: 2025-12-25 12:20:47 ----------------------------------------- -[I 2025-12-25 12:20:49,071] A new study created in memory with name: no-name-ec26a4e4-e72b-46c9-ac48-3f15ac965752 - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 12:22:17,631] Trial 0 finished with value: 0.44218897323156653 and parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3030898844927862, 'lr': 0.001955058837564275, 'weight_decay': 0.007447648959980482, 'batch_size': 64}. Best is trial 0 with value: 0.44218897323156653. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.442189 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3030898844927862, 'lr': 0.001955058837564275, 'weight_decay': 0.007447648959980482, 'batch_size': 64} - Best Value (CSI): 0.442189 - Best Trial: 0 - Best Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3030898844927862, 'lr': 0.001955058837564275, 'weight_decay': 0.007447648959980482, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 12:26:11,534] Trial 1 finished with value: 0.43655507319270415 and parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.28072538881292963, 'lr': 0.00019506747991079865, 'weight_decay': 0.00019063955505826884, 'batch_size': 32}. Best is trial 0 with value: 0.44218897323156653. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.436555 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.28072538881292963, 'lr': 0.00019506747991079865, 'weight_decay': 0.00019063955505826884, 'batch_size': 32} - Best Value (CSI): 0.442189 - Best Trial: 0 - Best Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3030898844927862, 'lr': 0.001955058837564275, 'weight_decay': 0.007447648959980482, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 12:27:20,761] Trial 2 finished with value: 0.44575071722001636 and parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.31872263749219437, 'lr': 0.005765858986062639, 'weight_decay': 0.018240178593739387, 'batch_size': 128}. Best is trial 2 with value: 0.44575071722001636. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.445751 - Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.31872263749219437, 'lr': 0.005765858986062639, 'weight_decay': 0.018240178593739387, 'batch_size': 128} - Best Value (CSI): 0.445751 - Best Trial: 2 - Best Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.31872263749219437, 'lr': 0.005765858986062639, 'weight_decay': 0.018240178593739387, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 12:29:37,887] Trial 3 finished with value: 0.364202816387301 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.2599678020912778, 'lr': 1.2773225158265967e-05, 'weight_decay': 0.0182755801465914, 'batch_size': 128}. Best is trial 2 with value: 0.44575071722001636. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.364203 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.2599678020912778, 'lr': 1.2773225158265967e-05, 'weight_decay': 0.0182755801465914, 'batch_size': 128} - Best Value (CSI): 0.445751 - Best Trial: 2 - Best Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.31872263749219437, 'lr': 0.005765858986062639, 'weight_decay': 0.018240178593739387, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 12:30:40,835] Trial 4 finished with value: 0.45804386918458945 and parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64}. Best is trial 4 with value: 0.45804386918458945. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.458044 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:30:44,737] Trial 5 pruned. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.357026 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2824434571547936, 'lr': 0.00015670744978832889, 'weight_decay': 0.08038633816580291, 'batch_size': 256} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:31:25,625] Trial 6 pruned. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.397371 - Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.27571736806746655, 'lr': 0.0010484358638395426, 'weight_decay': 0.0014591343137277972, 'batch_size': 32} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:31:37,547] Trial 7 pruned. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.350637 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.1323548103129416, 'lr': 0.009863808126161649, 'weight_decay': 0.02961603019697385, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 12:32:17,711] Trial 8 finished with value: 0.44338262491522884 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.1466867870538984, 'lr': 0.001693818291573039, 'weight_decay': 0.039070272763145356, 'batch_size': 256}. Best is trial 4 with value: 0.45804386918458945. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.443383 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.1466867870538984, 'lr': 0.001693818291573039, 'weight_decay': 0.039070272763145356, 'batch_size': 256} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:32:42,329] Trial 9 pruned. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.379451 - Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.25868285339204555, 'lr': 0.000928154608033677, 'weight_decay': 0.02948261057108364, 'batch_size': 32} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:32:52,027] Trial 10 pruned. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.380863 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.397876564892657, 'lr': 0.00012189586374027731, 'weight_decay': 0.0016572999032519328, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:33:05,029] Trial 11 pruned. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.402340 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.18877635217160305, 'lr': 0.009420850370487378, 'weight_decay': 0.004689016033794637, 'batch_size': 128} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:33:11,948] Trial 12 pruned. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.361607 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.19197043210099302, 'lr': 0.0033567629580377374, 'weight_decay': 0.0006487956948535049, 'batch_size': 128} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:33:17,980] Trial 13 pruned. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.390335 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.10232034266447343, 'lr': 0.0004991189116664977, 'weight_decay': 0.007215354339295886, 'batch_size': 128} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 12:35:12,234] Trial 14 finished with value: 0.4448563605723827 and parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.3212320171864835, 'lr': 0.0004158136526403668, 'weight_decay': 0.01261756477739757, 'batch_size': 64}. Best is trial 4 with value: 0.45804386918458945. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.444856 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.3212320171864835, 'lr': 0.0004158136526403668, 'weight_decay': 0.01261756477739757, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:35:17,969] Trial 15 pruned. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.393626 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2157998865972745, 'lr': 0.003976186418327894, 'weight_decay': 0.002785121778424057, 'batch_size': 128} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:35:28,528] Trial 16 pruned. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.363636 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.33622072821687193, 'lr': 4.572717291142988e-05, 'weight_decay': 0.0005132750914645513, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 12:36:01,194] Trial 17 finished with value: 0.44405593432187024 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.21995920351595014, 'lr': 0.0005590895255450863, 'weight_decay': 0.0032059344595958264, 'batch_size': 256}. Best is trial 4 with value: 0.45804386918458945. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.444056 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.21995920351595014, 'lr': 0.0005590895255450863, 'weight_decay': 0.0032059344595958264, 'batch_size': 256} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:36:12,963] Trial 18 pruned. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.334542 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.23229299411420037, 'lr': 0.0037171675682189233, 'weight_decay': 0.01308022895298601, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:36:18,326] Trial 19 pruned. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.388278 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.34969917964574393, 'lr': 0.0003324217131663012, 'weight_decay': 0.09447790675681712, 'batch_size': 128} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:36:30,639] Trial 20 pruned. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.370175 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.18574763414817527, 'lr': 8.28744620523519e-05, 'weight_decay': 0.00011524648126209329, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 12:37:54,077] Trial 21 finished with value: 0.44884203929252187 and parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.3165197572801948, 'lr': 0.0003137129275690668, 'weight_decay': 0.012893229372231772, 'batch_size': 64}. Best is trial 4 with value: 0.45804386918458945. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.448842 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.3165197572801948, 'lr': 0.0003137129275690668, 'weight_decay': 0.012893229372231772, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 12:39:09,407] Trial 22 finished with value: 0.44993767614289487 and parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.36135229303584626, 'lr': 0.0006716038989574651, 'weight_decay': 0.007626557531969339, 'batch_size': 64}. Best is trial 4 with value: 0.45804386918458945. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.449938 - Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.36135229303584626, 'lr': 0.0006716038989574651, 'weight_decay': 0.007626557531969339, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:39:21,055] Trial 23 pruned. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.382883 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.3668349517722456, 'lr': 0.0002532158426220643, 'weight_decay': 0.005138341316519868, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 12:41:04,196] Trial 24 finished with value: 0.44762756332419773 and parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.3613222573739081, 'lr': 0.000742476614635606, 'weight_decay': 0.008776835146842056, 'batch_size': 64}. Best is trial 4 with value: 0.45804386918458945. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.447628 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.3613222573739081, 'lr': 0.000742476614635606, 'weight_decay': 0.008776835146842056, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:41:26,813] Trial 25 pruned. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.401361 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3820463488273737, 'lr': 0.0002979274348337873, 'weight_decay': 0.0035471358368307383, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 12:42:34,025] Trial 26 finished with value: 0.4478794825014267 and parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3320569099601034, 'lr': 0.0006549553175406609, 'weight_decay': 0.0019449875979163313, 'batch_size': 64}. Best is trial 4 with value: 0.45804386918458945. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.447879 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3320569099601034, 'lr': 0.0006549553175406609, 'weight_decay': 0.0019449875979163313, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 12:43:45,525] Trial 27 finished with value: 0.44074694078978016 and parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2984721699901297, 'lr': 0.0014463125185893945, 'weight_decay': 0.006484942864968747, 'batch_size': 64}. Best is trial 4 with value: 0.45804386918458945. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.440747 - Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2984721699901297, 'lr': 0.0014463125185893945, 'weight_decay': 0.006484942864968747, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:44:07,114] Trial 28 pruned. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.382189 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.35184872866342254, 'lr': 0.0003409568220534784, 'weight_decay': 0.011757530065296522, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:44:29,001] Trial 29 pruned. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.381853 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.31356906706092436, 'lr': 0.0013612452517498593, 'weight_decay': 0.008558702111249799, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 12:45:29,588] Trial 30 finished with value: 0.4535129106138909 and parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.29700362350170323, 'lr': 0.0007363919989189423, 'weight_decay': 0.004711887406818941, 'batch_size': 64}. Best is trial 4 with value: 0.45804386918458945. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.453513 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.29700362350170323, 'lr': 0.0007363919989189423, 'weight_decay': 0.004711887406818941, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 12:46:36,301] Trial 31 finished with value: 0.4529614322785312 and parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.30710707937759785, 'lr': 0.0008021223027181391, 'weight_decay': 0.005094542798401313, 'batch_size': 64}. Best is trial 4 with value: 0.45804386918458945. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.452961 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.30710707937759785, 'lr': 0.0008021223027181391, 'weight_decay': 0.005094542798401313, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:46:52,806] Trial 32 pruned. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.387931 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.2938728066629516, 'lr': 0.0008939917564680358, 'weight_decay': 0.004472859985448667, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:47:08,987] Trial 33 pruned. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.368829 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2897814922671426, 'lr': 0.0020872558870075764, 'weight_decay': 0.0027463609432431153, 'batch_size': 32} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 12:48:04,700] Trial 34 finished with value: 0.44645788505724493 and parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.26815753306866824, 'lr': 0.0005098439495092957, 'weight_decay': 0.0011716491688531176, 'batch_size': 64}. Best is trial 4 with value: 0.45804386918458945. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.446458 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.26815753306866824, 'lr': 0.0005098439495092957, 'weight_decay': 0.0011716491688531176, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:48:08,729] Trial 35 pruned. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.391869 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.30396070762963723, 'lr': 0.0007052445990521698, 'weight_decay': 0.00509409530027027, 'batch_size': 256} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:48:17,256] Trial 36 pruned. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.384550 - Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.25213140590038885, 'lr': 0.00020598237345580123, 'weight_decay': 0.002319356828956063, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:48:49,524] Trial 37 pruned. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.377131 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.2835469248431385, 'lr': 0.0010805932045774413, 'weight_decay': 0.0031362691458226145, 'batch_size': 32} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:48:58,119] Trial 38 pruned. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.380389 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2682535329198042, 'lr': 0.0023341164646031465, 'weight_decay': 0.0011412438050227664, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:49:01,851] Trial 39 pruned. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.369600 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3297146681604942, 'lr': 0.0011952712590815805, 'weight_decay': 0.006226098219278781, 'batch_size': 256} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 12:50:17,284] Trial 40 finished with value: 0.44742080457167804 and parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.27827984694928637, 'lr': 0.0004998661263842745, 'weight_decay': 0.008975335493183818, 'batch_size': 64}. Best is trial 4 with value: 0.45804386918458945. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.447421 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.27827984694928637, 'lr': 0.0004998661263842745, 'weight_decay': 0.008975335493183818, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 12:51:34,483] Trial 41 pruned. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.440278 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.3092793619797802, 'lr': 0.00035532563501533754, 'weight_decay': 0.015498264845155546, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:51:51,605] Trial 42 pruned. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.393657 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.30361986077978304, 'lr': 0.0006861817478236086, 'weight_decay': 0.022203276784917035, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:52:04,016] Trial 43 pruned. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.371292 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.31984884980701733, 'lr': 0.00021710282120668617, 'weight_decay': 0.0038272910096189758, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:52:20,427] Trial 44 pruned. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.397143 - Parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.34184828000455625, 'lr': 0.0009370546192129732, 'weight_decay': 0.02008250148924776, 'batch_size': 32} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:52:39,326] Trial 45 pruned. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.394291 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.32413081234112273, 'lr': 0.00040949542706099405, 'weight_decay': 0.0069924847530983825, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:52:50,015] Trial 46 pruned. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.392483 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.2858855772968885, 'lr': 0.00013979590316330156, 'weight_decay': 0.010063637242493383, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:52:58,662] Trial 47 pruned. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.394858 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3375144664343513, 'lr': 0.0016859769065375196, 'weight_decay': 0.05245867429439613, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:53:07,219] Trial 48 pruned. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.401987 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.31408638115981524, 'lr': 0.0002566479910049154, 'weight_decay': 0.01454334700945019, 'batch_size': 256} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) -[I 2025-12-25 12:53:50,987] Trial 49 pruned. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.436782 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.26842232578815695, 'lr': 0.0004424002785522765, 'weight_decay': 0.006060002915360702, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:53:56,996] Trial 50 pruned. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.384276 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.24876317372435752, 'lr': 0.0008412416602305427, 'weight_decay': 0.003945062130563805, 'batch_size': 128} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:54:08,816] Trial 51 pruned. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.394810 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.32962022265060825, 'lr': 0.0006115928538703145, 'weight_decay': 0.001982207954512991, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 12:55:23,206] Trial 52 finished with value: 0.4468819910822286 and parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3467177526430348, 'lr': 0.0006123189722460588, 'weight_decay': 0.0016421838356256698, 'batch_size': 64}. Best is trial 4 with value: 0.45804386918458945. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.446882 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3467177526430348, 'lr': 0.0006123189722460588, 'weight_decay': 0.0016421838356256698, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 12:56:29,865] Trial 53 finished with value: 0.4452100573976905 and parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.33245343440855685, 'lr': 0.001154534910680273, 'weight_decay': 0.0022861359729042454, 'batch_size': 64}. Best is trial 4 with value: 0.45804386918458945. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.445210 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.33245343440855685, 'lr': 0.001154534910680273, 'weight_decay': 0.0022861359729042454, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:56:42,353] Trial 54 pruned. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.393458 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.29856790084179835, 'lr': 0.00042272631197288644, 'weight_decay': 0.01120232524453897, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:56:54,979] Trial 55 pruned. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.368682 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.35916871420238616, 'lr': 0.0007724142389849759, 'weight_decay': 0.004242090504899397, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:57:35,184] Trial 56 pruned. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.378490 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.3175312631472569, 'lr': 0.0005951803646420242, 'weight_decay': 0.005469728922735565, 'batch_size': 32} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:57:57,398] Trial 57 pruned. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.409002 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.3662254522846362, 'lr': 0.00025802019513211427, 'weight_decay': 0.008128287239617473, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:58:17,308] Trial 58 pruned. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.400387 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.37608582436963994, 'lr': 0.000364920401451748, 'weight_decay': 0.002844443368716279, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:58:27,761] Trial 59 pruned. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.407202 - Parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3521475087396897, 'lr': 0.00017612218264484892, 'weight_decay': 0.010671700300238155, 'batch_size': 128} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:58:51,118] Trial 60 pruned. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.385565 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.296093316157962, 'lr': 0.0010175659101703122, 'weight_decay': 0.007215360960390544, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:59:14,733] Trial 61 pruned. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.387755 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.33873169120694124, 'lr': 0.0007639371978429725, 'weight_decay': 0.005179110190075277, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 12:59:37,858] Trial 62 pruned. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.409266 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.32449997476713527, 'lr': 0.0005888623668986277, 'weight_decay': 0.00890726065273608, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 13:00:01,409] Trial 63 pruned. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.394167 - Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.3434587439063985, 'lr': 0.00045936188096764615, 'weight_decay': 0.003847531025210179, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 13:00:23,285] Trial 64 pruned. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.405697 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.3931561224174617, 'lr': 0.00030238344699819793, 'weight_decay': 0.01640944067131828, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 13:01:43,353] Trial 65 finished with value: 0.44631979818124196 and parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.35934992882251976, 'lr': 0.0007648642749050024, 'weight_decay': 0.012692251882808972, 'batch_size': 64}. Best is trial 4 with value: 0.45804386918458945. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.446320 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.35934992882251976, 'lr': 0.0007648642749050024, 'weight_decay': 0.012692251882808972, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 13:01:47,901] Trial 66 pruned. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.392887 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.3131320827461861, 'lr': 0.0014304844779285753, 'weight_decay': 0.007497280684585532, 'batch_size': 256} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 13:02:03,747] Trial 67 pruned. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.401835 - Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.375346075393719, 'lr': 0.0005156838619160703, 'weight_decay': 0.004919512146674691, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) -[I 2025-12-25 13:02:50,895] Trial 68 pruned. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.455708 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3094610643909057, 'lr': 0.0009269062257519986, 'weight_decay': 0.0032885658001533726, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 13:03:07,239] Trial 69 pruned. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.388889 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3333631414503363, 'lr': 0.0012236962794381554, 'weight_decay': 0.0011728390524270332, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 13:03:50,638] Trial 70 pruned. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.404361 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.3543026416498448, 'lr': 0.0006839639600248091, 'weight_decay': 0.006108864951673952, 'batch_size': 32} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 13:04:08,691] Trial 71 pruned. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.395615 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.2924271957310219, 'lr': 0.0004888502678903594, 'weight_decay': 0.008791052009003831, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 13:04:26,848] Trial 72 pruned. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.404050 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.281958176792086, 'lr': 0.00033621501305853185, 'weight_decay': 0.009426090166760352, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 13:04:42,934] Trial 73 pruned. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.401810 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.14824207637207454, 'lr': 0.0005385393184223331, 'weight_decay': 0.013426865328246934, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 13:05:58,748] Trial 74 finished with value: 0.453204577546142 and parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.2757017961350162, 'lr': 0.0008696408873587868, 'weight_decay': 0.006905596007502906, 'batch_size': 64}. Best is trial 4 with value: 0.45804386918458945. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.453205 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.2757017961350162, 'lr': 0.0008696408873587868, 'weight_decay': 0.006905596007502906, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 13:06:15,512] Trial 75 pruned. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.404255 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.30262218003171565, 'lr': 0.0007856305419497532, 'weight_decay': 0.0045416130024549875, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 13:06:25,655] Trial 76 pruned. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.403493 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.32160793120272935, 'lr': 0.0010957419821704239, 'weight_decay': 0.005867393297833387, 'batch_size': 128} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) -[I 2025-12-25 13:06:59,653] Trial 77 pruned. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.447049 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.2873932704649612, 'lr': 0.0009163973357109387, 'weight_decay': 0.00692941390297169, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 13:08:04,080] Trial 78 finished with value: 0.451396736975014 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.2774312063550167, 'lr': 0.0017172531167077474, 'weight_decay': 0.011404894937525997, 'batch_size': 64}. Best is trial 4 with value: 0.45804386918458945. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.451397 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.2774312063550167, 'lr': 0.0017172531167077474, 'weight_decay': 0.011404894937525997, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 13:08:08,302] Trial 79 pruned. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.372093 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.2754335957144859, 'lr': 0.0024807060044943663, 'weight_decay': 0.01785623431781284, 'batch_size': 256} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 13:08:28,257] Trial 80 pruned. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.379243 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3031890975608758, 'lr': 0.0018715260456711623, 'weight_decay': 0.010302398930144377, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 13:08:44,325] Trial 81 pruned. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.395122 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2900360478017097, 'lr': 0.0016493047763866445, 'weight_decay': 0.012285335649839772, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 13:09:00,441] Trial 82 pruned. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.403151 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2747262233393889, 'lr': 0.0014109641583037195, 'weight_decay': 0.007933666453623348, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 13:10:29,717] Trial 83 finished with value: 0.4452273981923434 and parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.26332940221823825, 'lr': 0.0006639517563753639, 'weight_decay': 0.025302135803708964, 'batch_size': 64}. Best is trial 4 with value: 0.45804386918458945. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.445227 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.26332940221823825, 'lr': 0.0006639517563753639, 'weight_decay': 0.025302135803708964, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 13:10:46,025] Trial 84 pruned. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.404630 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.30730922645665276, 'lr': 0.0003965161940822661, 'weight_decay': 0.016227474548902856, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 13:11:09,875] Trial 85 pruned. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.383495 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.32621579285498103, 'lr': 0.0010389803503562834, 'weight_decay': 0.0035719874358489815, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 13:11:27,905] Trial 86 pruned. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.395973 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.34372848358798946, 'lr': 0.0008985426267477046, 'weight_decay': 0.004420770615157944, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 13:12:34,143] Trial 87 pruned. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.446524 - Parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.31625093636559537, 'lr': 0.0012521978854270583, 'weight_decay': 0.01093760192270259, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 13:12:50,530] Trial 88 pruned. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.394340 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.2512575941687539, 'lr': 0.0005575411103507515, 'weight_decay': 0.006618260740670107, 'batch_size': 32} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 13:14:02,844] Trial 89 finished with value: 0.44499309911441637 and parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.29472089970257903, 'lr': 0.0006876009521136475, 'weight_decay': 0.0026352446617291967, 'batch_size': 64}. Best is trial 4 with value: 0.45804386918458945. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.444993 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.29472089970257903, 'lr': 0.0006876009521136475, 'weight_decay': 0.0026352446617291967, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 13:14:09,567] Trial 90 pruned. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.384342 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.3349255354326314, 'lr': 0.0004288089190368402, 'weight_decay': 0.008137769465740834, 'batch_size': 128} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 13:15:17,450] Trial 91 finished with value: 0.4424558565091475 and parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.2821070050399821, 'lr': 0.00048305461591210264, 'weight_decay': 0.014252289600816268, 'batch_size': 64}. Best is trial 4 with value: 0.45804386918458945. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.442456 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.2821070050399821, 'lr': 0.00048305461591210264, 'weight_decay': 0.014252289600816268, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 13:15:26,093] Trial 92 pruned. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.394195 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.2566664560922411, 'lr': 0.000373875832199835, 'weight_decay': 0.005600118215416452, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 13:16:33,474] Trial 93 finished with value: 0.44543734556448883 and parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.27343220508292815, 'lr': 0.0006313921286729982, 'weight_decay': 0.008746902450829092, 'batch_size': 64}. Best is trial 4 with value: 0.45804386918458945. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.445437 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.27343220508292815, 'lr': 0.0006313921286729982, 'weight_decay': 0.008746902450829092, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 13:17:32,626] Trial 94 finished with value: 0.45367666201068 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.27964191118005544, 'lr': 0.000799688009872337, 'weight_decay': 0.009892487939565426, 'batch_size': 64}. Best is trial 4 with value: 0.45804386918458945. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.453677 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.27964191118005544, 'lr': 0.000799688009872337, 'weight_decay': 0.009892487939565426, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) -[I 2025-12-25 13:18:05,456] Trial 95 pruned. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.448751 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.2871907389180207, 'lr': 0.0007936422477586058, 'weight_decay': 0.010653754247890024, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 13:18:23,680] Trial 96 pruned. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.394444 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.30780551871181067, 'lr': 0.0009974876317695378, 'weight_decay': 0.019722085272954097, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) -[I 2025-12-25 13:18:52,851] Trial 97 pruned. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.443500 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.3013910134250278, 'lr': 0.0008624441911632399, 'weight_decay': 0.005074384371044865, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) -[I 2025-12-25 13:19:38,756] Trial 98 pruned. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.446696 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.24167261815124635, 'lr': 0.0005652645884763109, 'weight_decay': 0.006730693309143569, 'batch_size': 64} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 13:19:46,642] Trial 99 pruned. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.390639 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.2643060097575511, 'lr': 0.0011347345893885192, 'weight_decay': 0.012336978488023544, 'batch_size': 256} - Best Value (CSI): 0.458044 - Best Trial: 4 - Best Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.4580 -Best Hyperparameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1698480826585593, 'lr': 0.0003762961039889282, 'weight_decay': 0.0014343061148430866, 'batch_size': 64} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.4422 - - 최종 CSI: 0.3906 - - 최고 CSI: 0.4580 - - 최저 CSI: 0.3345 - - 평균 CSI: 0.4079 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/deepgbm_smote_gwangju_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 28, Best CSI: 0.4120 - Fold 1 학습 완료 (검증 CSI: 0.4120) -Fold 2 학습 중... - Early stopping at epoch 23, Best CSI: 0.4670 - Fold 2 학습 완료 (검증 CSI: 0.4670) -Fold 3 학습 중... - Early stopping at epoch 32, Best CSI: 0.4646 - Fold 3 학습 완료 (검증 CSI: 0.4646) - -모든 모델 저장 완료: ../save_model/deepgbm_optima/deepgbm_smote_gwangju.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/deepgbm_optima/scaler/deepgbm_smote_gwangju_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: ../save_model/deepgbm_optima/deepgbm_smote_gwangju.pkl - -✓ 완료: deepgbm_smote/deepgbm_smote_gwangju.py (소요 시간: 3605초) - ----------------------------------------- -실행 중: deepgbm_smote/deepgbm_smote_incheon.py -시작 시간: 2025-12-25 13:20:52 ----------------------------------------- -[I 2025-12-25 13:20:53,409] A new study created in memory with name: no-name-5345f514-53a7-4c32-89be-386daec718ee - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 13:21:38,314] Trial 0 finished with value: 0.5288806849603345 and parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.13019815005255592, 'lr': 0.0017111913942698992, 'weight_decay': 0.03207567445544088, 'batch_size': 128}. Best is trial 0 with value: 0.5288806849603345. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.528881 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.13019815005255592, 'lr': 0.0017111913942698992, 'weight_decay': 0.03207567445544088, 'batch_size': 128} - Best Value (CSI): 0.528881 - Best Trial: 0 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.13019815005255592, 'lr': 0.0017111913942698992, 'weight_decay': 0.03207567445544088, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 13:25:00,626] Trial 1 finished with value: 0.5049464584116119 and parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.13496565457563842, 'lr': 1.4291888571586994e-05, 'weight_decay': 0.0014397268969090545, 'batch_size': 32}. Best is trial 0 with value: 0.5288806849603345. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.504946 - Parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.13496565457563842, 'lr': 1.4291888571586994e-05, 'weight_decay': 0.0014397268969090545, 'batch_size': 32} - Best Value (CSI): 0.528881 - Best Trial: 0 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.13019815005255592, 'lr': 0.0017111913942698992, 'weight_decay': 0.03207567445544088, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 13:27:37,216] Trial 2 finished with value: 0.4906676060590651 and parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.271471092682458, 'lr': 1.086354640232579e-05, 'weight_decay': 0.0015198639876740406, 'batch_size': 64}. Best is trial 0 with value: 0.5288806849603345. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.490668 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.271471092682458, 'lr': 1.086354640232579e-05, 'weight_decay': 0.0015198639876740406, 'batch_size': 64} - Best Value (CSI): 0.528881 - Best Trial: 0 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.13019815005255592, 'lr': 0.0017111913942698992, 'weight_decay': 0.03207567445544088, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 13:28:46,189] Trial 3 finished with value: 0.5060383859826026 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1349734305933428, 'lr': 8.682885475954621e-05, 'weight_decay': 0.04149528028889058, 'batch_size': 128}. Best is trial 0 with value: 0.5288806849603345. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.506038 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1349734305933428, 'lr': 8.682885475954621e-05, 'weight_decay': 0.04149528028889058, 'batch_size': 128} - Best Value (CSI): 0.528881 - Best Trial: 0 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.13019815005255592, 'lr': 0.0017111913942698992, 'weight_decay': 0.03207567445544088, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 13:30:31,377] Trial 4 finished with value: 0.4917046580420097 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.38285211488438053, 'lr': 2.465355833449838e-05, 'weight_decay': 0.008143695976343924, 'batch_size': 256}. Best is trial 0 with value: 0.5288806849603345. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.491705 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.38285211488438053, 'lr': 2.465355833449838e-05, 'weight_decay': 0.008143695976343924, 'batch_size': 256} - Best Value (CSI): 0.528881 - Best Trial: 0 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.13019815005255592, 'lr': 0.0017111913942698992, 'weight_decay': 0.03207567445544088, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 13:31:05,904] Trial 5 finished with value: 0.5248410667586786 and parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.10560193269379775, 'lr': 0.00016352788876529878, 'weight_decay': 0.05256224532351117, 'batch_size': 256}. Best is trial 0 with value: 0.5288806849603345. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.524841 - Parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.10560193269379775, 'lr': 0.00016352788876529878, 'weight_decay': 0.05256224532351117, 'batch_size': 256} - Best Value (CSI): 0.528881 - Best Trial: 0 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.13019815005255592, 'lr': 0.0017111913942698992, 'weight_decay': 0.03207567445544088, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 13:32:06,776] Trial 6 finished with value: 0.5209065799149006 and parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.11628478098203561, 'lr': 0.0001492848265557852, 'weight_decay': 0.0001685578955279736, 'batch_size': 128}. Best is trial 0 with value: 0.5288806849603345. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.520907 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.11628478098203561, 'lr': 0.0001492848265557852, 'weight_decay': 0.0001685578955279736, 'batch_size': 128} - Best Value (CSI): 0.528881 - Best Trial: 0 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.13019815005255592, 'lr': 0.0017111913942698992, 'weight_decay': 0.03207567445544088, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 13:32:17,118] Trial 7 pruned. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.405635 - Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.23680933861323059, 'lr': 1.576029032544915e-05, 'weight_decay': 0.0007211798655465211, 'batch_size': 64} - Best Value (CSI): 0.528881 - Best Trial: 0 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.13019815005255592, 'lr': 0.0017111913942698992, 'weight_decay': 0.03207567445544088, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 13:32:53,149] Trial 8 finished with value: 0.5483885776901485 and parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.392769565148829, 'lr': 0.0014778518768326881, 'weight_decay': 0.05615490031554831, 'batch_size': 256}. Best is trial 8 with value: 0.5483885776901485. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.548389 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.392769565148829, 'lr': 0.0014778518768326881, 'weight_decay': 0.05615490031554831, 'batch_size': 256} - Best Value (CSI): 0.548389 - Best Trial: 8 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.392769565148829, 'lr': 0.0014778518768326881, 'weight_decay': 0.05615490031554831, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 13:33:18,374] Trial 9 pruned. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.495383 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.14442526096231215, 'lr': 4.385886370968864e-05, 'weight_decay': 0.0403428287809734, 'batch_size': 128} - Best Value (CSI): 0.548389 - Best Trial: 8 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.392769565148829, 'lr': 0.0014778518768326881, 'weight_decay': 0.05615490031554831, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 13:33:55,959] Trial 10 finished with value: 0.5530162000533873 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.3896760245898689, 'lr': 0.008394441820755244, 'weight_decay': 0.006973187213110583, 'batch_size': 256}. Best is trial 10 with value: 0.5530162000533873. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.553016 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.3896760245898689, 'lr': 0.008394441820755244, 'weight_decay': 0.006973187213110583, 'batch_size': 256} - Best Value (CSI): 0.553016 - Best Trial: 10 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.3896760245898689, 'lr': 0.008394441820755244, 'weight_decay': 0.006973187213110583, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 13:34:27,848] Trial 11 finished with value: 0.5525590785026059 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.39959974330443243, 'lr': 0.0095096065717139, 'weight_decay': 0.01001916699114309, 'batch_size': 256}. Best is trial 10 with value: 0.5530162000533873. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.552559 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.39959974330443243, 'lr': 0.0095096065717139, 'weight_decay': 0.01001916699114309, 'batch_size': 256} - Best Value (CSI): 0.553016 - Best Trial: 10 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.3896760245898689, 'lr': 0.008394441820755244, 'weight_decay': 0.006973187213110583, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 13:34:58,272] Trial 12 finished with value: 0.54352511804275 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.35773761444124325, 'lr': 0.008686495473035837, 'weight_decay': 0.007759768653904916, 'batch_size': 256}. Best is trial 10 with value: 0.5530162000533873. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.543525 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.35773761444124325, 'lr': 0.008686495473035837, 'weight_decay': 0.007759768653904916, 'batch_size': 256} - Best Value (CSI): 0.553016 - Best Trial: 10 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.3896760245898689, 'lr': 0.008394441820755244, 'weight_decay': 0.006973187213110583, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 13:35:32,424] Trial 13 finished with value: 0.5525550793206873 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.3380484909232751, 'lr': 0.009818054972668985, 'weight_decay': 0.007395520844885814, 'batch_size': 256}. Best is trial 10 with value: 0.5530162000533873. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.552555 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.3380484909232751, 'lr': 0.009818054972668985, 'weight_decay': 0.007395520844885814, 'batch_size': 256} - Best Value (CSI): 0.553016 - Best Trial: 10 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.3896760245898689, 'lr': 0.008394441820755244, 'weight_decay': 0.006973187213110583, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 13:37:52,146] Trial 14 finished with value: 0.5480862609987603 and parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.3270364344661163, 'lr': 0.0033711105829348, 'weight_decay': 0.01786704315123361, 'batch_size': 32}. Best is trial 10 with value: 0.5530162000533873. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.548086 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.3270364344661163, 'lr': 0.0033711105829348, 'weight_decay': 0.01786704315123361, 'batch_size': 32} - Best Value (CSI): 0.553016 - Best Trial: 10 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.3896760245898689, 'lr': 0.008394441820755244, 'weight_decay': 0.006973187213110583, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 13:38:02,255] Trial 15 pruned. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.512965 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.38604142581900763, 'lr': 0.000834151259394319, 'weight_decay': 0.003914260788420277, 'batch_size': 256} - Best Value (CSI): 0.553016 - Best Trial: 10 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.3896760245898689, 'lr': 0.008394441820755244, 'weight_decay': 0.006973187213110583, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 13:38:30,239] Trial 16 finished with value: 0.55220459385759 and parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3956480333479846, 'lr': 0.0042568769936931015, 'weight_decay': 0.01443341855849047, 'batch_size': 256}. Best is trial 10 with value: 0.5530162000533873. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.552205 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3956480333479846, 'lr': 0.0042568769936931015, 'weight_decay': 0.01443341855849047, 'batch_size': 256} - Best Value (CSI): 0.553016 - Best Trial: 10 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.3896760245898689, 'lr': 0.008394441820755244, 'weight_decay': 0.006973187213110583, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 13:38:35,235] Trial 17 pruned. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.489723 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.3126214816576463, 'lr': 0.0007335863099701944, 'weight_decay': 0.09598619992155015, 'batch_size': 256} - Best Value (CSI): 0.553016 - Best Trial: 10 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.3896760245898689, 'lr': 0.008394441820755244, 'weight_decay': 0.006973187213110583, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 13:40:05,878] Trial 18 finished with value: 0.5535288395204495 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.3581056250305848, 'lr': 0.004459240130445109, 'weight_decay': 0.003630474051287576, 'batch_size': 64}. Best is trial 18 with value: 0.5535288395204495. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.553529 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.3581056250305848, 'lr': 0.004459240130445109, 'weight_decay': 0.003630474051287576, 'batch_size': 64} - Best Value (CSI): 0.553529 - Best Trial: 18 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.3581056250305848, 'lr': 0.004459240130445109, 'weight_decay': 0.003630474051287576, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 13:41:17,487] Trial 19 finished with value: 0.5561378414721172 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3586534716330606, 'lr': 0.003900235486039173, 'weight_decay': 0.0041126507262302155, 'batch_size': 64}. Best is trial 19 with value: 0.5561378414721172. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.556138 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3586534716330606, 'lr': 0.003900235486039173, 'weight_decay': 0.0041126507262302155, 'batch_size': 64} - Best Value (CSI): 0.556138 - Best Trial: 19 - Best Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3586534716330606, 'lr': 0.003900235486039173, 'weight_decay': 0.0041126507262302155, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 13:42:25,591] Trial 20 finished with value: 0.5492234396625131 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.353252133334309, 'lr': 0.000470093150982225, 'weight_decay': 0.003256639970124781, 'batch_size': 64}. Best is trial 19 with value: 0.5561378414721172. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.549223 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.353252133334309, 'lr': 0.000470093150982225, 'weight_decay': 0.003256639970124781, 'batch_size': 64} - Best Value (CSI): 0.556138 - Best Trial: 19 - Best Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3586534716330606, 'lr': 0.003900235486039173, 'weight_decay': 0.0041126507262302155, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 13:43:32,259] Trial 21 finished with value: 0.5489011456122262 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3559476683850265, 'lr': 0.005146921783446939, 'weight_decay': 0.004623667516538521, 'batch_size': 64}. Best is trial 19 with value: 0.5561378414721172. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.548901 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3559476683850265, 'lr': 0.005146921783446939, 'weight_decay': 0.004623667516538521, 'batch_size': 64} - Best Value (CSI): 0.556138 - Best Trial: 19 - Best Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3586534716330606, 'lr': 0.003900235486039173, 'weight_decay': 0.0041126507262302155, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 13:44:47,537] Trial 22 finished with value: 0.5443467271299186 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.31087625586636114, 'lr': 0.0024903207721008003, 'weight_decay': 0.0019917835008676607, 'batch_size': 64}. Best is trial 19 with value: 0.5561378414721172. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.544347 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.31087625586636114, 'lr': 0.0024903207721008003, 'weight_decay': 0.0019917835008676607, 'batch_size': 64} - Best Value (CSI): 0.556138 - Best Trial: 19 - Best Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3586534716330606, 'lr': 0.003900235486039173, 'weight_decay': 0.0041126507262302155, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 13:46:01,793] Trial 23 pruned. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.518452 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.36688835706536216, 'lr': 0.0050609927006253184, 'weight_decay': 0.004937800788087662, 'batch_size': 64} - Best Value (CSI): 0.556138 - Best Trial: 19 - Best Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3586534716330606, 'lr': 0.003900235486039173, 'weight_decay': 0.0041126507262302155, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 13:47:06,033] Trial 24 finished with value: 0.552454520872199 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3685878921718711, 'lr': 0.0016919294608933506, 'weight_decay': 0.017899173230388032, 'batch_size': 64}. Best is trial 19 with value: 0.5561378414721172. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.552455 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3685878921718711, 'lr': 0.0016919294608933506, 'weight_decay': 0.017899173230388032, 'batch_size': 64} - Best Value (CSI): 0.556138 - Best Trial: 19 - Best Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3586534716330606, 'lr': 0.003900235486039173, 'weight_decay': 0.0041126507262302155, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 13:47:55,368] Trial 25 finished with value: 0.5479248115878822 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.29511814307663975, 'lr': 0.002732041234363212, 'weight_decay': 0.0023392342126760837, 'batch_size': 64}. Best is trial 19 with value: 0.5561378414721172. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.547925 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.29511814307663975, 'lr': 0.002732041234363212, 'weight_decay': 0.0023392342126760837, 'batch_size': 64} - Best Value (CSI): 0.556138 - Best Trial: 19 - Best Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3586534716330606, 'lr': 0.003900235486039173, 'weight_decay': 0.0041126507262302155, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 13:48:15,204] Trial 26 pruned. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.438745 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.335545460783242, 'lr': 0.00616823661802727, 'weight_decay': 0.0009533077125998719, 'batch_size': 32} - Best Value (CSI): 0.556138 - Best Trial: 19 - Best Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3586534716330606, 'lr': 0.003900235486039173, 'weight_decay': 0.0041126507262302155, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 13:48:46,064] Trial 27 pruned. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.516072 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.37367646371113195, 'lr': 0.0033687362562177395, 'weight_decay': 0.003179715254923748, 'batch_size': 64} - Best Value (CSI): 0.556138 - Best Trial: 19 - Best Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3586534716330606, 'lr': 0.003900235486039173, 'weight_decay': 0.0041126507262302155, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 13:48:56,959] Trial 28 pruned. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.456500 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3490824981284713, 'lr': 0.00585461397740787, 'weight_decay': 0.005385772391598644, 'batch_size': 64} - Best Value (CSI): 0.556138 - Best Trial: 19 - Best Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3586534716330606, 'lr': 0.003900235486039173, 'weight_decay': 0.0041126507262302155, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 13:51:10,895] Trial 29 finished with value: 0.5640599235240535 and parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32}. Best is trial 29 with value: 0.5640599235240535. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.564060 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 13:52:46,203] Trial 30 finished with value: 0.5478498546599913 and parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.32794093630662263, 'lr': 0.0020558171474186963, 'weight_decay': 0.017399550832494545, 'batch_size': 32}. Best is trial 29 with value: 0.5640599235240535. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.547850 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.32794093630662263, 'lr': 0.0020558171474186963, 'weight_decay': 0.017399550832494545, 'batch_size': 32} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 13:54:53,116] Trial 31 finished with value: 0.5522002837681764 and parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3732880637756076, 'lr': 0.0013491278163157271, 'weight_decay': 0.02496238119486242, 'batch_size': 32}. Best is trial 29 with value: 0.5640599235240535. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.552200 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3732880637756076, 'lr': 0.0013491278163157271, 'weight_decay': 0.02496238119486242, 'batch_size': 32} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 13:57:31,086] Trial 32 pruned. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.513465 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.39790592714453904, 'lr': 0.003488696479210172, 'weight_decay': 0.011861274346108935, 'batch_size': 32} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 13:57:53,838] Trial 33 pruned. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.419551 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.37959923756038877, 'lr': 0.006502954468002988, 'weight_decay': 0.006480308925305888, 'batch_size': 32} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 13:59:37,114] Trial 34 finished with value: 0.5528343930964836 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3529584858893925, 'lr': 0.0024676277938387742, 'weight_decay': 0.02652292541496655, 'batch_size': 64}. Best is trial 29 with value: 0.5640599235240535. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.552834 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3529584858893925, 'lr': 0.0024676277938387742, 'weight_decay': 0.02652292541496655, 'batch_size': 64} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 13:59:47,301] Trial 35 pruned. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.501031 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.36972502768561877, 'lr': 0.0039670702238082485, 'weight_decay': 0.010976358434624292, 'batch_size': 128} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 14:00:12,527] Trial 36 pruned. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.359069 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.38244724440876426, 'lr': 0.006902862951144316, 'weight_decay': 0.005937086278317264, 'batch_size': 32} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 14:01:48,909] Trial 37 finished with value: 0.5457052655937307 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.3428361178990439, 'lr': 0.0012289721900373563, 'weight_decay': 0.002686868828393289, 'batch_size': 64}. Best is trial 29 with value: 0.5640599235240535. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.545705 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.3428361178990439, 'lr': 0.0012289721900373563, 'weight_decay': 0.002686868828393289, 'batch_size': 64} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 14:01:59,275] Trial 38 pruned. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.499716 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3661573321752806, 'lr': 0.0019910838828712217, 'weight_decay': 0.009125766108972038, 'batch_size': 128} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) -[I 2025-12-25 14:03:35,694] Trial 39 pruned. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.550350 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3999742112094783, 'lr': 0.0048947479413759334, 'weight_decay': 0.0015183841006861105, 'batch_size': 32} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) -[I 2025-12-25 14:04:30,577] Trial 40 pruned. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.564860 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.2680399457495293, 'lr': 0.002888010607345406, 'weight_decay': 0.004441982581824427, 'batch_size': 64} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 14:05:53,241] Trial 41 finished with value: 0.5454088844771653 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.35247532313456237, 'lr': 0.00217226541792598, 'weight_decay': 0.02985937516126587, 'batch_size': 64}. Best is trial 29 with value: 0.5640599235240535. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.545409 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.35247532313456237, 'lr': 0.00217226541792598, 'weight_decay': 0.02985937516126587, 'batch_size': 64} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 14:06:17,862] Trial 42 pruned. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.532147 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3827140645995263, 'lr': 0.004047406851457327, 'weight_decay': 0.026087537072840717, 'batch_size': 64} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) -[I 2025-12-25 14:07:11,732] Trial 43 pruned. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.569887 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.3456976133552634, 'lr': 0.007912675132818445, 'weight_decay': 0.012851317097398141, 'batch_size': 64} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 14:07:37,509] Trial 44 pruned. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.546115 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3636027021253773, 'lr': 0.009832716160164017, 'weight_decay': 0.03973804437835329, 'batch_size': 64} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 14:08:06,566] Trial 45 finished with value: 0.5498447507355956 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.3868834636534955, 'lr': 0.002665761049139668, 'weight_decay': 0.008881044502256942, 'batch_size': 256}. Best is trial 29 with value: 0.5640599235240535. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.549845 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.3868834636534955, 'lr': 0.002665761049139668, 'weight_decay': 0.008881044502256942, 'batch_size': 256} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 14:08:54,978] Trial 46 finished with value: 0.5519662468290093 and parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.3308522318278813, 'lr': 0.007086353755203787, 'weight_decay': 0.024327623141549785, 'batch_size': 128}. Best is trial 29 with value: 0.5640599235240535. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.551966 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.3308522318278813, 'lr': 0.007086353755203787, 'weight_decay': 0.024327623141549785, 'batch_size': 128} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 14:08:59,765] Trial 47 pruned. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.514161 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.38318899277382856, 'lr': 0.0016815446652921617, 'weight_decay': 0.007412400101452919, 'batch_size': 256} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 14:09:54,404] Trial 48 finished with value: 0.544412972466544 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.35507122987621503, 'lr': 0.0011403902025806793, 'weight_decay': 0.00398886035832696, 'batch_size': 64}. Best is trial 29 with value: 0.5640599235240535. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.544413 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.35507122987621503, 'lr': 0.0011403902025806793, 'weight_decay': 0.00398886035832696, 'batch_size': 64} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 14:10:21,991] Trial 49 pruned. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.515909 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.34327637298727015, 'lr': 0.004466272380864732, 'weight_decay': 0.04977494450435723, 'batch_size': 256} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 14:11:15,885] Trial 50 finished with value: 0.5519336276168777 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.3169443450654049, 'lr': 0.0029899387277342207, 'weight_decay': 0.016145708176385692, 'batch_size': 64}. Best is trial 29 with value: 0.5640599235240535. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.551934 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.3169443450654049, 'lr': 0.0029899387277342207, 'weight_decay': 0.016145708176385692, 'batch_size': 64} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 14:11:25,999] Trial 51 pruned. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.554251 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.39550994042982823, 'lr': 0.008035381634864645, 'weight_decay': 0.010719853687970016, 'batch_size': 256} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 14:11:58,212] Trial 52 finished with value: 0.5580988083995089 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.38886965934744144, 'lr': 0.00930129788993002, 'weight_decay': 0.006641191391996269, 'batch_size': 256}. Best is trial 29 with value: 0.5640599235240535. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.558099 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.38886965934744144, 'lr': 0.00930129788993002, 'weight_decay': 0.006641191391996269, 'batch_size': 256} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) -[I 2025-12-25 14:12:16,926] Trial 53 pruned. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.563059 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.36219567248026807, 'lr': 0.005105009118340125, 'weight_decay': 0.0063706645229347604, 'batch_size': 256} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 14:12:41,365] Trial 54 finished with value: 0.5500388933814969 and parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.37761657955649447, 'lr': 0.006461972739285352, 'weight_decay': 0.001866272678243917, 'batch_size': 256}. Best is trial 29 with value: 0.5640599235240535. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.550039 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.37761657955649447, 'lr': 0.006461972739285352, 'weight_decay': 0.001866272678243917, 'batch_size': 256} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) -[I 2025-12-25 14:12:57,608] Trial 55 pruned. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.564006 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3886341945037289, 'lr': 0.009828485802816663, 'weight_decay': 0.0036837821810642686, 'batch_size': 256} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 14:13:02,001] Trial 56 pruned. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.524721 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.36026911139579065, 'lr': 0.004205604832834483, 'weight_decay': 0.002547574025627072, 'batch_size': 256} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) -[I 2025-12-25 14:13:41,401] Trial 57 pruned. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.565347 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3762492856231148, 'lr': 0.002331599977200593, 'weight_decay': 0.020905972622629394, 'batch_size': 64} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 14:15:40,819] Trial 58 finished with value: 0.5524205749520328 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3382724584314224, 'lr': 0.005383393598097932, 'weight_decay': 0.00741297289454602, 'batch_size': 32}. Best is trial 29 with value: 0.5640599235240535. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.552421 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3382724584314224, 'lr': 0.005383393598097932, 'weight_decay': 0.00741297289454602, 'batch_size': 32} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 14:16:12,445] Trial 59 finished with value: 0.5571828225762477 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.38875942829059945, 'lr': 0.003515599290779117, 'weight_decay': 0.014727104464215258, 'batch_size': 128}. Best is trial 29 with value: 0.5640599235240535. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.557183 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.38875942829059945, 'lr': 0.003515599290779117, 'weight_decay': 0.014727104464215258, 'batch_size': 128} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 14:16:55,544] Trial 60 finished with value: 0.5556229300695238 and parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.39215001441199926, 'lr': 0.003533980615245225, 'weight_decay': 0.005246264861585461, 'batch_size': 128}. Best is trial 29 with value: 0.5640599235240535. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.555623 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.39215001441199926, 'lr': 0.003533980615245225, 'weight_decay': 0.005246264861585461, 'batch_size': 128} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 14:17:42,777] Trial 61 finished with value: 0.5500971828189395 and parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.39919320123923957, 'lr': 0.0032806641128551627, 'weight_decay': 0.005553899927124503, 'batch_size': 128}. Best is trial 29 with value: 0.5640599235240535. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.550097 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.39919320123923957, 'lr': 0.0032806641128551627, 'weight_decay': 0.005553899927124503, 'batch_size': 128} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 14:17:56,221] Trial 62 pruned. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.544126 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3903671965335468, 'lr': 0.008119165067412344, 'weight_decay': 0.014752823024071111, 'batch_size': 128} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 14:18:35,107] Trial 63 finished with value: 0.5506699399557876 and parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.37207690588797177, 'lr': 0.005708102116451483, 'weight_decay': 0.008958128873315282, 'batch_size': 128}. Best is trial 29 with value: 0.5640599235240535. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.550670 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.37207690588797177, 'lr': 0.005708102116451483, 'weight_decay': 0.008958128873315282, 'batch_size': 128} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 14:18:43,158] Trial 64 pruned. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.509508 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.38852339843328487, 'lr': 0.00356228170594514, 'weight_decay': 0.004373072694131, 'batch_size': 128} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 14:19:18,201] Trial 65 pruned. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.512605 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3753267740699764, 'lr': 0.007684446191623141, 'weight_decay': 0.0033234710610171763, 'batch_size': 128} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 14:19:23,939] Trial 66 pruned. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.509944 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3628747748390071, 'lr': 0.004525622084747493, 'weight_decay': 0.012823303513662105, 'batch_size': 128} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 14:19:30,441] Trial 67 pruned. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.505505 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3916318516689186, 'lr': 0.005898191678374707, 'weight_decay': 0.006462987343363901, 'batch_size': 128} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 14:20:05,263] Trial 68 finished with value: 0.5481964727831011 and parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.38289836771293767, 'lr': 0.003802368890787154, 'weight_decay': 0.005386581492503432, 'batch_size': 128}. Best is trial 29 with value: 0.5640599235240535. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.548196 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.38289836771293767, 'lr': 0.003802368890787154, 'weight_decay': 0.005386581492503432, 'batch_size': 128} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 14:22:10,653] Trial 69 finished with value: 0.5468490828361315 and parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3700830091667097, 'lr': 0.002015021881225428, 'weight_decay': 0.01002184684087424, 'batch_size': 32}. Best is trial 29 with value: 0.5640599235240535. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.546849 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3700830091667097, 'lr': 0.002015021881225428, 'weight_decay': 0.01002184684087424, 'batch_size': 32} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 14:22:15,419] Trial 70 pruned. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.492894 - Parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3492403724879569, 'lr': 0.0029595309414597562, 'weight_decay': 0.0028635370044332222, 'batch_size': 256} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 14:23:12,795] Trial 71 finished with value: 0.5501255721330461 and parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3617835944975803, 'lr': 0.0026179651186102938, 'weight_decay': 0.018324115030386556, 'batch_size': 64}. Best is trial 29 with value: 0.5640599235240535. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.550126 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3617835944975803, 'lr': 0.0026179651186102938, 'weight_decay': 0.018324115030386556, 'batch_size': 64} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 14:24:07,659] Trial 72 pruned. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.525995 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3562329868588043, 'lr': 0.0016458957656892061, 'weight_decay': 0.004405760466724258, 'batch_size': 64} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 14:24:13,612] Trial 73 pruned. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.506297 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3762135278919068, 'lr': 0.0045787447331704706, 'weight_decay': 0.00789835169592414, 'batch_size': 128} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 14:24:30,308] Trial 74 pruned. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.514983 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.38583816837406404, 'lr': 0.00652599468168578, 'weight_decay': 0.013473080129332647, 'batch_size': 32} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 14:24:48,613] Trial 75 pruned. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.524958 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.3989489345079227, 'lr': 0.0035136390343059047, 'weight_decay': 0.03204945328199728, 'batch_size': 64} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 14:24:52,726] Trial 76 pruned. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.519706 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.35029761471605975, 'lr': 0.009992145798445777, 'weight_decay': 0.004976014287419708, 'batch_size': 256} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 14:25:04,726] Trial 77 pruned. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.514536 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.36651102490082377, 'lr': 0.002254176075467637, 'weight_decay': 0.0037747531821335405, 'batch_size': 64} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 14:25:41,296] Trial 78 pruned. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.545864 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3902463391858062, 'lr': 0.005356046900755139, 'weight_decay': 0.010191199284001912, 'batch_size': 32} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 14:26:18,661] Trial 79 finished with value: 0.5532615692714635 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.3788906169806617, 'lr': 0.00732394392235785, 'weight_decay': 0.021282641416254033, 'batch_size': 128}. Best is trial 29 with value: 0.5640599235240535. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.553262 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.3788906169806617, 'lr': 0.00732394392235785, 'weight_decay': 0.021282641416254033, 'batch_size': 128} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) -[I 2025-12-25 14:26:44,675] Trial 80 pruned. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.571291 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.379510510009853, 'lr': 0.006950163552364199, 'weight_decay': 0.0069398686924610365, 'batch_size': 128} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 14:26:57,527] Trial 81 pruned. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.543333 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.36922748748873424, 'lr': 0.008597724382758931, 'weight_decay': 0.0196369853155942, 'batch_size': 128} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) -[I 2025-12-25 14:27:23,372] Trial 82 pruned. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.568889 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.39401569862082036, 'lr': 0.00374187451268323, 'weight_decay': 0.024094818639435713, 'batch_size': 128} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) -[I 2025-12-25 14:27:49,262] Trial 83 pruned. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.568932 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.35596176801833795, 'lr': 0.00490974511705209, 'weight_decay': 0.011612853957952581, 'batch_size': 128} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 14:29:07,162] Trial 84 finished with value: 0.5596224684130995 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.3805161112450537, 'lr': 0.0031387083711752074, 'weight_decay': 0.03857363798614982, 'batch_size': 64}. Best is trial 29 with value: 0.5640599235240535. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.559622 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.3805161112450537, 'lr': 0.0031387083711752074, 'weight_decay': 0.03857363798614982, 'batch_size': 64} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 14:29:12,419] Trial 85 pruned. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.509040 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.3794199359484997, 'lr': 0.003090255433871397, 'weight_decay': 0.03823741683288731, 'batch_size': 256} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 14:30:25,490] Trial 86 finished with value: 0.5583351686251206 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.3916869945045396, 'lr': 0.0061210411330035845, 'weight_decay': 0.020954635231294892, 'batch_size': 64}. Best is trial 29 with value: 0.5640599235240535. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.558335 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.3916869945045396, 'lr': 0.0061210411330035845, 'weight_decay': 0.020954635231294892, 'batch_size': 64} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 14:31:20,507] Trial 87 finished with value: 0.5522397196626114 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.39277713967012207, 'lr': 0.004057363770632231, 'weight_decay': 0.016166104081782394, 'batch_size': 64}. Best is trial 29 with value: 0.5640599235240535. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.552240 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.39277713967012207, 'lr': 0.004057363770632231, 'weight_decay': 0.016166104081782394, 'batch_size': 64} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 14:31:42,537] Trial 88 pruned. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.520694 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.37116099859917034, 'lr': 0.0059981258023725, 'weight_decay': 0.0353293846259034, 'batch_size': 64} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 14:31:52,996] Trial 89 pruned. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.504561 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.3840698271230542, 'lr': 0.00706799757579173, 'weight_decay': 0.022211052066867264, 'batch_size': 64} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) -[I 2025-12-25 14:32:36,657] Trial 90 pruned. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.565627 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.3776591693160896, 'lr': 0.0026960539003804285, 'weight_decay': 0.02689813377820558, 'batch_size': 64} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) -[I 2025-12-25 14:33:20,160] Trial 91 pruned. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.572433 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.38809036045605855, 'lr': 0.0083078482805021, 'weight_decay': 0.029933906781820546, 'batch_size': 64} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 14:34:02,745] Trial 92 finished with value: 0.552067394809641 and parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.3964414928022711, 'lr': 0.004788094234785517, 'weight_decay': 0.020952910169463664, 'batch_size': 128}. Best is trial 29 with value: 0.5640599235240535. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.552067 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.3964414928022711, 'lr': 0.004788094234785517, 'weight_decay': 0.020952910169463664, 'batch_size': 128} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 14:34:29,743] Trial 93 finished with value: 0.5533087253927373 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.3992687678212946, 'lr': 0.00578639944524712, 'weight_decay': 0.047399903305537464, 'batch_size': 256}. Best is trial 29 with value: 0.5640599235240535. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.553309 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.3992687678212946, 'lr': 0.00578639944524712, 'weight_decay': 0.047399903305537464, 'batch_size': 256} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 14:35:48,336] Trial 94 finished with value: 0.5601283588528756 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.3829340561309562, 'lr': 0.00569893847770036, 'weight_decay': 0.04322993540333474, 'batch_size': 64}. Best is trial 29 with value: 0.5640599235240535. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.560128 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.3829340561309562, 'lr': 0.00569893847770036, 'weight_decay': 0.04322993540333474, 'batch_size': 64} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 14:37:02,754] Trial 95 finished with value: 0.5583295328158188 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.3996669753110856, 'lr': 0.0032839615734994955, 'weight_decay': 0.04861158267858316, 'batch_size': 64}. Best is trial 29 with value: 0.5640599235240535. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.558330 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.3996669753110856, 'lr': 0.0032839615734994955, 'weight_decay': 0.04861158267858316, 'batch_size': 64} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 14:38:04,314] Trial 96 finished with value: 0.5609967505712838 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.36703756746800537, 'lr': 0.0032203948571691106, 'weight_decay': 0.06867984315874796, 'batch_size': 64}. Best is trial 29 with value: 0.5640599235240535. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.560997 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.36703756746800537, 'lr': 0.0032203948571691106, 'weight_decay': 0.06867984315874796, 'batch_size': 64} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 14:39:13,446] Trial 97 finished with value: 0.5568270607866324 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.38495592816698543, 'lr': 0.003252585169234384, 'weight_decay': 0.06156751863797559, 'batch_size': 64}. Best is trial 29 with value: 0.5640599235240535. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.556827 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.38495592816698543, 'lr': 0.003252585169234384, 'weight_decay': 0.06156751863797559, 'batch_size': 64} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 14:40:13,275] Trial 98 pruned. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.513040 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.36773073923539235, 'lr': 0.0030469656131888343, 'weight_decay': 0.06571431527643279, 'batch_size': 64} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 14:41:19,702] Trial 99 pruned. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.509504 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3849927935636696, 'lr': 0.0019296040861643848, 'weight_decay': 0.06970240545560971, 'batch_size': 64} - Best Value (CSI): 0.564060 - Best Trial: 29 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.5641 -Best Hyperparameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3785345227219112, 'lr': 0.0018955834640803318, 'weight_decay': 0.02389399379756967, 'batch_size': 32} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.5289 - - 최종 CSI: 0.5095 - - 최고 CSI: 0.5724 - - 최저 CSI: 0.3591 - - 평균 CSI: 0.5323 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/deepgbm_smote_incheon_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 27, Best CSI: 0.5559 - Fold 1 학습 완료 (검증 CSI: 0.5559) -Fold 2 학습 중... - Early stopping at epoch 20, Best CSI: 0.5858 - Fold 2 학습 완료 (검증 CSI: 0.5858) -Fold 3 학습 중... - Early stopping at epoch 29, Best CSI: 0.5293 - Fold 3 학습 완료 (검증 CSI: 0.5293) - -모든 모델 저장 완료: ../save_model/deepgbm_optima/deepgbm_smote_incheon.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/deepgbm_optima/scaler/deepgbm_smote_incheon_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: ../save_model/deepgbm_optima/deepgbm_smote_incheon.pkl - -✓ 완료: deepgbm_smote/deepgbm_smote_incheon.py (소요 시간: 4927초) - ----------------------------------------- -실행 중: deepgbm_smote/deepgbm_smote_seoul.py -시작 시간: 2025-12-25 14:42:59 ----------------------------------------- -[I 2025-12-25 14:43:00,260] A new study created in memory with name: no-name-ffc31f63-05f8-40f9-a5d6-45f5e1352786 - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 14:46:45,085] Trial 0 finished with value: 0.4508535953476343 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.30728587476448527, 'lr': 1.000203985680316e-05, 'weight_decay': 0.003987777011752342, 'batch_size': 64}. Best is trial 0 with value: 0.4508535953476343. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.450854 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.30728587476448527, 'lr': 1.000203985680316e-05, 'weight_decay': 0.003987777011752342, 'batch_size': 64} - Best Value (CSI): 0.450854 - Best Trial: 0 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.30728587476448527, 'lr': 1.000203985680316e-05, 'weight_decay': 0.003987777011752342, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 14:48:06,456] Trial 1 finished with value: 0.525924434892679 and parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.18426713081780022, 'lr': 0.0003645481715694547, 'weight_decay': 0.0006025603689159255, 'batch_size': 32}. Best is trial 1 with value: 0.525924434892679. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.525924 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.18426713081780022, 'lr': 0.0003645481715694547, 'weight_decay': 0.0006025603689159255, 'batch_size': 32} - Best Value (CSI): 0.525924 - Best Trial: 1 - Best Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.18426713081780022, 'lr': 0.0003645481715694547, 'weight_decay': 0.0006025603689159255, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 14:49:30,166] Trial 2 finished with value: 0.5455936260415034 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3439460671463674, 'lr': 0.0008517970401325805, 'weight_decay': 0.000995753664819177, 'batch_size': 32}. Best is trial 2 with value: 0.5455936260415034. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.545594 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3439460671463674, 'lr': 0.0008517970401325805, 'weight_decay': 0.000995753664819177, 'batch_size': 32} - Best Value (CSI): 0.545594 - Best Trial: 2 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3439460671463674, 'lr': 0.0008517970401325805, 'weight_decay': 0.000995753664819177, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 14:50:07,431] Trial 3 finished with value: 0.5396153740192587 and parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.3622696450918991, 'lr': 0.0010500096209988517, 'weight_decay': 0.0008962660004569143, 'batch_size': 128}. Best is trial 2 with value: 0.5455936260415034. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.539615 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.3622696450918991, 'lr': 0.0010500096209988517, 'weight_decay': 0.0008962660004569143, 'batch_size': 128} - Best Value (CSI): 0.545594 - Best Trial: 2 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3439460671463674, 'lr': 0.0008517970401325805, 'weight_decay': 0.000995753664819177, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 14:54:12,617] Trial 4 finished with value: 0.4789973908283082 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.21638949613243655, 'lr': 1.3094496398794056e-05, 'weight_decay': 0.00010103220444626475, 'batch_size': 32}. Best is trial 2 with value: 0.5455936260415034. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.478997 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.21638949613243655, 'lr': 1.3094496398794056e-05, 'weight_decay': 0.00010103220444626475, 'batch_size': 32} - Best Value (CSI): 0.545594 - Best Trial: 2 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3439460671463674, 'lr': 0.0008517970401325805, 'weight_decay': 0.000995753664819177, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 14:56:10,894] Trial 5 finished with value: 0.5360118488993978 and parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.3343315812150822, 'lr': 0.0009334974108041811, 'weight_decay': 0.06894584829060015, 'batch_size': 32}. Best is trial 2 with value: 0.5455936260415034. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.536012 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.3343315812150822, 'lr': 0.0009334974108041811, 'weight_decay': 0.06894584829060015, 'batch_size': 32} - Best Value (CSI): 0.545594 - Best Trial: 2 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3439460671463674, 'lr': 0.0008517970401325805, 'weight_decay': 0.000995753664819177, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 14:56:32,110] Trial 6 pruned. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.419426 - Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.20500000138642377, 'lr': 0.0033404920914416295, 'weight_decay': 0.022310568425550067, 'batch_size': 64} - Best Value (CSI): 0.545594 - Best Trial: 2 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3439460671463674, 'lr': 0.0008517970401325805, 'weight_decay': 0.000995753664819177, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 14:57:00,390] Trial 7 pruned. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.357557 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15465490593049164, 'lr': 0.0031326371210666708, 'weight_decay': 0.0034501505004738337, 'batch_size': 32} - Best Value (CSI): 0.545594 - Best Trial: 2 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3439460671463674, 'lr': 0.0008517970401325805, 'weight_decay': 0.000995753664819177, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 14:57:20,707] Trial 8 pruned. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.428382 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.380072767808451, 'lr': 0.0005714460572869697, 'weight_decay': 0.02316417826413371, 'batch_size': 64} - Best Value (CSI): 0.545594 - Best Trial: 2 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3439460671463674, 'lr': 0.0008517970401325805, 'weight_decay': 0.000995753664819177, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 14:58:10,680] Trial 9 finished with value: 0.5293987188565076 and parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.11724715552689532, 'lr': 0.0008345973222954815, 'weight_decay': 0.059969136602845884, 'batch_size': 128}. Best is trial 2 with value: 0.5455936260415034. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.529399 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.11724715552689532, 'lr': 0.0008345973222954815, 'weight_decay': 0.059969136602845884, 'batch_size': 128} - Best Value (CSI): 0.545594 - Best Trial: 2 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3439460671463674, 'lr': 0.0008517970401325805, 'weight_decay': 0.000995753664819177, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 14:58:14,833] Trial 10 pruned. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.340584 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.28284878743741976, 'lr': 0.00011573845310934916, 'weight_decay': 0.00011581326110588363, 'batch_size': 256} - Best Value (CSI): 0.545594 - Best Trial: 2 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3439460671463674, 'lr': 0.0008517970401325805, 'weight_decay': 0.000995753664819177, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 14:58:54,352] Trial 11 finished with value: 0.5394437449718735 and parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.38118032253812956, 'lr': 0.005576663540758183, 'weight_decay': 0.0009793124869490345, 'batch_size': 128}. Best is trial 2 with value: 0.5455936260415034. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.539444 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.38118032253812956, 'lr': 0.005576663540758183, 'weight_decay': 0.0009793124869490345, 'batch_size': 128} - Best Value (CSI): 0.545594 - Best Trial: 2 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3439460671463674, 'lr': 0.0008517970401325805, 'weight_decay': 0.000995753664819177, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 14:59:00,661] Trial 12 pruned. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.416723 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.33997327438240044, 'lr': 0.001915174484989086, 'weight_decay': 0.0007765211130503106, 'batch_size': 128} - Best Value (CSI): 0.545594 - Best Trial: 2 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3439460671463674, 'lr': 0.0008517970401325805, 'weight_decay': 0.000995753664819177, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 14:59:07,589] Trial 13 pruned. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.411877 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2529663733115357, 'lr': 0.007542558868686926, 'weight_decay': 0.001651650574338428, 'batch_size': 256} - Best Value (CSI): 0.545594 - Best Trial: 2 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3439460671463674, 'lr': 0.0008517970401325805, 'weight_decay': 0.000995753664819177, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 14:59:13,144] Trial 14 pruned. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.375073 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.3933776946036169, 'lr': 0.00015432819699046392, 'weight_decay': 0.0004043273424432723, 'batch_size': 128} - Best Value (CSI): 0.545594 - Best Trial: 2 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3439460671463674, 'lr': 0.0008517970401325805, 'weight_decay': 0.000995753664819177, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 14:59:31,303] Trial 15 pruned. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.411652 - Parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.34084332309547344, 'lr': 0.0018003472054846717, 'weight_decay': 0.00034190392980553574, 'batch_size': 32} - Best Value (CSI): 0.545594 - Best Trial: 2 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3439460671463674, 'lr': 0.0008517970401325805, 'weight_decay': 0.000995753664819177, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 14:59:37,196] Trial 16 pruned. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.381090 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2795945974423067, 'lr': 0.00021129561778561245, 'weight_decay': 0.0019965376262843075, 'batch_size': 128} - Best Value (CSI): 0.545594 - Best Trial: 2 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3439460671463674, 'lr': 0.0008517970401325805, 'weight_decay': 0.000995753664819177, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 14:59:41,873] Trial 17 pruned. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.387287 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.35599993970203114, 'lr': 0.009790100237625877, 'weight_decay': 0.0049103025211650695, 'batch_size': 256} - Best Value (CSI): 0.545594 - Best Trial: 2 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3439460671463674, 'lr': 0.0008517970401325805, 'weight_decay': 0.000995753664819177, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 15:01:52,954] Trial 18 finished with value: 0.5491567855652856 and parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3064435260296208, 'lr': 0.0015506149265468588, 'weight_decay': 0.0002831812943797127, 'batch_size': 32}. Best is trial 18 with value: 0.5491567855652856. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.549157 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3064435260296208, 'lr': 0.0015506149265468588, 'weight_decay': 0.0002831812943797127, 'batch_size': 32} - Best Value (CSI): 0.549157 - Best Trial: 18 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3064435260296208, 'lr': 0.0015506149265468588, 'weight_decay': 0.0002831812943797127, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 15:04:12,212] Trial 19 finished with value: 0.5408000309371045 and parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.31116770443228325, 'lr': 0.0004588295795850845, 'weight_decay': 0.00023495563365901547, 'batch_size': 32}. Best is trial 18 with value: 0.5491567855652856. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.540800 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.31116770443228325, 'lr': 0.0004588295795850845, 'weight_decay': 0.00023495563365901547, 'batch_size': 32} - Best Value (CSI): 0.549157 - Best Trial: 18 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3064435260296208, 'lr': 0.0015506149265468588, 'weight_decay': 0.0002831812943797127, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 15:06:35,949] Trial 20 finished with value: 0.5433764549746279 and parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.25020133387286525, 'lr': 0.0015947752458759993, 'weight_decay': 0.0002111658205226042, 'batch_size': 32}. Best is trial 18 with value: 0.5491567855652856. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.543376 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.25020133387286525, 'lr': 0.0015947752458759993, 'weight_decay': 0.0002111658205226042, 'batch_size': 32} - Best Value (CSI): 0.549157 - Best Trial: 18 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3064435260296208, 'lr': 0.0015506149265468588, 'weight_decay': 0.0002831812943797127, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 15:09:21,937] Trial 21 finished with value: 0.5396354961914005 and parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.2533612105675193, 'lr': 0.0014586287885228954, 'weight_decay': 0.00024155173628217656, 'batch_size': 32}. Best is trial 18 with value: 0.5491567855652856. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.539635 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.2533612105675193, 'lr': 0.0014586287885228954, 'weight_decay': 0.00024155173628217656, 'batch_size': 32} - Best Value (CSI): 0.549157 - Best Trial: 18 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3064435260296208, 'lr': 0.0015506149265468588, 'weight_decay': 0.0002831812943797127, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 15:11:53,662] Trial 22 finished with value: 0.5519482358554147 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.30783375436158716, 'lr': 0.002966791528451573, 'weight_decay': 0.00021121544626635818, 'batch_size': 32}. Best is trial 22 with value: 0.5519482358554147. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.551948 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.30783375436158716, 'lr': 0.002966791528451573, 'weight_decay': 0.00021121544626635818, 'batch_size': 32} - Best Value (CSI): 0.551948 - Best Trial: 22 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.30783375436158716, 'lr': 0.002966791528451573, 'weight_decay': 0.00021121544626635818, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 15:13:59,123] Trial 23 finished with value: 0.5436788708989481 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3133193432183727, 'lr': 0.004759759741134538, 'weight_decay': 0.0004541710764261718, 'batch_size': 32}. Best is trial 22 with value: 0.5519482358554147. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.543679 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3133193432183727, 'lr': 0.004759759741134538, 'weight_decay': 0.0004541710764261718, 'batch_size': 32} - Best Value (CSI): 0.551948 - Best Trial: 22 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.30783375436158716, 'lr': 0.002966791528451573, 'weight_decay': 0.00021121544626635818, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 15:16:09,413] Trial 24 finished with value: 0.5375118231813986 and parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2875863681013543, 'lr': 0.003560336950354922, 'weight_decay': 0.00015529807868816514, 'batch_size': 32}. Best is trial 22 with value: 0.5519482358554147. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.537512 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2875863681013543, 'lr': 0.003560336950354922, 'weight_decay': 0.00015529807868816514, 'batch_size': 32} - Best Value (CSI): 0.551948 - Best Trial: 22 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.30783375436158716, 'lr': 0.002966791528451573, 'weight_decay': 0.00021121544626635818, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 15:16:45,875] Trial 25 pruned. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.431535 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.3224794727693314, 'lr': 0.003062838394686467, 'weight_decay': 0.0003258848371724907, 'batch_size': 32} - Best Value (CSI): 0.551948 - Best Trial: 22 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.30783375436158716, 'lr': 0.002966791528451573, 'weight_decay': 0.00021121544626635818, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 15:19:18,281] Trial 26 finished with value: 0.5346976693236375 and parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.35883789899547747, 'lr': 0.000672065255210116, 'weight_decay': 0.00016773644795629294, 'batch_size': 32}. Best is trial 22 with value: 0.5519482358554147. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.534698 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.35883789899547747, 'lr': 0.000672065255210116, 'weight_decay': 0.00016773644795629294, 'batch_size': 32} - Best Value (CSI): 0.551948 - Best Trial: 22 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.30783375436158716, 'lr': 0.002966791528451573, 'weight_decay': 0.00021121544626635818, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 15:21:32,526] Trial 27 finished with value: 0.5456253431137915 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3010513479923853, 'lr': 0.0022209269818772824, 'weight_decay': 0.0004249706081515585, 'batch_size': 32}. Best is trial 22 with value: 0.5519482358554147. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.545625 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3010513479923853, 'lr': 0.0022209269818772824, 'weight_decay': 0.0004249706081515585, 'batch_size': 32} - Best Value (CSI): 0.551948 - Best Trial: 22 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.30783375436158716, 'lr': 0.002966791528451573, 'weight_decay': 0.00021121544626635818, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 15:21:53,753] Trial 28 pruned. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.382284 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.29210129442167265, 'lr': 0.005749088341707622, 'weight_decay': 0.0004879471531562422, 'batch_size': 32} - Best Value (CSI): 0.551948 - Best Trial: 22 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.30783375436158716, 'lr': 0.002966791528451573, 'weight_decay': 0.00021121544626635818, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 15:22:17,943] Trial 29 pruned. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.429371 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.30241787741892673, 'lr': 0.002216717102493332, 'weight_decay': 0.0001021980952127991, 'batch_size': 64} - Best Value (CSI): 0.551948 - Best Trial: 22 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.30783375436158716, 'lr': 0.002966791528451573, 'weight_decay': 0.00021121544626635818, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 15:22:27,607] Trial 30 pruned. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.428960 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.27373443129021285, 'lr': 0.009525366945767832, 'weight_decay': 0.0002670487895507725, 'batch_size': 256} - Best Value (CSI): 0.551948 - Best Trial: 22 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.30783375436158716, 'lr': 0.002966791528451573, 'weight_decay': 0.00021121544626635818, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 15:23:31,183] Trial 31 pruned. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.439530 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3230968201766208, 'lr': 0.0012537013480098582, 'weight_decay': 0.0005849756222902274, 'batch_size': 32} - Best Value (CSI): 0.551948 - Best Trial: 22 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.30783375436158716, 'lr': 0.002966791528451573, 'weight_decay': 0.00021121544626635818, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 15:26:15,212] Trial 32 finished with value: 0.5401046468147536 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.30283641304368547, 'lr': 0.002123437730250974, 'weight_decay': 0.00017195703335470705, 'batch_size': 32}. Best is trial 22 with value: 0.5519482358554147. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.540105 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.30283641304368547, 'lr': 0.002123437730250974, 'weight_decay': 0.00017195703335470705, 'batch_size': 32} - Best Value (CSI): 0.551948 - Best Trial: 22 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.30783375436158716, 'lr': 0.002966791528451573, 'weight_decay': 0.00021121544626635818, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 15:28:29,072] Trial 33 finished with value: 0.5397866417895059 and parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.32750038599712994, 'lr': 0.0010550463911948112, 'weight_decay': 0.0006420264924056293, 'batch_size': 32}. Best is trial 22 with value: 0.5519482358554147. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.539787 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.32750038599712994, 'lr': 0.0010550463911948112, 'weight_decay': 0.0006420264924056293, 'batch_size': 32} - Best Value (CSI): 0.551948 - Best Trial: 22 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.30783375436158716, 'lr': 0.002966791528451573, 'weight_decay': 0.00021121544626635818, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 15:30:35,802] Trial 34 finished with value: 0.5372252355320684 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.265803110652568, 'lr': 0.0007436843246306633, 'weight_decay': 0.00034082679107521436, 'batch_size': 32}. Best is trial 22 with value: 0.5519482358554147. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.537225 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.265803110652568, 'lr': 0.0007436843246306633, 'weight_decay': 0.00034082679107521436, 'batch_size': 32} - Best Value (CSI): 0.551948 - Best Trial: 22 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.30783375436158716, 'lr': 0.002966791528451573, 'weight_decay': 0.00021121544626635818, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 15:31:00,674] Trial 35 pruned. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.383750 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.29965919646546635, 'lr': 0.001289290667240502, 'weight_decay': 0.0010005871888855112, 'batch_size': 32} - Best Value (CSI): 0.551948 - Best Trial: 22 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.30783375436158716, 'lr': 0.002966791528451573, 'weight_decay': 0.00021121544626635818, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 15:31:11,605] Trial 36 pruned. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.417853 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.3447284562584963, 'lr': 0.00039976166050618127, 'weight_decay': 0.0004862898947022558, 'batch_size': 64} - Best Value (CSI): 0.551948 - Best Trial: 22 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.30783375436158716, 'lr': 0.002966791528451573, 'weight_decay': 0.00021121544626635818, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 15:33:58,289] Trial 37 finished with value: 0.5508569550486778 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.2291790760975918, 'lr': 0.0025518143873532375, 'weight_decay': 0.0002811391060899786, 'batch_size': 32}. Best is trial 22 with value: 0.5519482358554147. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.550857 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.2291790760975918, 'lr': 0.0025518143873532375, 'weight_decay': 0.0002811391060899786, 'batch_size': 32} - Best Value (CSI): 0.551948 - Best Trial: 22 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.30783375436158716, 'lr': 0.002966791528451573, 'weight_decay': 0.00021121544626635818, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 15:34:49,894] Trial 38 pruned. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.439127 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.23875670696225643, 'lr': 0.002531620801733404, 'weight_decay': 0.00015515153605804332, 'batch_size': 32} - Best Value (CSI): 0.551948 - Best Trial: 22 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.30783375436158716, 'lr': 0.002966791528451573, 'weight_decay': 0.00021121544626635818, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 15:35:19,293] Trial 39 pruned. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.409904 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.23583937537835994, 'lr': 0.004413795120757935, 'weight_decay': 0.0002607341793285278, 'batch_size': 32} - Best Value (CSI): 0.551948 - Best Trial: 22 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.30783375436158716, 'lr': 0.002966791528451573, 'weight_decay': 0.00021121544626635818, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 15:38:29,158] Trial 40 finished with value: 0.5425594768739478 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.26817443857070855, 'lr': 0.002675727602071018, 'weight_decay': 0.00012743820199935215, 'batch_size': 32}. Best is trial 22 with value: 0.5519482358554147. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.542559 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.26817443857070855, 'lr': 0.002675727602071018, 'weight_decay': 0.00012743820199935215, 'batch_size': 32} - Best Value (CSI): 0.551948 - Best Trial: 22 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.30783375436158716, 'lr': 0.002966791528451573, 'weight_decay': 0.00021121544626635818, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 15:39:26,215] Trial 41 pruned. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.432877 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.3204972433078976, 'lr': 0.0010115514845421185, 'weight_decay': 0.00035897706666956165, 'batch_size': 32} - Best Value (CSI): 0.551948 - Best Trial: 22 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.30783375436158716, 'lr': 0.002966791528451573, 'weight_decay': 0.00021121544626635818, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 15:42:13,371] Trial 42 finished with value: 0.5397755856517467 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.21219022901568552, 'lr': 0.003912278547368843, 'weight_decay': 0.0006755741680659985, 'batch_size': 32}. Best is trial 22 with value: 0.5519482358554147. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.539776 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.21219022901568552, 'lr': 0.003912278547368843, 'weight_decay': 0.0006755741680659985, 'batch_size': 32} - Best Value (CSI): 0.551948 - Best Trial: 22 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.30783375436158716, 'lr': 0.002966791528451573, 'weight_decay': 0.00021121544626635818, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 15:42:24,959] Trial 43 pruned. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.410013 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2999287678025374, 'lr': 0.0016605877306594488, 'weight_decay': 0.00022613255264611012, 'batch_size': 64} - Best Value (CSI): 0.551948 - Best Trial: 22 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.30783375436158716, 'lr': 0.002966791528451573, 'weight_decay': 0.00021121544626635818, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 15:45:25,337] Trial 44 finished with value: 0.5427111100563745 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.3328404836272447, 'lr': 0.0027035058156746946, 'weight_decay': 0.0008898480532852508, 'batch_size': 32}. Best is trial 22 with value: 0.5519482358554147. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.542711 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.3328404836272447, 'lr': 0.0027035058156746946, 'weight_decay': 0.0008898480532852508, 'batch_size': 32} - Best Value (CSI): 0.551948 - Best Trial: 22 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.30783375436158716, 'lr': 0.002966791528451573, 'weight_decay': 0.00021121544626635818, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 15:46:38,642] Trial 45 pruned. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.444053 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.36982846806411174, 'lr': 0.0008346750536329451, 'weight_decay': 0.00048271519945000793, 'batch_size': 32} - Best Value (CSI): 0.551948 - Best Trial: 22 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.30783375436158716, 'lr': 0.002966791528451573, 'weight_decay': 0.00021121544626635818, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 15:46:44,793] Trial 46 pruned. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.402859 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.18851221986492092, 'lr': 0.0005461422249488945, 'weight_decay': 0.0003094548600401349, 'batch_size': 256} - Best Value (CSI): 0.551948 - Best Trial: 22 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.30783375436158716, 'lr': 0.002966791528451573, 'weight_decay': 0.00021121544626635818, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 15:49:57,328] Trial 47 finished with value: 0.5551122990255606 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32}. Best is trial 47 with value: 0.5551122990255606. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.555112 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 15:50:22,259] Trial 48 pruned. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.421367 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.2867159927404103, 'lr': 0.005849114833446652, 'weight_decay': 0.00014000127793485653, 'batch_size': 32} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 15:51:02,124] Trial 49 finished with value: 0.5496426805192284 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.2644987457864242, 'lr': 0.0035762232804438156, 'weight_decay': 0.00020189839613300096, 'batch_size': 128}. Best is trial 47 with value: 0.5551122990255606. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.549643 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.2644987457864242, 'lr': 0.0035762232804438156, 'weight_decay': 0.00020189839613300096, 'batch_size': 128} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 15:51:09,232] Trial 50 pruned. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.421088 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2658734136809995, 'lr': 0.003777225726017691, 'weight_decay': 0.00010498145199765597, 'batch_size': 128} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 15:51:22,446] Trial 51 pruned. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.423639 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.2828669915547005, 'lr': 0.0021652909271299204, 'weight_decay': 0.00019600801707460777, 'batch_size': 128} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 15:52:04,965] Trial 52 finished with value: 0.5429496749250999 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.31174675515312916, 'lr': 0.003348483949379577, 'weight_decay': 0.00018467036808896486, 'batch_size': 128}. Best is trial 47 with value: 0.5551122990255606. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.542950 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.31174675515312916, 'lr': 0.003348483949379577, 'weight_decay': 0.00018467036808896486, 'batch_size': 128} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 15:52:12,723] Trial 53 pruned. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.409302 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.2959382383840792, 'lr': 0.0017198136771535409, 'weight_decay': 0.00012762513380244135, 'batch_size': 128} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 15:52:19,997] Trial 54 pruned. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.389971 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.22741425908389445, 'lr': 0.006820403305604162, 'weight_decay': 0.0002709928396149154, 'batch_size': 128} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 15:52:41,694] Trial 55 pruned. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.416174 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.2746741937318617, 'lr': 0.004204212801949633, 'weight_decay': 0.00020015455756145308, 'batch_size': 32} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 15:53:08,685] Trial 56 pruned. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.432011 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3116344394030576, 'lr': 0.0029079133204477285, 'weight_decay': 0.0003749528833508456, 'batch_size': 64} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 15:53:13,814] Trial 57 pruned. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.415929 - Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.25431573334635343, 'lr': 0.002051805244648747, 'weight_decay': 0.0002810525410688232, 'batch_size': 256} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 15:53:35,169] Trial 58 pruned. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.404959 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.2866322256547168, 'lr': 0.001320607058855454, 'weight_decay': 0.00012973260193495161, 'batch_size': 32} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 15:54:18,546] Trial 59 finished with value: 0.5426186570626749 and parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.26431729624182404, 'lr': 0.004666274255509036, 'weight_decay': 0.00020747413364079098, 'batch_size': 128}. Best is trial 47 with value: 0.5551122990255606. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.542619 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.26431729624182404, 'lr': 0.004666274255509036, 'weight_decay': 0.00020747413364079098, 'batch_size': 128} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 15:54:41,819] Trial 60 pruned. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.408276 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.27645016286734386, 'lr': 0.0032693288649595868, 'weight_decay': 0.00010295952159879064, 'batch_size': 32} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 15:57:27,179] Trial 61 finished with value: 0.5473159984134375 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2923678768192364, 'lr': 0.001823076893114372, 'weight_decay': 0.00039224896165501055, 'batch_size': 32}. Best is trial 47 with value: 0.5551122990255606. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.547316 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2923678768192364, 'lr': 0.001823076893114372, 'weight_decay': 0.00039224896165501055, 'batch_size': 32} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 15:58:09,973] Trial 62 pruned. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.433622 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2919990777791464, 'lr': 0.002425606876221241, 'weight_decay': 0.0003986986609255551, 'batch_size': 32} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 16:00:28,285] Trial 63 finished with value: 0.5390267692674363 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.30788548443327857, 'lr': 0.0017680065479197561, 'weight_decay': 0.0002511530485817768, 'batch_size': 32}. Best is trial 47 with value: 0.5551122990255606. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.539027 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.30788548443327857, 'lr': 0.0017680065479197561, 'weight_decay': 0.0002511530485817768, 'batch_size': 32} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 16:00:48,414] Trial 64 pruned. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.417339 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.31854839518403866, 'lr': 0.001184623230083902, 'weight_decay': 0.00015986788346418346, 'batch_size': 32} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 16:03:57,111] Trial 65 finished with value: 0.5483247042652541 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2966696749481464, 'lr': 0.0014157179190875163, 'weight_decay': 0.0003141187743709938, 'batch_size': 32}. Best is trial 47 with value: 0.5551122990255606. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.548325 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2966696749481464, 'lr': 0.0014157179190875163, 'weight_decay': 0.0003141187743709938, 'batch_size': 32} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 16:06:19,272] Trial 66 finished with value: 0.5444509624020047 and parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2807475458352785, 'lr': 0.0015382212029165891, 'weight_decay': 0.00029309279032462785, 'batch_size': 32}. Best is trial 47 with value: 0.5551122990255606. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.544451 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2807475458352785, 'lr': 0.0015382212029165891, 'weight_decay': 0.00029309279032462785, 'batch_size': 32} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 16:06:40,935] Trial 67 pruned. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.424387 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.25979902834650753, 'lr': 0.0014834818525830413, 'weight_decay': 0.00019571705461647132, 'batch_size': 32} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 16:07:02,338] Trial 68 pruned. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.419720 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2935147879012179, 'lr': 0.0009828905414706445, 'weight_decay': 0.000583339363673902, 'batch_size': 32} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 16:07:39,298] Trial 69 finished with value: 0.5443343253311369 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.24939172595023476, 'lr': 0.0028377650824360575, 'weight_decay': 0.00016064891745365363, 'batch_size': 256}. Best is trial 47 with value: 0.5551122990255606. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.544334 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.24939172595023476, 'lr': 0.0028377650824360575, 'weight_decay': 0.00016064891745365363, 'batch_size': 256} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 16:07:46,506] Trial 70 pruned. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.409683 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2731184555381746, 'lr': 0.002018867024899613, 'weight_decay': 0.00032889558423331597, 'batch_size': 128} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 16:09:42,489] Trial 71 finished with value: 0.548456555061225 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.30385971184536087, 'lr': 0.0022802507071167503, 'weight_decay': 0.0003882939743487846, 'batch_size': 32}. Best is trial 47 with value: 0.5551122990255606. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.548457 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.30385971184536087, 'lr': 0.0022802507071167503, 'weight_decay': 0.0003882939743487846, 'batch_size': 32} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 16:10:26,536] Trial 72 pruned. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.439291 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3068258614508931, 'lr': 0.0032396423192508354, 'weight_decay': 0.00024490911346042017, 'batch_size': 32} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 16:10:49,080] Trial 73 pruned. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.374580 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3343252571504894, 'lr': 0.00505314456135114, 'weight_decay': 0.0004186667170842817, 'batch_size': 32} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 16:11:37,524] Trial 74 pruned. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.447386 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.29156397874050327, 'lr': 0.002438096068350259, 'weight_decay': 0.00022393727582921226, 'batch_size': 32} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 16:11:59,763] Trial 75 pruned. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.414304 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.31632495327915366, 'lr': 0.0038633368317031918, 'weight_decay': 0.0003351470542069251, 'batch_size': 32} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 16:12:21,733] Trial 76 pruned. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.421257 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3270041538502192, 'lr': 0.0018064280290616046, 'weight_decay': 0.00046557266740697716, 'batch_size': 32} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 16:12:34,178] Trial 77 pruned. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.426413 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.30657985222174966, 'lr': 0.0011605524832605512, 'weight_decay': 0.00013520811307706615, 'batch_size': 64} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 16:13:48,819] Trial 78 pruned. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.455213 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.28015503479961246, 'lr': 0.0009075864099013342, 'weight_decay': 0.00017444903990837077, 'batch_size': 32} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 16:14:09,185] Trial 79 pruned. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.394097 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2981050466710655, 'lr': 0.0014919676829296946, 'weight_decay': 0.0005656132429688443, 'batch_size': 32} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 16:15:52,598] Trial 80 finished with value: 0.5454608964029193 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3456645847753878, 'lr': 0.0027305353960707904, 'weight_decay': 0.0002810888001567299, 'batch_size': 32}. Best is trial 47 with value: 0.5551122990255606. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.545461 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3456645847753878, 'lr': 0.0027305353960707904, 'weight_decay': 0.0002810888001567299, 'batch_size': 32} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 16:16:49,262] Trial 81 pruned. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.433921 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3006617797091948, 'lr': 0.0021608856917207397, 'weight_decay': 0.0003696649877559582, 'batch_size': 32} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 16:17:15,022] Trial 82 pruned. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.422715 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.2885971035835962, 'lr': 0.00184428417885235, 'weight_decay': 0.00042927452819224775, 'batch_size': 32} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 16:17:44,199] Trial 83 pruned. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.407804 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.3148191031579349, 'lr': 0.0024806244554500226, 'weight_decay': 0.00023451113776365134, 'batch_size': 32} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 16:18:42,428] Trial 84 pruned. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.443306 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3060330545730837, 'lr': 0.0038740300838300944, 'weight_decay': 0.00030590690719650314, 'batch_size': 32} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 16:19:12,121] Trial 85 pruned. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.424735 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3257914217680902, 'lr': 0.0030731277797985727, 'weight_decay': 0.0005377921877721304, 'batch_size': 32} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 16:19:59,747] Trial 86 pruned. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.442690 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2971661206877544, 'lr': 0.0012668594613971366, 'weight_decay': 0.0006545783204436583, 'batch_size': 32} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 16:20:16,361] Trial 87 pruned. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.449963 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.2807678299649076, 'lr': 0.0022380999497003105, 'weight_decay': 0.00040983762306075417, 'batch_size': 128} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 16:20:43,005] Trial 88 pruned. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.397234 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.2713918882606174, 'lr': 0.0015104519677196602, 'weight_decay': 0.0002174552123747164, 'batch_size': 32} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 16:20:54,270] Trial 89 pruned. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.427260 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.2851500307029224, 'lr': 0.0034986703211592066, 'weight_decay': 0.0007375773843662398, 'batch_size': 256} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 16:21:07,208] Trial 90 pruned. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.425265 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.31650680392298464, 'lr': 0.005225382704025388, 'weight_decay': 0.00018093240808906777, 'batch_size': 64} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 16:21:52,947] Trial 91 pruned. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.430478 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3042673861596279, 'lr': 0.0019460050369808624, 'weight_decay': 0.0005046912174149538, 'batch_size': 32} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 16:22:32,052] Trial 92 pruned. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.409367 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.32298770911133307, 'lr': 0.0007171993277376123, 'weight_decay': 0.0003164796545828495, 'batch_size': 32} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 16:23:18,764] Trial 93 pruned. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.430194 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.34113095474512234, 'lr': 0.0011289361724929547, 'weight_decay': 0.0008234605216643915, 'batch_size': 32} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 16:23:44,733] Trial 94 pruned. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.423957 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.2940809848587586, 'lr': 0.001419560681680845, 'weight_decay': 0.00036706323603798516, 'batch_size': 32} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 16:24:29,057] Trial 95 pruned. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.440608 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.28808923268599684, 'lr': 0.002433596355632242, 'weight_decay': 0.0002609856322165701, 'batch_size': 32} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 16:24:43,566] Trial 96 pruned. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.433003 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.33419408060205935, 'lr': 0.001730796243523346, 'weight_decay': 0.0011934780592893453, 'batch_size': 128} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 16:27:05,818] Trial 97 finished with value: 0.544763696185606 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3135717917602914, 'lr': 0.0009304455471872464, 'weight_decay': 0.00044798108052991435, 'batch_size': 32}. Best is trial 47 with value: 0.5551122990255606. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.544764 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3135717917602914, 'lr': 0.0009304455471872464, 'weight_decay': 0.00044798108052991435, 'batch_size': 32} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 16:29:38,243] Trial 98 finished with value: 0.5420730188786149 and parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.2692567282306375, 'lr': 0.00285300771483714, 'weight_decay': 0.0001466427781138184, 'batch_size': 32}. Best is trial 47 with value: 0.5551122990255606. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.542073 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.2692567282306375, 'lr': 0.00285300771483714, 'weight_decay': 0.0001466427781138184, 'batch_size': 32} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 16:30:01,420] Trial 99 pruned. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.387779 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.27677985786792736, 'lr': 0.004480882273211401, 'weight_decay': 0.00028257223022779996, 'batch_size': 32} - Best Value (CSI): 0.555112 - Best Trial: 47 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.5551 -Best Hyperparameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2869842021080176, 'lr': 0.002077449117732186, 'weight_decay': 0.00019614736051849963, 'batch_size': 32} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.4509 - - 최종 CSI: 0.3878 - - 최고 CSI: 0.5551 - - 최저 CSI: 0.3406 - - 평균 CSI: 0.4615 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/deepgbm_smote_seoul_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 36, Best CSI: 0.4557 - Fold 1 학습 완료 (검증 CSI: 0.4557) -Fold 2 학습 중... - Early stopping at epoch 26, Best CSI: 0.6214 - Fold 2 학습 완료 (검증 CSI: 0.6214) -Fold 3 학습 중... - Early stopping at epoch 21, Best CSI: 0.5878 - Fold 3 학습 완료 (검증 CSI: 0.5878) - -모든 모델 저장 완료: ../save_model/deepgbm_optima/deepgbm_smote_seoul.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/deepgbm_optima/scaler/deepgbm_smote_seoul_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: ../save_model/deepgbm_optima/deepgbm_smote_seoul.pkl - -✓ 완료: deepgbm_smote/deepgbm_smote_seoul.py (소요 시간: 6577초) - -========================================== -DeepGBM SMOTE 파일 실행 완료 -종료 시간: 2025-12-25 16:32:36 -총 소요 시간: 9시간 20분 17초 -성공: 6개 -실패: 0개 -========================================== diff --git a/Analysis_code/5.optima/run_bash/deepgbm/deepgbm_smotenc_ctgan20000.log b/Analysis_code/5.optima/run_bash/deepgbm/deepgbm_smotenc_ctgan20000.log deleted file mode 100644 index cd5ed667a1d7f6e4061d6294914eeee4486f9013..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/run_bash/deepgbm/deepgbm_smotenc_ctgan20000.log +++ /dev/null @@ -1,7845 +0,0 @@ -nohup: ignoring input -/bin/bash: /opt/conda/lib/libtinfo.so.6: no version information available (required by /bin/bash) -========================================== -DeepGBM SMOTENC CTGAN20000 파일 실행 시작 -시작 시간: 2025-12-25 14:57:05 -GPU: 1번 (CUDA_VISIBLE_DEVICES=1) -========================================== - ----------------------------------------- -실행 중: deepgbm_smotenc_ctgan20000/deepgbm_smotenc_ctgan20000_busan.py -시작 시간: 2025-12-25 14:57:05 ----------------------------------------- -[I 2025-12-25 14:57:06,241] A new study created in memory with name: no-name-eb8323f1-96d7-4643-98ec-8d2df07d750c - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 15:07:39,621] Trial 0 finished with value: 0.38200403097658286 and parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.1333297311898249, 'lr': 0.00615017216005229, 'weight_decay': 0.0003045902464521587, 'batch_size': 32}. Best is trial 0 with value: 0.38200403097658286. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.382004 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.1333297311898249, 'lr': 0.00615017216005229, 'weight_decay': 0.0003045902464521587, 'batch_size': 32} - Best Value (CSI): 0.382004 - Best Trial: 0 - Best Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.1333297311898249, 'lr': 0.00615017216005229, 'weight_decay': 0.0003045902464521587, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 15:12:06,249] Trial 1 finished with value: 0.3729435020995049 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.1912816397239528, 'lr': 0.0005791584746257493, 'weight_decay': 0.00040982274330501276, 'batch_size': 64}. Best is trial 0 with value: 0.38200403097658286. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.372944 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.1912816397239528, 'lr': 0.0005791584746257493, 'weight_decay': 0.00040982274330501276, 'batch_size': 64} - Best Value (CSI): 0.382004 - Best Trial: 0 - Best Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.1333297311898249, 'lr': 0.00615017216005229, 'weight_decay': 0.0003045902464521587, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 15:21:20,996] Trial 2 finished with value: 0.3667007243525391 and parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.13648445758598787, 'lr': 0.0005559814918719669, 'weight_decay': 0.006821685660997404, 'batch_size': 32}. Best is trial 0 with value: 0.38200403097658286. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.366701 - Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.13648445758598787, 'lr': 0.0005559814918719669, 'weight_decay': 0.006821685660997404, 'batch_size': 32} - Best Value (CSI): 0.382004 - Best Trial: 0 - Best Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.1333297311898249, 'lr': 0.00615017216005229, 'weight_decay': 0.0003045902464521587, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 15:34:21,871] Trial 3 finished with value: 0.35103779076802705 and parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.1522276108930393, 'lr': 0.009449103644069388, 'weight_decay': 0.0003042241687949215, 'batch_size': 32}. Best is trial 0 with value: 0.38200403097658286. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.351038 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.1522276108930393, 'lr': 0.009449103644069388, 'weight_decay': 0.0003042241687949215, 'batch_size': 32} - Best Value (CSI): 0.382004 - Best Trial: 0 - Best Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.1333297311898249, 'lr': 0.00615017216005229, 'weight_decay': 0.0003045902464521587, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 15:37:12,462] Trial 4 finished with value: 0.30790915551462367 and parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.3252899291868173, 'lr': 0.00014610098602859932, 'weight_decay': 0.00326558091572378, 'batch_size': 256}. Best is trial 0 with value: 0.38200403097658286. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.307909 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.3252899291868173, 'lr': 0.00014610098602859932, 'weight_decay': 0.00326558091572378, 'batch_size': 256} - Best Value (CSI): 0.382004 - Best Trial: 0 - Best Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.1333297311898249, 'lr': 0.00615017216005229, 'weight_decay': 0.0003045902464521587, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 15:40:18,636] Trial 5 finished with value: 0.40671898361820197 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128}. Best is trial 5 with value: 0.40671898361820197. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.406719 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 15:42:01,761] Trial 6 pruned. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.351111 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.2189002223682855, 'lr': 0.004680197433470761, 'weight_decay': 0.023680480455596023, 'batch_size': 64} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 15:42:15,137] Trial 7 pruned. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.231972 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.3487567742596628, 'lr': 3.435806119472047e-05, 'weight_decay': 0.06867658751305938, 'batch_size': 256} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 15:43:06,784] Trial 8 pruned. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.304147 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.3369330067886509, 'lr': 0.004362342419901845, 'weight_decay': 0.006485285912896107, 'batch_size': 64} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 15:46:29,401] Trial 9 pruned. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.390208 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.29605613359264776, 'lr': 0.0007961455924277049, 'weight_decay': 0.09281873988315219, 'batch_size': 32} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 15:47:15,867] Trial 10 pruned. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.340000 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.39886242730263094, 'lr': 0.0018615801867103744, 'weight_decay': 0.0197669240079979, 'batch_size': 128} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 15:47:37,002] Trial 11 pruned. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.282707 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2568280408374718, 'lr': 0.00927306703762698, 'weight_decay': 0.0008757163297695279, 'batch_size': 128} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 15:48:20,682] Trial 12 pruned. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.334770 - Parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.10542487993301274, 'lr': 0.0021067508121053206, 'weight_decay': 0.00013076309388201509, 'batch_size': 128} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 15:49:09,119] Trial 13 pruned. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.357247 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.24750293906136608, 'lr': 0.0014990615026426934, 'weight_decay': 0.0006533280077384548, 'batch_size': 128} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 15:52:00,439] Trial 14 pruned. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.377333 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.18286071340610577, 'lr': 0.00019291565449876534, 'weight_decay': 0.0015450235765999106, 'batch_size': 32} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 15:54:38,352] Trial 15 finished with value: 0.39048583916850105 and parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.10227576812035125, 'lr': 0.003577471166789113, 'weight_decay': 0.00011848910175519835, 'batch_size': 128}. Best is trial 5 with value: 0.40671898361820197. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.390486 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.10227576812035125, 'lr': 0.003577471166789113, 'weight_decay': 0.00011848910175519835, 'batch_size': 128} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 15:55:36,746] Trial 16 pruned. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.338686 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.2769198657984911, 'lr': 0.0031901340835931444, 'weight_decay': 0.00014348293833039044, 'batch_size': 128} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 15:57:57,751] Trial 17 pruned. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.337868 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.10085905859004908, 'lr': 0.003312706396752194, 'weight_decay': 0.0017567210448623985, 'batch_size': 128} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 15:58:16,743] Trial 18 pruned. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.250737 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.23225405945164299, 'lr': 0.009271249323437201, 'weight_decay': 0.0001063841221887277, 'batch_size': 128} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) -[I 2025-12-25 15:59:41,587] Trial 19 pruned. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.393827 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.20446881292366725, 'lr': 0.0011335894227662876, 'weight_decay': 0.0037863537599554845, 'batch_size': 128} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 16:00:11,026] Trial 20 pruned. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.366522 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.17241727147579755, 'lr': 0.0022800452642749674, 'weight_decay': 0.0014286330019689097, 'batch_size': 256} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 16:01:32,244] Trial 21 pruned. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.259601 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.1308439139981149, 'lr': 0.005319997551844396, 'weight_decay': 0.0002473892626569892, 'batch_size': 32} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 16:02:49,064] Trial 22 pruned. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.255385 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.1589347171268578, 'lr': 0.006131752822751828, 'weight_decay': 0.00020710123372067574, 'batch_size': 32} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 16:03:41,381] Trial 23 pruned. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.316493 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.1236737820568346, 'lr': 0.0029853343815495134, 'weight_decay': 0.0004470301783458002, 'batch_size': 128} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 16:04:02,939] Trial 24 pruned. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.306452 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.16056046776496816, 'lr': 0.006049680630105982, 'weight_decay': 0.00010268275349655151, 'batch_size': 128} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) -[I 2025-12-25 16:11:00,555] Trial 25 pruned. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.387887 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.20424959440640558, 'lr': 0.0014054688866728035, 'weight_decay': 0.00021384456254942854, 'batch_size': 32} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) -[I 2025-12-25 16:11:57,005] Trial 26 pruned. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.417582 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.10044740306812594, 'lr': 0.009706308030408846, 'weight_decay': 0.0005918945329035963, 'batch_size': 256} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 16:12:46,302] Trial 27 pruned. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.301310 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.13398875110121763, 'lr': 0.003474949706995593, 'weight_decay': 0.00029714231204834004, 'batch_size': 64} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 16:13:11,665] Trial 28 pruned. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.299699 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.1727917412775734, 'lr': 0.0054808298084877485, 'weight_decay': 0.0001821955033847968, 'batch_size': 128} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 16:13:58,884] Trial 29 pruned. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.320000 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.18664206770731803, 'lr': 0.0023366420265324476, 'weight_decay': 0.0008045873453247382, 'batch_size': 64} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 16:17:22,020] Trial 30 pruned. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.354319 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.14416523110067841, 'lr': 0.0008649111496379273, 'weight_decay': 0.00036302834775424667, 'batch_size': 32} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 16:19:52,833] Trial 31 pruned. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.368207 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.12279307327266856, 'lr': 0.0003667120886148564, 'weight_decay': 0.0004438671711016867, 'batch_size': 64} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 16:20:57,400] Trial 32 pruned. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.271162 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1471678220244815, 'lr': 0.0005284743236880506, 'weight_decay': 0.00016268784415207646, 'batch_size': 64} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 16:23:05,286] Trial 33 pruned. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.346209 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.149323250528724, 'lr': 0.0011986570118383735, 'weight_decay': 0.00030781127231329725, 'batch_size': 64} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 16:25:05,192] Trial 34 pruned. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.312500 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.1224017775834313, 'lr': 0.006792930067537478, 'weight_decay': 0.0002596425678225213, 'batch_size': 32} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 16:26:08,522] Trial 35 pruned. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.326316 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.19614941681347786, 'lr': 0.0038026366449378274, 'weight_decay': 0.0005550903933219131, 'batch_size': 64} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 16:26:21,882] Trial 36 pruned. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.334315 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.2272550868344475, 'lr': 0.007117201596562857, 'weight_decay': 0.00016845629211626332, 'batch_size': 256} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 16:27:47,531] Trial 37 pruned. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.286595 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.16514763545944527, 'lr': 0.004492390142491886, 'weight_decay': 0.0003650419642981542, 'batch_size': 32} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 16:29:17,541] Trial 38 pruned. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.353741 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.11376630275273082, 'lr': 0.0006649723500500475, 'weight_decay': 0.014080622653255026, 'batch_size': 64} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 16:29:41,427] Trial 39 pruned. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.296241 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.14609853301017112, 'lr': 0.0023010676783185337, 'weight_decay': 0.031593917158786504, 'batch_size': 128} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 16:29:53,864] Trial 40 pruned. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.226126 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.1200558201058454, 'lr': 8.238946147028848e-05, 'weight_decay': 0.004904923367515343, 'batch_size': 256} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 16:33:25,695] Trial 41 pruned. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.335235 - Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.13904953362157724, 'lr': 0.0004601481090357038, 'weight_decay': 0.0059334842533007226, 'batch_size': 32} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 16:35:02,208] Trial 42 pruned. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.326174 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.1362974113138044, 'lr': 0.00025495244668202185, 'weight_decay': 0.008230418117296887, 'batch_size': 32} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 16:44:30,766] Trial 43 finished with value: 0.37372538352483936 and parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.11500078184178893, 'lr': 0.0008971206647729568, 'weight_decay': 0.0028824030637893527, 'batch_size': 32}. Best is trial 5 with value: 0.40671898361820197. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.373725 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.11500078184178893, 'lr': 0.0008971206647729568, 'weight_decay': 0.0028824030637893527, 'batch_size': 32} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 16:57:09,350] Trial 44 finished with value: 0.3858569546113486 and parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.11156276814673882, 'lr': 0.0008735889919749028, 'weight_decay': 0.0027052087882148347, 'batch_size': 32}. Best is trial 5 with value: 0.40671898361820197. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.385857 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.11156276814673882, 'lr': 0.0008735889919749028, 'weight_decay': 0.0027052087882148347, 'batch_size': 32} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) -[I 2025-12-25 17:05:18,715] Trial 45 pruned. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.407692 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.10902690738992907, 'lr': 0.000987062854785785, 'weight_decay': 0.0020545097312299424, 'batch_size': 32} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 17:17:42,223] Trial 46 pruned. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.336782 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.11240011850690662, 'lr': 0.0017728939404814226, 'weight_decay': 0.0031985298365952157, 'batch_size': 32} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 17:20:43,692] Trial 47 pruned. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.359155 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.11467102734898724, 'lr': 0.0006344043083619914, 'weight_decay': 0.0024667436676921294, 'batch_size': 32} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 17:36:36,353] Trial 48 finished with value: 0.3857232627473353 and parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.1043422961653995, 'lr': 0.00442587844341532, 'weight_decay': 0.0011621136500711013, 'batch_size': 32}. Best is trial 5 with value: 0.40671898361820197. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.385723 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.1043422961653995, 'lr': 0.00442587844341532, 'weight_decay': 0.0011621136500711013, 'batch_size': 32} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 17:37:23,718] Trial 49 pruned. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.332353 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.10402436928736737, 'lr': 0.004621610495619911, 'weight_decay': 0.0009726524530541223, 'batch_size': 128} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 17:39:12,640] Trial 50 pruned. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.258065 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.12719375709011554, 'lr': 0.0075252514459180535, 'weight_decay': 0.0012300571649401738, 'batch_size': 32} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) -[I 2025-12-25 17:45:17,876] Trial 51 pruned. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.401370 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.10109737567989377, 'lr': 0.003028165899051981, 'weight_decay': 0.0027504027042338417, 'batch_size': 32} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 17:46:33,363] Trial 52 pruned. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.320346 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.13129793914369212, 'lr': 0.001481532884357565, 'weight_decay': 0.0018890375815431247, 'batch_size': 32} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 17:48:54,808] Trial 53 pruned. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.295031 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.11549644536193453, 'lr': 0.004046619329973408, 'weight_decay': 0.0037065849177916597, 'batch_size': 32} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 17:49:34,159] Trial 54 pruned. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.251908 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15425463648448123, 'lr': 0.009796278594102578, 'weight_decay': 0.0022875593476935716, 'batch_size': 128} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) -[I 2025-12-25 17:56:25,722] Trial 55 pruned. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.397622 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.13681335810227524, 'lr': 0.002786936085766453, 'weight_decay': 0.00163223881691868, 'batch_size': 32} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 17:57:05,878] Trial 56 pruned. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.318862 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.11069002012224309, 'lr': 0.004984763551845672, 'weight_decay': 0.0001291019440928184, 'batch_size': 128} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 17:58:16,969] Trial 57 pruned. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.349640 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.31113124319006835, 'lr': 0.001870353353578518, 'weight_decay': 0.0011146207794431311, 'batch_size': 32} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 17:59:20,076] Trial 58 pruned. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.191223 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.10105045439970599, 'lr': 0.007513096860505891, 'weight_decay': 0.0007535007523173838, 'batch_size': 32} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 17:59:40,488] Trial 59 pruned. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.326951 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.12702920491781292, 'lr': 0.003863363949300385, 'weight_decay': 0.0012088754394051124, 'batch_size': 128} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 18:01:09,199] Trial 60 pruned. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.317529 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.2723068108847165, 'lr': 0.0026421842641347637, 'weight_decay': 0.001593135583905912, 'batch_size': 32} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 18:02:10,833] Trial 61 pruned. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.382022 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.11969669753274281, 'lr': 0.0008297313909699557, 'weight_decay': 0.00020769538994261697, 'batch_size': 128} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 18:03:03,939] Trial 62 pruned. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.329609 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.13670540424386163, 'lr': 0.0011691650901202856, 'weight_decay': 0.0008860998832163965, 'batch_size': 64} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 18:05:08,138] Trial 63 finished with value: 0.38830989839578073 and parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.1570856791181315, 'lr': 0.005315054576773846, 'weight_decay': 0.0006728305820472547, 'batch_size': 256}. Best is trial 5 with value: 0.40671898361820197. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.388310 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.1570856791181315, 'lr': 0.005315054576773846, 'weight_decay': 0.0006728305820472547, 'batch_size': 256} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) -[I 2025-12-25 18:06:17,509] Trial 64 pruned. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.415775 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15577111562404, 'lr': 0.005644041929587199, 'weight_decay': 0.0006229430589220063, 'batch_size': 256} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 18:07:45,937] Trial 65 finished with value: 0.38839365211378957 and parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.1279018225231914, 'lr': 0.0077457943418727205, 'weight_decay': 0.0004969208612056993, 'batch_size': 256}. Best is trial 5 with value: 0.40671898361820197. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.388394 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.1279018225231914, 'lr': 0.0077457943418727205, 'weight_decay': 0.0004969208612056993, 'batch_size': 256} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 18:08:01,278] Trial 66 pruned. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.340599 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.14413996986051586, 'lr': 0.008358316154697815, 'weight_decay': 0.00040228522229636643, 'batch_size': 256} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 18:08:34,614] Trial 67 pruned. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.338150 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.12870097776983516, 'lr': 0.0064279439737954, 'weight_decay': 0.0004952350834768033, 'batch_size': 256} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 18:10:07,137] Trial 68 pruned. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.366265 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.1786797959722209, 'lr': 0.0052234708273334735, 'weight_decay': 0.0005361500092919291, 'batch_size': 256} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 18:10:22,308] Trial 69 pruned. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.245877 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.16522318177024176, 'lr': 0.008465923402403201, 'weight_decay': 0.0007061943937561288, 'batch_size': 256} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) -[I 2025-12-25 18:11:28,932] Trial 70 pruned. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.413924 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.10571807854649783, 'lr': 0.0035216075002353488, 'weight_decay': 0.00031046562933354275, 'batch_size': 256} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 18:13:10,468] Trial 71 finished with value: 0.4011772244854422 and parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.11908960868684904, 'lr': 0.006117552079172186, 'weight_decay': 0.0009129071249698151, 'batch_size': 256}. Best is trial 5 with value: 0.40671898361820197. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.401177 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.11908960868684904, 'lr': 0.006117552079172186, 'weight_decay': 0.0009129071249698151, 'batch_size': 256} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) -[I 2025-12-25 18:14:03,872] Trial 72 pruned. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.412983 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.12340326831532598, 'lr': 0.006382813882890589, 'weight_decay': 0.0009380580138075627, 'batch_size': 256} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 18:15:06,449] Trial 73 pruned. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.343646 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.14243132125038444, 'lr': 0.00987564463759118, 'weight_decay': 0.0006861427099044916, 'batch_size': 256} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 18:15:17,207] Trial 74 pruned. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.336986 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.1514195754247138, 'lr': 0.00436633570565048, 'weight_decay': 0.00044390499935163417, 'batch_size': 256} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 18:15:28,205] Trial 75 pruned. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.184615 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.13052268585282767, 'lr': 0.007736480374361614, 'weight_decay': 0.0014537740550699852, 'batch_size': 256} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 18:15:41,956] Trial 76 pruned. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.353096 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.10849905859140657, 'lr': 0.005508695408396211, 'weight_decay': 0.0005813895318419942, 'batch_size': 256} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 18:17:16,193] Trial 77 finished with value: 0.39102092604728816 and parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.11959130541721946, 'lr': 0.003457043811124447, 'weight_decay': 0.00034744669098163726, 'batch_size': 128}. Best is trial 5 with value: 0.40671898361820197. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.391021 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.11959130541721946, 'lr': 0.003457043811124447, 'weight_decay': 0.00034744669098163726, 'batch_size': 128} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 18:18:49,265] Trial 78 finished with value: 0.38039690710557844 and parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.12159998388585104, 'lr': 0.003371286199246197, 'weight_decay': 0.0008305118804503275, 'batch_size': 128}. Best is trial 5 with value: 0.40671898361820197. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.380397 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.12159998388585104, 'lr': 0.003371286199246197, 'weight_decay': 0.0008305118804503275, 'batch_size': 128} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 18:19:08,892] Trial 79 pruned. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.320242 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.10063182861391519, 'lr': 0.004499713151713611, 'weight_decay': 0.001034342713745363, 'batch_size': 128} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 18:19:27,118] Trial 80 pruned. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.315485 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.11481715230868643, 'lr': 0.0025411037797610225, 'weight_decay': 0.0002475132862843732, 'batch_size': 128} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 18:19:42,644] Trial 81 pruned. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.329882 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.13249965071391034, 'lr': 0.0065790205061311705, 'weight_decay': 0.000374622685292399, 'batch_size': 128} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 18:19:57,888] Trial 82 pruned. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.309659 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.10880613051170143, 'lr': 0.005830277894761178, 'weight_decay': 0.00046472833226147324, 'batch_size': 128} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 18:20:18,369] Trial 83 pruned. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.342606 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.13923265391015635, 'lr': 0.003894792201659016, 'weight_decay': 0.0002808148770939549, 'batch_size': 256} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 18:20:33,878] Trial 84 pruned. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.348178 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.12102770447487761, 'lr': 0.0031385586187517014, 'weight_decay': 0.00034240382870881215, 'batch_size': 128} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 18:20:44,184] Trial 85 pruned. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.352861 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.1474079139521567, 'lr': 0.004828548262909157, 'weight_decay': 0.0006450887134128369, 'batch_size': 256} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 18:21:02,373] Trial 86 pruned. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.317437 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.11589415618001286, 'lr': 0.008448712954074471, 'weight_decay': 0.001335415875601387, 'batch_size': 128} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 18:21:58,981] Trial 87 finished with value: 0.3971331455468843 and parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.12660032068742688, 'lr': 0.006652881762385428, 'weight_decay': 0.0005063524673281321, 'batch_size': 256}. Best is trial 5 with value: 0.40671898361820197. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.397133 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.12660032068742688, 'lr': 0.006652881762385428, 'weight_decay': 0.0005063524673281321, 'batch_size': 256} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 18:22:08,888] Trial 88 pruned. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.264122 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.10823807206037883, 'lr': 0.007457762145157222, 'weight_decay': 0.0007622729327164687, 'batch_size': 256} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) -[I 2025-12-25 18:22:54,335] Trial 89 pruned. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.396053 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.13111030156739334, 'lr': 0.006452167483957661, 'weight_decay': 0.0005476882121211639, 'batch_size': 256} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 18:24:00,424] Trial 90 finished with value: 0.3770461945105574 and parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.12292335041091423, 'lr': 0.002001594101355978, 'weight_decay': 0.0004227959796655832, 'batch_size': 256}. Best is trial 5 with value: 0.40671898361820197. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.377046 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.12292335041091423, 'lr': 0.002001594101355978, 'weight_decay': 0.0004227959796655832, 'batch_size': 256} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 18:25:24,079] Trial 91 finished with value: 0.38503613354788896 and parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.14071661041360847, 'lr': 0.005102591888743379, 'weight_decay': 0.0003148545208828977, 'batch_size': 256}. Best is trial 5 with value: 0.40671898361820197. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.385036 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.14071661041360847, 'lr': 0.005102591888743379, 'weight_decay': 0.0003148545208828977, 'batch_size': 256} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 18:25:35,713] Trial 92 pruned. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.341667 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.14003966837361392, 'lr': 0.0048752652556196, 'weight_decay': 0.0010676842647772719, 'batch_size': 256} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 18:26:00,193] Trial 93 pruned. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.280236 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.11728008203167606, 'lr': 0.0038204833281482967, 'weight_decay': 0.0003296299284006589, 'batch_size': 256} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 18:26:57,203] Trial 94 finished with value: 0.38335452279464954 and parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.12642856896410576, 'lr': 0.0056033122384444795, 'weight_decay': 0.0002293502591008029, 'batch_size': 256}. Best is trial 5 with value: 0.40671898361820197. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.383355 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.12642856896410576, 'lr': 0.0056033122384444795, 'weight_decay': 0.0002293502591008029, 'batch_size': 256} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 18:27:09,124] Trial 95 pruned. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.268366 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.10781027151787033, 'lr': 0.008888886303763142, 'weight_decay': 0.00017724027785152356, 'batch_size': 256} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 18:27:20,745] Trial 96 pruned. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.335165 - Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.15029645112606724, 'lr': 0.0027955809759112687, 'weight_decay': 0.0005010071305988381, 'batch_size': 256} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 18:27:41,055] Trial 97 pruned. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.268702 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.13534038476992516, 'lr': 0.007051733601595868, 'weight_decay': 0.0008220966142636274, 'batch_size': 128} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 18:28:07,891] Trial 98 pruned. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.362745 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.1600183052181945, 'lr': 0.004496298701220488, 'weight_decay': 0.00030149607638163875, 'batch_size': 256} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 18:28:24,551] Trial 99 pruned. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.330137 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.1124738917266832, 'lr': 0.0033584912705342668, 'weight_decay': 0.00039786642153368825, 'batch_size': 128} - Best Value (CSI): 0.406719 - Best Trial: 5 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.4067 -Best Hyperparameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2843714965028271, 'lr': 0.009315324608427497, 'weight_decay': 0.022174119634941862, 'batch_size': 128} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.3820 - - 최종 CSI: 0.3301 - - 최고 CSI: 0.4176 - - 최저 CSI: 0.1846 - - 평균 CSI: 0.3369 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/deepgbm_smotenc_ctgan20000_busan_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 34, Best CSI: 0.3801 - Fold 1 학습 완료 (검증 CSI: 0.3801) -Fold 2 학습 중... - Early stopping at epoch 23, Best CSI: 0.4721 - Fold 2 학습 완료 (검증 CSI: 0.4721) -Fold 3 학습 중... - Early stopping at epoch 38, Best CSI: 0.4197 - Fold 3 학습 완료 (검증 CSI: 0.4197) - -모든 모델 저장 완료: ../save_model/deepgbm_optima/deepgbm_smotenc_ctgan20000_busan.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/deepgbm_optima/scaler/deepgbm_smotenc_ctgan20000_busan_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: ../save_model/deepgbm_optima/deepgbm_smotenc_ctgan20000_busan.pkl -======================================== -Trial 1 완료 - Value (CSI): 0.385679 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2848573987586112, 'lr': 0.007340360080223874, 'weight_decay': 0.016783140287706385, 'batch_size': 64} - Best Value (CSI): 0.385679 - Best Trial: 1 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2848573987586112, 'lr': 0.007340360080223874, 'weight_decay': 0.016783140287706385, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 17:32:45,095] Trial 2 finished with value: 0.2986276841911237 and parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3746721221053714, 'lr': 2.952713484968621e-05, 'weight_decay': 0.004740750336710883, 'batch_size': 256}. Best is trial 1 with value: 0.3856790077158836. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.298628 - Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.3746721221053714, 'lr': 2.952713484968621e-05, 'weight_decay': 0.004740750336710883, 'batch_size': 256} - Best Value (CSI): 0.385679 - Best Trial: 1 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2848573987586112, 'lr': 0.007340360080223874, 'weight_decay': 0.016783140287706385, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 17:34:58,338] Trial 3 finished with value: 0.3037065629179909 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.14701030015786512, 'lr': 5.216475326013391e-05, 'weight_decay': 0.029889243290260662, 'batch_size': 128}. Best is trial 1 with value: 0.3856790077158836. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.303707 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.14701030015786512, 'lr': 5.216475326013391e-05, 'weight_decay': 0.029889243290260662, 'batch_size': 128} - Best Value (CSI): 0.385679 - Best Trial: 1 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2848573987586112, 'lr': 0.007340360080223874, 'weight_decay': 0.016783140287706385, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 17:36:29,928] Trial 4 finished with value: 0.320579746066292 and parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.121646436817294, 'lr': 6.727487030603425e-05, 'weight_decay': 0.0005256624960787881, 'batch_size': 128}. Best is trial 1 with value: 0.3856790077158836. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.320580 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.121646436817294, 'lr': 6.727487030603425e-05, 'weight_decay': 0.0005256624960787881, 'batch_size': 128} - Best Value (CSI): 0.385679 - Best Trial: 1 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2848573987586112, 'lr': 0.007340360080223874, 'weight_decay': 0.016783140287706385, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 17:37:42,875] Trial 5 finished with value: 0.3728367971943143 and parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.3327179334010073, 'lr': 0.0029472196473923572, 'weight_decay': 0.0002558079622873686, 'batch_size': 256}. Best is trial 1 with value: 0.3856790077158836. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.372837 - Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.3327179334010073, 'lr': 0.0029472196473923572, 'weight_decay': 0.0002558079622873686, 'batch_size': 256} - Best Value (CSI): 0.385679 - Best Trial: 1 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2848573987586112, 'lr': 0.007340360080223874, 'weight_decay': 0.016783140287706385, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 17:38:32,537] Trial 6 pruned. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.261563 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.3168833984251789, 'lr': 0.00013016620722235356, 'weight_decay': 0.0006047424598373846, 'batch_size': 32} - Best Value (CSI): 0.385679 - Best Trial: 1 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2848573987586112, 'lr': 0.007340360080223874, 'weight_decay': 0.016783140287706385, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 17:40:02,161] Trial 7 finished with value: 0.3543437698570853 and parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.38043745238576543, 'lr': 0.0007226450013182126, 'weight_decay': 0.0015903753489726108, 'batch_size': 128}. Best is trial 1 with value: 0.3856790077158836. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.354344 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.38043745238576543, 'lr': 0.0007226450013182126, 'weight_decay': 0.0015903753489726108, 'batch_size': 128} - Best Value (CSI): 0.385679 - Best Trial: 1 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2848573987586112, 'lr': 0.007340360080223874, 'weight_decay': 0.016783140287706385, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 17:42:07,170] Trial 8 pruned. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.301766 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2773607825626969, 'lr': 0.0005859019881779902, 'weight_decay': 0.0016385428838565678, 'batch_size': 64} - Best Value (CSI): 0.385679 - Best Trial: 1 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2848573987586112, 'lr': 0.007340360080223874, 'weight_decay': 0.016783140287706385, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 17:42:44,619] Trial 9 pruned. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.210393 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.18534018537983848, 'lr': 2.9683462284887478e-05, 'weight_decay': 0.0008225148626672035, 'batch_size': 32} - Best Value (CSI): 0.385679 - Best Trial: 1 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2848573987586112, 'lr': 0.007340360080223874, 'weight_decay': 0.016783140287706385, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 17:45:19,240] Trial 10 finished with value: 0.42421665871258857 and parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23749084860307185, 'lr': 0.009370159012270448, 'weight_decay': 0.07499307287280156, 'batch_size': 64}. Best is trial 10 with value: 0.42421665871258857. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.424217 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23749084860307185, 'lr': 0.009370159012270448, 'weight_decay': 0.07499307287280156, 'batch_size': 64} - Best Value (CSI): 0.424217 - Best Trial: 10 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23749084860307185, 'lr': 0.009370159012270448, 'weight_decay': 0.07499307287280156, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 17:48:42,261] Trial 11 finished with value: 0.4307323196661675 and parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64}. Best is trial 11 with value: 0.4307323196661675. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.430732 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} - Best Value (CSI): 0.430732 - Best Trial: 11 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 17:52:01,098] Trial 12 finished with value: 0.42153393601603795 and parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.22315479556256956, 'lr': 0.008812284431471919, 'weight_decay': 0.06667295762377227, 'batch_size': 64}. Best is trial 11 with value: 0.4307323196661675. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.421534 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.22315479556256956, 'lr': 0.008812284431471919, 'weight_decay': 0.06667295762377227, 'batch_size': 64} - Best Value (CSI): 0.430732 - Best Trial: 11 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 17:54:47,339] Trial 13 finished with value: 0.4034030872912259 and parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23311295737234916, 'lr': 0.0021838499272363848, 'weight_decay': 0.08628139019391722, 'batch_size': 64}. Best is trial 11 with value: 0.4307323196661675. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.403403 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23311295737234916, 'lr': 0.0021838499272363848, 'weight_decay': 0.08628139019391722, 'batch_size': 64} - Best Value (CSI): 0.430732 - Best Trial: 11 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 17:57:55,358] Trial 14 finished with value: 0.40968728720923303 and parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19754713188569664, 'lr': 0.009945449525975654, 'weight_decay': 0.012854075488803903, 'batch_size': 64}. Best is trial 11 with value: 0.4307323196661675. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.409687 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19754713188569664, 'lr': 0.009945449525975654, 'weight_decay': 0.012854075488803903, 'batch_size': 64} - Best Value (CSI): 0.430732 - Best Trial: 11 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 18:00:34,943] Trial 15 finished with value: 0.3952509776109269 and parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2522596763481665, 'lr': 0.0013070974614867957, 'weight_decay': 0.043461785851368936, 'batch_size': 64}. Best is trial 11 with value: 0.4307323196661675. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.395251 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2522596763481665, 'lr': 0.0013070974614867957, 'weight_decay': 0.043461785851368936, 'batch_size': 64} - Best Value (CSI): 0.430732 - Best Trial: 11 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 18:03:20,076] Trial 16 finished with value: 0.4088328396770544 and parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.2544338555138684, 'lr': 0.004677267709926582, 'weight_decay': 0.0807044470169193, 'batch_size': 64}. Best is trial 11 with value: 0.4307323196661675. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.408833 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.2544338555138684, 'lr': 0.004677267709926582, 'weight_decay': 0.0807044470169193, 'batch_size': 64} - Best Value (CSI): 0.430732 - Best Trial: 11 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 18:03:48,453] Trial 17 pruned. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.332636 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.18648436361058998, 'lr': 0.0011608089602853637, 'weight_decay': 0.0290344780015774, 'batch_size': 64} - Best Value (CSI): 0.430732 - Best Trial: 11 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 18:04:32,303] Trial 18 finished with value: 0.37793174270817165 and parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.20525289617103892, 'lr': 0.005047197238627658, 'weight_decay': 0.009627468404161656, 'batch_size': 256}. Best is trial 11 with value: 0.4307323196661675. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.377932 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.20525289617103892, 'lr': 0.005047197238627658, 'weight_decay': 0.009627468404161656, 'batch_size': 256} - Best Value (CSI): 0.430732 - Best Trial: 11 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 18:05:11,479] Trial 19 pruned. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.305927 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.10106350188299201, 'lr': 0.0002799389297057265, 'weight_decay': 0.006096906325289003, 'batch_size': 32} - Best Value (CSI): 0.430732 - Best Trial: 11 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 18:05:31,216] Trial 20 pruned. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.163721 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.1602911793555841, 'lr': 1.0031812145737914e-05, 'weight_decay': 0.02179490620499538, 'batch_size': 64} - Best Value (CSI): 0.430732 - Best Trial: 11 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 18:08:34,657] Trial 21 finished with value: 0.4231529582097365 and parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.22828990125210155, 'lr': 0.009423829800023327, 'weight_decay': 0.09967290709828559, 'batch_size': 64}. Best is trial 11 with value: 0.4307323196661675. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.423153 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.22828990125210155, 'lr': 0.009423829800023327, 'weight_decay': 0.09967290709828559, 'batch_size': 64} - Best Value (CSI): 0.430732 - Best Trial: 11 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 18:11:54,429] Trial 22 finished with value: 0.4067124559746507 and parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2325376947826469, 'lr': 0.005046363063258625, 'weight_decay': 0.05133246763235007, 'batch_size': 64}. Best is trial 11 with value: 0.4307323196661675. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.406712 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2325376947826469, 'lr': 0.005046363063258625, 'weight_decay': 0.05133246763235007, 'batch_size': 64} - Best Value (CSI): 0.430732 - Best Trial: 11 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 18:14:06,669] Trial 23 finished with value: 0.39671492049207974 and parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.2632891730669977, 'lr': 0.00965365890406693, 'weight_decay': 0.04042888183333823, 'batch_size': 64}. Best is trial 11 with value: 0.4307323196661675. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.396715 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.2632891730669977, 'lr': 0.00965365890406693, 'weight_decay': 0.04042888183333823, 'batch_size': 64} - Best Value (CSI): 0.430732 - Best Trial: 11 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 18:17:04,081] Trial 24 finished with value: 0.42720967059261244 and parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.21863509492149125, 'lr': 0.0023248878957764013, 'weight_decay': 0.08571852973548237, 'batch_size': 64}. Best is trial 11 with value: 0.4307323196661675. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.427210 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.21863509492149125, 'lr': 0.0023248878957764013, 'weight_decay': 0.08571852973548237, 'batch_size': 64} - Best Value (CSI): 0.430732 - Best Trial: 11 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 18:19:40,035] Trial 25 finished with value: 0.40237437877823495 and parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.21357424996120083, 'lr': 0.002144093961873882, 'weight_decay': 0.04667294659064852, 'batch_size': 64}. Best is trial 11 with value: 0.4307323196661675. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.402374 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.21357424996120083, 'lr': 0.002144093961873882, 'weight_decay': 0.04667294659064852, 'batch_size': 64} - Best Value (CSI): 0.430732 - Best Trial: 11 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 18:20:21,214] Trial 26 pruned. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.363825 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.24340594288189873, 'lr': 0.003556438413357864, 'weight_decay': 0.021931615736668155, 'batch_size': 64} - Best Value (CSI): 0.430732 - Best Trial: 11 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 18:23:53,630] Trial 27 finished with value: 0.4160426954620579 and parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.17231829954982364, 'lr': 0.00545503090987752, 'weight_decay': 0.05916776181579717, 'batch_size': 32}. Best is trial 11 with value: 0.4307323196661675. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.416043 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.17231829954982364, 'lr': 0.00545503090987752, 'weight_decay': 0.05916776181579717, 'batch_size': 32} - Best Value (CSI): 0.430732 - Best Trial: 11 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 18:24:02,885] Trial 28 pruned. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.309055 - Parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.20670480300462657, 'lr': 0.001770409831421198, 'weight_decay': 0.029703394623959854, 'batch_size': 256} - Best Value (CSI): 0.430732 - Best Trial: 11 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 18:25:52,378] Trial 29 finished with value: 0.40383060707703633 and parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.27201085743598696, 'lr': 0.0035933768127341874, 'weight_decay': 0.09310316747227268, 'batch_size': 128}. Best is trial 11 with value: 0.4307323196661675. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.403831 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.27201085743598696, 'lr': 0.0035933768127341874, 'weight_decay': 0.09310316747227268, 'batch_size': 128} - Best Value (CSI): 0.430732 - Best Trial: 11 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 18:26:26,782] Trial 30 pruned. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.328571 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2962818062314527, 'lr': 0.0032074278337085077, 'weight_decay': 0.01341143901405962, 'batch_size': 64} - Best Value (CSI): 0.430732 - Best Trial: 11 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 18:29:18,612] Trial 31 finished with value: 0.40881139068605893 and parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2252976071001744, 'lr': 0.0060078748811469495, 'weight_decay': 0.08824532971780802, 'batch_size': 64}. Best is trial 11 with value: 0.4307323196661675. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.408811 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2252976071001744, 'lr': 0.0060078748811469495, 'weight_decay': 0.08824532971780802, 'batch_size': 64} - Best Value (CSI): 0.430732 - Best Trial: 11 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 18:31:50,561] Trial 32 finished with value: 0.40214826942393067 and parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.24649037880923885, 'lr': 0.007605691257890702, 'weight_decay': 0.05053192197241287, 'batch_size': 64}. Best is trial 11 with value: 0.4307323196661675. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.402148 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.24649037880923885, 'lr': 0.007605691257890702, 'weight_decay': 0.05053192197241287, 'batch_size': 64} - Best Value (CSI): 0.430732 - Best Trial: 11 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 18:34:36,065] Trial 33 finished with value: 0.42049143430056074 and parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.21865870207257745, 'lr': 0.005960575335137106, 'weight_decay': 0.09954427849242226, 'batch_size': 64}. Best is trial 11 with value: 0.4307323196661675. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.420491 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.21865870207257745, 'lr': 0.005960575335137106, 'weight_decay': 0.09954427849242226, 'batch_size': 64} - Best Value (CSI): 0.430732 - Best Trial: 11 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 18:37:13,265] Trial 34 finished with value: 0.4078006416230125 and parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.23928927245235473, 'lr': 0.007733959982864252, 'weight_decay': 0.059511656793378075, 'batch_size': 64}. Best is trial 11 with value: 0.4307323196661675. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.407801 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.23928927245235473, 'lr': 0.007733959982864252, 'weight_decay': 0.059511656793378075, 'batch_size': 64} - Best Value (CSI): 0.430732 - Best Trial: 11 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 18:37:47,238] Trial 35 pruned. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.363420 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.27134027308812675, 'lr': 0.003857826684909271, 'weight_decay': 0.031212835147525864, 'batch_size': 64} - Best Value (CSI): 0.430732 - Best Trial: 11 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 18:38:55,926] Trial 36 finished with value: 0.40836705758590797 and parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.2914542789532121, 'lr': 0.009801969979271827, 'weight_decay': 0.06653467916239415, 'batch_size': 256}. Best is trial 11 with value: 0.4307323196661675. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.408367 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.2914542789532121, 'lr': 0.009801969979271827, 'weight_decay': 0.06653467916239415, 'batch_size': 256} - Best Value (CSI): 0.430732 - Best Trial: 11 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 18:39:11,495] Trial 37 pruned. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.352814 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.1937653358822804, 'lr': 0.0029958003067072424, 'weight_decay': 0.0369298365507583, 'batch_size': 128} - Best Value (CSI): 0.430732 - Best Trial: 11 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 18:41:46,985] Trial 38 finished with value: 0.41279691251749534 and parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.2138135828046362, 'lr': 0.005123055780222242, 'weight_decay': 0.020402972377308332, 'batch_size': 64}. Best is trial 11 with value: 0.4307323196661675. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.412797 - Parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.2138135828046362, 'lr': 0.005123055780222242, 'weight_decay': 0.020402972377308332, 'batch_size': 64} - Best Value (CSI): 0.430732 - Best Trial: 11 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 18:42:08,605] Trial 39 pruned. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.344828 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.2574704694359799, 'lr': 0.0066053293068389475, 'weight_decay': 0.09936317765147569, 'batch_size': 128} - Best Value (CSI): 0.430732 - Best Trial: 11 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 18:48:38,004] Trial 40 finished with value: 0.41128349249131935 and parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.30627768480981177, 'lr': 0.0022323582181983433, 'weight_decay': 0.06687823910316276, 'batch_size': 32}. Best is trial 11 with value: 0.4307323196661675. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.411283 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.30627768480981177, 'lr': 0.0022323582181983433, 'weight_decay': 0.06687823910316276, 'batch_size': 32} - Best Value (CSI): 0.430732 - Best Trial: 11 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 18:48:55,922] Trial 41 pruned. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.299807 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.22353751960608617, 'lr': 0.00724204792874194, 'weight_decay': 0.06546966847844535, 'batch_size': 64} - Best Value (CSI): 0.430732 - Best Trial: 11 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 18:49:15,854] Trial 42 pruned. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.346491 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23477593164959804, 'lr': 0.009602638935963578, 'weight_decay': 0.037764357386960615, 'batch_size': 64} - Best Value (CSI): 0.430732 - Best Trial: 11 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 18:51:57,820] Trial 43 finished with value: 0.41808661723681856 and parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.20197808275072954, 'lr': 0.004253784220987185, 'weight_decay': 0.06601402406138104, 'batch_size': 64}. Best is trial 11 with value: 0.4307323196661675. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.418087 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.20197808275072954, 'lr': 0.004253784220987185, 'weight_decay': 0.06601402406138104, 'batch_size': 64} - Best Value (CSI): 0.430732 - Best Trial: 11 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 18:52:20,399] Trial 44 pruned. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.323529 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2218459105267715, 'lr': 0.007253516732757605, 'weight_decay': 0.047146360946487186, 'batch_size': 64} - Best Value (CSI): 0.430732 - Best Trial: 11 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 18:52:50,474] Trial 45 pruned. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.379913 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.24159014299193804, 'lr': 0.0025396691082781478, 'weight_decay': 0.026292851128864047, 'batch_size': 64} - Best Value (CSI): 0.430732 - Best Trial: 11 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 18:53:25,984] Trial 46 pruned. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.391204 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.18433001821122869, 'lr': 0.004092991016348934, 'weight_decay': 0.07468036277031787, 'batch_size': 64} - Best Value (CSI): 0.430732 - Best Trial: 11 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 18:54:30,284] Trial 47 finished with value: 0.40036502003894486 and parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.2848488530576282, 'lr': 0.006760840868383694, 'weight_decay': 0.036148244190647834, 'batch_size': 256}. Best is trial 11 with value: 0.4307323196661675. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.400365 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.2848488530576282, 'lr': 0.006760840868383694, 'weight_decay': 0.036148244190647834, 'batch_size': 256} - Best Value (CSI): 0.430732 - Best Trial: 11 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 18:54:52,342] Trial 48 pruned. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.370370 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.25523746156992333, 'lr': 0.0016002909095353512, 'weight_decay': 0.016912832498253125, 'batch_size': 64} - Best Value (CSI): 0.430732 - Best Trial: 11 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 18:57:28,978] Trial 49 finished with value: 0.41828104724060117 and parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2302632322923392, 'lr': 0.0027603176153533403, 'weight_decay': 0.048966604591236654, 'batch_size': 64}. Best is trial 11 with value: 0.4307323196661675. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.418281 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2302632322923392, 'lr': 0.0027603176153533403, 'weight_decay': 0.048966604591236654, 'batch_size': 64} - Best Value (CSI): 0.430732 - Best Trial: 11 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 19:01:21,478] Trial 50 finished with value: 0.42426212563397964 and parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.212330681339756, 'lr': 0.004205333666457319, 'weight_decay': 0.09816136632085802, 'batch_size': 32}. Best is trial 11 with value: 0.4307323196661675. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.424262 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.212330681339756, 'lr': 0.004205333666457319, 'weight_decay': 0.09816136632085802, 'batch_size': 32} - Best Value (CSI): 0.430732 - Best Trial: 11 - Best Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23178114116339094, 'lr': 0.007074238908032745, 'weight_decay': 0.055751033425856605, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 19:06:37,449] Trial 51 finished with value: 0.43407422794617584 and parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32}. Best is trial 51 with value: 0.43407422794617584. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.434074 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 19:10:42,290] Trial 52 finished with value: 0.42082832354028327 and parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.21300573900718572, 'lr': 0.004727438186661075, 'weight_decay': 0.09835883461428876, 'batch_size': 32}. Best is trial 51 with value: 0.43407422794617584. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.420828 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.21300573900718572, 'lr': 0.004727438186661075, 'weight_decay': 0.09835883461428876, 'batch_size': 32} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 19:15:56,722] Trial 53 finished with value: 0.41949280928743987 and parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2020438360977361, 'lr': 0.003090471271376684, 'weight_decay': 0.07967114753019448, 'batch_size': 32}. Best is trial 51 with value: 0.43407422794617584. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.419493 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2020438360977361, 'lr': 0.003090471271376684, 'weight_decay': 0.07967114753019448, 'batch_size': 32} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 19:21:09,510] Trial 54 finished with value: 0.427132534648724 and parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.24803947359680517, 'lr': 0.005927786012811929, 'weight_decay': 0.07490316217111197, 'batch_size': 32}. Best is trial 51 with value: 0.43407422794617584. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.427133 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.24803947359680517, 'lr': 0.005927786012811929, 'weight_decay': 0.07490316217111197, 'batch_size': 32} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 19:24:59,595] Trial 55 finished with value: 0.4197194348106534 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2490046390973562, 'lr': 0.0038285638564561596, 'weight_decay': 0.05398506440503409, 'batch_size': 32}. Best is trial 51 with value: 0.43407422794617584. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.419719 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2490046390973562, 'lr': 0.0038285638564561596, 'weight_decay': 0.05398506440503409, 'batch_size': 32} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 19:28:30,745] Trial 56 finished with value: 0.39940673759607087 and parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2637445488023327, 'lr': 0.0057400718659215925, 'weight_decay': 0.07486684542201437, 'batch_size': 32}. Best is trial 51 with value: 0.43407422794617584. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.399407 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2637445488023327, 'lr': 0.0057400718659215925, 'weight_decay': 0.07486684542201437, 'batch_size': 32} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 19:29:07,704] Trial 57 pruned. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.322799 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.19272047479576604, 'lr': 0.0010204042812459282, 'weight_decay': 0.04109061550913597, 'batch_size': 32} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 19:32:44,326] Trial 58 pruned. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.348243 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.17590732962824757, 'lr': 0.001886731907218819, 'weight_decay': 0.058328735729890877, 'batch_size': 32} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 19:33:16,324] Trial 59 pruned. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.303901 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.239995074916181, 'lr': 0.002633112385391826, 'weight_decay': 0.027583019436489237, 'batch_size': 32} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 19:38:31,383] Trial 60 finished with value: 0.4308991188902496 and parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.21270708382121373, 'lr': 0.005277156599127611, 'weight_decay': 0.07100057734691462, 'batch_size': 32}. Best is trial 51 with value: 0.43407422794617584. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.430899 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.21270708382121373, 'lr': 0.005277156599127611, 'weight_decay': 0.07100057734691462, 'batch_size': 32} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 19:39:11,897] Trial 61 pruned. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.376658 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.20932512088998403, 'lr': 0.004888466579318628, 'weight_decay': 0.07587152926378347, 'batch_size': 32} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 19:39:50,296] Trial 62 pruned. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.374046 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2189093809995362, 'lr': 0.00780340408333206, 'weight_decay': 0.07967094584167915, 'batch_size': 32} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 19:41:13,543] Trial 63 pruned. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.416185 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.23266325827139642, 'lr': 0.005993168204026863, 'weight_decay': 0.04698579566995875, 'batch_size': 32} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 19:46:34,987] Trial 64 finished with value: 0.41763777750982234 and parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20356247756032733, 'lr': 0.00471789488310128, 'weight_decay': 0.056636190295222766, 'batch_size': 32}. Best is trial 51 with value: 0.43407422794617584. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.417638 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.20356247756032733, 'lr': 0.00471789488310128, 'weight_decay': 0.056636190295222766, 'batch_size': 32} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 19:50:00,536] Trial 65 finished with value: 0.4070351765655115 and parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.22729944987771575, 'lr': 0.0036550016598206132, 'weight_decay': 0.035371927474825884, 'batch_size': 32}. Best is trial 51 with value: 0.43407422794617584. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.407035 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.22729944987771575, 'lr': 0.0036550016598206132, 'weight_decay': 0.035371927474825884, 'batch_size': 32} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 19:50:35,321] Trial 66 pruned. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.259317 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.24436651563167983, 'lr': 0.007875940360112839, 'weight_decay': 0.08348010762488307, 'batch_size': 32} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 19:51:26,682] Trial 67 pruned. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.380723 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.19584489315215609, 'lr': 0.005858802186624893, 'weight_decay': 0.04281084185898097, 'batch_size': 32} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 19:51:38,304] Trial 68 pruned. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.344086 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.2122139164905525, 'lr': 0.0031579606963262397, 'weight_decay': 0.056797423553631404, 'batch_size': 128} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 19:52:13,700] Trial 69 pruned. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.310658 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.23477195854993635, 'lr': 0.004198451015060448, 'weight_decay': 0.07333535112188005, 'batch_size': 32} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 19:58:14,732] Trial 70 finished with value: 0.4032492135727754 and parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2518471429537309, 'lr': 0.009004625048552001, 'weight_decay': 0.09762585069517558, 'batch_size': 32}. Best is trial 51 with value: 0.43407422794617584. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.403249 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2518471429537309, 'lr': 0.009004625048552001, 'weight_decay': 0.09762585069517558, 'batch_size': 32} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 19:58:35,870] Trial 71 pruned. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.388889 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.2228576383603036, 'lr': 0.008007373959863484, 'weight_decay': 0.08715529138598666, 'batch_size': 256} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 20:01:57,902] Trial 72 finished with value: 0.41996973409792965 and parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.21631459337182884, 'lr': 0.006382293155322122, 'weight_decay': 0.09994078754523282, 'batch_size': 64}. Best is trial 51 with value: 0.43407422794617584. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.419970 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.21631459337182884, 'lr': 0.006382293155322122, 'weight_decay': 0.09994078754523282, 'batch_size': 64} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 20:02:29,415] Trial 73 pruned. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.175565 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.22879083305022235, 'lr': 0.009827351717226991, 'weight_decay': 0.06177496236319921, 'batch_size': 32} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 20:03:00,691] Trial 74 pruned. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.402913 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.20612033452910047, 'lr': 0.005693282558569551, 'weight_decay': 0.06801769507785034, 'batch_size': 64} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 20:03:20,293] Trial 75 pruned. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.369710 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.2374748230479039, 'lr': 0.004478186993895352, 'weight_decay': 0.051903959821338067, 'batch_size': 128} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 20:03:38,369] Trial 76 pruned. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.221649 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.24535886083356154, 'lr': 0.00812611875407826, 'weight_decay': 0.07993779922953767, 'batch_size': 64} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 20:04:12,572] Trial 77 pruned. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.335556 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.21911958312498603, 'lr': 0.006534878012297473, 'weight_decay': 0.04409438383706514, 'batch_size': 32} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 20:04:20,856] Trial 78 pruned. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.305357 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.25975254845165796, 'lr': 0.003649796319945675, 'weight_decay': 0.03408499025373447, 'batch_size': 256} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 20:04:50,639] Trial 79 pruned. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.396373 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.19011943260264244, 'lr': 0.005159114067066938, 'weight_decay': 0.06353554019523935, 'batch_size': 64} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 20:05:10,342] Trial 80 pruned. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.359580 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.22710442124516608, 'lr': 0.009869676687408024, 'weight_decay': 0.0871070741602575, 'batch_size': 64} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 20:05:28,525] Trial 81 pruned. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.292929 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.20887823288945753, 'lr': 0.007127703094232709, 'weight_decay': 0.07036069938847393, 'batch_size': 64} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 20:05:47,718] Trial 82 pruned. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.314961 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.19671465103788788, 'lr': 0.00846359060423983, 'weight_decay': 0.05275568207687822, 'batch_size': 64} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 20:06:06,796] Trial 83 pruned. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.278293 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.23695540480940538, 'lr': 0.006463414966220404, 'weight_decay': 0.0849445334042718, 'batch_size': 64} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 20:06:25,927] Trial 84 pruned. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.338422 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.22275974426732878, 'lr': 0.005398972184782542, 'weight_decay': 0.09884881636930135, 'batch_size': 64} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 20:06:59,191] Trial 85 pruned. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.379233 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.2491550488922752, 'lr': 0.0033583043263127202, 'weight_decay': 0.061317073522414764, 'batch_size': 64} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 20:08:31,838] Trial 86 pruned. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.388626 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.2126823549603015, 'lr': 0.004224392324596293, 'weight_decay': 0.04215650420945348, 'batch_size': 32} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 20:08:52,507] Trial 87 pruned. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.350365 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.20047294591397416, 'lr': 0.007012384015873315, 'weight_decay': 0.030103887265738143, 'batch_size': 64} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 20:09:10,421] Trial 88 pruned. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.385681 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.22958427269187817, 'lr': 0.008615158759380797, 'weight_decay': 0.06831267809545653, 'batch_size': 128} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 20:09:48,900] Trial 89 pruned. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.372549 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.18510270795623265, 'lr': 0.004690531455264671, 'weight_decay': 0.05053497484686443, 'batch_size': 64} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 20:15:47,690] Trial 90 finished with value: 0.4339155939492993 and parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2661337802700446, 'lr': 0.0023284381209485055, 'weight_decay': 0.08342499411622561, 'batch_size': 32}. Best is trial 51 with value: 0.43407422794617584. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.433916 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2661337802700446, 'lr': 0.0023284381209485055, 'weight_decay': 0.08342499411622561, 'batch_size': 32} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 20:19:52,943] Trial 91 finished with value: 0.4214778719462193 and parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.26563931257895024, 'lr': 0.002574107371872439, 'weight_decay': 0.08443682533307036, 'batch_size': 32}. Best is trial 51 with value: 0.43407422794617584. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.421478 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.26563931257895024, 'lr': 0.002574107371872439, 'weight_decay': 0.08443682533307036, 'batch_size': 32} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 20:23:25,318] Trial 92 finished with value: 0.41716036262214184 and parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2560738006923415, 'lr': 0.0031229574669147096, 'weight_decay': 0.07285488406601091, 'batch_size': 32}. Best is trial 51 with value: 0.43407422794617584. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.417160 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2560738006923415, 'lr': 0.0031229574669147096, 'weight_decay': 0.07285488406601091, 'batch_size': 32} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 20:24:42,548] Trial 93 pruned. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.382536 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.24141143177477284, 'lr': 0.0022482348483322647, 'weight_decay': 0.06078606510237429, 'batch_size': 32} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 20:29:46,314] Trial 94 finished with value: 0.42500326725304527 and parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.21701059651915255, 'lr': 0.008675808310166717, 'weight_decay': 0.08091015753193935, 'batch_size': 32}. Best is trial 51 with value: 0.43407422794617584. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.425003 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.21701059651915255, 'lr': 0.008675808310166717, 'weight_decay': 0.08091015753193935, 'batch_size': 32} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 20:30:23,265] Trial 95 pruned. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.346260 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.21891960812528677, 'lr': 0.0054107833201511414, 'weight_decay': 0.0805991363417232, 'batch_size': 32} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 20:31:17,116] Trial 96 pruned. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.390995 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.27814244682301226, 'lr': 0.0037286443285049816, 'weight_decay': 0.08730717310482743, 'batch_size': 32} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 20:31:53,566] Trial 97 pruned. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.365789 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.2504994296100569, 'lr': 0.008837309315090603, 'weight_decay': 0.04689625748476855, 'batch_size': 32} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 20:36:08,169] Trial 98 finished with value: 0.41104829724454256 and parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.20586397015001542, 'lr': 0.006795712557385779, 'weight_decay': 0.05589865761672832, 'batch_size': 32}. Best is trial 51 with value: 0.43407422794617584. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.411048 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.20586397015001542, 'lr': 0.006795712557385779, 'weight_decay': 0.05589865761672832, 'batch_size': 32} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 20:41:47,650] Trial 99 finished with value: 0.4198799524659114 and parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2262534272124283, 'lr': 0.004211137199121187, 'weight_decay': 0.09992308248709598, 'batch_size': 32}. Best is trial 51 with value: 0.43407422794617584. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.419880 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2262534272124283, 'lr': 0.004211137199121187, 'weight_decay': 0.09992308248709598, 'batch_size': 32} - Best Value (CSI): 0.434074 - Best Trial: 51 - Best Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.4341 -Best Hyperparameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2100809214334562, 'lr': 0.0045042768238180075, 'weight_decay': 0.09966580216480231, 'batch_size': 32} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.3647 - - 최종 CSI: 0.4199 - - 최고 CSI: 0.4341 - - 최저 CSI: 0.1637 - - 평균 CSI: 0.3694 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/deepgbm_smotenc_ctgan20000_daegu_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 45, Best CSI: 0.4680 - Fold 1 학습 완료 (검증 CSI: 0.4680) -Fold 2 학습 중... - Early stopping at epoch 37, Best CSI: 0.4349 - Fold 2 학습 완료 (검증 CSI: 0.4349) -Fold 3 학습 중... - Early stopping at epoch 27, Best CSI: 0.3607 - Fold 3 학습 완료 (검증 CSI: 0.3607) - -모든 모델 저장 완료: ../save_model/deepgbm_optima/deepgbm_smotenc_ctgan20000_daegu.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/deepgbm_optima/scaler/deepgbm_smotenc_ctgan20000_daegu_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: ../save_model/deepgbm_optima/deepgbm_smotenc_ctgan20000_daegu.pkl - -✓ 완료: deepgbm_smotenc_ctgan20000/deepgbm_smotenc_ctgan20000_daegu.py (소요 시간: 11983초) - ----------------------------------------- -실행 중: deepgbm_smotenc_ctgan20000/deepgbm_smotenc_ctgan20000_daejeon.py -시작 시간: 2025-12-25 20:46:32 ----------------------------------------- -[I 2025-12-25 20:46:33,619] A new study created in memory with name: no-name-fca98561-827d-4155-be33-7d2f5e601517 - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 0.9433658536585365, 1: 0.8871100917431193, 2: 1.2304511039002355} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 0.9428292682926829, 1: 0.8906912442396313, 2: 1.2245311708058795} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15784}) -[I 2025-12-25 20:49:28,839] Trial 0 finished with value: 0.4262594899720438 and parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.21101723172705014, 'lr': 0.00032904926177824474, 'weight_decay': 0.0005335686459176832, 'batch_size': 64}. Best is trial 0 with value: 0.4262594899720438. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.426259 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.21101723172705014, 'lr': 0.00032904926177824474, 'weight_decay': 0.0005335686459176832, 'batch_size': 64} - Best Value (CSI): 0.426259 - Best Trial: 0 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.21101723172705014, 'lr': 0.00032904926177824474, 'weight_decay': 0.0005335686459176832, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 0.9433658536585365, 1: 0.8871100917431193, 2: 1.2304511039002355} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 0.9428292682926829, 1: 0.8906912442396313, 2: 1.2245311708058795} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15784}) -[I 2025-12-25 20:51:43,445] Trial 1 finished with value: 0.37761252619367713 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.37637668416255254, 'lr': 4.0591580335925086e-05, 'weight_decay': 0.0003313851061364189, 'batch_size': 256}. Best is trial 0 with value: 0.4262594899720438. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.377613 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.37637668416255254, 'lr': 4.0591580335925086e-05, 'weight_decay': 0.0003313851061364189, 'batch_size': 256} - Best Value (CSI): 0.426259 - Best Trial: 0 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.21101723172705014, 'lr': 0.00032904926177824474, 'weight_decay': 0.0005335686459176832, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 0.9433658536585365, 1: 0.8871100917431193, 2: 1.2304511039002355} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 0.9428292682926829, 1: 0.8906912442396313, 2: 1.2245311708058795} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15784}) -[I 2025-12-25 20:54:38,537] Trial 2 finished with value: 0.4284431001824986 and parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.20135809721865588, 'lr': 0.0004408130658105509, 'weight_decay': 0.015761320258034627, 'batch_size': 64}. Best is trial 2 with value: 0.4284431001824986. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.428443 - Parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.20135809721865588, 'lr': 0.0004408130658105509, 'weight_decay': 0.015761320258034627, 'batch_size': 64} - Best Value (CSI): 0.428443 - Best Trial: 2 - Best Parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.20135809721865588, 'lr': 0.0004408130658105509, 'weight_decay': 0.015761320258034627, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 0.9433658536585365, 1: 0.8871100917431193, 2: 1.2304511039002355} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 0.9428292682926829, 1: 0.8906912442396313, 2: 1.2245311708058795} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15784}) -[I 2025-12-25 20:56:03,134] Trial 3 finished with value: 0.46394179016547543 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.18046371845819598, 'lr': 0.007259702087428587, 'weight_decay': 0.0006423878376771966, 'batch_size': 128}. Best is trial 3 with value: 0.46394179016547543. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.463942 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.18046371845819598, 'lr': 0.007259702087428587, 'weight_decay': 0.0006423878376771966, 'batch_size': 128} - Best Value (CSI): 0.463942 - Best Trial: 3 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.18046371845819598, 'lr': 0.007259702087428587, 'weight_decay': 0.0006423878376771966, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 0.9433658536585365, 1: 0.8871100917431193, 2: 1.2304511039002355} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 0.9428292682926829, 1: 0.8906912442396313, 2: 1.2245311708058795} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15784}) -[I 2025-12-25 20:57:42,922] Trial 4 finished with value: 0.3761129480891374 and parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.2614339955176517, 'lr': 3.423086082730074e-05, 'weight_decay': 0.01883085482178125, 'batch_size': 256}. Best is trial 3 with value: 0.46394179016547543. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.376113 - Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.2614339955176517, 'lr': 3.423086082730074e-05, 'weight_decay': 0.01883085482178125, 'batch_size': 256} - Best Value (CSI): 0.463942 - Best Trial: 3 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.18046371845819598, 'lr': 0.007259702087428587, 'weight_decay': 0.0006423878376771966, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 0.9433658536585365, 1: 0.8871100917431193, 2: 1.2304511039002355} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 0.9428292682926829, 1: 0.8906912442396313, 2: 1.2245311708058795} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15784}) -[I 2025-12-25 20:59:10,311] Trial 5 finished with value: 0.4495286719767657 and parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.38323514145036885, 'lr': 0.001649216556756964, 'weight_decay': 0.0002454822547733107, 'batch_size': 128}. Best is trial 3 with value: 0.46394179016547543. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.449529 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.38323514145036885, 'lr': 0.001649216556756964, 'weight_decay': 0.0002454822547733107, 'batch_size': 128} - Best Value (CSI): 0.463942 - Best Trial: 3 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.18046371845819598, 'lr': 0.007259702087428587, 'weight_decay': 0.0006423878376771966, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:00:19,820] Trial 6 pruned. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.386473 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.2445687166150087, 'lr': 0.00365514189324657, 'weight_decay': 0.0037412826746722216, 'batch_size': 64} - Best Value (CSI): 0.463942 - Best Trial: 3 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.18046371845819598, 'lr': 0.007259702087428587, 'weight_decay': 0.0006423878376771966, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:00:47,242] Trial 7 pruned. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.322247 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.22483504459808512, 'lr': 0.00013226940862088685, 'weight_decay': 0.002378529339802384, 'batch_size': 32} - Best Value (CSI): 0.463942 - Best Trial: 3 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.18046371845819598, 'lr': 0.007259702087428587, 'weight_decay': 0.0006423878376771966, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:01:34,718] Trial 8 pruned. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.339660 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.1442942912044119, 'lr': 0.0020903096064110466, 'weight_decay': 0.06641112594814864, 'batch_size': 32} - Best Value (CSI): 0.463942 - Best Trial: 3 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.18046371845819598, 'lr': 0.007259702087428587, 'weight_decay': 0.0006423878376771966, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 0.9433658536585365, 1: 0.8871100917431193, 2: 1.2304511039002355} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 0.9428292682926829, 1: 0.8906912442396313, 2: 1.2245311708058795} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15784}) -[I 2025-12-25 21:02:59,293] Trial 9 finished with value: 0.48118035803105963 and parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.24489832566128836, 'lr': 0.008409036563040598, 'weight_decay': 0.08915563100169602, 'batch_size': 256}. Best is trial 9 with value: 0.48118035803105963. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.481180 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.24489832566128836, 'lr': 0.008409036563040598, 'weight_decay': 0.08915563100169602, 'batch_size': 256} - Best Value (CSI): 0.481180 - Best Trial: 9 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.24489832566128836, 'lr': 0.008409036563040598, 'weight_decay': 0.08915563100169602, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:03:33,983] Trial 10 pruned. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.400189 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.10597827716797298, 'lr': 0.00882626295819218, 'weight_decay': 0.07192763765931887, 'batch_size': 256} - Best Value (CSI): 0.481180 - Best Trial: 9 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.24489832566128836, 'lr': 0.008409036563040598, 'weight_decay': 0.08915563100169602, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:04:20,739] Trial 11 pruned. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.411527 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.2883670748062774, 'lr': 0.007167506741677508, 'weight_decay': 0.0011192823464008421, 'batch_size': 128} - Best Value (CSI): 0.481180 - Best Trial: 9 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.24489832566128836, 'lr': 0.008409036563040598, 'weight_decay': 0.08915563100169602, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:04:38,226] Trial 12 pruned. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.361029 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.169652388778825, 'lr': 0.008949523184205159, 'weight_decay': 0.00011464824351005747, 'batch_size': 128} - Best Value (CSI): 0.481180 - Best Trial: 9 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.24489832566128836, 'lr': 0.008409036563040598, 'weight_decay': 0.08915563100169602, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 0.9433658536585365, 1: 0.8871100917431193, 2: 1.2304511039002355} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 0.9428292682926829, 1: 0.8906912442396313, 2: 1.2245311708058795} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15784}) -[I 2025-12-25 21:06:28,402] Trial 13 finished with value: 0.4394321600142265 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.29551756773465965, 'lr': 0.0010634968828297107, 'weight_decay': 0.0040550946798717956, 'batch_size': 128}. Best is trial 9 with value: 0.48118035803105963. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.439432 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.29551756773465965, 'lr': 0.0010634968828297107, 'weight_decay': 0.0040550946798717956, 'batch_size': 128} - Best Value (CSI): 0.481180 - Best Trial: 9 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.24489832566128836, 'lr': 0.008409036563040598, 'weight_decay': 0.08915563100169602, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 0.9433658536585365, 1: 0.8871100917431193, 2: 1.2304511039002355} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 0.9428292682926829, 1: 0.8906912442396313, 2: 1.2245311708058795} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15784}) -[I 2025-12-25 21:07:13,787] Trial 14 finished with value: 0.4489298908426979 and parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.166127693361648, 'lr': 0.0038123506633168753, 'weight_decay': 0.001147575656494536, 'batch_size': 256}. Best is trial 9 with value: 0.48118035803105963. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.448930 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.166127693361648, 'lr': 0.0038123506633168753, 'weight_decay': 0.001147575656494536, 'batch_size': 256} - Best Value (CSI): 0.481180 - Best Trial: 9 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.24489832566128836, 'lr': 0.008409036563040598, 'weight_decay': 0.08915563100169602, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:07:28,222] Trial 15 pruned. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.376562 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.19711303928102408, 'lr': 0.0008780118155778272, 'weight_decay': 0.011499804927084611, 'batch_size': 128} - Best Value (CSI): 0.481180 - Best Trial: 9 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.24489832566128836, 'lr': 0.008409036563040598, 'weight_decay': 0.08915563100169602, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:07:41,839] Trial 16 pruned. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.381434 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.11337836414869765, 'lr': 0.002937375032802072, 'weight_decay': 0.039785435855219854, 'batch_size': 256} - Best Value (CSI): 0.481180 - Best Trial: 9 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.24489832566128836, 'lr': 0.008409036563040598, 'weight_decay': 0.08915563100169602, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:08:26,022] Trial 17 pruned. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.314642 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.2555086163169648, 'lr': 0.004902898336806034, 'weight_decay': 0.007243489545013331, 'batch_size': 32} - Best Value (CSI): 0.481180 - Best Trial: 9 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.24489832566128836, 'lr': 0.008409036563040598, 'weight_decay': 0.08915563100169602, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:08:34,764] Trial 18 pruned. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.361277 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.16913222083933588, 'lr': 0.00984632956276224, 'weight_decay': 0.09803672587215481, 'batch_size': 256} - Best Value (CSI): 0.481180 - Best Trial: 9 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.24489832566128836, 'lr': 0.008409036563040598, 'weight_decay': 0.08915563100169602, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:08:57,883] Trial 19 pruned. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.390459 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.13695033170144744, 'lr': 0.0020079242671124844, 'weight_decay': 0.032355058380779574, 'batch_size': 128} - Best Value (CSI): 0.481180 - Best Trial: 9 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.24489832566128836, 'lr': 0.008409036563040598, 'weight_decay': 0.08915563100169602, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:09:27,672] Trial 20 pruned. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.412963 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.321153785679115, 'lr': 0.0049622960755986295, 'weight_decay': 0.0077296703769385595, 'batch_size': 128} - Best Value (CSI): 0.481180 - Best Trial: 9 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.24489832566128836, 'lr': 0.008409036563040598, 'weight_decay': 0.08915563100169602, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:09:39,924] Trial 21 pruned. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.364381 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.39871399752923675, 'lr': 0.0014913703555511349, 'weight_decay': 0.00023616474927675284, 'batch_size': 128} - Best Value (CSI): 0.481180 - Best Trial: 9 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.24489832566128836, 'lr': 0.008409036563040598, 'weight_decay': 0.08915563100169602, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:09:59,653] Trial 22 pruned. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.394440 - Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.34675629933932606, 'lr': 0.0027554004223360818, 'weight_decay': 0.000762245220937114, 'batch_size': 128} - Best Value (CSI): 0.481180 - Best Trial: 9 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.24489832566128836, 'lr': 0.008409036563040598, 'weight_decay': 0.08915563100169602, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:10:28,825] Trial 23 pruned. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.409914 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.3272991197932211, 'lr': 0.0054557870911055234, 'weight_decay': 0.0019511420664850153, 'batch_size': 128} - Best Value (CSI): 0.481180 - Best Trial: 9 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.24489832566128836, 'lr': 0.008409036563040598, 'weight_decay': 0.08915563100169602, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:10:40,543] Trial 24 pruned. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.357280 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.2858771496548033, 'lr': 0.0011578528241657075, 'weight_decay': 0.00010958405583395432, 'batch_size': 128} - Best Value (CSI): 0.481180 - Best Trial: 9 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.24489832566128836, 'lr': 0.008409036563040598, 'weight_decay': 0.08915563100169602, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:10:52,839] Trial 25 pruned. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.372633 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.23081055907541315, 'lr': 0.004329572611625722, 'weight_decay': 0.00037741101749830887, 'batch_size': 256} - Best Value (CSI): 0.481180 - Best Trial: 9 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.24489832566128836, 'lr': 0.008409036563040598, 'weight_decay': 0.08915563100169602, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:11:23,459] Trial 26 pruned. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.390110 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.26446881975398895, 'lr': 0.002132870624871925, 'weight_decay': 0.0002121976779071309, 'batch_size': 64} - Best Value (CSI): 0.481180 - Best Trial: 9 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.24489832566128836, 'lr': 0.008409036563040598, 'weight_decay': 0.08915563100169602, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:12:30,210] Trial 27 pruned. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.359204 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.23357188257378922, 'lr': 0.0060255307071021245, 'weight_decay': 0.0006647488934516185, 'batch_size': 32} - Best Value (CSI): 0.481180 - Best Trial: 9 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.24489832566128836, 'lr': 0.008409036563040598, 'weight_decay': 0.08915563100169602, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:12:47,349] Trial 28 pruned. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.382382 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.35756642474718736, 'lr': 0.0006939727100590357, 'weight_decay': 0.0014369605147767754, 'batch_size': 128} - Best Value (CSI): 0.481180 - Best Trial: 9 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.24489832566128836, 'lr': 0.008409036563040598, 'weight_decay': 0.08915563100169602, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:13:18,164] Trial 29 pruned. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.360656 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2144213488034115, 'lr': 0.0015988615068126945, 'weight_decay': 0.0005025255070221872, 'batch_size': 64} - Best Value (CSI): 0.481180 - Best Trial: 9 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.24489832566128836, 'lr': 0.008409036563040598, 'weight_decay': 0.08915563100169602, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:13:28,138] Trial 30 pruned. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.366071 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.31353135492791917, 'lr': 0.002940274812184209, 'weight_decay': 0.0008186730463566985, 'batch_size': 256} - Best Value (CSI): 0.481180 - Best Trial: 9 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.24489832566128836, 'lr': 0.008409036563040598, 'weight_decay': 0.08915563100169602, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:13:36,695] Trial 31 pruned. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.370674 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.1874617235650119, 'lr': 0.003644482818412619, 'weight_decay': 0.0009164362720786244, 'batch_size': 256} - Best Value (CSI): 0.481180 - Best Trial: 9 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.24489832566128836, 'lr': 0.008409036563040598, 'weight_decay': 0.08915563100169602, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:13:50,371] Trial 32 pruned. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.365274 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.21532987233517925, 'lr': 0.006453568114558021, 'weight_decay': 0.0014047247844893988, 'batch_size': 256} - Best Value (CSI): 0.481180 - Best Trial: 9 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.24489832566128836, 'lr': 0.008409036563040598, 'weight_decay': 0.08915563100169602, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:14:04,505] Trial 33 pruned. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.382166 - Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.18403611540317585, 'lr': 0.003561473438297543, 'weight_decay': 0.000607534155459557, 'batch_size': 256} - Best Value (CSI): 0.481180 - Best Trial: 9 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.24489832566128836, 'lr': 0.008409036563040598, 'weight_decay': 0.08915563100169602, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:14:12,703] Trial 34 pruned. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.371622 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.20439664568407634, 'lr': 0.009751937369184794, 'weight_decay': 0.0005054826248978718, 'batch_size': 256} - Best Value (CSI): 0.481180 - Best Trial: 9 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.24489832566128836, 'lr': 0.008409036563040598, 'weight_decay': 0.08915563100169602, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:14:21,533] Trial 35 pruned. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.377953 - Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.24273347310142515, 'lr': 0.006148030878072652, 'weight_decay': 0.00035097393175730995, 'batch_size': 256} - Best Value (CSI): 0.481180 - Best Trial: 9 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.24489832566128836, 'lr': 0.008409036563040598, 'weight_decay': 0.08915563100169602, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:15:02,491] Trial 36 pruned. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.378578 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.2664895402934331, 'lr': 0.0006521694070273213, 'weight_decay': 0.0030959861678185427, 'batch_size': 64} - Best Value (CSI): 0.481180 - Best Trial: 9 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.24489832566128836, 'lr': 0.008409036563040598, 'weight_decay': 0.08915563100169602, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:15:20,916] Trial 37 pruned. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.395108 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.21807802058442796, 'lr': 0.0037961161200202737, 'weight_decay': 0.0011713877841381041, 'batch_size': 256} - Best Value (CSI): 0.481180 - Best Trial: 9 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.24489832566128836, 'lr': 0.008409036563040598, 'weight_decay': 0.08915563100169602, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:16:09,841] Trial 38 pruned. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.383117 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.2439763909261289, 'lr': 0.0003514440663251721, 'weight_decay': 0.0017701740005099463, 'batch_size': 32} - Best Value (CSI): 0.481180 - Best Trial: 9 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.24489832566128836, 'lr': 0.008409036563040598, 'weight_decay': 0.08915563100169602, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:16:21,648] Trial 39 pruned. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.290848 - Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.15070470124058294, 'lr': 1.5515931942954363e-05, 'weight_decay': 0.002407732439647774, 'batch_size': 128} - Best Value (CSI): 0.481180 - Best Trial: 9 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.24489832566128836, 'lr': 0.008409036563040598, 'weight_decay': 0.08915563100169602, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:16:28,637] Trial 40 pruned. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.339016 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.3763585315960131, 'lr': 0.00020369967356384842, 'weight_decay': 0.000986042239241149, 'batch_size': 256} - Best Value (CSI): 0.481180 - Best Trial: 9 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.24489832566128836, 'lr': 0.008409036563040598, 'weight_decay': 0.08915563100169602, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 0.9433658536585365, 1: 0.8871100917431193, 2: 1.2304511039002355} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 0.9428292682926829, 1: 0.8906912442396313, 2: 1.2245311708058795} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15784}) -[I 2025-12-25 21:17:56,428] Trial 41 finished with value: 0.4548972752875507 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.28611498964467275, 'lr': 0.002555313921001397, 'weight_decay': 0.004922653582178948, 'batch_size': 128}. Best is trial 9 with value: 0.48118035803105963. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.454897 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.28611498964467275, 'lr': 0.002555313921001397, 'weight_decay': 0.004922653582178948, 'batch_size': 128} - Best Value (CSI): 0.481180 - Best Trial: 9 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.24489832566128836, 'lr': 0.008409036563040598, 'weight_decay': 0.08915563100169602, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 0.9433658536585365, 1: 0.8871100917431193, 2: 1.2304511039002355} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 0.9428292682926829, 1: 0.8906912442396313, 2: 1.2245311708058795} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15784}) -[I 2025-12-25 21:19:45,373] Trial 42 finished with value: 0.4739067741664577 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2813690380757722, 'lr': 0.007364108060332943, 'weight_decay': 0.021392391804391238, 'batch_size': 128}. Best is trial 9 with value: 0.48118035803105963. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.473907 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2813690380757722, 'lr': 0.007364108060332943, 'weight_decay': 0.021392391804391238, 'batch_size': 128} - Best Value (CSI): 0.481180 - Best Trial: 9 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.24489832566128836, 'lr': 0.008409036563040598, 'weight_decay': 0.08915563100169602, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 0.9433658536585365, 1: 0.8871100917431193, 2: 1.2304511039002355} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 0.9428292682926829, 1: 0.8906912442396313, 2: 1.2245311708058795} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15784}) -[I 2025-12-25 21:22:24,903] Trial 43 finished with value: 0.4811835602195654 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.284338319363738, 'lr': 0.006962757874257798, 'weight_decay': 0.02081649568092699, 'batch_size': 128}. Best is trial 43 with value: 0.4811835602195654. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.481184 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.284338319363738, 'lr': 0.006962757874257798, 'weight_decay': 0.02081649568092699, 'batch_size': 128} - Best Value (CSI): 0.481184 - Best Trial: 43 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.284338319363738, 'lr': 0.006962757874257798, 'weight_decay': 0.02081649568092699, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 0.9433658536585365, 1: 0.8871100917431193, 2: 1.2304511039002355} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 0.9428292682926829, 1: 0.8906912442396313, 2: 1.2245311708058795} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15784}) -[I 2025-12-25 21:24:35,232] Trial 44 finished with value: 0.4808147654352907 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.27640451898897334, 'lr': 0.007543093358568035, 'weight_decay': 0.02174392535437996, 'batch_size': 128}. Best is trial 43 with value: 0.4811835602195654. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.480815 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.27640451898897334, 'lr': 0.007543093358568035, 'weight_decay': 0.02174392535437996, 'batch_size': 128} - Best Value (CSI): 0.481184 - Best Trial: 43 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.284338319363738, 'lr': 0.006962757874257798, 'weight_decay': 0.02081649568092699, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 0.9433658536585365, 1: 0.8871100917431193, 2: 1.2304511039002355} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 0.9428292682926829, 1: 0.8906912442396313, 2: 1.2245311708058795} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15784}) -[I 2025-12-25 21:26:57,239] Trial 45 finished with value: 0.48167020129419075 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.27259933582257756, 'lr': 0.007743526940984613, 'weight_decay': 0.02282125726521158, 'batch_size': 128}. Best is trial 45 with value: 0.48167020129419075. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.481670 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.27259933582257756, 'lr': 0.007743526940984613, 'weight_decay': 0.02282125726521158, 'batch_size': 128} - Best Value (CSI): 0.481670 - Best Trial: 45 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.27259933582257756, 'lr': 0.007743526940984613, 'weight_decay': 0.02282125726521158, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:27:31,157] Trial 46 pruned. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.407372 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2728281848814167, 'lr': 0.007676036251741119, 'weight_decay': 0.02311928369727232, 'batch_size': 128} - Best Value (CSI): 0.481670 - Best Trial: 45 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.27259933582257756, 'lr': 0.007743526940984613, 'weight_decay': 0.02282125726521158, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 0.9433658536585365, 1: 0.8871100917431193, 2: 1.2304511039002355} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 0.9428292682926829, 1: 0.8906912442396313, 2: 1.2245311708058795} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15784}) -[I 2025-12-25 21:30:33,545] Trial 47 finished with value: 0.4848928597361463 and parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128}. Best is trial 47 with value: 0.4848928597361463. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.484893 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:31:06,338] Trial 48 pruned. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.408203 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2529559393458279, 'lr': 0.009570690790397043, 'weight_decay': 0.046040703833816386, 'batch_size': 128} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 0.9433658536585365, 1: 0.8871100917431193, 2: 1.2304511039002355} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 0.9428292682926829, 1: 0.8906912442396313, 2: 1.2245311708058795} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15784}) -[I 2025-12-25 21:33:16,448] Trial 49 finished with value: 0.47913001410952166 and parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.29815367806371273, 'lr': 0.006187347395753423, 'weight_decay': 0.014508047935757468, 'batch_size': 128}. Best is trial 47 with value: 0.4848928597361463. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.479130 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.29815367806371273, 'lr': 0.006187347395753423, 'weight_decay': 0.014508047935757468, 'batch_size': 128} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:33:37,985] Trial 50 pruned. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.374625 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.27096416013403246, 'lr': 0.004748062861203474, 'weight_decay': 0.024083777865791935, 'batch_size': 128} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 0.9433658536585365, 1: 0.8871100917431193, 2: 1.2304511039002355} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 0.9428292682926829, 1: 0.8906912442396313, 2: 1.2245311708058795} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15784}) -[I 2025-12-25 21:35:30,117] Trial 51 finished with value: 0.4826587132041303 and parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.3024196472520981, 'lr': 0.007326820636660214, 'weight_decay': 0.014222989318425297, 'batch_size': 128}. Best is trial 47 with value: 0.4848928597361463. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.482659 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.3024196472520981, 'lr': 0.007326820636660214, 'weight_decay': 0.014222989318425297, 'batch_size': 128} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:35:53,929] Trial 52 pruned. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.393459 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.29998234436199417, 'lr': 0.007143216561088489, 'weight_decay': 0.015634499797199195, 'batch_size': 128} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:36:28,939] Trial 53 pruned. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.422101 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.25522400001303186, 'lr': 0.009667479832295336, 'weight_decay': 0.03135578226930194, 'batch_size': 128} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:37:12,562] Trial 54 pruned. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.420434 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.27682698116455784, 'lr': 0.004913042404566072, 'weight_decay': 0.05050830064356937, 'batch_size': 128} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:37:40,039] Trial 55 pruned. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.385017 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2642514982646438, 'lr': 0.007542982794204647, 'weight_decay': 0.01211705783362002, 'batch_size': 128} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 0.9433658536585365, 1: 0.8871100917431193, 2: 1.2304511039002355} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 0.9428292682926829, 1: 0.8906912442396313, 2: 1.2245311708058795} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15784}) -[I 2025-12-25 21:40:19,098] Trial 56 finished with value: 0.4844240760703545 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.29357489655063185, 'lr': 0.005304077634705985, 'weight_decay': 0.027520750919757787, 'batch_size': 128}. Best is trial 47 with value: 0.4848928597361463. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.484424 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.29357489655063185, 'lr': 0.005304077634705985, 'weight_decay': 0.027520750919757787, 'batch_size': 128} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 0.9433658536585365, 1: 0.8871100917431193, 2: 1.2304511039002355} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 0.9428292682926829, 1: 0.8906912442396313, 2: 1.2245311708058795} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15784}) -[I 2025-12-25 21:42:01,456] Trial 57 finished with value: 0.474693972288278 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.30866576502511606, 'lr': 0.0049975745374650615, 'weight_decay': 0.0633397449513323, 'batch_size': 128}. Best is trial 47 with value: 0.4848928597361463. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.474694 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.30866576502511606, 'lr': 0.0049975745374650615, 'weight_decay': 0.0633397449513323, 'batch_size': 128} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:43:43,307] Trial 58 pruned. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.417594 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.2924814695550796, 'lr': 0.0039023688488274556, 'weight_decay': 0.03045252614907524, 'batch_size': 32} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:44:08,046] Trial 59 pruned. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.317443 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.2603850545785468, 'lr': 0.005692969086004813, 'weight_decay': 0.09927239872441294, 'batch_size': 64} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:44:20,114] Trial 60 pruned. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.329126 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.30616232566337487, 'lr': 0.00989853160778781, 'weight_decay': 0.037739709955277624, 'batch_size': 128} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 0.9433658536585365, 1: 0.8871100917431193, 2: 1.2304511039002355} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 0.9428292682926829, 1: 0.8906912442396313, 2: 1.2245311708058795} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15784}) -[I 2025-12-25 21:46:10,376] Trial 61 finished with value: 0.4768835026777287 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2910184690088797, 'lr': 0.007377411355590754, 'weight_decay': 0.01834454750166698, 'batch_size': 128}. Best is trial 47 with value: 0.4848928597361463. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.476884 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2910184690088797, 'lr': 0.007377411355590754, 'weight_decay': 0.01834454750166698, 'batch_size': 128} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:46:29,794] Trial 62 pruned. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.402737 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2768622119677462, 'lr': 0.00792461111596149, 'weight_decay': 0.024055848571056256, 'batch_size': 128} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:46:48,805] Trial 63 pruned. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.399048 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2822245971644818, 'lr': 0.0055737783980538275, 'weight_decay': 0.010497952569368052, 'batch_size': 128} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:47:19,694] Trial 64 pruned. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.410867 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.24899395949250894, 'lr': 0.004370513814320774, 'weight_decay': 0.017835974270869213, 'batch_size': 128} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:47:53,536] Trial 65 pruned. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.431267 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.32249418176575506, 'lr': 0.00302011768170808, 'weight_decay': 0.026530407624991714, 'batch_size': 128} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:48:32,518] Trial 66 pruned. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.433457 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.29774963308584923, 'lr': 0.006289378651212446, 'weight_decay': 0.04214701796900457, 'batch_size': 128} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:48:58,551] Trial 67 pruned. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.400374 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.27094056510424347, 'lr': 0.008189418597413558, 'weight_decay': 0.054248915579466254, 'batch_size': 128} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:50:25,365] Trial 68 pruned. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.403509 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.28730386633631966, 'lr': 0.0021924216689570577, 'weight_decay': 0.034627821018889254, 'batch_size': 32} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 0.9433658536585365, 1: 0.8871100917431193, 2: 1.2304511039002355} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 0.9428292682926829, 1: 0.8906912442396313, 2: 1.2245311708058795} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15784}) -[I 2025-12-25 21:52:10,227] Trial 69 finished with value: 0.47228056504486066 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.24013881327330386, 'lr': 0.0034067009095296624, 'weight_decay': 0.07930598637701577, 'batch_size': 128}. Best is trial 47 with value: 0.4848928597361463. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.472281 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.24013881327330386, 'lr': 0.0034067009095296624, 'weight_decay': 0.07930598637701577, 'batch_size': 128} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 0.9433658536585365, 1: 0.8871100917431193, 2: 1.2304511039002355} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 0.9428292682926829, 1: 0.8906912442396313, 2: 1.2245311708058795} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15784}) -[I 2025-12-25 21:55:58,201] Trial 70 finished with value: 0.4848639846173235 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2627805323298385, 'lr': 0.004401145415017848, 'weight_decay': 0.02866171134528252, 'batch_size': 64}. Best is trial 47 with value: 0.4848928597361463. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.484864 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2627805323298385, 'lr': 0.004401145415017848, 'weight_decay': 0.02866171134528252, 'batch_size': 64} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:56:31,969] Trial 71 pruned. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.403272 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.27856385182863547, 'lr': 0.004494259472352582, 'weight_decay': 0.028410085677772864, 'batch_size': 64} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:57:11,262] Trial 72 pruned. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.401932 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2607551004188599, 'lr': 0.005778210353964066, 'weight_decay': 0.020233331288262664, 'batch_size': 128} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:57:46,827] Trial 73 pruned. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.346275 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.25395857966710816, 'lr': 0.007472302309428705, 'weight_decay': 0.03247929244628862, 'batch_size': 64} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:58:32,686] Trial 74 pruned. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.404473 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2297869718741404, 'lr': 0.00430805586725335, 'weight_decay': 0.04174234083827567, 'batch_size': 64} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:59:17,610] Trial 75 pruned. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.379541 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.26500783956404583, 'lr': 0.00856380349860931, 'weight_decay': 0.017957061370711593, 'batch_size': 64} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 0.9433658536585365, 1: 0.8871100917431193, 2: 1.2304511039002355} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 0.9428292682926829, 1: 0.8906912442396313, 2: 1.2245311708058795} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15784}) -[I 2025-12-25 22:02:12,303] Trial 76 finished with value: 0.46907975651404676 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.3039982142293721, 'lr': 0.006447303150290649, 'weight_decay': 0.026741460619738318, 'batch_size': 64}. Best is trial 47 with value: 0.4848928597361463. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.469080 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.3039982142293721, 'lr': 0.006447303150290649, 'weight_decay': 0.026741460619738318, 'batch_size': 64} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 22:02:31,233] Trial 77 pruned. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.399829 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.2922652626293276, 'lr': 0.005203751412469963, 'weight_decay': 0.013171026544706189, 'batch_size': 128} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 0.9433658536585365, 1: 0.8871100917431193, 2: 1.2304511039002355} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 0.9428292682926829, 1: 0.8906912442396313, 2: 1.2245311708058795} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15784}) -[I 2025-12-25 22:04:30,085] Trial 78 finished with value: 0.47558042800929096 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.3147219122357237, 'lr': 0.0030458707822316423, 'weight_decay': 0.057395842279937645, 'batch_size': 128}. Best is trial 47 with value: 0.4848928597361463. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.475580 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.3147219122357237, 'lr': 0.0030458707822316423, 'weight_decay': 0.057395842279937645, 'batch_size': 128} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 22:04:45,030] Trial 79 pruned. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.411815 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.2720800369212929, 'lr': 0.00834566861020941, 'weight_decay': 0.009960479698931135, 'batch_size': 256} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 0.9433658536585365, 1: 0.8871100917431193, 2: 1.2304511039002355} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 0.9428292682926829, 1: 0.8906912442396313, 2: 1.2245311708058795} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15784}) -[I 2025-12-25 22:06:42,509] Trial 80 finished with value: 0.46250877478901514 and parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.28580434235054003, 'lr': 0.004066707231488422, 'weight_decay': 0.014173168749111774, 'batch_size': 128}. Best is trial 47 with value: 0.4848928597361463. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.462509 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.28580434235054003, 'lr': 0.004066707231488422, 'weight_decay': 0.014173168749111774, 'batch_size': 128} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 22:07:08,503] Trial 81 pruned. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.397612 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.3003029128473533, 'lr': 0.006311411661529209, 'weight_decay': 0.01606354770042392, 'batch_size': 128} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 22:07:34,486] Trial 82 pruned. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.394429 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2984490288372278, 'lr': 0.006790874619870127, 'weight_decay': 0.02062554731749367, 'batch_size': 128} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 22:07:54,959] Trial 83 pruned. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.368164 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2822265875270956, 'lr': 0.008693289138954476, 'weight_decay': 0.014631455389729361, 'batch_size': 128} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 22:08:21,033] Trial 84 pruned. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.396709 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.29345930067793174, 'lr': 0.005477261317380699, 'weight_decay': 0.036743627418298015, 'batch_size': 128} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 22:08:55,802] Trial 85 pruned. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.435018 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.3119630470505606, 'lr': 0.00363774233944351, 'weight_decay': 0.04752629967758706, 'batch_size': 128} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 22:11:12,349] Trial 86 pruned. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.421632 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.24809868960274103, 'lr': 0.0025541097467457956, 'weight_decay': 0.026256301191778297, 'batch_size': 32} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 22:11:24,739] Trial 87 pruned. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.370256 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2691385466742335, 'lr': 0.006331549332167146, 'weight_decay': 0.016477888176712648, 'batch_size': 256} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 22:11:50,571] Trial 88 pruned. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.382766 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.25905727435126585, 'lr': 0.009520057453971319, 'weight_decay': 0.020920058753506828, 'batch_size': 128} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 22:12:21,652] Trial 89 pruned. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.318584 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.27675606764485633, 'lr': 0.004882510664088383, 'weight_decay': 0.009178839907191778, 'batch_size': 64} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 22:12:54,729] Trial 90 pruned. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.422263 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.33118813426411803, 'lr': 0.007196826612193463, 'weight_decay': 0.012680933537315387, 'batch_size': 128} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 22:13:11,694] Trial 91 pruned. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.361742 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.29118734794277984, 'lr': 0.0071946063936407356, 'weight_decay': 0.017549756448256203, 'batch_size': 128} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 22:13:26,477] Trial 92 pruned. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.336266 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.28770740608994494, 'lr': 0.009902328925614918, 'weight_decay': 0.01912514382337648, 'batch_size': 128} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 0.9433658536585365, 1: 0.8871100917431193, 2: 1.2304511039002355} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 0.9428292682926829, 1: 0.8906912442396313, 2: 1.2245311708058795} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15784}) -[I 2025-12-25 22:16:09,983] Trial 93 finished with value: 0.4782856871746312 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.30399221197018894, 'lr': 0.005587344078483064, 'weight_decay': 0.03086909231574752, 'batch_size': 128}. Best is trial 47 with value: 0.4848928597361463. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.478286 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.30399221197018894, 'lr': 0.005587344078483064, 'weight_decay': 0.03086909231574752, 'batch_size': 128} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 22:16:35,816] Trial 94 pruned. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.387812 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.26663731666077267, 'lr': 0.005651492535082516, 'weight_decay': 0.022975238951654577, 'batch_size': 128} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 22:17:18,565] Trial 95 pruned. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.399431 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.27946131687001685, 'lr': 0.004426067031478167, 'weight_decay': 0.030510826027656587, 'batch_size': 128} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 22:17:39,991] Trial 96 pruned. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.406764 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.30588821276698747, 'lr': 0.008450743971849828, 'weight_decay': 0.035970417318175844, 'batch_size': 128} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 22:17:52,507] Trial 97 pruned. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.403226 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.315723666768097, 'lr': 0.005240085946549746, 'weight_decay': 0.042652992628428595, 'batch_size': 256} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 0.9433658536585365, 1: 0.8871100917431193, 2: 1.2304511039002355} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 0.9428292682926829, 1: 0.8906912442396313, 2: 1.2245311708058795} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15784}) -[I 2025-12-25 22:19:22,601] Trial 98 finished with value: 0.46361115734747677 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2996171042730319, 'lr': 0.00323290218084579, 'weight_decay': 0.025058497000452918, 'batch_size': 128}. Best is trial 47 with value: 0.4848928597361463. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.463611 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2996171042730319, 'lr': 0.00323290218084579, 'weight_decay': 0.025058497000452918, 'batch_size': 128} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 22:19:44,013] Trial 99 pruned. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.406946 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.2736092397710576, 'lr': 0.003967032998237749, 'weight_decay': 0.014496634087094515, 'batch_size': 128} - Best Value (CSI): 0.484893 - Best Trial: 47 - Best Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.4849 -Best Hyperparameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.2751230389403302, 'lr': 0.007765569142416956, 'weight_decay': 0.019237770834817113, 'batch_size': 128} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.4263 - - 최종 CSI: 0.4069 - - 최고 CSI: 0.4849 - - 최저 CSI: 0.2908 - - 평균 CSI: 0.4044 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/deepgbm_smotenc_ctgan20000_daejeon_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 42, Best CSI: 0.4353 - Fold 1 학습 완료 (검증 CSI: 0.4353) -Fold 2 학습 중... - Early stopping at epoch 19, Best CSI: 0.4869 - Fold 2 학습 완료 (검증 CSI: 0.4869) -Fold 3 학습 중... - Early stopping at epoch 36, Best CSI: 0.5338 - Fold 3 학습 완료 (검증 CSI: 0.5338) - -모든 모델 저장 완료: ../save_model/deepgbm_optima/deepgbm_smotenc_ctgan20000_daejeon.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/deepgbm_optima/scaler/deepgbm_smotenc_ctgan20000_daejeon_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: ../save_model/deepgbm_optima/deepgbm_smotenc_ctgan20000_daejeon.pkl - -✓ 완료: deepgbm_smotenc_ctgan20000/deepgbm_smotenc_ctgan20000_daejeon.py (소요 시간: 5740초) - ----------------------------------------- -실행 중: deepgbm_smotenc_ctgan20000/deepgbm_smotenc_ctgan20000_gwangju.py -시작 시간: 2025-12-25 22:22:12 ----------------------------------------- -[I 2025-12-25 22:22:13,993] A new study created in memory with name: no-name-d2c3d161-8daf-41cf-933a-f5374fc41acb - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-25 22:24:08,266] Trial 0 finished with value: 0.3914969362009899 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.1005969536528481, 'lr': 9.106420380441998e-05, 'weight_decay': 0.00024631062407710143, 'batch_size': 256}. Best is trial 0 with value: 0.3914969362009899. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.391497 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.1005969536528481, 'lr': 9.106420380441998e-05, 'weight_decay': 0.00024631062407710143, 'batch_size': 256} - Best Value (CSI): 0.391497 - Best Trial: 0 - Best Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.1005969536528481, 'lr': 9.106420380441998e-05, 'weight_decay': 0.00024631062407710143, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-25 22:27:01,897] Trial 1 finished with value: 0.4490234094416914 and parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2800153824343252, 'lr': 0.0006426978978963236, 'weight_decay': 0.0002771814864448882, 'batch_size': 64}. Best is trial 1 with value: 0.4490234094416914. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.449023 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2800153824343252, 'lr': 0.0006426978978963236, 'weight_decay': 0.0002771814864448882, 'batch_size': 64} - Best Value (CSI): 0.449023 - Best Trial: 1 - Best Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 2, 'dropout': 0.2800153824343252, 'lr': 0.0006426978978963236, 'weight_decay': 0.0002771814864448882, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-25 22:32:01,283] Trial 2 finished with value: 0.4832850681063274 and parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64}. Best is trial 2 with value: 0.4832850681063274. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.483285 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-25 22:33:17,138] Trial 3 finished with value: 0.46209732074500826 and parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.15382979787722542, 'lr': 0.0048153117236909805, 'weight_decay': 0.00836147136484166, 'batch_size': 256}. Best is trial 2 with value: 0.4832850681063274. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.462097 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.15382979787722542, 'lr': 0.0048153117236909805, 'weight_decay': 0.00836147136484166, 'batch_size': 256} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-25 22:38:35,880] Trial 4 finished with value: 0.44662669651384457 and parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.2012826167008137, 'lr': 0.0004745986869838708, 'weight_decay': 0.030997494280022273, 'batch_size': 32}. Best is trial 2 with value: 0.4832850681063274. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.446627 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.2012826167008137, 'lr': 0.0004745986869838708, 'weight_decay': 0.030997494280022273, 'batch_size': 32} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:39:05,897] Trial 5 pruned. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.355042 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.33300494559993876, 'lr': 0.00010467119807363395, 'weight_decay': 0.019421753007736225, 'batch_size': 64} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:39:29,452] Trial 6 pruned. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.395445 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.10418943609452273, 'lr': 0.0003482604316403126, 'weight_decay': 0.016655087073069005, 'batch_size': 256} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:40:53,895] Trial 7 pruned. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.378251 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.3791838796178063, 'lr': 0.0007944001031089349, 'weight_decay': 0.0005643542319288052, 'batch_size': 32} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:41:40,262] Trial 8 pruned. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.379787 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.15981188089818552, 'lr': 0.0001780970969454513, 'weight_decay': 0.00030343867571144313, 'batch_size': 64} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-25 22:42:59,361] Trial 9 finished with value: 0.44560810472430235 and parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.20554963703698184, 'lr': 0.0012819942638136947, 'weight_decay': 0.0005796746714362216, 'batch_size': 64}. Best is trial 2 with value: 0.4832850681063274. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.445608 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.20554963703698184, 'lr': 0.0012819942638136947, 'weight_decay': 0.0005796746714362216, 'batch_size': 64} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:43:19,318] Trial 10 pruned. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.297587 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.29188775703175424, 'lr': 0.009913974040037141, 'weight_decay': 0.08066185951083446, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:43:28,991] Trial 11 pruned. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.359801 - Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.23977557359531745, 'lr': 0.007764804235280423, 'weight_decay': 0.004156952695486679, 'batch_size': 256} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:43:51,645] Trial 12 pruned. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.364169 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.33612673067815574, 'lr': 0.003018909056657062, 'weight_decay': 0.0027964716579474604, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:44:00,822] Trial 13 pruned. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.268085 - Parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.15920244233429115, 'lr': 1.5556000751724564e-05, 'weight_decay': 0.004649100730992759, 'batch_size': 256} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:44:22,063] Trial 14 pruned. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.277062 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.3866630328335943, 'lr': 0.0034424027684260487, 'weight_decay': 0.0019971894495344348, 'batch_size': 64} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:44:37,220] Trial 15 pruned. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.363423 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.27203148114404235, 'lr': 0.003292922224233365, 'weight_decay': 0.006752045900919438, 'batch_size': 256} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:44:50,181] Trial 16 pruned. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.280285 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.3188051025491085, 'lr': 0.009398000920422278, 'weight_decay': 0.0015622435851774016, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:45:26,958] Trial 17 pruned. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.348079 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.362209808885587, 'lr': 0.0017615741745661787, 'weight_decay': 0.00010224554980671716, 'batch_size': 32} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:45:44,250] Trial 18 pruned. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.330539 - Parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.2467967864538977, 'lr': 0.005071423052666507, 'weight_decay': 0.008463836149891074, 'batch_size': 256} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:46:06,207] Trial 19 pruned. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.332117 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.3109575217251736, 'lr': 0.001907568706004695, 'weight_decay': 0.008974569643014452, 'batch_size': 64} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-25 22:47:12,863] Trial 20 finished with value: 0.47467736850738945 and parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.3391713729243251, 'lr': 0.005154123509073468, 'weight_decay': 0.0013100023348637823, 'batch_size': 256}. Best is trial 2 with value: 0.4832850681063274. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.474677 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.3391713729243251, 'lr': 0.005154123509073468, 'weight_decay': 0.0013100023348637823, 'batch_size': 256} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:47:20,761] Trial 21 pruned. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.335758 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.35228792761741656, 'lr': 0.0051072777364021575, 'weight_decay': 0.0014676161052040227, 'batch_size': 256} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:47:28,516] Trial 22 pruned. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.332924 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2979545427569133, 'lr': 0.0058937096622344145, 'weight_decay': 0.0030233829962338613, 'batch_size': 256} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-25 22:48:37,525] Trial 23 finished with value: 0.46152269174610555 and parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.34429415752022674, 'lr': 0.0026196531142408963, 'weight_decay': 0.0012077808614528581, 'batch_size': 256}. Best is trial 2 with value: 0.4832850681063274. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.461523 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.34429415752022674, 'lr': 0.0026196531142408963, 'weight_decay': 0.0012077808614528581, 'batch_size': 256} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:48:45,096] Trial 24 pruned. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.357569 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.317729291448378, 'lr': 0.0012642392640698458, 'weight_decay': 0.004744950473102117, 'batch_size': 256} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:49:04,459] Trial 25 pruned. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.347500 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.3941388199404078, 'lr': 0.005306849436722333, 'weight_decay': 0.0024501012977334985, 'batch_size': 64} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-25 22:50:25,248] Trial 26 finished with value: 0.46354769238393456 and parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.36530496476049584, 'lr': 0.004301550316843092, 'weight_decay': 0.010891762518604346, 'batch_size': 128}. Best is trial 2 with value: 0.4832850681063274. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.463548 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.36530496476049584, 'lr': 0.004301550316843092, 'weight_decay': 0.010891762518604346, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-25 22:51:55,375] Trial 27 finished with value: 0.4763354759206342 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.36628641331682654, 'lr': 0.009339719796417296, 'weight_decay': 0.015259278594557491, 'batch_size': 128}. Best is trial 2 with value: 0.4832850681063274. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.476335 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.36628641331682654, 'lr': 0.009339719796417296, 'weight_decay': 0.015259278594557491, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:52:05,385] Trial 28 pruned. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.271028 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.36968901928401093, 'lr': 0.007777489527765142, 'weight_decay': 0.037300833162262674, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-25 22:53:31,766] Trial 29 finished with value: 0.4619882052837505 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.39870152813014903, 'lr': 0.009527536002147115, 'weight_decay': 0.0009342753933426574, 'batch_size': 128}. Best is trial 2 with value: 0.4832850681063274. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.461988 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.39870152813014903, 'lr': 0.009527536002147115, 'weight_decay': 0.0009342753933426574, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:53:48,522] Trial 30 pruned. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.339576 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.352760459215956, 'lr': 0.0021457899903276558, 'weight_decay': 0.005016171330066203, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:54:00,637] Trial 31 pruned. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.343001 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.38132903853031946, 'lr': 0.00393090055438325, 'weight_decay': 0.012353747865064593, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-25 22:55:03,762] Trial 32 finished with value: 0.4572021950070324 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.366777294382283, 'lr': 0.006377225437427263, 'weight_decay': 0.011120970962374573, 'batch_size': 128}. Best is trial 2 with value: 0.4832850681063274. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.457202 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.366777294382283, 'lr': 0.006377225437427263, 'weight_decay': 0.011120970962374573, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:55:16,675] Trial 33 pruned. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.360494 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.33434358053781027, 'lr': 0.004461418942109357, 'weight_decay': 0.006784460113560662, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-25 22:56:48,494] Trial 34 finished with value: 0.4644290417231065 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3735571099790338, 'lr': 0.003011791421017191, 'weight_decay': 0.0038057823600348276, 'batch_size': 128}. Best is trial 2 with value: 0.4832850681063274. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.464429 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3735571099790338, 'lr': 0.003011791421017191, 'weight_decay': 0.0038057823600348276, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:57:26,228] Trial 35 pruned. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.223013 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.34426565258489045, 'lr': 0.009986582264340087, 'weight_decay': 0.0032469985955951583, 'batch_size': 32} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-25 22:59:40,145] Trial 36 finished with value: 0.4639132985072327 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3211828540908625, 'lr': 0.0026204213264570046, 'weight_decay': 0.001938240829847954, 'batch_size': 64}. Best is trial 2 with value: 0.4832850681063274. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.463913 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3211828540908625, 'lr': 0.0026204213264570046, 'weight_decay': 0.001938240829847954, 'batch_size': 64} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-25 23:01:01,545] Trial 37 finished with value: 0.47373144078881024 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.38190964257972215, 'lr': 0.005919744704054083, 'weight_decay': 0.00587910421633594, 'batch_size': 128}. Best is trial 2 with value: 0.4832850681063274. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.473731 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.38190964257972215, 'lr': 0.005919744704054083, 'weight_decay': 0.00587910421633594, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-25 23:03:25,221] Trial 38 finished with value: 0.47021249124259645 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.3978868128232501, 'lr': 0.00658770674575674, 'weight_decay': 0.02177455515477852, 'batch_size': 64}. Best is trial 2 with value: 0.4832850681063274. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.470212 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.3978868128232501, 'lr': 0.00658770674575674, 'weight_decay': 0.02177455515477852, 'batch_size': 64} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:04:01,433] Trial 39 pruned. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.324353 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.35846075390041665, 'lr': 0.006770136651049132, 'weight_decay': 0.006123847802988946, 'batch_size': 32} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:04:29,009] Trial 40 pruned. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.373536 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3810640500274266, 'lr': 0.0006742690891153435, 'weight_decay': 0.015862860392165647, 'batch_size': 64} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-25 23:06:31,538] Trial 41 finished with value: 0.4656580313645577 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.3981208758027062, 'lr': 0.006694479310270003, 'weight_decay': 0.019126848493060813, 'batch_size': 64}. Best is trial 2 with value: 0.4832850681063274. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.465658 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.3981208758027062, 'lr': 0.006694479310270003, 'weight_decay': 0.019126848493060813, 'batch_size': 64} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:06:56,785] Trial 42 pruned. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.323810 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.3783770341662833, 'lr': 0.0043431001487228334, 'weight_decay': 0.03136625934126597, 'batch_size': 64} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:07:22,890] Trial 43 pruned. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.332889 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.34898520498150337, 'lr': 0.0063337501378291205, 'weight_decay': 0.021831553254289832, 'batch_size': 64} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-25 23:10:08,116] Trial 44 finished with value: 0.4665117600046857 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3383766980998423, 'lr': 0.007852289710540488, 'weight_decay': 0.012795706280567063, 'batch_size': 64}. Best is trial 2 with value: 0.4832850681063274. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.466512 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3383766980998423, 'lr': 0.007852289710540488, 'weight_decay': 0.012795706280567063, 'batch_size': 64} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:10:34,878] Trial 45 pruned. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.345616 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3882820272494991, 'lr': 0.0035247635520507226, 'weight_decay': 0.006410367279124853, 'batch_size': 64} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:10:50,852] Trial 46 pruned. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.384431 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.33111005629953494, 'lr': 0.005045059420725095, 'weight_decay': 0.025862282204055672, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:11:27,991] Trial 47 pruned. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.266791 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.35682885403615, 'lr': 0.009787646180378253, 'weight_decay': 0.016225044749668637, 'batch_size': 32} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-25 23:14:38,282] Trial 48 finished with value: 0.4563438542159066 and parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.3710330570584067, 'lr': 0.0012604974616036385, 'weight_decay': 0.04320465339749285, 'batch_size': 64}. Best is trial 2 with value: 0.4832850681063274. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.456344 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.3710330570584067, 'lr': 0.0012604974616036385, 'weight_decay': 0.04320465339749285, 'batch_size': 64} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-25 23:16:06,987] Trial 49 finished with value: 0.4773549731338256 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.38711196363843936, 'lr': 0.007262066409069914, 'weight_decay': 0.04972496383809627, 'batch_size': 128}. Best is trial 2 with value: 0.4832850681063274. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.477355 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.38711196363843936, 'lr': 0.007262066409069914, 'weight_decay': 0.04972496383809627, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:16:23,265] Trial 50 pruned. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.348168 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.3858111512386037, 'lr': 0.0035612870727074466, 'weight_decay': 0.04786149768006714, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:16:39,974] Trial 51 pruned. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.358612 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.39406056514955823, 'lr': 0.007234862223556834, 'weight_decay': 0.08235827642267513, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:16:56,899] Trial 52 pruned. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.375309 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.3632830769082415, 'lr': 0.005820155647848395, 'weight_decay': 0.05770847719352885, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-25 23:17:57,607] Trial 53 finished with value: 0.4754556034362705 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.39834704273126204, 'lr': 0.007924421840144552, 'weight_decay': 0.02402252926556552, 'batch_size': 128}. Best is trial 2 with value: 0.4832850681063274. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.475456 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.39834704273126204, 'lr': 0.007924421840144552, 'weight_decay': 0.02402252926556552, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:18:13,386] Trial 54 pruned. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.329502 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3758321489359507, 'lr': 0.008079322743907671, 'weight_decay': 0.027579971716862512, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:18:27,685] Trial 55 pruned. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.349105 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3533508379987766, 'lr': 0.0042702306918374995, 'weight_decay': 0.060241627385951714, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:18:38,325] Trial 56 pruned. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.313850 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3853512946509898, 'lr': 0.0025968322426770177, 'weight_decay': 0.032172857786145356, 'batch_size': 256} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:18:56,074] Trial 57 pruned. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.329936 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.32858461241902387, 'lr': 0.005183914418428007, 'weight_decay': 0.008855669122951128, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-25 23:20:12,665] Trial 58 finished with value: 0.4814271786552286 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.30948560445510426, 'lr': 0.009970385564610116, 'weight_decay': 0.013887119168940188, 'batch_size': 128}. Best is trial 2 with value: 0.4832850681063274. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.481427 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.30948560445510426, 'lr': 0.009970385564610116, 'weight_decay': 0.013887119168940188, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:20:23,277] Trial 59 pruned. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.334586 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.3086343099289128, 'lr': 0.009793571447098469, 'weight_decay': 0.09712343862421366, 'batch_size': 256} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:20:39,172] Trial 60 pruned. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.363218 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.32482956953765735, 'lr': 0.00802582984966101, 'weight_decay': 0.014782189794453789, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:20:53,166] Trial 61 pruned. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.347607 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.34338505821613385, 'lr': 0.0055458452598045865, 'weight_decay': 0.019702223539195412, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:21:09,305] Trial 62 pruned. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.383275 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.28090582673994446, 'lr': 0.008082100426959142, 'weight_decay': 0.010516745296717181, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-25 23:22:30,629] Trial 63 finished with value: 0.46435118648017415 and parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3655885292214273, 'lr': 0.0038325042950142774, 'weight_decay': 0.007658490402361315, 'batch_size': 128}. Best is trial 2 with value: 0.4832850681063274. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.464351 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3655885292214273, 'lr': 0.0038325042950142774, 'weight_decay': 0.007658490402361315, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:22:47,102] Trial 64 pruned. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.363073 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3394163211556534, 'lr': 0.005322155248779461, 'weight_decay': 0.004830084699129099, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:22:59,239] Trial 65 pruned. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.336306 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.3062555620062305, 'lr': 0.007517754971596113, 'weight_decay': 0.01361337878801424, 'batch_size': 256} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:23:14,658] Trial 66 pruned. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.319629 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.37309470978775383, 'lr': 0.009761755892159208, 'weight_decay': 0.02592825284344551, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-25 23:24:47,617] Trial 67 finished with value: 0.46534020382452906 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3598614822213377, 'lr': 0.004575031218885208, 'weight_decay': 0.009972131898757152, 'batch_size': 128}. Best is trial 2 with value: 0.4832850681063274. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.465340 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3598614822213377, 'lr': 0.004575031218885208, 'weight_decay': 0.009972131898757152, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-25 23:25:55,465] Trial 68 finished with value: 0.4687949301483345 and parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.38900220192855833, 'lr': 0.005914949882280429, 'weight_decay': 0.003932154573111431, 'batch_size': 128}. Best is trial 2 with value: 0.4832850681063274. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.468795 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.38900220192855833, 'lr': 0.005914949882280429, 'weight_decay': 0.003932154573111431, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:26:06,643] Trial 69 pruned. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.330729 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3496613695814781, 'lr': 0.008300023069876402, 'weight_decay': 0.007944676456925443, 'batch_size': 256} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:26:56,714] Trial 70 pruned. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.339130 - Parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.37954403140892984, 'lr': 0.0031642233400748926, 'weight_decay': 0.017084109188035906, 'batch_size': 32} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:27:18,280] Trial 71 pruned. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.335484 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.39792185561611537, 'lr': 0.006637945463801181, 'weight_decay': 0.02299450556287274, 'batch_size': 64} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:27:42,233] Trial 72 pruned. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.357881 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.3872270414285178, 'lr': 0.006359425662464759, 'weight_decay': 0.03646840203585204, 'batch_size': 64} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-25 23:29:06,081] Trial 73 finished with value: 0.4726118234463648 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3934191933618364, 'lr': 0.004762012143515294, 'weight_decay': 0.019600871187309132, 'batch_size': 128}. Best is trial 2 with value: 0.4832850681063274. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.472612 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3934191933618364, 'lr': 0.004762012143515294, 'weight_decay': 0.019600871187309132, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:29:23,064] Trial 74 pruned. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.351250 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.37018320667678395, 'lr': 0.004224403989096567, 'weight_decay': 0.012069197619808604, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:29:40,989] Trial 75 pruned. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.392361 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3589510913349602, 'lr': 0.005216355816743394, 'weight_decay': 0.005527383921710401, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:29:57,162] Trial 76 pruned. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.316883 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.378679110842704, 'lr': 0.00839063022877975, 'weight_decay': 0.01786275773214014, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:30:11,811] Trial 77 pruned. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.338028 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3920309812244853, 'lr': 0.009917516331123678, 'weight_decay': 0.014527006007614786, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:30:30,488] Trial 78 pruned. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.283290 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.33453920305894835, 'lr': 0.007020823375409739, 'weight_decay': 0.009957977252845003, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:30:41,774] Trial 79 pruned. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.396249 - Parameters: {'d_main': 96, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.3167916362544814, 'lr': 0.0037705320451241336, 'weight_decay': 0.00258281359221636, 'batch_size': 256} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:30:58,248] Trial 80 pruned. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.352798 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.34732018987698293, 'lr': 0.0045986188384404166, 'weight_decay': 0.0076715134016013846, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) -[I 2025-12-25 23:31:55,313] Trial 81 pruned. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.498282 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.39599511728348813, 'lr': 0.00621006172030482, 'weight_decay': 0.022125193154988884, 'batch_size': 64} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:32:21,044] Trial 82 pruned. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.341207 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.38997814662187885, 'lr': 0.0073691794018006795, 'weight_decay': 0.01976563378910939, 'batch_size': 64} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:32:35,368] Trial 83 pruned. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.312420 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.38304220126073135, 'lr': 0.008519484273262776, 'weight_decay': 0.02887991300588204, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:33:31,415] Trial 84 pruned. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.376721 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.398945376417183, 'lr': 0.005897569873484095, 'weight_decay': 0.02381470091512575, 'batch_size': 32} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:33:47,712] Trial 85 pruned. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.367104 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3724762433085644, 'lr': 0.0029422060599869656, 'weight_decay': 0.014457701083360192, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:34:16,915] Trial 86 pruned. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.310479 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3661097828696568, 'lr': 0.004817554977301824, 'weight_decay': 0.012102343898671321, 'batch_size': 64} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:34:25,660] Trial 87 pruned. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.250000 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.3806915863216654, 'lr': 0.0069584949262775355, 'weight_decay': 0.03634768789445125, 'batch_size': 256} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:34:43,584] Trial 88 pruned. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.325611 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.39100668663900123, 'lr': 0.008917205470864187, 'weight_decay': 0.0034373627583911886, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:34:58,005] Trial 89 pruned. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.300475 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.36099600314289704, 'lr': 0.0034235712944343123, 'weight_decay': 0.030630504073245374, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:35:25,949] Trial 90 pruned. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.296392 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.37665379448560177, 'lr': 0.0056550981795301354, 'weight_decay': 0.01974024623897317, 'batch_size': 64} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:35:41,325] Trial 91 pruned. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.384988 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.38861855684218577, 'lr': 0.006430244013697935, 'weight_decay': 0.005555524203764986, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:35:55,465] Trial 92 pruned. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.342965 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.399874395094421, 'lr': 0.004071208607427997, 'weight_decay': 0.0029628906611872583, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:36:11,085] Trial 93 pruned. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.363962 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.3862285334885257, 'lr': 0.007371126705309927, 'weight_decay': 0.002269814891939352, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) -[I 2025-12-25 23:36:46,349] Trial 94 pruned. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.501029 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.36937544967024094, 'lr': 0.008792824740803541, 'weight_decay': 0.004178520445195884, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-25 23:38:19,920] Trial 95 finished with value: 0.4745812926591617 and parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3899684211463129, 'lr': 0.00508619492869192, 'weight_decay': 0.0042134905428849794, 'batch_size': 128}. Best is trial 2 with value: 0.4832850681063274. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.474581 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.3899684211463129, 'lr': 0.00508619492869192, 'weight_decay': 0.0042134905428849794, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:38:36,167] Trial 96 pruned. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.353165 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3550580974713845, 'lr': 0.0055344663322735126, 'weight_decay': 0.01617834254615003, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:38:46,710] Trial 97 pruned. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.326276 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.37516935677893853, 'lr': 0.004657364323796894, 'weight_decay': 0.00675832014038623, 'batch_size': 256} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:39:02,800] Trial 98 pruned. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.326873 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.38178102745337067, 'lr': 0.009971262404789526, 'weight_decay': 0.009299117286042031, 'batch_size': 128} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-25 23:41:38,073] Trial 99 finished with value: 0.454180750021214 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3933961142810686, 'lr': 0.0071016030591518646, 'weight_decay': 0.01107627951948891, 'batch_size': 64}. Best is trial 2 with value: 0.4832850681063274. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.454181 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.3933961142810686, 'lr': 0.0071016030591518646, 'weight_decay': 0.01107627951948891, 'batch_size': 64} - Best Value (CSI): 0.483285 - Best Trial: 2 - Best Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.4833 -Best Hyperparameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.3184031589315668, 'lr': 0.00908394353608693, 'weight_decay': 0.005195807637314873, 'batch_size': 64} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.3915 - - 최종 CSI: 0.4542 - - 최고 CSI: 0.5010 - - 최저 CSI: 0.2230 - - 평균 CSI: 0.3758 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/deepgbm_smotenc_ctgan20000_gwangju_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 47, Best CSI: 0.4493 - Fold 1 학습 완료 (검증 CSI: 0.4493) -Fold 2 학습 중... - Early stopping at epoch 49, Best CSI: 0.5379 - Fold 2 학습 완료 (검증 CSI: 0.5379) -Fold 3 학습 중... - Early stopping at epoch 38, Best CSI: 0.5036 - Fold 3 학습 완료 (검증 CSI: 0.5036) - -모든 모델 저장 완료: ../save_model/deepgbm_optima/deepgbm_smotenc_ctgan20000_gwangju.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/deepgbm_optima/scaler/deepgbm_smotenc_ctgan20000_gwangju_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: ../save_model/deepgbm_optima/deepgbm_smotenc_ctgan20000_gwangju.pkl - -✓ 완료: deepgbm_smotenc_ctgan20000/deepgbm_smotenc_ctgan20000_gwangju.py (소요 시간: 5011초) - ----------------------------------------- -실행 중: deepgbm_smotenc_ctgan20000/deepgbm_smotenc_ctgan20000_incheon.py -시작 시간: 2025-12-25 23:45:43 ----------------------------------------- -[I 2025-12-25 23:45:44,808] A new study created in memory with name: no-name-ca31852a-8e14-4a7d-b3d5-5beadf95467a - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-25 23:47:26,918] Trial 0 finished with value: 0.54044559241215 and parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.3667052648040591, 'lr': 0.0019007657888356479, 'weight_decay': 0.0022412385655779226, 'batch_size': 64}. Best is trial 0 with value: 0.54044559241215. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.540446 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.3667052648040591, 'lr': 0.0019007657888356479, 'weight_decay': 0.0022412385655779226, 'batch_size': 64} - Best Value (CSI): 0.540446 - Best Trial: 0 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.3667052648040591, 'lr': 0.0019007657888356479, 'weight_decay': 0.0022412385655779226, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-25 23:49:00,886] Trial 1 finished with value: 0.5059505530556793 and parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.28950660981777837, 'lr': 0.0001201402245665964, 'weight_decay': 0.0001727707593349708, 'batch_size': 128}. Best is trial 0 with value: 0.54044559241215. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.505951 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.28950660981777837, 'lr': 0.0001201402245665964, 'weight_decay': 0.0001727707593349708, 'batch_size': 128} - Best Value (CSI): 0.540446 - Best Trial: 0 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.3667052648040591, 'lr': 0.0019007657888356479, 'weight_decay': 0.0022412385655779226, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-25 23:50:06,634] Trial 2 finished with value: 0.5341442398644815 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.20134548227098573, 'lr': 0.001866779904833721, 'weight_decay': 0.0010820972195939363, 'batch_size': 128}. Best is trial 0 with value: 0.54044559241215. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.534144 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.20134548227098573, 'lr': 0.001866779904833721, 'weight_decay': 0.0010820972195939363, 'batch_size': 128} - Best Value (CSI): 0.540446 - Best Trial: 0 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.3667052648040591, 'lr': 0.0019007657888356479, 'weight_decay': 0.0022412385655779226, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-25 23:54:05,324] Trial 3 finished with value: 0.5287648277131348 and parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.15336000999474075, 'lr': 0.0021730156931134563, 'weight_decay': 0.0013088301573688959, 'batch_size': 32}. Best is trial 0 with value: 0.54044559241215. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.528765 - Parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.15336000999474075, 'lr': 0.0021730156931134563, 'weight_decay': 0.0013088301573688959, 'batch_size': 32} - Best Value (CSI): 0.540446 - Best Trial: 0 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.3667052648040591, 'lr': 0.0019007657888356479, 'weight_decay': 0.0022412385655779226, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-25 23:55:20,977] Trial 4 finished with value: 0.5289736293053533 and parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.21509639780137682, 'lr': 0.0012927196883953352, 'weight_decay': 0.04148662110058731, 'batch_size': 128}. Best is trial 0 with value: 0.54044559241215. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.528974 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.21509639780137682, 'lr': 0.0012927196883953352, 'weight_decay': 0.04148662110058731, 'batch_size': 128} - Best Value (CSI): 0.540446 - Best Trial: 0 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.3667052648040591, 'lr': 0.0019007657888356479, 'weight_decay': 0.0022412385655779226, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-25 23:55:36,808] Trial 5 pruned. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.447813 - Parameters: {'d_main': 160, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.3959963040577539, 'lr': 0.00011182494828586522, 'weight_decay': 0.002136410736447527, 'batch_size': 128} - Best Value (CSI): 0.540446 - Best Trial: 0 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.3667052648040591, 'lr': 0.0019007657888356479, 'weight_decay': 0.0022412385655779226, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-25 23:59:12,600] Trial 6 pruned. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.438788 - Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 4, 'dropout': 0.12302605992272903, 'lr': 2.8884236978658085e-05, 'weight_decay': 0.0051450772150614344, 'batch_size': 32} - Best Value (CSI): 0.540446 - Best Trial: 0 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.3667052648040591, 'lr': 0.0019007657888356479, 'weight_decay': 0.0022412385655779226, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 00:01:40,793] Trial 7 finished with value: 0.5408824531335323 and parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.2066212300577071, 'lr': 0.003323662463686277, 'weight_decay': 0.0025328064540124278, 'batch_size': 64}. Best is trial 7 with value: 0.5408824531335323. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.540882 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.2066212300577071, 'lr': 0.003323662463686277, 'weight_decay': 0.0025328064540124278, 'batch_size': 64} - Best Value (CSI): 0.540882 - Best Trial: 7 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.2066212300577071, 'lr': 0.003323662463686277, 'weight_decay': 0.0025328064540124278, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:02:41,576] Trial 8 pruned. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.438084 - Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.22571976062080706, 'lr': 6.134396216911527e-05, 'weight_decay': 0.010502763907771492, 'batch_size': 32} - Best Value (CSI): 0.540882 - Best Trial: 7 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.2066212300577071, 'lr': 0.003323662463686277, 'weight_decay': 0.0025328064540124278, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 00:04:46,040] Trial 9 pruned. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.491772 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.293472508247844, 'lr': 0.0002718024634711874, 'weight_decay': 0.010615902352143382, 'batch_size': 64} - Best Value (CSI): 0.540882 - Best Trial: 7 - Best Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.2066212300577071, 'lr': 0.003323662463686277, 'weight_decay': 0.0025328064540124278, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 00:05:42,367] Trial 10 finished with value: 0.5442597491498226 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10769839287398476, 'lr': 0.009525131239793653, 'weight_decay': 0.07430773407010675, 'batch_size': 256}. Best is trial 10 with value: 0.5442597491498226. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.544260 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10769839287398476, 'lr': 0.009525131239793653, 'weight_decay': 0.07430773407010675, 'batch_size': 256} - Best Value (CSI): 0.544260 - Best Trial: 10 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10769839287398476, 'lr': 0.009525131239793653, 'weight_decay': 0.07430773407010675, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 00:06:30,727] Trial 11 finished with value: 0.5438698344359757 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10797291582631306, 'lr': 0.008277150236091012, 'weight_decay': 0.09761956663509892, 'batch_size': 256}. Best is trial 10 with value: 0.5442597491498226. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.543870 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10797291582631306, 'lr': 0.008277150236091012, 'weight_decay': 0.09761956663509892, 'batch_size': 256} - Best Value (CSI): 0.544260 - Best Trial: 10 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10769839287398476, 'lr': 0.009525131239793653, 'weight_decay': 0.07430773407010675, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 00:07:22,635] Trial 12 finished with value: 0.5454211999115509 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.1019145630795297, 'lr': 0.009473145037889064, 'weight_decay': 0.09377828327575906, 'batch_size': 256}. Best is trial 12 with value: 0.5454211999115509. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.545421 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.1019145630795297, 'lr': 0.009473145037889064, 'weight_decay': 0.09377828327575906, 'batch_size': 256} - Best Value (CSI): 0.545421 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.1019145630795297, 'lr': 0.009473145037889064, 'weight_decay': 0.09377828327575906, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 00:08:11,909] Trial 13 finished with value: 0.544122117522429 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.10308919524155724, 'lr': 0.008765344334768232, 'weight_decay': 0.07944364874867733, 'batch_size': 256}. Best is trial 12 with value: 0.5454211999115509. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.544122 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.10308919524155724, 'lr': 0.008765344334768232, 'weight_decay': 0.07944364874867733, 'batch_size': 256} - Best Value (CSI): 0.545421 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.1019145630795297, 'lr': 0.009473145037889064, 'weight_decay': 0.09377828327575906, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:08:23,445] Trial 14 pruned. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.433395 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.15887615464281568, 'lr': 0.0005803030601695833, 'weight_decay': 0.03715146424395707, 'batch_size': 256} - Best Value (CSI): 0.545421 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.1019145630795297, 'lr': 0.009473145037889064, 'weight_decay': 0.09377828327575906, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:08:34,469] Trial 15 pruned. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.481622 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1529391312910724, 'lr': 0.009242987414399018, 'weight_decay': 0.028154723850654588, 'batch_size': 256} - Best Value (CSI): 0.545421 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.1019145630795297, 'lr': 0.009473145037889064, 'weight_decay': 0.09377828327575906, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:08:46,342] Trial 16 pruned. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.447088 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.13222004068614257, 'lr': 0.004459319732899502, 'weight_decay': 0.09998847856475053, 'batch_size': 256} - Best Value (CSI): 0.545421 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.1019145630795297, 'lr': 0.009473145037889064, 'weight_decay': 0.09377828327575906, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) -[I 2025-12-26 00:09:07,583] Trial 17 pruned. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.556604 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.17030358937171652, 'lr': 0.000882950119227547, 'weight_decay': 0.025076832389689236, 'batch_size': 256} - Best Value (CSI): 0.545421 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.1019145630795297, 'lr': 0.009473145037889064, 'weight_decay': 0.09377828327575906, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 00:09:49,899] Trial 18 finished with value: 0.529326218580414 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.10405617420506673, 'lr': 0.004165233163183057, 'weight_decay': 0.015430079468391332, 'batch_size': 256}. Best is trial 12 with value: 0.5454211999115509. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.529326 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.10405617420506673, 'lr': 0.004165233163183057, 'weight_decay': 0.015430079468391332, 'batch_size': 256} - Best Value (CSI): 0.545421 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.1019145630795297, 'lr': 0.009473145037889064, 'weight_decay': 0.09377828327575906, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:09:58,378] Trial 19 pruned. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.327622 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.17890001679453238, 'lr': 1.0919634385681597e-05, 'weight_decay': 0.04994289332535135, 'batch_size': 256} - Best Value (CSI): 0.545421 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.1019145630795297, 'lr': 0.009473145037889064, 'weight_decay': 0.09377828327575906, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:10:09,095] Trial 20 pruned. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.445879 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.1371796324607018, 'lr': 0.0005888443024477293, 'weight_decay': 0.0554355495193096, 'batch_size': 256} - Best Value (CSI): 0.545421 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.1019145630795297, 'lr': 0.009473145037889064, 'weight_decay': 0.09377828327575906, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:10:19,066] Trial 21 pruned. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.428387 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.10001084990755102, 'lr': 0.00851752884982044, 'weight_decay': 0.0629985588672389, 'batch_size': 256} - Best Value (CSI): 0.545421 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.1019145630795297, 'lr': 0.009473145037889064, 'weight_decay': 0.09377828327575906, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:10:29,010] Trial 22 pruned. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.427284 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.12836603089669577, 'lr': 0.005426813208439263, 'weight_decay': 0.09431668470773782, 'batch_size': 256} - Best Value (CSI): 0.545421 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.1019145630795297, 'lr': 0.009473145037889064, 'weight_decay': 0.09377828327575906, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:10:40,786] Trial 23 pruned. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.463023 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.10646024314196056, 'lr': 0.009422942961845163, 'weight_decay': 0.02249564832452241, 'batch_size': 256} - Best Value (CSI): 0.545421 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.1019145630795297, 'lr': 0.009473145037889064, 'weight_decay': 0.09377828327575906, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) -[I 2025-12-26 00:11:01,041] Trial 24 pruned. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.570136 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.13462358717992445, 'lr': 0.0036481434195272796, 'weight_decay': 0.05494537199885521, 'batch_size': 256} - Best Value (CSI): 0.545421 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.1019145630795297, 'lr': 0.009473145037889064, 'weight_decay': 0.09377828327575906, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 00:11:59,452] Trial 25 finished with value: 0.5356927816012992 and parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.181240125595102, 'lr': 0.005545841210289506, 'weight_decay': 0.028862928599039286, 'batch_size': 256}. Best is trial 12 with value: 0.5454211999115509. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.535693 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.181240125595102, 'lr': 0.005545841210289506, 'weight_decay': 0.028862928599039286, 'batch_size': 256} - Best Value (CSI): 0.545421 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.1019145630795297, 'lr': 0.009473145037889064, 'weight_decay': 0.09377828327575906, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:12:09,924] Trial 26 pruned. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.437229 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.14944290934737137, 'lr': 0.0028741768902834346, 'weight_decay': 0.06843083558879022, 'batch_size': 256} - Best Value (CSI): 0.545421 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.1019145630795297, 'lr': 0.009473145037889064, 'weight_decay': 0.09377828327575906, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:13:01,190] Trial 27 pruned. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.409567 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.12036785571074947, 'lr': 0.00595543977240383, 'weight_decay': 0.01660922370705496, 'batch_size': 32} - Best Value (CSI): 0.545421 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.1019145630795297, 'lr': 0.009473145037889064, 'weight_decay': 0.09377828327575906, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:13:29,645] Trial 28 pruned. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.450695 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.10106244395208261, 'lr': 0.002553503037575875, 'weight_decay': 0.06282082102273907, 'batch_size': 64} - Best Value (CSI): 0.545421 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.1019145630795297, 'lr': 0.009473145037889064, 'weight_decay': 0.09377828327575906, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:13:56,447] Trial 29 pruned. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.464832 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.14158012633839195, 'lr': 0.0018287077063598811, 'weight_decay': 0.037138023905174546, 'batch_size': 64} - Best Value (CSI): 0.545421 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.1019145630795297, 'lr': 0.009473145037889064, 'weight_decay': 0.09377828327575906, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:14:05,114] Trial 30 pruned. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.466624 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.17148322591128828, 'lr': 0.006064997061384621, 'weight_decay': 0.09589021330825949, 'batch_size': 256} - Best Value (CSI): 0.545421 - Best Trial: 12 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.1019145630795297, 'lr': 0.009473145037889064, 'weight_decay': 0.09377828327575906, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 00:14:54,322] Trial 31 finished with value: 0.548082869767588 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.11810161420146811, 'lr': 0.005626161255766633, 'weight_decay': 0.07813595965260633, 'batch_size': 256}. Best is trial 31 with value: 0.548082869767588. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.548083 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.11810161420146811, 'lr': 0.005626161255766633, 'weight_decay': 0.07813595965260633, 'batch_size': 256} - Best Value (CSI): 0.548083 - Best Trial: 31 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.11810161420146811, 'lr': 0.005626161255766633, 'weight_decay': 0.07813595965260633, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) -[I 2025-12-26 00:15:14,582] Trial 32 pruned. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.583805 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.1196883182041709, 'lr': 0.009231259496872554, 'weight_decay': 0.03994868882735761, 'batch_size': 256} - Best Value (CSI): 0.548083 - Best Trial: 31 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.11810161420146811, 'lr': 0.005626161255766633, 'weight_decay': 0.07813595965260633, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 00:15:57,597] Trial 33 finished with value: 0.5496514767249386 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.12040597835986357, 'lr': 0.004042336529579042, 'weight_decay': 0.07140326236268495, 'batch_size': 256}. Best is trial 33 with value: 0.5496514767249386. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.549651 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.12040597835986357, 'lr': 0.004042336529579042, 'weight_decay': 0.07140326236268495, 'batch_size': 256} - Best Value (CSI): 0.549651 - Best Trial: 33 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.12040597835986357, 'lr': 0.004042336529579042, 'weight_decay': 0.07140326236268495, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 00:17:04,516] Trial 34 finished with value: 0.5391510656805605 and parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.1440196627983718, 'lr': 0.003918233945876215, 'weight_decay': 0.053582605029085746, 'batch_size': 128}. Best is trial 33 with value: 0.5496514767249386. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.539151 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.1440196627983718, 'lr': 0.003918233945876215, 'weight_decay': 0.053582605029085746, 'batch_size': 128} - Best Value (CSI): 0.549651 - Best Trial: 33 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.12040597835986357, 'lr': 0.004042336529579042, 'weight_decay': 0.07140326236268495, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:17:15,413] Trial 35 pruned. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.440122 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.12125628535109054, 'lr': 0.00205771861570579, 'weight_decay': 0.03765043519065167, 'batch_size': 256} - Best Value (CSI): 0.549651 - Best Trial: 33 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.12040597835986357, 'lr': 0.004042336529579042, 'weight_decay': 0.07140326236268495, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) -[I 2025-12-26 00:17:40,307] Trial 36 pruned. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.573415 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.15582312694613848, 'lr': 0.0015301742172401072, 'weight_decay': 0.06686969189870928, 'batch_size': 128} - Best Value (CSI): 0.549651 - Best Trial: 33 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.12040597835986357, 'lr': 0.004042336529579042, 'weight_decay': 0.07140326236268495, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) -[I 2025-12-26 00:19:21,405] Trial 37 pruned. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.584624 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.18661236561140981, 'lr': 0.0027138712796909363, 'weight_decay': 0.020148793273370078, 'batch_size': 32} - Best Value (CSI): 0.549651 - Best Trial: 33 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.12040597835986357, 'lr': 0.004042336529579042, 'weight_decay': 0.07140326236268495, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:19:31,296] Trial 38 pruned. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.441103 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.11691325658117041, 'lr': 0.005059497387616477, 'weight_decay': 0.00011463260645479976, 'batch_size': 256} - Best Value (CSI): 0.549651 - Best Trial: 33 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.12040597835986357, 'lr': 0.004042336529579042, 'weight_decay': 0.07140326236268495, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:19:47,465] Trial 39 pruned. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.437925 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.1321856276295156, 'lr': 0.0012119410759001772, 'weight_decay': 0.0007447268103318002, 'batch_size': 128} - Best Value (CSI): 0.549651 - Best Trial: 33 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.12040597835986357, 'lr': 0.004042336529579042, 'weight_decay': 0.07140326236268495, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 00:22:05,886] Trial 40 finished with value: 0.5450780727734363 and parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.1627381954613088, 'lr': 0.003053118654783677, 'weight_decay': 0.03208414716624912, 'batch_size': 64}. Best is trial 33 with value: 0.5496514767249386. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.545078 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.1627381954613088, 'lr': 0.003053118654783677, 'weight_decay': 0.03208414716624912, 'batch_size': 64} - Best Value (CSI): 0.549651 - Best Trial: 33 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.12040597835986357, 'lr': 0.004042336529579042, 'weight_decay': 0.07140326236268495, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:22:34,478] Trial 41 pruned. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.424321 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.11763077084774717, 'lr': 0.003136654209320503, 'weight_decay': 0.06968439212950128, 'batch_size': 64} - Best Value (CSI): 0.549651 - Best Trial: 33 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.12040597835986357, 'lr': 0.004042336529579042, 'weight_decay': 0.07140326236268495, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:23:02,438] Trial 42 pruned. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.433138 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.13979633165120775, 'lr': 0.006484002731884658, 'weight_decay': 0.03824784233278941, 'batch_size': 64} - Best Value (CSI): 0.549651 - Best Trial: 33 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.12040597835986357, 'lr': 0.004042336529579042, 'weight_decay': 0.07140326236268495, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:23:31,328] Trial 43 pruned. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.436482 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.16028541086882056, 'lr': 0.003969660167201104, 'weight_decay': 0.09998370263815894, 'batch_size': 64} - Best Value (CSI): 0.549651 - Best Trial: 33 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.12040597835986357, 'lr': 0.004042336529579042, 'weight_decay': 0.07140326236268495, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:24:00,280] Trial 44 pruned. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.408730 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.11775871666351921, 'lr': 0.0070655583004284464, 'weight_decay': 0.05080300277860471, 'batch_size': 64} - Best Value (CSI): 0.549651 - Best Trial: 33 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.12040597835986357, 'lr': 0.004042336529579042, 'weight_decay': 0.07140326236268495, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:24:46,463] Trial 45 pruned. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.417772 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.19780340972592655, 'lr': 0.0022044168879631725, 'weight_decay': 0.07861419812841668, 'batch_size': 32} - Best Value (CSI): 0.549651 - Best Trial: 33 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.12040597835986357, 'lr': 0.004042336529579042, 'weight_decay': 0.07140326236268495, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:25:07,632] Trial 46 pruned. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.355731 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.14812429697728946, 'lr': 0.009974439328352243, 'weight_decay': 0.03245233114100497, 'batch_size': 64} - Best Value (CSI): 0.549651 - Best Trial: 33 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.12040597835986357, 'lr': 0.004042336529579042, 'weight_decay': 0.07140326236268495, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 00:26:00,667] Trial 47 finished with value: 0.5392433468956933 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.16578046533882615, 'lr': 0.006417645399657734, 'weight_decay': 0.04557757070587515, 'batch_size': 256}. Best is trial 33 with value: 0.5496514767249386. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.539243 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 5, 'dropout': 0.16578046533882615, 'lr': 0.006417645399657734, 'weight_decay': 0.04557757070587515, 'batch_size': 256} - Best Value (CSI): 0.549651 - Best Trial: 33 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.12040597835986357, 'lr': 0.004042336529579042, 'weight_decay': 0.07140326236268495, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 00:26:50,680] Trial 48 finished with value: 0.5399853400567142 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.12870986052120786, 'lr': 0.004508473370455997, 'weight_decay': 0.02875539371865502, 'batch_size': 256}. Best is trial 33 with value: 0.5496514767249386. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.539985 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.12870986052120786, 'lr': 0.004508473370455997, 'weight_decay': 0.02875539371865502, 'batch_size': 256} - Best Value (CSI): 0.549651 - Best Trial: 33 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.12040597835986357, 'lr': 0.004042336529579042, 'weight_decay': 0.07140326236268495, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) -[I 2025-12-26 00:27:10,518] Trial 49 pruned. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.583987 - Parameters: {'d_main': 96, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.1100386507119037, 'lr': 0.003155297085711408, 'weight_decay': 0.07640358141392502, 'batch_size': 256} - Best Value (CSI): 0.549651 - Best Trial: 33 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.12040597835986357, 'lr': 0.004042336529579042, 'weight_decay': 0.07140326236268495, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) -[I 2025-12-26 00:27:41,192] Trial 50 pruned. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.511041 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.23528595317438578, 'lr': 0.00731541676552626, 'weight_decay': 0.04725055252177155, 'batch_size': 128} - Best Value (CSI): 0.549651 - Best Trial: 33 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.12040597835986357, 'lr': 0.004042336529579042, 'weight_decay': 0.07140326236268495, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:27:51,357] Trial 51 pruned. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.438295 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1027705791733015, 'lr': 0.004749677885665039, 'weight_decay': 0.07753517392239728, 'batch_size': 256} - Best Value (CSI): 0.549651 - Best Trial: 33 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.12040597835986357, 'lr': 0.004042336529579042, 'weight_decay': 0.07140326236268495, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:28:01,409] Trial 52 pruned. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.417910 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1147415771269165, 'lr': 0.007734953512221603, 'weight_decay': 0.07151311136696416, 'batch_size': 256} - Best Value (CSI): 0.549651 - Best Trial: 33 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.12040597835986357, 'lr': 0.004042336529579042, 'weight_decay': 0.07140326236268495, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) -[I 2025-12-26 00:28:22,206] Trial 53 pruned. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.540719 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10068109528194977, 'lr': 0.009676687429529544, 'weight_decay': 0.04630342462547213, 'batch_size': 256} - Best Value (CSI): 0.549651 - Best Trial: 33 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.12040597835986357, 'lr': 0.004042336529579042, 'weight_decay': 0.07140326236268495, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) -[I 2025-12-26 00:28:42,614] Trial 54 pruned. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.551995 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.1310536058663749, 'lr': 0.006904084411649362, 'weight_decay': 0.09691173066578251, 'batch_size': 256} - Best Value (CSI): 0.549651 - Best Trial: 33 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.12040597835986357, 'lr': 0.004042336529579042, 'weight_decay': 0.07140326236268495, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:28:52,425] Trial 55 pruned. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.441846 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.11322150267841806, 'lr': 0.003897281937271959, 'weight_decay': 0.030160311017941175, 'batch_size': 256} - Best Value (CSI): 0.549651 - Best Trial: 33 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.12040597835986357, 'lr': 0.004042336529579042, 'weight_decay': 0.07140326236268495, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:29:03,478] Trial 56 pruned. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.419924 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.14638794791825438, 'lr': 0.00510723662645598, 'weight_decay': 0.061487483603322804, 'batch_size': 256} - Best Value (CSI): 0.549651 - Best Trial: 33 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.12040597835986357, 'lr': 0.004042336529579042, 'weight_decay': 0.07140326236268495, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:29:14,583] Trial 57 pruned. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.444725 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.12680373183997196, 'lr': 0.007252924279052623, 'weight_decay': 0.010515785849892587, 'batch_size': 256} - Best Value (CSI): 0.549651 - Best Trial: 33 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.12040597835986357, 'lr': 0.004042336529579042, 'weight_decay': 0.07140326236268495, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) -[I 2025-12-26 00:30:36,123] Trial 58 pruned. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.549150 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.15795620947363545, 'lr': 0.0033438481642037933, 'weight_decay': 0.023339873234751174, 'batch_size': 32} - Best Value (CSI): 0.549651 - Best Trial: 33 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.12040597835986357, 'lr': 0.004042336529579042, 'weight_decay': 0.07140326236268495, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:30:46,018] Trial 59 pruned. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.426158 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.11082832524254957, 'lr': 0.002540209625358045, 'weight_decay': 0.0835191096932168, 'batch_size': 256} - Best Value (CSI): 0.549651 - Best Trial: 33 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.12040597835986357, 'lr': 0.004042336529579042, 'weight_decay': 0.07140326236268495, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:31:08,259] Trial 60 pruned. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.373663 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.13917345047918933, 'lr': 0.005317191441900549, 'weight_decay': 0.05597436315191188, 'batch_size': 64} - Best Value (CSI): 0.549651 - Best Trial: 33 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.12040597835986357, 'lr': 0.004042336529579042, 'weight_decay': 0.07140326236268495, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:31:18,639] Trial 61 pruned. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.423607 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.12610694921241553, 'lr': 0.00997569639363915, 'weight_decay': 0.07955990395203798, 'batch_size': 256} - Best Value (CSI): 0.549651 - Best Trial: 33 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.12040597835986357, 'lr': 0.004042336529579042, 'weight_decay': 0.07140326236268495, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 00:32:08,028] Trial 62 finished with value: 0.5502041022090476 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10029619278557904, 'lr': 0.007931406644933343, 'weight_decay': 0.09626294183442244, 'batch_size': 256}. Best is trial 62 with value: 0.5502041022090476. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.550204 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10029619278557904, 'lr': 0.007931406644933343, 'weight_decay': 0.09626294183442244, 'batch_size': 256} - Best Value (CSI): 0.550204 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10029619278557904, 'lr': 0.007931406644933343, 'weight_decay': 0.09626294183442244, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 00:32:52,988] Trial 63 finished with value: 0.5457134941573479 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.11031039765826121, 'lr': 0.007676885182154922, 'weight_decay': 0.061355325210686165, 'batch_size': 256}. Best is trial 62 with value: 0.5502041022090476. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.545713 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.11031039765826121, 'lr': 0.007676885182154922, 'weight_decay': 0.061355325210686165, 'batch_size': 256} - Best Value (CSI): 0.550204 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10029619278557904, 'lr': 0.007931406644933343, 'weight_decay': 0.09626294183442244, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:33:03,785] Trial 64 pruned. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.456413 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.11001122502119348, 'lr': 0.005404304693574052, 'weight_decay': 0.04419722440085392, 'batch_size': 256} - Best Value (CSI): 0.550204 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10029619278557904, 'lr': 0.007931406644933343, 'weight_decay': 0.09626294183442244, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:33:14,438] Trial 65 pruned. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.442821 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.1353187797757808, 'lr': 0.007158751322376289, 'weight_decay': 0.0566421358322544, 'batch_size': 256} - Best Value (CSI): 0.550204 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10029619278557904, 'lr': 0.007931406644933343, 'weight_decay': 0.09626294183442244, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:33:25,095] Trial 66 pruned. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.435682 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.1253576753104251, 'lr': 0.007987829951502273, 'weight_decay': 0.032853505080592725, 'batch_size': 256} - Best Value (CSI): 0.550204 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10029619278557904, 'lr': 0.007931406644933343, 'weight_decay': 0.09626294183442244, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) -[I 2025-12-26 00:33:44,970] Trial 67 pruned. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.583651 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10060998089687596, 'lr': 0.00440008982492711, 'weight_decay': 0.09966191484143383, 'batch_size': 256} - Best Value (CSI): 0.550204 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10029619278557904, 'lr': 0.007931406644933343, 'weight_decay': 0.09626294183442244, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) -[I 2025-12-26 00:34:05,314] Trial 68 pruned. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.583799 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10849359754330477, 'lr': 0.0034453922287061073, 'weight_decay': 0.06376740723385275, 'batch_size': 256} - Best Value (CSI): 0.550204 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10029619278557904, 'lr': 0.007931406644933343, 'weight_decay': 0.09626294183442244, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:34:16,266] Trial 69 pruned. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.443746 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.1497564333327584, 'lr': 0.005910539177815773, 'weight_decay': 0.03804338333821477, 'batch_size': 256} - Best Value (CSI): 0.550204 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10029619278557904, 'lr': 0.007931406644933343, 'weight_decay': 0.09626294183442244, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:34:44,695] Trial 70 pruned. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.407234 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.11553986976503003, 'lr': 0.007937117632203283, 'weight_decay': 0.08168078625508159, 'batch_size': 64} - Best Value (CSI): 0.550204 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10029619278557904, 'lr': 0.007931406644933343, 'weight_decay': 0.09626294183442244, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:34:55,341] Trial 71 pruned. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.440689 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10022917851452216, 'lr': 0.0061416904675594625, 'weight_decay': 0.06434764338722652, 'batch_size': 256} - Best Value (CSI): 0.550204 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10029619278557904, 'lr': 0.007931406644933343, 'weight_decay': 0.09626294183442244, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:35:06,063] Trial 72 pruned. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.420812 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.12042825119211578, 'lr': 0.008766254634445655, 'weight_decay': 0.05297788475663313, 'batch_size': 256} - Best Value (CSI): 0.550204 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10029619278557904, 'lr': 0.007931406644933343, 'weight_decay': 0.09626294183442244, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:35:16,064] Trial 73 pruned. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.442623 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.13713161077692956, 'lr': 0.004413554433040063, 'weight_decay': 0.08299596256234486, 'batch_size': 256} - Best Value (CSI): 0.550204 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10029619278557904, 'lr': 0.007931406644933343, 'weight_decay': 0.09626294183442244, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:35:32,443] Trial 74 pruned. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.398802 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10963185631578243, 'lr': 0.007757577868385006, 'weight_decay': 0.042569952575620205, 'batch_size': 128} - Best Value (CSI): 0.550204 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10029619278557904, 'lr': 0.007931406644933343, 'weight_decay': 0.09626294183442244, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) -[I 2025-12-26 00:35:52,633] Trial 75 pruned. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.585076 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.12490884963697325, 'lr': 0.005528026327736817, 'weight_decay': 0.06532510146163475, 'batch_size': 256} - Best Value (CSI): 0.550204 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10029619278557904, 'lr': 0.007931406644933343, 'weight_decay': 0.09626294183442244, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:36:43,429] Trial 76 pruned. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.357992 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.1425370901758967, 'lr': 0.009964660587062926, 'weight_decay': 0.08814597477479234, 'batch_size': 32} - Best Value (CSI): 0.550204 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10029619278557904, 'lr': 0.007931406644933343, 'weight_decay': 0.09626294183442244, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) -[I 2025-12-26 00:37:04,625] Trial 77 pruned. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.544153 - Parameters: {'d_main': 64, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.1233840146144245, 'lr': 0.004247683398321402, 'weight_decay': 0.0517623137806593, 'batch_size': 256} - Best Value (CSI): 0.550204 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10029619278557904, 'lr': 0.007931406644933343, 'weight_decay': 0.09626294183442244, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:37:15,354] Trial 78 pruned. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.445783 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.11006304474219661, 'lr': 0.0064979149300802095, 'weight_decay': 0.07336333406642745, 'batch_size': 256} - Best Value (CSI): 0.550204 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10029619278557904, 'lr': 0.007931406644933343, 'weight_decay': 0.09626294183442244, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:37:43,656] Trial 79 pruned. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.399061 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.13242996360599582, 'lr': 0.00809935985840178, 'weight_decay': 0.09687188549048982, 'batch_size': 64} - Best Value (CSI): 0.550204 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10029619278557904, 'lr': 0.007931406644933343, 'weight_decay': 0.09626294183442244, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) -[I 2025-12-26 00:38:04,971] Trial 80 pruned. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.570538 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10661119293721677, 'lr': 0.0035784644734490356, 'weight_decay': 0.05916319332085249, 'batch_size': 256} - Best Value (CSI): 0.550204 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10029619278557904, 'lr': 0.007931406644933343, 'weight_decay': 0.09626294183442244, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 00:38:46,465] Trial 81 finished with value: 0.5333310685623037 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.1177818759383586, 'lr': 0.008488625796027119, 'weight_decay': 0.08365886973578984, 'batch_size': 256}. Best is trial 62 with value: 0.5502041022090476. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.533331 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.1177818759383586, 'lr': 0.008488625796027119, 'weight_decay': 0.08365886973578984, 'batch_size': 256} - Best Value (CSI): 0.550204 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10029619278557904, 'lr': 0.007931406644933343, 'weight_decay': 0.09626294183442244, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:38:57,907] Trial 82 pruned. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.468593 - Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10681616712877211, 'lr': 0.006129368867997624, 'weight_decay': 0.06944829036999534, 'batch_size': 256} - Best Value (CSI): 0.550204 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10029619278557904, 'lr': 0.007931406644933343, 'weight_decay': 0.09626294183442244, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) -[I 2025-12-26 00:39:18,398] Trial 83 pruned. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.563960 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10062730050858844, 'lr': 0.005370522193284279, 'weight_decay': 0.04639958044589333, 'batch_size': 256} - Best Value (CSI): 0.550204 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10029619278557904, 'lr': 0.007931406644933343, 'weight_decay': 0.09626294183442244, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 00:39:57,812] Trial 84 finished with value: 0.5443993450467787 and parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.1169199247244405, 'lr': 0.004791684959471504, 'weight_decay': 0.09655373884293487, 'batch_size': 256}. Best is trial 62 with value: 0.5502041022090476. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.544399 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.1169199247244405, 'lr': 0.004791684959471504, 'weight_decay': 0.09655373884293487, 'batch_size': 256} - Best Value (CSI): 0.550204 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10029619278557904, 'lr': 0.007931406644933343, 'weight_decay': 0.09626294183442244, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) -[I 2025-12-26 00:40:19,081] Trial 85 pruned. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.584164 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.11703355861532837, 'lr': 0.002910539698355419, 'weight_decay': 0.035298492893928626, 'batch_size': 256} - Best Value (CSI): 0.550204 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10029619278557904, 'lr': 0.007931406644933343, 'weight_decay': 0.09626294183442244, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) -[I 2025-12-26 00:40:38,908] Trial 86 pruned. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.562464 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.12995485681765323, 'lr': 0.004776994113049706, 'weight_decay': 0.09972233342994503, 'batch_size': 256} - Best Value (CSI): 0.550204 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10029619278557904, 'lr': 0.007931406644933343, 'weight_decay': 0.09626294183442244, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:40:54,537] Trial 87 pruned. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.419293 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.15019824752377078, 'lr': 0.0037711488016715588, 'weight_decay': 0.07238097585331865, 'batch_size': 128} - Best Value (CSI): 0.550204 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10029619278557904, 'lr': 0.007931406644933343, 'weight_decay': 0.09626294183442244, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:41:22,936] Trial 88 pruned. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.385942 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.1407645225566533, 'lr': 0.006735207664263645, 'weight_decay': 0.056226553216804274, 'batch_size': 64} - Best Value (CSI): 0.550204 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10029619278557904, 'lr': 0.007931406644933343, 'weight_decay': 0.09626294183442244, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) -[I 2025-12-26 00:41:41,368] Trial 89 pruned. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.553030 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.12256297330998901, 'lr': 0.00246241436833551, 'weight_decay': 0.04302285790993002, 'batch_size': 256} - Best Value (CSI): 0.550204 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10029619278557904, 'lr': 0.007931406644933343, 'weight_decay': 0.09626294183442244, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:42:30,548] Trial 90 pruned. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.326102 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.11151658723158726, 'lr': 0.008637301440924958, 'weight_decay': 0.08351033466774432, 'batch_size': 32} - Best Value (CSI): 0.550204 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10029619278557904, 'lr': 0.007931406644933343, 'weight_decay': 0.09626294183442244, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) -[I 2025-12-26 00:42:51,151] Trial 91 pruned. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.586462 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10697556321790372, 'lr': 0.00997027125478668, 'weight_decay': 0.06678521291341949, 'batch_size': 256} - Best Value (CSI): 0.550204 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10029619278557904, 'lr': 0.007931406644933343, 'weight_decay': 0.09626294183442244, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) -[I 2025-12-26 00:43:12,055] Trial 92 pruned. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.581963 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.11639625853095183, 'lr': 0.006848142410680243, 'weight_decay': 0.08634441869139166, 'batch_size': 256} - Best Value (CSI): 0.550204 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10029619278557904, 'lr': 0.007931406644933343, 'weight_decay': 0.09626294183442244, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) -[I 2025-12-26 00:43:32,127] Trial 93 pruned. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.538040 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.1288092937971269, 'lr': 0.004852312502239798, 'weight_decay': 0.05337612867027623, 'batch_size': 256} - Best Value (CSI): 0.550204 - Best Trial: 62 - Best Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10029619278557904, 'lr': 0.007931406644933343, 'weight_decay': 0.09626294183442244, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 00:44:16,036] Trial 94 finished with value: 0.5515777046032605 and parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.10014845072807586, 'lr': 0.008578508208533469, 'weight_decay': 0.07361767414227417, 'batch_size': 256}. Best is trial 94 with value: 0.5515777046032605. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.551578 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.10014845072807586, 'lr': 0.008578508208533469, 'weight_decay': 0.07361767414227417, 'batch_size': 256} - Best Value (CSI): 0.551578 - Best Trial: 94 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.10014845072807586, 'lr': 0.008578508208533469, 'weight_decay': 0.07361767414227417, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:44:27,248] Trial 95 pruned. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.440099 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.10053509412887335, 'lr': 0.008332550797411463, 'weight_decay': 0.07464042355316727, 'batch_size': 256} - Best Value (CSI): 0.551578 - Best Trial: 94 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.10014845072807586, 'lr': 0.008578508208533469, 'weight_decay': 0.07361767414227417, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) -[I 2025-12-26 00:44:48,939] Trial 96 pruned. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.520998 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.12173712529228915, 'lr': 0.005323374999248873, 'weight_decay': 0.06124698468709382, 'batch_size': 256} - Best Value (CSI): 0.551578 - Best Trial: 94 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.10014845072807586, 'lr': 0.008578508208533469, 'weight_decay': 0.07361767414227417, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 00:45:00,089] Trial 97 pruned. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.449784 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.11399391880866064, 'lr': 0.005926063042462059, 'weight_decay': 0.049246166062706515, 'batch_size': 256} - Best Value (CSI): 0.551578 - Best Trial: 94 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.10014845072807586, 'lr': 0.008578508208533469, 'weight_decay': 0.07361767414227417, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) -[I 2025-12-26 00:45:21,839] Trial 98 pruned. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.544170 - Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.13461647462442722, 'lr': 0.0040740327396090945, 'weight_decay': 0.0275813257120184, 'batch_size': 256} - Best Value (CSI): 0.551578 - Best Trial: 94 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.10014845072807586, 'lr': 0.008578508208533469, 'weight_decay': 0.07361767414227417, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) -[I 2025-12-26 00:46:15,170] Trial 99 pruned. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.546789 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.1065302958243868, 'lr': 0.007218393562947236, 'weight_decay': 0.038322882595800314, 'batch_size': 64} - Best Value (CSI): 0.551578 - Best Trial: 94 - Best Parameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.10014845072807586, 'lr': 0.008578508208533469, 'weight_decay': 0.07361767414227417, 'batch_size': 256} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.5516 -Best Hyperparameters: {'d_main': 64, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.10014845072807586, 'lr': 0.008578508208533469, 'weight_decay': 0.07361767414227417, 'batch_size': 256} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.5404 - - 최종 CSI: 0.5468 - - 최고 CSI: 0.5865 - - 최저 CSI: 0.3261 - - 평균 CSI: 0.4873 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/deepgbm_smotenc_ctgan20000_incheon_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 14, Best CSI: 0.4799 - Fold 1 학습 완료 (검증 CSI: 0.4799) -Fold 2 학습 중... - Early stopping at epoch 30, Best CSI: 0.5939 - Fold 2 학습 완료 (검증 CSI: 0.5939) -Fold 3 학습 중... - Early stopping at epoch 25, Best CSI: 0.5610 - Fold 3 학습 완료 (검증 CSI: 0.5610) - -모든 모델 저장 완료: ../save_model/deepgbm_optima/deepgbm_smotenc_ctgan20000_incheon.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/deepgbm_optima/scaler/deepgbm_smotenc_ctgan20000_incheon_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: ../save_model/deepgbm_optima/deepgbm_smotenc_ctgan20000_incheon.pkl - -✓ 완료: deepgbm_smotenc_ctgan20000/deepgbm_smotenc_ctgan20000_incheon.py (소요 시간: 3683초) - ----------------------------------------- -실행 중: deepgbm_smotenc_ctgan20000/deepgbm_smotenc_ctgan20000_seoul.py -시작 시간: 2025-12-26 00:47:06 ----------------------------------------- -[I 2025-12-26 00:47:07,713] A new study created in memory with name: no-name-03175cf9-1d5b-4a6e-bdf9-7ac88c0b6582 - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 00:49:09,404] Trial 0 finished with value: 0.49860941539715525 and parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.25254539424314093, 'lr': 0.0005617369324276381, 'weight_decay': 0.00010662009745115875, 'batch_size': 64}. Best is trial 0 with value: 0.49860941539715525. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.498609 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.25254539424314093, 'lr': 0.0005617369324276381, 'weight_decay': 0.00010662009745115875, 'batch_size': 64} - Best Value (CSI): 0.498609 - Best Trial: 0 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.25254539424314093, 'lr': 0.0005617369324276381, 'weight_decay': 0.00010662009745115875, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 00:50:16,411] Trial 1 finished with value: 0.47295026545449703 and parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.29891826584209974, 'lr': 0.00012475855901992078, 'weight_decay': 0.028620301098035702, 'batch_size': 256}. Best is trial 0 with value: 0.49860941539715525. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.472950 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.29891826584209974, 'lr': 0.00012475855901992078, 'weight_decay': 0.028620301098035702, 'batch_size': 256} - Best Value (CSI): 0.498609 - Best Trial: 0 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.25254539424314093, 'lr': 0.0005617369324276381, 'weight_decay': 0.00010662009745115875, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 00:52:15,940] Trial 2 finished with value: 0.44787046029452576 and parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.3109816773506793, 'lr': 1.1386714319911892e-05, 'weight_decay': 0.029572949896356834, 'batch_size': 128}. Best is trial 0 with value: 0.49860941539715525. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.447870 - Parameters: {'d_main': 256, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.3109816773506793, 'lr': 1.1386714319911892e-05, 'weight_decay': 0.029572949896356834, 'batch_size': 128} - Best Value (CSI): 0.498609 - Best Trial: 0 - Best Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.25254539424314093, 'lr': 0.0005617369324276381, 'weight_decay': 0.00010662009745115875, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 00:52:50,514] Trial 3 finished with value: 0.509879094136492 and parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.15716668876308398, 'lr': 0.002505562535491622, 'weight_decay': 0.0010247794805652143, 'batch_size': 256}. Best is trial 3 with value: 0.509879094136492. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.509879 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.15716668876308398, 'lr': 0.002505562535491622, 'weight_decay': 0.0010247794805652143, 'batch_size': 256} - Best Value (CSI): 0.509879 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.15716668876308398, 'lr': 0.002505562535491622, 'weight_decay': 0.0010247794805652143, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 00:55:19,042] Trial 4 finished with value: 0.4743948646027698 and parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.21828929004180328, 'lr': 4.7808266938063634e-05, 'weight_decay': 0.0007282296523659097, 'batch_size': 64}. Best is trial 3 with value: 0.509879094136492. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.474395 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.21828929004180328, 'lr': 4.7808266938063634e-05, 'weight_decay': 0.0007282296523659097, 'batch_size': 64} - Best Value (CSI): 0.509879 - Best Trial: 3 - Best Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.15716668876308398, 'lr': 0.002505562535491622, 'weight_decay': 0.0010247794805652143, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 00:56:08,504] Trial 5 finished with value: 0.5477355590816262 and parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.35897357546772146, 'lr': 0.00796023516397056, 'weight_decay': 0.09321148861405949, 'batch_size': 256}. Best is trial 5 with value: 0.5477355590816262. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.547736 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.35897357546772146, 'lr': 0.00796023516397056, 'weight_decay': 0.09321148861405949, 'batch_size': 256} - Best Value (CSI): 0.547736 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.35897357546772146, 'lr': 0.00796023516397056, 'weight_decay': 0.09321148861405949, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 00:56:37,501] Trial 6 pruned. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.342052 - Parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.2680992918953701, 'lr': 1.8788968520392145e-05, 'weight_decay': 0.006335177828729479, 'batch_size': 32} - Best Value (CSI): 0.547736 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.35897357546772146, 'lr': 0.00796023516397056, 'weight_decay': 0.09321148861405949, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 00:57:10,123] Trial 7 pruned. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.282649 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3321038344813615, 'lr': 1.2267942572129646e-05, 'weight_decay': 0.0009986446948957897, 'batch_size': 32} - Best Value (CSI): 0.547736 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.35897357546772146, 'lr': 0.00796023516397056, 'weight_decay': 0.09321148861405949, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 01:01:23,173] Trial 8 finished with value: 0.5083167404655692 and parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3876707058786192, 'lr': 0.00048622617842201005, 'weight_decay': 0.00655077730227745, 'batch_size': 32}. Best is trial 5 with value: 0.5477355590816262. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.508317 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.3876707058786192, 'lr': 0.00048622617842201005, 'weight_decay': 0.00655077730227745, 'batch_size': 32} - Best Value (CSI): 0.547736 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.35897357546772146, 'lr': 0.00796023516397056, 'weight_decay': 0.09321148861405949, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:02:01,341] Trial 9 pruned. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.360717 - Parameters: {'d_main': 64, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.38403558315891784, 'lr': 9.21998724832433e-05, 'weight_decay': 0.002033165405891799, 'batch_size': 32} - Best Value (CSI): 0.547736 - Best Trial: 5 - Best Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.35897357546772146, 'lr': 0.00796023516397056, 'weight_decay': 0.09321148861405949, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 01:02:57,907] Trial 10 finished with value: 0.5657974901513136 and parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256}. Best is trial 10 with value: 0.5657974901513136. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.565797 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 01:04:08,789] Trial 11 finished with value: 0.5582078162847205 and parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.10780724766196015, 'lr': 0.009656432736570138, 'weight_decay': 0.0991079507676134, 'batch_size': 256}. Best is trial 10 with value: 0.5657974901513136. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.558208 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.10780724766196015, 'lr': 0.009656432736570138, 'weight_decay': 0.0991079507676134, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 01:05:00,636] Trial 12 finished with value: 0.536267682969468 and parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.10215728926137342, 'lr': 0.00845654349268458, 'weight_decay': 0.06580097512788673, 'batch_size': 256}. Best is trial 10 with value: 0.5657974901513136. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.536268 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.10215728926137342, 'lr': 0.00845654349268458, 'weight_decay': 0.06580097512788673, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:05:17,500] Trial 13 pruned. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.439189 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.11309829273299493, 'lr': 0.003682051195654335, 'weight_decay': 0.094717980809892, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:05:30,194] Trial 14 pruned. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.413344 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.1535546776052753, 'lr': 0.00160584857514054, 'weight_decay': 0.025214492313235234, 'batch_size': 128} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 01:06:24,044] Trial 15 finished with value: 0.5352402302912023 and parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.19512312295471101, 'lr': 0.009926931946755257, 'weight_decay': 0.015341727578467426, 'batch_size': 256}. Best is trial 10 with value: 0.5657974901513136. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.535240 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.19512312295471101, 'lr': 0.009926931946755257, 'weight_decay': 0.015341727578467426, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:06:32,428] Trial 16 pruned. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.423139 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.13522570579652243, 'lr': 0.0013706372261094609, 'weight_decay': 0.043802071659648584, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:06:41,789] Trial 17 pruned. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.437819 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.10018764448984192, 'lr': 0.003877116656013006, 'weight_decay': 0.014971578579742906, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:07:23,976] Trial 18 pruned. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.433588 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.18820530103634028, 'lr': 0.0011255825612293481, 'weight_decay': 0.05130603807321384, 'batch_size': 64} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:07:48,603] Trial 19 pruned. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.447077 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1412441021884708, 'lr': 0.004235828251133253, 'weight_decay': 0.09819586692416048, 'batch_size': 128} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:08:06,981] Trial 20 pruned. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.449811 - Parameters: {'d_main': 128, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.17614802356724185, 'lr': 0.005608086654008918, 'weight_decay': 0.0422245782452127, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 01:09:05,153] Trial 21 finished with value: 0.5631324644186134 and parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.12923381952984464, 'lr': 0.009342728310721199, 'weight_decay': 0.08524338742076888, 'batch_size': 256}. Best is trial 10 with value: 0.5657974901513136. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.563132 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.12923381952984464, 'lr': 0.009342728310721199, 'weight_decay': 0.08524338742076888, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 01:09:55,560] Trial 22 finished with value: 0.536965981414783 and parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.12496580784462663, 'lr': 0.009641271126421522, 'weight_decay': 0.05742792101682836, 'batch_size': 256}. Best is trial 10 with value: 0.5657974901513136. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.536966 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.12496580784462663, 'lr': 0.009641271126421522, 'weight_decay': 0.05742792101682836, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:10:03,303] Trial 23 pruned. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.444618 - Parameters: {'d_main': 192, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.12473726849896447, 'lr': 0.0028495836527775457, 'weight_decay': 0.017442043733128635, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:10:20,029] Trial 24 pruned. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.451852 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.10050766022350172, 'lr': 0.005080275559900223, 'weight_decay': 0.0976436467513916, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:10:28,266] Trial 25 pruned. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.433735 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.14824886619041971, 'lr': 0.002114816499987826, 'weight_decay': 0.04689863993221635, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:10:35,676] Trial 26 pruned. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.451484 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.16473409594137764, 'lr': 0.0059036327729321365, 'weight_decay': 0.030292108591217844, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 01:12:29,838] Trial 27 pruned. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.501274 - Parameters: {'d_main': 96, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.12542687243388767, 'lr': 0.0026649678377323495, 'weight_decay': 0.0627510282424863, 'batch_size': 64} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:12:41,491] Trial 28 pruned. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.405152 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.20966599109861195, 'lr': 0.005798891553711698, 'weight_decay': 0.017618226227701404, 'batch_size': 128} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 01:14:46,694] Trial 29 finished with value: 0.5233306342708856 and parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.1698102302932065, 'lr': 0.001363507182787418, 'weight_decay': 0.008529289969318454, 'batch_size': 64}. Best is trial 10 with value: 0.5657974901513136. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.523331 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.1698102302932065, 'lr': 0.001363507182787418, 'weight_decay': 0.008529289969318454, 'batch_size': 64} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:14:53,964] Trial 30 pruned. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.392359 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.1293003618398662, 'lr': 0.0011157823272516727, 'weight_decay': 0.06518695815967147, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:15:01,337] Trial 31 pruned. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.447735 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.2312603994764229, 'lr': 0.0072762201538325525, 'weight_decay': 0.0933477093819344, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 01:15:42,739] Trial 32 finished with value: 0.5303323712328316 and parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.14823788001465182, 'lr': 0.00728075208772201, 'weight_decay': 0.03939816243951985, 'batch_size': 256}. Best is trial 10 with value: 0.5657974901513136. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.530332 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.14823788001465182, 'lr': 0.00728075208772201, 'weight_decay': 0.03939816243951985, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:15:55,152] Trial 33 pruned. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.455810 - Parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.24756117454943752, 'lr': 0.00989624777755689, 'weight_decay': 0.03049380047640989, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 01:16:31,015] Trial 34 finished with value: 0.529993910246214 and parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.1194331604252038, 'lr': 0.004100994586737723, 'weight_decay': 0.0690443264930513, 'batch_size': 256}. Best is trial 10 with value: 0.5657974901513136. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.529994 - Parameters: {'d_main': 192, 'd_hidden': 256, 'n_blocks': 3, 'dropout': 0.1194331604252038, 'lr': 0.004100994586737723, 'weight_decay': 0.0690443264930513, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:16:38,359] Trial 35 pruned. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.461073 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.18332667802088354, 'lr': 0.005659088298021359, 'weight_decay': 0.0334210602206272, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:16:44,067] Trial 36 pruned. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.409825 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 2, 'dropout': 0.1604443447882551, 'lr': 0.0027460443918513313, 'weight_decay': 0.0705588216812739, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:16:53,286] Trial 37 pruned. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.394825 - Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.27635410151360057, 'lr': 0.009934371332939828, 'weight_decay': 0.021308226053985385, 'batch_size': 128} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:17:07,124] Trial 38 pruned. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.395529 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 3, 'dropout': 0.1117511036453075, 'lr': 0.006387600810723465, 'weight_decay': 0.040420035058477646, 'batch_size': 64} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:17:39,432] Trial 39 pruned. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.410601 - Parameters: {'d_main': 160, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.1421156861320548, 'lr': 0.000607249814094972, 'weight_decay': 0.027164302357791364, 'batch_size': 32} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:17:45,517] Trial 40 pruned. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.452492 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.3206582962238784, 'lr': 0.003226852110642448, 'weight_decay': 0.09805718915821852, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 01:18:28,196] Trial 41 finished with value: 0.5422970899509355 and parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.11672476117135427, 'lr': 0.007776642750170445, 'weight_decay': 0.05595658806326156, 'batch_size': 256}. Best is trial 10 with value: 0.5657974901513136. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.542297 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.11672476117135427, 'lr': 0.007776642750170445, 'weight_decay': 0.05595658806326156, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 01:19:18,336] Trial 42 finished with value: 0.5425734316686407 and parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.11409458082717218, 'lr': 0.007034332204610135, 'weight_decay': 0.06763567411107038, 'batch_size': 256}. Best is trial 10 with value: 0.5657974901513136. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.542573 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.11409458082717218, 'lr': 0.007034332204610135, 'weight_decay': 0.06763567411107038, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:19:25,088] Trial 43 pruned. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.425178 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.10946563388336114, 'lr': 0.0042511183589127675, 'weight_decay': 0.074382543611822, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:19:51,944] Trial 44 pruned. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.331683 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.1316710538402613, 'lr': 0.007146820667453135, 'weight_decay': 0.049286585317073174, 'batch_size': 32} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:19:58,616] Trial 45 pruned. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.439024 - Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.3485630367992857, 'lr': 0.004476924390328516, 'weight_decay': 0.08076200791991599, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:20:05,394] Trial 46 pruned. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.402256 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.15432789267365343, 'lr': 0.0019259873866568024, 'weight_decay': 0.07073601909719147, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:20:12,414] Trial 47 pruned. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.439476 - Parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.10053866688834341, 'lr': 0.003450693198416156, 'weight_decay': 0.03536147245214299, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:20:41,467] Trial 48 pruned. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.297173 - Parameters: {'d_main': 64, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.13610691050138274, 'lr': 0.0076283214691741895, 'weight_decay': 0.051197606203410885, 'batch_size': 32} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:21:05,720] Trial 49 pruned. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.456386 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.11448245308155942, 'lr': 0.004982548626260849, 'weight_decay': 0.09755409511522563, 'batch_size': 128} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:21:11,787] Trial 50 pruned. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.415219 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.19792179970604962, 'lr': 0.0022539730627043797, 'weight_decay': 0.05781551904129336, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:21:18,232] Trial 51 pruned. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.428459 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.11005618200380084, 'lr': 0.007960589364416262, 'weight_decay': 0.0552320451339676, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:21:24,685] Trial 52 pruned. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.431545 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.11720147714746906, 'lr': 0.007837274018201994, 'weight_decay': 0.077797146076287, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:21:31,733] Trial 53 pruned. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.467136 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.13844306670700557, 'lr': 0.0061581521619264775, 'weight_decay': 0.040235382551265714, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:21:38,131] Trial 54 pruned. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.415739 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.12363447642442357, 'lr': 0.009408190483971443, 'weight_decay': 0.021838090274106114, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:21:44,846] Trial 55 pruned. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.408654 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.17321124126460036, 'lr': 0.0033579983154139073, 'weight_decay': 0.05022984187865108, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:21:52,187] Trial 56 pruned. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.456869 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.14310325294649373, 'lr': 0.005324089517180886, 'weight_decay': 0.07729038077536858, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:22:05,237] Trial 57 pruned. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.466561 - Parameters: {'d_main': 160, 'd_hidden': 64, 'n_blocks': 3, 'dropout': 0.1559183849571359, 'lr': 0.00998027254454398, 'weight_decay': 0.05875832721338847, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:22:21,564] Trial 58 pruned. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.415748 - Parameters: {'d_main': 128, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.10817496117090926, 'lr': 0.0041436778124385905, 'weight_decay': 0.09815900390004917, 'batch_size': 64} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 01:23:14,883] Trial 59 finished with value: 0.5369375015100614 and parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.12906354081419563, 'lr': 0.006550131806153976, 'weight_decay': 0.03816050334944652, 'batch_size': 256}. Best is trial 10 with value: 0.5657974901513136. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.536938 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.12906354081419563, 'lr': 0.006550131806153976, 'weight_decay': 0.03816050334944652, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:23:21,230] Trial 60 pruned. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.434180 - Parameters: {'d_main': 192, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.1012763013058034, 'lr': 0.004779057318065506, 'weight_decay': 0.026841812267314333, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:23:27,788] Trial 61 pruned. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.428571 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.12165966610020537, 'lr': 0.008037675741030096, 'weight_decay': 0.06292000756850075, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:23:41,704] Trial 62 pruned. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.463659 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.1328433502183065, 'lr': 0.008345177425980826, 'weight_decay': 0.04868936309899401, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 01:24:29,011] Trial 63 finished with value: 0.548895187665947 and parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.11728532038581209, 'lr': 0.006319507377618241, 'weight_decay': 0.07874528187658836, 'batch_size': 256}. Best is trial 10 with value: 0.5657974901513136. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.548895 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.11728532038581209, 'lr': 0.006319507377618241, 'weight_decay': 0.07874528187658836, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:24:35,389] Trial 64 pruned. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.446178 - Parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.11485381061797043, 'lr': 0.0060166011000717945, 'weight_decay': 0.07758408291819936, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:24:44,676] Trial 65 pruned. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.409722 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.14504114351788294, 'lr': 0.003512413711868491, 'weight_decay': 0.08360424446232625, 'batch_size': 128} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:24:51,577] Trial 66 pruned. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.445341 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.16395355136514023, 'lr': 0.004840124590846542, 'weight_decay': 0.061651536300328144, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 01:25:47,683] Trial 67 finished with value: 0.5512789377857006 and parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.100031475942269, 'lr': 0.006826955927321861, 'weight_decay': 0.09973844949972972, 'batch_size': 256}. Best is trial 10 with value: 0.5657974901513136. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.551279 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.100031475942269, 'lr': 0.006826955927321861, 'weight_decay': 0.09973844949972972, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:26:20,003] Trial 68 pruned. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.341134 - Parameters: {'d_main': 224, 'd_hidden': 256, 'n_blocks': 6, 'dropout': 0.1066292494176178, 'lr': 0.0064638740516152204, 'weight_decay': 0.09939395036544936, 'batch_size': 32} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:26:27,251] Trial 69 pruned. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.427451 - Parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.1245896740517777, 'lr': 0.002802832718454946, 'weight_decay': 0.03387067549897562, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:26:44,848] Trial 70 pruned. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.410046 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 6, 'dropout': 0.10263763001480719, 'lr': 0.005256041605062858, 'weight_decay': 0.04367847932654872, 'batch_size': 64} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:26:51,265] Trial 71 pruned. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.435070 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.11721513234328487, 'lr': 0.008639652423499188, 'weight_decay': 0.07268246423719095, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:26:57,818] Trial 72 pruned. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.430189 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.13192736964450763, 'lr': 0.006891488925908063, 'weight_decay': 0.08355737471964135, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:27:03,846] Trial 73 pruned. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.406342 - Parameters: {'d_main': 96, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.11871447574881547, 'lr': 0.009786943614708192, 'weight_decay': 0.059219483920107084, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:27:11,029] Trial 74 pruned. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.420775 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 6, 'dropout': 0.11166574549091715, 'lr': 0.003946037019721871, 'weight_decay': 0.04822363430279504, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:27:17,740] Trial 75 pruned. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.448361 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.13817128175084362, 'lr': 0.007167141744793665, 'weight_decay': 0.08244879630605882, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:27:23,425] Trial 76 pruned. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.441820 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 2, 'dropout': 0.10003863571054683, 'lr': 0.005519774435953239, 'weight_decay': 0.08100124483650961, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:27:30,777] Trial 77 pruned. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.468983 - Parameters: {'d_main': 256, 'd_hidden': 192, 'n_blocks': 5, 'dropout': 0.1257279287882203, 'lr': 0.008392181566703839, 'weight_decay': 0.06730410171392288, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) -[I 2025-12-26 01:27:57,861] Trial 78 pruned. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.536246 - Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.1112888297013719, 'lr': 0.004376909353610049, 'weight_decay': 0.045073882375685735, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:28:06,389] Trial 79 pruned. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.438627 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.15210130795935012, 'lr': 0.006670350143994888, 'weight_decay': 0.032467560701983623, 'batch_size': 128} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) -[I 2025-12-26 01:28:37,384] Trial 80 pruned. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.542373 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 6, 'dropout': 0.14518070963421165, 'lr': 0.0053536928906253965, 'weight_decay': 0.06249314376111498, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:28:43,760] Trial 81 pruned. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.362489 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.12436477302529395, 'lr': 0.009835525836034337, 'weight_decay': 0.0563283118691329, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:28:50,132] Trial 82 pruned. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.440406 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.1073598929029249, 'lr': 0.00846380379209577, 'weight_decay': 0.0999057115535506, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 01:29:48,863] Trial 83 finished with value: 0.5401008788879833 and parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.13324159371395203, 'lr': 0.0071922642886845635, 'weight_decay': 0.06715454757946063, 'batch_size': 256}. Best is trial 10 with value: 0.5657974901513136. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.540101 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.13324159371395203, 'lr': 0.0071922642886845635, 'weight_decay': 0.06715454757946063, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 01:30:29,459] Trial 84 pruned. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.513441 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.13255650206383865, 'lr': 0.007096988680959557, 'weight_decay': 0.07013341495146849, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:30:35,787] Trial 85 pruned. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.436962 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.11582757179010825, 'lr': 0.0036901460210835776, 'weight_decay': 0.08563146469743467, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:31:02,465] Trial 86 pruned. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.424691 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.13501808815403032, 'lr': 0.005932747309339245, 'weight_decay': 0.05088794249852813, 'batch_size': 32} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:31:08,541] Trial 87 pruned. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.442760 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.10724492681878241, 'lr': 0.004753198134511028, 'weight_decay': 0.04232271331508332, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:31:25,099] Trial 88 pruned. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.336877 - Parameters: {'d_main': 256, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.1204127890703194, 'lr': 0.008059572689508765, 'weight_decay': 0.08716314449906024, 'batch_size': 64} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:31:31,663] Trial 89 pruned. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.437792 - Parameters: {'d_main': 128, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.1484800236032622, 'lr': 0.002980711108441323, 'weight_decay': 0.06792436946976993, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:31:37,382] Trial 90 pruned. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.443134 - Parameters: {'d_main': 224, 'd_hidden': 64, 'n_blocks': 2, 'dropout': 0.14106325517469248, 'lr': 0.006121576880151821, 'weight_decay': 0.03771856675495574, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:31:43,755] Trial 91 pruned. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.445205 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.12886082955520972, 'lr': 0.008585604748907214, 'weight_decay': 0.0577909420025908, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:31:57,831] Trial 92 pruned. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.451437 - Parameters: {'d_main': 160, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.12012711196760774, 'lr': 0.007356204375862358, 'weight_decay': 0.0875071547245646, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:32:04,772] Trial 93 pruned. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.469167 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.10466426752205814, 'lr': 0.008540683427631602, 'weight_decay': 0.0705017292810407, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:32:11,124] Trial 94 pruned. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.420455 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 4, 'dropout': 0.11388880219555003, 'lr': 0.006956168143656705, 'weight_decay': 0.05432528689989613, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:32:17,897] Trial 95 pruned. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.391020 - Parameters: {'d_main': 192, 'd_hidden': 128, 'n_blocks': 5, 'dropout': 0.16133135068014567, 'lr': 0.009682661627739526, 'weight_decay': 0.07484846021400264, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:32:23,903] Trial 96 pruned. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.425759 - Parameters: {'d_main': 224, 'd_hidden': 128, 'n_blocks': 3, 'dropout': 0.12692221992145408, 'lr': 0.00469144283887213, 'weight_decay': 0.08769734870064443, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:32:30,309] Trial 97 pruned. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.438982 - Parameters: {'d_main': 256, 'd_hidden': 64, 'n_blocks': 4, 'dropout': 0.29450116978879315, 'lr': 0.0059625171795270855, 'weight_decay': 0.09996156868326624, 'batch_size': 256} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 01:33:58,581] Trial 98 finished with value: 0.5501145869977568 and parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.13833322969096906, 'lr': 0.003951632515561313, 'weight_decay': 0.04461794241236279, 'batch_size': 128}. Best is trial 10 with value: 0.5657974901513136. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.550115 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.13833322969096906, 'lr': 0.003951632515561313, 'weight_decay': 0.04461794241236279, 'batch_size': 128} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 01:34:07,945] Trial 99 pruned. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.444351 - Parameters: {'d_main': 224, 'd_hidden': 192, 'n_blocks': 4, 'dropout': 0.13743763081930566, 'lr': 0.0041304570249015475, 'weight_decay': 0.04400800237316215, 'batch_size': 128} - Best Value (CSI): 0.565797 - Best Trial: 10 - Best Parameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.5658 -Best Hyperparameters: {'d_main': 128, 'd_hidden': 64, 'n_blocks': 5, 'dropout': 0.1024240157205574, 'lr': 0.009019177625524915, 'weight_decay': 0.08874117499066106, 'batch_size': 256} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.4986 - - 최종 CSI: 0.4444 - - 최고 CSI: 0.5658 - - 최저 CSI: 0.2826 - - 평균 CSI: 0.4509 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/deepgbm_smotenc_ctgan20000_seoul_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 42, Best CSI: 0.4873 - Fold 1 학습 완료 (검증 CSI: 0.4873) -Fold 2 학습 중... - Early stopping at epoch 30, Best CSI: 0.5746 - Fold 2 학습 완료 (검증 CSI: 0.5746) -Fold 3 학습 중... - Early stopping at epoch 33, Best CSI: 0.5781 - Fold 3 학습 완료 (검증 CSI: 0.5781) - -모든 모델 저장 완료: ../save_model/deepgbm_optima/deepgbm_smotenc_ctgan20000_seoul.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/deepgbm_optima/scaler/deepgbm_smotenc_ctgan20000_seoul_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: ../save_model/deepgbm_optima/deepgbm_smotenc_ctgan20000_seoul.pkl - -✓ 완료: deepgbm_smotenc_ctgan20000/deepgbm_smotenc_ctgan20000_seoul.py (소요 시간: 2883초) - -========================================== -DeepGBM SMOTENC CTGAN20000 파일 실행 완료 -종료 시간: 2025-12-26 01:35:09 -총 소요 시간: 10시간 38분 4초 -성공: 6개 -실패: 0개 -========================================== diff --git a/Analysis_code/5.optima/run_bash/deepgbm/run_deepgbm_ctgan10000.sh b/Analysis_code/5.optima/run_bash/deepgbm/run_deepgbm_ctgan10000.sh deleted file mode 100755 index 4ce18cec7d07cf11c42dd257f5edc2c622011efa..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/run_bash/deepgbm/run_deepgbm_ctgan10000.sh +++ /dev/null @@ -1,80 +0,0 @@ -#!/bin/bash - -# 스크립트 디렉토리로 이동 (상위 디렉토리인 5.optima로 이동) -cd "$(dirname "$0")/../.." - -# 시작 시간 기록 -START_TIME=$(date +%s) -echo "==========================================" -echo "DeepGBM CTGAN10000 파일 실행 시작" -echo "시작 시간: $(date '+%Y-%m-%d %H:%M:%S')" -echo "GPU: 0번 (CUDA_VISIBLE_DEVICES=0)" -echo "==========================================" -echo "" - -# 실행할 파일 목록 -FILES=( - "deepgbm_ctgan10000_busan.py" - "deepgbm_ctgan10000_daegu.py" - "deepgbm_ctgan10000_daejeon.py" - "deepgbm_ctgan10000_gwangju.py" - "deepgbm_ctgan10000_incheon.py" - "deepgbm_ctgan10000_seoul.py" -) - -# 에러 발생 시 중단 여부 (set -e를 사용하면 에러 발생 시 즉시 중단) -set -e - -# 각 파일 실행 -SUCCESS_COUNT=0 -FAIL_COUNT=0 - -for file in "${FILES[@]}"; do - filepath="deepgbm_ctgan10000/$file" - if [ ! -f "$filepath" ]; then - echo "⚠️ 경고: $filepath 파일을 찾을 수 없습니다. 건너뜁니다." - FAIL_COUNT=$((FAIL_COUNT + 1)) - continue - fi - - echo "----------------------------------------" - echo "실행 중: $filepath" - echo "시작 시간: $(date '+%Y-%m-%d %H:%M:%S')" - echo "----------------------------------------" - - FILE_START=$(date +%s) - - # Python 스크립트 실행 (GPU 0번 설정) - if CUDA_VISIBLE_DEVICES=0 python3 -u "$filepath"; then - FILE_END=$(date +%s) - FILE_DURATION=$((FILE_END - FILE_START)) - echo "" - echo "✓ 완료: $filepath (소요 시간: ${FILE_DURATION}초)" - SUCCESS_COUNT=$((SUCCESS_COUNT + 1)) - else - FILE_END=$(date +%s) - FILE_DURATION=$((FILE_END - FILE_START)) - echo "" - echo "✗ 실패: $filepath (소요 시간: ${FILE_DURATION}초)" - FAIL_COUNT=$((FAIL_COUNT + 1)) - echo "에러 발생으로 인해 스크립트를 중단합니다." - exit 1 - fi - echo "" -done - -# 종료 시간 기록 -END_TIME=$(date +%s) -TOTAL_DURATION=$((END_TIME - START_TIME)) -HOURS=$((TOTAL_DURATION / 3600)) -MINUTES=$(((TOTAL_DURATION % 3600) / 60)) -SECONDS=$((TOTAL_DURATION % 60)) - -echo "==========================================" -echo "DeepGBM CTGAN10000 파일 실행 완료" -echo "종료 시간: $(date '+%Y-%m-%d %H:%M:%S')" -echo "총 소요 시간: ${HOURS}시간 ${MINUTES}분 ${SECONDS}초" -echo "성공: ${SUCCESS_COUNT}개" -echo "실패: ${FAIL_COUNT}개" -echo "==========================================" - diff --git a/Analysis_code/5.optima/run_bash/deepgbm/run_deepgbm_pure.sh b/Analysis_code/5.optima/run_bash/deepgbm/run_deepgbm_pure.sh deleted file mode 100755 index 423cde0617b1e8c13020077e12abb6992bf340c2..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/run_bash/deepgbm/run_deepgbm_pure.sh +++ /dev/null @@ -1,80 +0,0 @@ -#!/bin/bash - -# 스크립트 디렉토리로 이동 (상위 디렉토리인 5.optima로 이동) -cd "$(dirname "$0")/../.." - -# 시작 시간 기록 -START_TIME=$(date +%s) -echo "==========================================" -echo "DeepGBM Pure 파일 실행 시작" -echo "시작 시간: $(date '+%Y-%m-%d %H:%M:%S')" -echo "GPU: 1번 (CUDA_VISIBLE_DEVICES=1)" -echo "==========================================" -echo "" - -# 실행할 파일 목록 -FILES=( - "deepgbm_pure_busan.py" - "deepgbm_pure_daegu.py" - "deepgbm_pure_daejeon.py" - "deepgbm_pure_gwangju.py" - "deepgbm_pure_incheon.py" - "deepgbm_pure_seoul.py" -) - -# 에러 발생 시 중단 여부 (set -e를 사용하면 에러 발생 시 즉시 중단) -set -e - -# 각 파일 실행 -SUCCESS_COUNT=0 -FAIL_COUNT=0 - -for file in "${FILES[@]}"; do - filepath="deepgbm_pure/$file" - if [ ! -f "$filepath" ]; then - echo "⚠️ 경고: $filepath 파일을 찾을 수 없습니다. 건너뜁니다." - FAIL_COUNT=$((FAIL_COUNT + 1)) - continue - fi - - echo "----------------------------------------" - echo "실행 중: $filepath" - echo "시작 시간: $(date '+%Y-%m-%d %H:%M:%S')" - echo "----------------------------------------" - - FILE_START=$(date +%s) - - # Python 스크립트 실행 (GPU 1번 설정) - if CUDA_VISIBLE_DEVICES=0 python3 -u "$filepath"; then - FILE_END=$(date +%s) - FILE_DURATION=$((FILE_END - FILE_START)) - echo "" - echo "✓ 완료: $filepath (소요 시간: ${FILE_DURATION}초)" - SUCCESS_COUNT=$((SUCCESS_COUNT + 1)) - else - FILE_END=$(date +%s) - FILE_DURATION=$((FILE_END - FILE_START)) - echo "" - echo "✗ 실패: $filepath (소요 시간: ${FILE_DURATION}초)" - FAIL_COUNT=$((FAIL_COUNT + 1)) - echo "에러 발생으로 인해 스크립트를 중단합니다." - exit 1 - fi - echo "" -done - -# 종료 시간 기록 -END_TIME=$(date +%s) -TOTAL_DURATION=$((END_TIME - START_TIME)) -HOURS=$((TOTAL_DURATION / 3600)) -MINUTES=$(((TOTAL_DURATION % 3600) / 60)) -SECONDS=$((TOTAL_DURATION % 60)) - -echo "==========================================" -echo "DeepGBM Pure 파일 실행 완료" -echo "종료 시간: $(date '+%Y-%m-%d %H:%M:%S')" -echo "총 소요 시간: ${HOURS}시간 ${MINUTES}분 ${SECONDS}초" -echo "성공: ${SUCCESS_COUNT}개" -echo "실패: ${FAIL_COUNT}개" -echo "==========================================" - diff --git a/Analysis_code/5.optima/run_bash/deepgbm/run_deepgbm_smote.sh b/Analysis_code/5.optima/run_bash/deepgbm/run_deepgbm_smote.sh deleted file mode 100755 index 625c31a93093b993110c3e510088a5b7ba4fdcea..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/run_bash/deepgbm/run_deepgbm_smote.sh +++ /dev/null @@ -1,80 +0,0 @@ -#!/bin/bash - -# 스크립트 디렉토리로 이동 (상위 디렉토리인 5.optima로 이동) -cd "$(dirname "$0")/../.." - -# 시작 시간 기록 -START_TIME=$(date +%s) -echo "==========================================" -echo "DeepGBM SMOTE 파일 실행 시작" -echo "시작 시간: $(date '+%Y-%m-%d %H:%M:%S')" -echo "GPU: 1번 (CUDA_VISIBLE_DEVICES=1)" -echo "==========================================" -echo "" - -# 실행할 파일 목록 -FILES=( - "deepgbm_smote_busan.py" - "deepgbm_smote_daegu.py" - "deepgbm_smote_daejeon.py" - "deepgbm_smote_gwangju.py" - "deepgbm_smote_incheon.py" - "deepgbm_smote_seoul.py" -) - -# 에러 발생 시 중단 여부 (set -e를 사용하면 에러 발생 시 즉시 중단) -set -e - -# 각 파일 실행 -SUCCESS_COUNT=0 -FAIL_COUNT=0 - -for file in "${FILES[@]}"; do - filepath="deepgbm_smote/$file" - if [ ! -f "$filepath" ]; then - echo "⚠️ 경고: $filepath 파일을 찾을 수 없습니다. 건너뜁니다." - FAIL_COUNT=$((FAIL_COUNT + 1)) - continue - fi - - echo "----------------------------------------" - echo "실행 중: $filepath" - echo "시작 시간: $(date '+%Y-%m-%d %H:%M:%S')" - echo "----------------------------------------" - - FILE_START=$(date +%s) - - # Python 스크립트 실행 (GPU 1번 설정) - if CUDA_VISIBLE_DEVICES=0 python3 -u "$filepath"; then - FILE_END=$(date +%s) - FILE_DURATION=$((FILE_END - FILE_START)) - echo "" - echo "✓ 완료: $filepath (소요 시간: ${FILE_DURATION}초)" - SUCCESS_COUNT=$((SUCCESS_COUNT + 1)) - else - FILE_END=$(date +%s) - FILE_DURATION=$((FILE_END - FILE_START)) - echo "" - echo "✗ 실패: $filepath (소요 시간: ${FILE_DURATION}초)" - FAIL_COUNT=$((FAIL_COUNT + 1)) - echo "에러 발생으로 인해 스크립트를 중단합니다." - exit 1 - fi - echo "" -done - -# 종료 시간 기록 -END_TIME=$(date +%s) -TOTAL_DURATION=$((END_TIME - START_TIME)) -HOURS=$((TOTAL_DURATION / 3600)) -MINUTES=$(((TOTAL_DURATION % 3600) / 60)) -SECONDS=$((TOTAL_DURATION % 60)) - -echo "==========================================" -echo "DeepGBM SMOTE 파일 실행 완료" -echo "종료 시간: $(date '+%Y-%m-%d %H:%M:%S')" -echo "총 소요 시간: ${HOURS}시간 ${MINUTES}분 ${SECONDS}초" -echo "성공: ${SUCCESS_COUNT}개" -echo "실패: ${FAIL_COUNT}개" -echo "==========================================" - diff --git a/Analysis_code/5.optima/run_bash/deepgbm/run_deepgbm_smotenc_ctgan20000.sh b/Analysis_code/5.optima/run_bash/deepgbm/run_deepgbm_smotenc_ctgan20000.sh deleted file mode 100755 index 4cea953e2afa69b147afaeb50df2e9180e00d667..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/run_bash/deepgbm/run_deepgbm_smotenc_ctgan20000.sh +++ /dev/null @@ -1,80 +0,0 @@ -#!/bin/bash - -# 스크립트 디렉토리로 이동 (상위 디렉토리인 5.optima로 이동) -cd "$(dirname "$0")/../.." - -# 시작 시간 기록 -START_TIME=$(date +%s) -echo "==========================================" -echo "DeepGBM SMOTENC CTGAN20000 파일 실행 시작" -echo "시작 시간: $(date '+%Y-%m-%d %H:%M:%S')" -echo "GPU: 1번 (CUDA_VISIBLE_DEVICES=1)" -echo "==========================================" -echo "" - -# 실행할 파일 목록 -FILES=( - "deepgbm_smotenc_ctgan20000_busan.py" - "deepgbm_smotenc_ctgan20000_daegu.py" - "deepgbm_smotenc_ctgan20000_daejeon.py" - "deepgbm_smotenc_ctgan20000_gwangju.py" - "deepgbm_smotenc_ctgan20000_incheon.py" - "deepgbm_smotenc_ctgan20000_seoul.py" -) - -# 에러 발생 시 중단 여부 (set -e를 사용하면 에러 발생 시 즉시 중단) -set -e - -# 각 파일 실행 -SUCCESS_COUNT=0 -FAIL_COUNT=0 - -for file in "${FILES[@]}"; do - filepath="deepgbm_smotenc_ctgan20000/$file" - if [ ! -f "$filepath" ]; then - echo "⚠️ 경고: $filepath 파일을 찾을 수 없습니다. 건너뜁니다." - FAIL_COUNT=$((FAIL_COUNT + 1)) - continue - fi - - echo "----------------------------------------" - echo "실행 중: $filepath" - echo "시작 시간: $(date '+%Y-%m-%d %H:%M:%S')" - echo "----------------------------------------" - - FILE_START=$(date +%s) - - # Python 스크립트 실행 (GPU 1번 설정) - if CUDA_VISIBLE_DEVICES=0 python3 -u "$filepath"; then - FILE_END=$(date +%s) - FILE_DURATION=$((FILE_END - FILE_START)) - echo "" - echo "✓ 완료: $filepath (소요 시간: ${FILE_DURATION}초)" - SUCCESS_COUNT=$((SUCCESS_COUNT + 1)) - else - FILE_END=$(date +%s) - FILE_DURATION=$((FILE_END - FILE_START)) - echo "" - echo "✗ 실패: $filepath (소요 시간: ${FILE_DURATION}초)" - FAIL_COUNT=$((FAIL_COUNT + 1)) - echo "에러 발생으로 인해 스크립트를 중단합니다." - exit 1 - fi - echo "" -done - -# 종료 시간 기록 -END_TIME=$(date +%s) -TOTAL_DURATION=$((END_TIME - START_TIME)) -HOURS=$((TOTAL_DURATION / 3600)) -MINUTES=$(((TOTAL_DURATION % 3600) / 60)) -SECONDS=$((TOTAL_DURATION % 60)) - -echo "==========================================" -echo "DeepGBM SMOTENC CTGAN20000 파일 실행 완료" -echo "종료 시간: $(date '+%Y-%m-%d %H:%M:%S')" -echo "총 소요 시간: ${HOURS}시간 ${MINUTES}분 ${SECONDS}초" -echo "성공: ${SUCCESS_COUNT}개" -echo "실패: ${FAIL_COUNT}개" -echo "==========================================" - diff --git a/Analysis_code/5.optima/run_bash/ft_transformer/ft_transformer_ctgan10000.log b/Analysis_code/5.optima/run_bash/ft_transformer/ft_transformer_ctgan10000.log deleted file mode 100644 index c33d31e2369e41c3b798779331261e4b57369994..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/run_bash/ft_transformer/ft_transformer_ctgan10000.log +++ /dev/null @@ -1,7974 +0,0 @@ -nohup: ignoring input -/bin/bash: /opt/conda/lib/libtinfo.so.6: no version information available (required by /bin/bash) -========================================== -FT-Transformer CTGAN10000 파일 실행 시작 -시작 시간: 2025-12-28 12:36:22 -GPU: 1번 (CUDA_VISIBLE_DEVICES=1) -========================================== - ----------------------------------------- -실행 중: ft_transformer_ctgan10000/ft_transformer_ctgan10000_busan.py -시작 시간: 2025-12-28 12:36:22 ----------------------------------------- -[I 2025-12-28 12:36:23,448] A new study created in memory with name: no-name-e80e745d-9835-433d-945d-46785d8fe8b9 - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 12:37:52,007] Trial 0 finished with value: 0.2937353546123581 and parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.15557858942827202, 'ffn_dropout': 0.16969935785804233, 'lr': 6.490237465988272e-05, 'weight_decay': 0.0011203727047510053, 'batch_size': 256}. Best is trial 0 with value: 0.2937353546123581. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.293735 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.15557858942827202, 'ffn_dropout': 0.16969935785804233, 'lr': 6.490237465988272e-05, 'weight_decay': 0.0011203727047510053, 'batch_size': 256} - Best Value (CSI): 0.293735 - Best Trial: 0 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.15557858942827202, 'ffn_dropout': 0.16969935785804233, 'lr': 6.490237465988272e-05, 'weight_decay': 0.0011203727047510053, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 12:40:30,192] Trial 1 finished with value: 0.2592751845674596 and parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.11569357924954832, 'ffn_dropout': 0.2717601648117537, 'lr': 3.2412384190319987e-05, 'weight_decay': 0.045120013876145344, 'batch_size': 256}. Best is trial 0 with value: 0.2937353546123581. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.259275 - Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.11569357924954832, 'ffn_dropout': 0.2717601648117537, 'lr': 3.2412384190319987e-05, 'weight_decay': 0.045120013876145344, 'batch_size': 256} - Best Value (CSI): 0.293735 - Best Trial: 0 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.15557858942827202, 'ffn_dropout': 0.16969935785804233, 'lr': 6.490237465988272e-05, 'weight_decay': 0.0011203727047510053, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 12:42:37,694] Trial 2 finished with value: 0.05763020768354185 and parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.27794328531059703, 'ffn_dropout': 0.38416020684121166, 'lr': 0.004195343130425373, 'weight_decay': 0.0034238609577708187, 'batch_size': 64}. Best is trial 0 with value: 0.2937353546123581. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.057630 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.27794328531059703, 'ffn_dropout': 0.38416020684121166, 'lr': 0.004195343130425373, 'weight_decay': 0.0034238609577708187, 'batch_size': 64} - Best Value (CSI): 0.293735 - Best Trial: 0 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.15557858942827202, 'ffn_dropout': 0.16969935785804233, 'lr': 6.490237465988272e-05, 'weight_decay': 0.0011203727047510053, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 12:48:38,996] Trial 3 finished with value: 0.3349144718213748 and parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.32923827238769926, 'ffn_dropout': 0.35307454041648356, 'lr': 1.4972537950935246e-05, 'weight_decay': 0.019938736065690722, 'batch_size': 32}. Best is trial 3 with value: 0.3349144718213748. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.334914 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.32923827238769926, 'ffn_dropout': 0.35307454041648356, 'lr': 1.4972537950935246e-05, 'weight_decay': 0.019938736065690722, 'batch_size': 32} - Best Value (CSI): 0.334914 - Best Trial: 3 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.32923827238769926, 'ffn_dropout': 0.35307454041648356, 'lr': 1.4972537950935246e-05, 'weight_decay': 0.019938736065690722, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 12:50:35,888] Trial 4 finished with value: 0.2927190406070285 and parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22423571821376748, 'ffn_dropout': 0.17164042763282372, 'lr': 2.9118459062015985e-05, 'weight_decay': 0.002271616984005451, 'batch_size': 128}. Best is trial 3 with value: 0.3349144718213748. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.292719 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22423571821376748, 'ffn_dropout': 0.17164042763282372, 'lr': 2.9118459062015985e-05, 'weight_decay': 0.002271616984005451, 'batch_size': 128} - Best Value (CSI): 0.334914 - Best Trial: 3 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.32923827238769926, 'ffn_dropout': 0.35307454041648356, 'lr': 1.4972537950935246e-05, 'weight_decay': 0.019938736065690722, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 12:51:08,623] Trial 5 pruned. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.256831 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.32039892571893924, 'ffn_dropout': 0.31021361449208007, 'lr': 1.9551091797222194e-05, 'weight_decay': 0.0012362676536468661, 'batch_size': 64} - Best Value (CSI): 0.334914 - Best Trial: 3 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.32923827238769926, 'ffn_dropout': 0.35307454041648356, 'lr': 1.4972537950935246e-05, 'weight_decay': 0.019938736065690722, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 12:51:28,907] Trial 6 pruned. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.218088 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1351375555133366, 'ffn_dropout': 0.3729374972870594, 'lr': 7.518669733226845e-05, 'weight_decay': 0.001629924080956464, 'batch_size': 128} - Best Value (CSI): 0.334914 - Best Trial: 3 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.32923827238769926, 'ffn_dropout': 0.35307454041648356, 'lr': 1.4972537950935246e-05, 'weight_decay': 0.019938736065690722, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 12:52:59,420] Trial 7 finished with value: 0.45793006881540704 and parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1948796003161526, 'ffn_dropout': 0.1414963905502595, 'lr': 0.000340207207119526, 'weight_decay': 0.08328209922823542, 'batch_size': 128}. Best is trial 7 with value: 0.45793006881540704. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.457930 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1948796003161526, 'ffn_dropout': 0.1414963905502595, 'lr': 0.000340207207119526, 'weight_decay': 0.08328209922823542, 'batch_size': 128} - Best Value (CSI): 0.457930 - Best Trial: 7 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1948796003161526, 'ffn_dropout': 0.1414963905502595, 'lr': 0.000340207207119526, 'weight_decay': 0.08328209922823542, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 12:53:44,117] Trial 8 finished with value: 0.45392645624637096 and parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2667330749361459, 'ffn_dropout': 0.22311728808305645, 'lr': 0.0021386972798200883, 'weight_decay': 0.00026921701567811834, 'batch_size': 256}. Best is trial 7 with value: 0.45793006881540704. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.453926 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2667330749361459, 'ffn_dropout': 0.22311728808305645, 'lr': 0.0021386972798200883, 'weight_decay': 0.00026921701567811834, 'batch_size': 256} - Best Value (CSI): 0.457930 - Best Trial: 7 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1948796003161526, 'ffn_dropout': 0.1414963905502595, 'lr': 0.000340207207119526, 'weight_decay': 0.08328209922823542, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:04:40,180] Trial 9 pruned. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.441761 - Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.3267010025242002, 'ffn_dropout': 0.15475455757614773, 'lr': 0.00025400607654542845, 'weight_decay': 0.00015788892922449722, 'batch_size': 32} - Best Value (CSI): 0.457930 - Best Trial: 7 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1948796003161526, 'ffn_dropout': 0.1414963905502595, 'lr': 0.000340207207119526, 'weight_decay': 0.08328209922823542, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:05:50,018] Trial 10 finished with value: 0.47923052284165424 and parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3822134547243423, 'ffn_dropout': 0.10076460097758799, 'lr': 0.0006135331541667003, 'weight_decay': 0.09879218512830837, 'batch_size': 128}. Best is trial 10 with value: 0.47923052284165424. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.479231 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3822134547243423, 'ffn_dropout': 0.10076460097758799, 'lr': 0.0006135331541667003, 'weight_decay': 0.09879218512830837, 'batch_size': 128} - Best Value (CSI): 0.479231 - Best Trial: 10 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3822134547243423, 'ffn_dropout': 0.10076460097758799, 'lr': 0.0006135331541667003, 'weight_decay': 0.09879218512830837, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:07:20,453] Trial 11 finished with value: 0.4727975682687428 and parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3636777556470543, 'ffn_dropout': 0.11969603042997873, 'lr': 0.0007594590074859042, 'weight_decay': 0.08838703826582563, 'batch_size': 128}. Best is trial 10 with value: 0.47923052284165424. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.472798 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3636777556470543, 'ffn_dropout': 0.11969603042997873, 'lr': 0.0007594590074859042, 'weight_decay': 0.08838703826582563, 'batch_size': 128} - Best Value (CSI): 0.479231 - Best Trial: 10 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3822134547243423, 'ffn_dropout': 0.10076460097758799, 'lr': 0.0006135331541667003, 'weight_decay': 0.09879218512830837, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:08:29,833] Trial 12 finished with value: 0.48862241437211223 and parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128}. Best is trial 12 with value: 0.48862241437211223. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.488622 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128} - Best Value (CSI): 0.488622 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 13:08:41,008] Trial 13 pruned. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.018321 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3835958117783593, 'ffn_dropout': 0.10406955815052532, 'lr': 0.009649351588332316, 'weight_decay': 0.02292264602371786, 'batch_size': 128} - Best Value (CSI): 0.488622 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:10:14,550] Trial 14 finished with value: 0.4828620884196826 and parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.398593527317624, 'ffn_dropout': 0.11227519393087858, 'lr': 0.0009397711411085843, 'weight_decay': 0.013368406810182924, 'batch_size': 128}. Best is trial 12 with value: 0.48862241437211223. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.482862 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.398593527317624, 'ffn_dropout': 0.11227519393087858, 'lr': 0.0009397711411085843, 'weight_decay': 0.013368406810182924, 'batch_size': 128} - Best Value (CSI): 0.488622 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:12:02,986] Trial 15 finished with value: 0.47892304666149643 and parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.39934023699397664, 'ffn_dropout': 0.19901780511969835, 'lr': 0.0013371590916870385, 'weight_decay': 0.01029812650718879, 'batch_size': 128}. Best is trial 12 with value: 0.48862241437211223. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.478923 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.39934023699397664, 'ffn_dropout': 0.19901780511969835, 'lr': 0.0013371590916870385, 'weight_decay': 0.01029812650718879, 'batch_size': 128} - Best Value (CSI): 0.488622 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 13:12:18,405] Trial 16 pruned. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.224979 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3537029172304629, 'ffn_dropout': 0.13719813351905136, 'lr': 0.0022152440412436273, 'weight_decay': 0.008684437237961428, 'batch_size': 128} - Best Value (CSI): 0.488622 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:17:07,001] Trial 17 finished with value: 0.477121662577825 and parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3975972411997598, 'ffn_dropout': 0.1958197542142851, 'lr': 0.00021772411963727646, 'weight_decay': 0.035822356811918865, 'batch_size': 32}. Best is trial 12 with value: 0.48862241437211223. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.477122 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3975972411997598, 'ffn_dropout': 0.1958197542142851, 'lr': 0.00021772411963727646, 'weight_decay': 0.035822356811918865, 'batch_size': 32} - Best Value (CSI): 0.488622 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:19:17,984] Trial 18 finished with value: 0.4731414749109968 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.29655734971314573, 'ffn_dropout': 0.12834519629902674, 'lr': 0.0008224792902485263, 'weight_decay': 0.010692431388100394, 'batch_size': 64}. Best is trial 12 with value: 0.48862241437211223. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.473141 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.29655734971314573, 'ffn_dropout': 0.12834519629902674, 'lr': 0.0008224792902485263, 'weight_decay': 0.010692431388100394, 'batch_size': 64} - Best Value (CSI): 0.488622 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:21:14,455] Trial 19 finished with value: 0.4691148088213118 and parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3544147730892721, 'ffn_dropout': 0.1057413321888555, 'lr': 0.0004751644231175245, 'weight_decay': 0.04395853372433978, 'batch_size': 128}. Best is trial 12 with value: 0.48862241437211223. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.469115 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3544147730892721, 'ffn_dropout': 0.1057413321888555, 'lr': 0.0004751644231175245, 'weight_decay': 0.04395853372433978, 'batch_size': 128} - Best Value (CSI): 0.488622 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:23:55,030] Trial 20 finished with value: 0.4543474376518259 and parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.29467335552206775, 'ffn_dropout': 0.2538825352655031, 'lr': 0.00013896032431370185, 'weight_decay': 0.004693117908748101, 'batch_size': 128}. Best is trial 12 with value: 0.48862241437211223. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.454347 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.29467335552206775, 'ffn_dropout': 0.2538825352655031, 'lr': 0.00013896032431370185, 'weight_decay': 0.004693117908748101, 'batch_size': 128} - Best Value (CSI): 0.488622 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:25:14,193] Trial 21 finished with value: 0.45288146868894624 and parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.37324935720316477, 'ffn_dropout': 0.10258062620671786, 'lr': 0.0006034434277637087, 'weight_decay': 0.09864974255898239, 'batch_size': 128}. Best is trial 12 with value: 0.48862241437211223. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.452881 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.37324935720316477, 'ffn_dropout': 0.10258062620671786, 'lr': 0.0006034434277637087, 'weight_decay': 0.09864974255898239, 'batch_size': 128} - Best Value (CSI): 0.488622 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:26:55,538] Trial 22 finished with value: 0.47877914246023673 and parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.39862093110642216, 'ffn_dropout': 0.13948398108079021, 'lr': 0.0014086356020661405, 'weight_decay': 0.04466897832152646, 'batch_size': 128}. Best is trial 12 with value: 0.48862241437211223. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.478779 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.39862093110642216, 'ffn_dropout': 0.13948398108079021, 'lr': 0.0014086356020661405, 'weight_decay': 0.04466897832152646, 'batch_size': 128} - Best Value (CSI): 0.488622 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:28:45,940] Trial 23 finished with value: 0.47052982357083595 and parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.36003248851868197, 'ffn_dropout': 0.1236856672429474, 'lr': 0.00048330418585209336, 'weight_decay': 0.022288217122697844, 'batch_size': 128}. Best is trial 12 with value: 0.48862241437211223. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.470530 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.36003248851868197, 'ffn_dropout': 0.1236856672429474, 'lr': 0.00048330418585209336, 'weight_decay': 0.022288217122697844, 'batch_size': 128} - Best Value (CSI): 0.488622 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:29:58,661] Trial 24 finished with value: 0.46532419413769066 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3744309598855003, 'ffn_dropout': 0.16154502867835663, 'lr': 0.0009194327399256198, 'weight_decay': 0.06473618930229175, 'batch_size': 128}. Best is trial 12 with value: 0.48862241437211223. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.465324 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3744309598855003, 'ffn_dropout': 0.16154502867835663, 'lr': 0.0009194327399256198, 'weight_decay': 0.06473618930229175, 'batch_size': 128} - Best Value (CSI): 0.488622 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:31:37,667] Trial 25 finished with value: 0.46748993623212404 and parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3419144780919314, 'ffn_dropout': 0.11054517310900602, 'lr': 0.0003703085958582872, 'weight_decay': 0.05680123566625818, 'batch_size': 128}. Best is trial 12 with value: 0.48862241437211223. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.467490 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3419144780919314, 'ffn_dropout': 0.11054517310900602, 'lr': 0.0003703085958582872, 'weight_decay': 0.05680123566625818, 'batch_size': 128} - Best Value (CSI): 0.488622 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 13:31:45,543] Trial 26 pruned. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.324832 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.38313565359053947, 'ffn_dropout': 0.1489847708228845, 'lr': 0.0001834971490941133, 'weight_decay': 0.0281407878419934, 'batch_size': 256} - Best Value (CSI): 0.488622 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 13:32:52,920] Trial 27 pruned. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.375367 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.35015814008993285, 'ffn_dropout': 0.10045397880157811, 'lr': 0.000605384401215078, 'weight_decay': 0.016494441691168846, 'batch_size': 32} - Best Value (CSI): 0.488622 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:34:58,160] Trial 28 finished with value: 0.47448310453993897 and parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.31137637896890275, 'ffn_dropout': 0.12831232328394068, 'lr': 0.001190805560051262, 'weight_decay': 0.06062942301563714, 'batch_size': 64}. Best is trial 12 with value: 0.48862241437211223. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.474483 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.31137637896890275, 'ffn_dropout': 0.12831232328394068, 'lr': 0.001190805560051262, 'weight_decay': 0.06062942301563714, 'batch_size': 64} - Best Value (CSI): 0.488622 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:36:01,474] Trial 29 finished with value: 0.44950940247059146 and parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3435125531676066, 'ffn_dropout': 0.17831475656208848, 'lr': 0.0003266200986608945, 'weight_decay': 0.029627013142545705, 'batch_size': 256}. Best is trial 12 with value: 0.48862241437211223. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.449509 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3435125531676066, 'ffn_dropout': 0.17831475656208848, 'lr': 0.0003266200986608945, 'weight_decay': 0.029627013142545705, 'batch_size': 256} - Best Value (CSI): 0.488622 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:37:30,027] Trial 30 finished with value: 0.408310760440532 and parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.377088238754656, 'ffn_dropout': 0.15690366014269008, 'lr': 0.00011370341164801367, 'weight_decay': 0.09532204491176723, 'batch_size': 128}. Best is trial 12 with value: 0.48862241437211223. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.408311 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.377088238754656, 'ffn_dropout': 0.15690366014269008, 'lr': 0.00011370341164801367, 'weight_decay': 0.09532204491176723, 'batch_size': 128} - Best Value (CSI): 0.488622 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:39:14,237] Trial 31 finished with value: 0.4767446535696614 and parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.39626503551762093, 'ffn_dropout': 0.20131956009948843, 'lr': 0.001448901293109124, 'weight_decay': 0.011549947898817236, 'batch_size': 128}. Best is trial 12 with value: 0.48862241437211223. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.476745 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.39626503551762093, 'ffn_dropout': 0.20131956009948843, 'lr': 0.001448901293109124, 'weight_decay': 0.011549947898817236, 'batch_size': 128} - Best Value (CSI): 0.488622 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:41:13,761] Trial 32 finished with value: 0.45805689434716906 and parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.39207271092663626, 'ffn_dropout': 0.12112848462976264, 'lr': 0.001074341677073069, 'weight_decay': 0.008137105788653596, 'batch_size': 128}. Best is trial 12 with value: 0.48862241437211223. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.458057 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.39207271092663626, 'ffn_dropout': 0.12112848462976264, 'lr': 0.001074341677073069, 'weight_decay': 0.008137105788653596, 'batch_size': 128} - Best Value (CSI): 0.488622 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 13:41:31,842] Trial 33 pruned. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.004668 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.36670797643769487, 'ffn_dropout': 0.1849571432882215, 'lr': 0.002231993714314073, 'weight_decay': 0.005463704256909418, 'batch_size': 128} - Best Value (CSI): 0.488622 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:43:45,246] Trial 34 finished with value: 0.4798258194478366 and parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39965058525369457, 'ffn_dropout': 0.14739586305927058, 'lr': 0.0006205749036542376, 'weight_decay': 0.014224766444528116, 'batch_size': 128}. Best is trial 12 with value: 0.48862241437211223. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.479826 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39965058525369457, 'ffn_dropout': 0.14739586305927058, 'lr': 0.0006205749036542376, 'weight_decay': 0.014224766444528116, 'batch_size': 128} - Best Value (CSI): 0.488622 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:45:42,928] Trial 35 finished with value: 0.4562823082054032 and parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3363725402175345, 'ffn_dropout': 0.14098570631901305, 'lr': 0.0004625682501499456, 'weight_decay': 0.015560850747105432, 'batch_size': 256}. Best is trial 12 with value: 0.48862241437211223. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.456282 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3363725402175345, 'ffn_dropout': 0.14098570631901305, 'lr': 0.0004625682501499456, 'weight_decay': 0.015560850747105432, 'batch_size': 256} - Best Value (CSI): 0.488622 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:50:13,747] Trial 36 finished with value: 0.477092949628616 and parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.37653812274167003, 'ffn_dropout': 0.1691727284873077, 'lr': 0.0006172859330167775, 'weight_decay': 0.036866097074344524, 'batch_size': 64}. Best is trial 12 with value: 0.48862241437211223. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.477093 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.37653812274167003, 'ffn_dropout': 0.1691727284873077, 'lr': 0.0006172859330167775, 'weight_decay': 0.036866097074344524, 'batch_size': 64} - Best Value (CSI): 0.488622 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 13:52:16,158] Trial 37 finished with value: 0.4752609649920519 and parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3661654289685232, 'ffn_dropout': 0.119511925548937, 'lr': 0.0008233183516473982, 'weight_decay': 0.05912132060829927, 'batch_size': 128}. Best is trial 12 with value: 0.48862241437211223. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.475261 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3661654289685232, 'ffn_dropout': 0.119511925548937, 'lr': 0.0008233183516473982, 'weight_decay': 0.05912132060829927, 'batch_size': 128} - Best Value (CSI): 0.488622 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:00:12,051] Trial 38 finished with value: 0.47065244225262176 and parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.33143453523864835, 'ffn_dropout': 0.15175014374290963, 'lr': 0.0002590205863273558, 'weight_decay': 0.030162094562368017, 'batch_size': 32}. Best is trial 12 with value: 0.48862241437211223. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.470652 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.33143453523864835, 'ffn_dropout': 0.15175014374290963, 'lr': 0.0002590205863273558, 'weight_decay': 0.030162094562368017, 'batch_size': 32} - Best Value (CSI): 0.488622 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 14:00:34,146] Trial 39 pruned. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.095329 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3807640592593791, 'ffn_dropout': 0.11931221379075743, 'lr': 0.00329631959465686, 'weight_decay': 0.02165367800506811, 'batch_size': 128} - Best Value (CSI): 0.488622 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:02:26,310] Trial 40 finished with value: 0.4629778012593533 and parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.31630388259078185, 'ffn_dropout': 0.10100627277463958, 'lr': 0.00036460331240556785, 'weight_decay': 0.015084661260940655, 'batch_size': 128}. Best is trial 12 with value: 0.48862241437211223. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.462978 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.31630388259078185, 'ffn_dropout': 0.10100627277463958, 'lr': 0.00036460331240556785, 'weight_decay': 0.015084661260940655, 'batch_size': 128} - Best Value (CSI): 0.488622 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:03:52,815] Trial 41 finished with value: 0.4800643751467312 and parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.39540012038536, 'ffn_dropout': 0.1355910718164778, 'lr': 0.0012961498074751127, 'weight_decay': 0.006649890579718473, 'batch_size': 128}. Best is trial 12 with value: 0.48862241437211223. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.480064 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.39540012038536, 'ffn_dropout': 0.1355910718164778, 'lr': 0.0012961498074751127, 'weight_decay': 0.006649890579718473, 'batch_size': 128} - Best Value (CSI): 0.488622 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 14:04:14,890] Trial 42 pruned. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.402906 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.38675520932243945, 'ffn_dropout': 0.13212876365160164, 'lr': 0.0016047312028104235, 'weight_decay': 0.0025627660164038615, 'batch_size': 128} - Best Value (CSI): 0.488622 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:05:13,383] Trial 43 finished with value: 0.4746127292865954 and parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.362746278945248, 'ffn_dropout': 0.16624037774191047, 'lr': 0.0009357456572516605, 'weight_decay': 0.006241825908190311, 'batch_size': 128}. Best is trial 12 with value: 0.48862241437211223. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.474613 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.362746278945248, 'ffn_dropout': 0.16624037774191047, 'lr': 0.0009357456572516605, 'weight_decay': 0.006241825908190311, 'batch_size': 128} - Best Value (CSI): 0.488622 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 14:05:54,155] Trial 44 pruned. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.400888 - Parameters: {'d_token': 256, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.386872159728992, 'ffn_dropout': 0.14682206739850118, 'lr': 0.000658820341563418, 'weight_decay': 0.0036239532601317903, 'batch_size': 128} - Best Value (CSI): 0.488622 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:07:17,133] Trial 45 finished with value: 0.4614794755387323 and parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3529831490780354, 'ffn_dropout': 0.11413511882455141, 'lr': 0.0010880661052147054, 'weight_decay': 0.006529020169872523, 'batch_size': 128}. Best is trial 12 with value: 0.48862241437211223. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.461479 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3529831490780354, 'ffn_dropout': 0.11413511882455141, 'lr': 0.0010880661052147054, 'weight_decay': 0.006529020169872523, 'batch_size': 128} - Best Value (CSI): 0.488622 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 14:07:35,383] Trial 46 pruned. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.056218 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3979205222472862, 'ffn_dropout': 0.13534521470769326, 'lr': 0.0030409579164347657, 'weight_decay': 0.07123373111029556, 'batch_size': 64} - Best Value (CSI): 0.488622 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 14:07:57,602] Trial 47 pruned. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.135351 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2433443547474716, 'ffn_dropout': 0.11459657812107736, 'lr': 0.0018325829414567692, 'weight_decay': 0.04583166411874843, 'batch_size': 128} - Best Value (CSI): 0.488622 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:13:14,777] Trial 48 finished with value: 0.4863966891820796 and parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.37101259980750617, 'ffn_dropout': 0.12868509252821492, 'lr': 0.0008107660526219226, 'weight_decay': 0.013713347427570575, 'batch_size': 32}. Best is trial 12 with value: 0.48862241437211223. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.486397 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.37101259980750617, 'ffn_dropout': 0.12868509252821492, 'lr': 0.0008107660526219226, 'weight_decay': 0.013713347427570575, 'batch_size': 32} - Best Value (CSI): 0.488622 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 14:14:01,675] Trial 49 pruned. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.406944 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.34037543936774317, 'ffn_dropout': 0.15872154635147503, 'lr': 0.0011677103841223374, 'weight_decay': 0.012530804373857996, 'batch_size': 32} - Best Value (CSI): 0.488622 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 14:14:43,657] Trial 50 pruned. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.026543 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3693623679219078, 'ffn_dropout': 0.13171183121490296, 'lr': 0.0018634936864645399, 'weight_decay': 0.019261736253364643, 'batch_size': 32} - Best Value (CSI): 0.488622 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3940644252777227, 'ffn_dropout': 0.10144489779979293, 'lr': 0.000927760920937013, 'weight_decay': 0.08621819676348708, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:18:54,909] Trial 51 finished with value: 0.4960458104166546 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32}. Best is trial 51 with value: 0.4960458104166546. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.496046 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:23:53,772] Trial 52 finished with value: 0.46589141195108974 and parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38796452002213944, 'ffn_dropout': 0.14667025480330814, 'lr': 0.0007849044294507805, 'weight_decay': 0.00817077613635832, 'batch_size': 32}. Best is trial 51 with value: 0.4960458104166546. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.465891 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38796452002213944, 'ffn_dropout': 0.14667025480330814, 'lr': 0.0007849044294507805, 'weight_decay': 0.00817077613635832, 'batch_size': 32} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:31:24,997] Trial 53 finished with value: 0.4810142381388513 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3737917793139734, 'ffn_dropout': 0.11392044025990927, 'lr': 0.0009761093807725675, 'weight_decay': 0.009214733134475187, 'batch_size': 32}. Best is trial 51 with value: 0.4960458104166546. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.481014 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3737917793139734, 'ffn_dropout': 0.11392044025990927, 'lr': 0.0009761093807725675, 'weight_decay': 0.009214733134475187, 'batch_size': 32} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:36:15,431] Trial 54 finished with value: 0.4918401751600367 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3582221003094483, 'ffn_dropout': 0.11204167603766357, 'lr': 0.000978955211134021, 'weight_decay': 0.0097903811788153, 'batch_size': 32}. Best is trial 51 with value: 0.4960458104166546. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.491840 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3582221003094483, 'ffn_dropout': 0.11204167603766357, 'lr': 0.000978955211134021, 'weight_decay': 0.0097903811788153, 'batch_size': 32} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:41:34,406] Trial 55 finished with value: 0.4914419586733148 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3574710981966181, 'ffn_dropout': 0.11515683866629714, 'lr': 0.0008795883495806496, 'weight_decay': 0.008962916854640188, 'batch_size': 32}. Best is trial 51 with value: 0.4960458104166546. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.491442 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3574710981966181, 'ffn_dropout': 0.11515683866629714, 'lr': 0.0008795883495806496, 'weight_decay': 0.008962916854640188, 'batch_size': 32} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:44:32,298] Trial 56 finished with value: 0.47513788872771934 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.35410940300587246, 'ffn_dropout': 0.124855963014258, 'lr': 0.0004672654251111365, 'weight_decay': 0.004500171607572147, 'batch_size': 32}. Best is trial 51 with value: 0.4960458104166546. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.475138 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.35410940300587246, 'ffn_dropout': 0.124855963014258, 'lr': 0.0004672654251111365, 'weight_decay': 0.004500171607572147, 'batch_size': 32} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:48:23,023] Trial 57 finished with value: 0.4847766356143078 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.327434937489462, 'ffn_dropout': 0.1103426934906433, 'lr': 0.0007771033367101665, 'weight_decay': 0.012154893746761264, 'batch_size': 32}. Best is trial 51 with value: 0.4960458104166546. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.484777 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.327434937489462, 'ffn_dropout': 0.1103426934906433, 'lr': 0.0007771033367101665, 'weight_decay': 0.012154893746761264, 'batch_size': 32} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 14:48:58,725] Trial 58 pruned. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.310606 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3296376390455716, 'ffn_dropout': 0.109908032088843, 'lr': 0.0008434689224837926, 'weight_decay': 0.011359710324373768, 'batch_size': 32} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 14:49:32,808] Trial 59 pruned. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.139330 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.349007959345058, 'ffn_dropout': 0.12652613223895007, 'lr': 0.001565042581478021, 'weight_decay': 0.017943368317390594, 'batch_size': 32} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:53:11,589] Trial 60 finished with value: 0.4752663406045627 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.360728155153809, 'ffn_dropout': 0.11070403167407866, 'lr': 0.0004836272468634505, 'weight_decay': 0.010128927956973718, 'batch_size': 32}. Best is trial 51 with value: 0.4960458104166546. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.475266 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.360728155153809, 'ffn_dropout': 0.11070403167407866, 'lr': 0.0004836272468634505, 'weight_decay': 0.010128927956973718, 'batch_size': 32} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 14:56:49,516] Trial 61 finished with value: 0.47569666929381427 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.36733691358981396, 'ffn_dropout': 0.10287756386749575, 'lr': 0.000689179169789766, 'weight_decay': 0.013609050014788092, 'batch_size': 32}. Best is trial 51 with value: 0.4960458104166546. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.475697 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.36733691358981396, 'ffn_dropout': 0.10287756386749575, 'lr': 0.000689179169789766, 'weight_decay': 0.013609050014788092, 'batch_size': 32} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) -[I 2025-12-28 15:00:49,903] Trial 62 pruned. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.494024 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.38063962491110953, 'ffn_dropout': 0.12055166998740467, 'lr': 0.001008744812308412, 'weight_decay': 0.008760852552239136, 'batch_size': 32} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 15:01:27,107] Trial 63 pruned. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.367589 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3450312713423307, 'ffn_dropout': 0.10054861941694547, 'lr': 0.0012767838668696887, 'weight_decay': 0.023293834592426566, 'batch_size': 32} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 15:05:05,205] Trial 64 finished with value: 0.47999660057389587 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.32530813585499624, 'ffn_dropout': 0.13888277875893368, 'lr': 0.0007779768891092811, 'weight_decay': 0.012415489897094439, 'batch_size': 32}. Best is trial 51 with value: 0.4960458104166546. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.479997 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.32530813585499624, 'ffn_dropout': 0.13888277875893368, 'lr': 0.0007779768891092811, 'weight_decay': 0.012415489897094439, 'batch_size': 32} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 15:08:33,325] Trial 65 finished with value: 0.47769918666333644 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3610737211388382, 'ffn_dropout': 0.11070323565454437, 'lr': 0.0004987937809962737, 'weight_decay': 0.01929302562327261, 'batch_size': 32}. Best is trial 51 with value: 0.4960458104166546. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.477699 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3610737211388382, 'ffn_dropout': 0.11070323565454437, 'lr': 0.0004987937809962737, 'weight_decay': 0.01929302562327261, 'batch_size': 32} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 15:09:10,050] Trial 66 pruned. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.351391 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3883297304056102, 'ffn_dropout': 0.12894956215955364, 'lr': 0.0010607679437823626, 'weight_decay': 0.004309641117141332, 'batch_size': 32} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 15:12:22,279] Trial 67 finished with value: 0.480106374482691 and parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3769604130306578, 'ffn_dropout': 0.1539590487212119, 'lr': 0.0007205367629380758, 'weight_decay': 0.007668007575572236, 'batch_size': 32}. Best is trial 51 with value: 0.4960458104166546. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.480106 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3769604130306578, 'ffn_dropout': 0.1539590487212119, 'lr': 0.0007205367629380758, 'weight_decay': 0.007668007575572236, 'batch_size': 32} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 15:12:31,734] Trial 68 pruned. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.345228 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3567795049954773, 'ffn_dropout': 0.11977232552083573, 'lr': 0.00030390055259658857, 'weight_decay': 0.005489703755012369, 'batch_size': 256} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 15:16:32,994] Trial 69 finished with value: 0.46267872897529605 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.33744697121157147, 'ffn_dropout': 0.11045973584981589, 'lr': 0.0004040301179122586, 'weight_decay': 0.010251278930057731, 'batch_size': 32}. Best is trial 51 with value: 0.4960458104166546. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.462679 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.33744697121157147, 'ffn_dropout': 0.11045973584981589, 'lr': 0.0004040301179122586, 'weight_decay': 0.010251278930057731, 'batch_size': 32} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 15:20:16,767] Trial 70 finished with value: 0.4715439515523785 and parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.38324380708584715, 'ffn_dropout': 0.14104476415241649, 'lr': 0.0005684728837502738, 'weight_decay': 0.014209432417588819, 'batch_size': 32}. Best is trial 51 with value: 0.4960458104166546. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.471544 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.38324380708584715, 'ffn_dropout': 0.14104476415241649, 'lr': 0.0005684728837502738, 'weight_decay': 0.014209432417588819, 'batch_size': 32} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 15:20:52,265] Trial 71 pruned. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.370690 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.37170813240412115, 'ffn_dropout': 0.1143040672181226, 'lr': 0.0009362064476428578, 'weight_decay': 0.009653993393918292, 'batch_size': 32} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) -[I 2025-12-28 15:24:07,639] Trial 72 pruned. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.502063 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.37235505973028693, 'ffn_dropout': 0.12742991014846708, 'lr': 0.0008857756015791197, 'weight_decay': 0.02545553001292108, 'batch_size': 32} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 15:24:51,224] Trial 73 pruned. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.027186 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3904887909060981, 'ffn_dropout': 0.10785977445913815, 'lr': 0.0012916915436174655, 'weight_decay': 0.007918283148256936, 'batch_size': 32} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 15:29:08,834] Trial 74 pruned. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.434229 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3764856938940627, 'ffn_dropout': 0.11757052816147007, 'lr': 0.0006924117433928905, 'weight_decay': 0.01643149853179107, 'batch_size': 32} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 15:29:45,521] Trial 75 pruned. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.362406 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3485598393765892, 'ffn_dropout': 0.10007510664548848, 'lr': 0.0010340307602541, 'weight_decay': 0.011574228942997795, 'batch_size': 32} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 15:32:08,707] Trial 76 finished with value: 0.4812105479665137 and parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3563441128686736, 'ffn_dropout': 0.12959915319151485, 'lr': 0.000560207656342641, 'weight_decay': 0.020323877437911343, 'batch_size': 64}. Best is trial 51 with value: 0.4960458104166546. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.481211 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3563441128686736, 'ffn_dropout': 0.12959915319151485, 'lr': 0.000560207656342641, 'weight_decay': 0.020323877437911343, 'batch_size': 64} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 15:34:30,260] Trial 77 finished with value: 0.4742636920564072 and parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3571794936713558, 'ffn_dropout': 0.13849309726138068, 'lr': 0.000528735691580323, 'weight_decay': 0.032708436709618836, 'batch_size': 64}. Best is trial 51 with value: 0.4960458104166546. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.474264 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3571794936713558, 'ffn_dropout': 0.13849309726138068, 'lr': 0.000528735691580323, 'weight_decay': 0.032708436709618836, 'batch_size': 64} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 15:37:08,500] Trial 78 finished with value: 0.46655083136932435 and parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.36304772056676266, 'ffn_dropout': 0.16234983084570767, 'lr': 0.0004146372598841977, 'weight_decay': 0.025912807570860816, 'batch_size': 64}. Best is trial 51 with value: 0.4960458104166546. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.466551 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.36304772056676266, 'ffn_dropout': 0.16234983084570767, 'lr': 0.0004146372598841977, 'weight_decay': 0.025912807570860816, 'batch_size': 64} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 15:39:40,213] Trial 79 finished with value: 0.4781811387060401 and parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3933794042536188, 'ffn_dropout': 0.1315804814336779, 'lr': 0.0005360147970284623, 'weight_decay': 0.02041324408538275, 'batch_size': 64}. Best is trial 51 with value: 0.4960458104166546. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.478181 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3933794042536188, 'ffn_dropout': 0.1315804814336779, 'lr': 0.0005360147970284623, 'weight_decay': 0.02041324408538275, 'batch_size': 64} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 15:42:16,189] Trial 80 finished with value: 0.4762260107765102 and parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3444553236728217, 'ffn_dropout': 0.14857277322123172, 'lr': 0.0006980823888271574, 'weight_decay': 0.016038409893148076, 'batch_size': 64}. Best is trial 51 with value: 0.4960458104166546. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.476226 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3444553236728217, 'ffn_dropout': 0.14857277322123172, 'lr': 0.0006980823888271574, 'weight_decay': 0.016038409893148076, 'batch_size': 64} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 15:43:19,718] Trial 81 finished with value: 0.4660245963783822 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3703518189908725, 'ffn_dropout': 0.12346411770726184, 'lr': 0.0008147905717846085, 'weight_decay': 0.009542979340541513, 'batch_size': 256}. Best is trial 51 with value: 0.4960458104166546. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.466025 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3703518189908725, 'ffn_dropout': 0.12346411770726184, 'lr': 0.0008147905717846085, 'weight_decay': 0.009542979340541513, 'batch_size': 256} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 15:43:54,835] Trial 82 pruned. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.195588 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3998967279272485, 'ffn_dropout': 0.10829283363692124, 'lr': 0.0014736043047723863, 'weight_decay': 0.012810186666718805, 'batch_size': 32} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 15:44:17,623] Trial 83 pruned. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.417630 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.38029297304843807, 'ffn_dropout': 0.11766019161101322, 'lr': 0.0005840189782815385, 'weight_decay': 0.007384794937248584, 'batch_size': 64} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 15:45:03,558] Trial 84 pruned. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.099222 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3844192924286456, 'ffn_dropout': 0.1308457441006873, 'lr': 0.0011364785362980806, 'weight_decay': 0.01845587731801211, 'batch_size': 32} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 15:45:58,380] Trial 85 pruned. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3673799032127775, 'ffn_dropout': 0.10678318700435284, 'lr': 0.0009824679272094257, 'weight_decay': 0.005787849510182729, 'batch_size': 32} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 15:50:01,747] Trial 86 finished with value: 0.4666107893598241 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.33533054976318616, 'ffn_dropout': 0.14470047159660998, 'lr': 0.000874708505268233, 'weight_decay': 0.03802186911462882, 'batch_size': 32}. Best is trial 51 with value: 0.4960458104166546. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.466611 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.33533054976318616, 'ffn_dropout': 0.14470047159660998, 'lr': 0.000874708505268233, 'weight_decay': 0.03802186911462882, 'batch_size': 32} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 15:52:23,318] Trial 87 finished with value: 0.46701544069958717 and parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3531749909563654, 'ffn_dropout': 0.11674410441233475, 'lr': 0.0012296745697082659, 'weight_decay': 0.007143927116599192, 'batch_size': 64}. Best is trial 51 with value: 0.4960458104166546. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.467015 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3531749909563654, 'ffn_dropout': 0.11674410441233475, 'lr': 0.0012296745697082659, 'weight_decay': 0.007143927116599192, 'batch_size': 64} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 15:56:27,421] Trial 88 finished with value: 0.4702611462644719 and parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3916757964429081, 'ffn_dropout': 0.1244705324160128, 'lr': 0.00041755130030716683, 'weight_decay': 0.009033455120720736, 'batch_size': 32}. Best is trial 51 with value: 0.4960458104166546. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.470261 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3916757964429081, 'ffn_dropout': 0.1244705324160128, 'lr': 0.00041755130030716683, 'weight_decay': 0.009033455120720736, 'batch_size': 32} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 15:58:00,928] Trial 89 finished with value: 0.46244481968980056 and parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.37795423555733976, 'ffn_dropout': 0.13490523112645492, 'lr': 0.000648786750939277, 'weight_decay': 0.014688902951160907, 'batch_size': 256}. Best is trial 51 with value: 0.4960458104166546. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.462445 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.37795423555733976, 'ffn_dropout': 0.13490523112645492, 'lr': 0.000648786750939277, 'weight_decay': 0.014688902951160907, 'batch_size': 256} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 15:58:34,883] Trial 90 pruned. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.108859 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3669920817279055, 'ffn_dropout': 0.15326164431750866, 'lr': 0.001777243343172068, 'weight_decay': 0.08266549285798874, 'batch_size': 32} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 16:03:05,722] Trial 91 finished with value: 0.4835326119899943 and parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3719642337170449, 'ffn_dropout': 0.1521286504855443, 'lr': 0.0007356980480054816, 'weight_decay': 0.007651810738369785, 'batch_size': 32}. Best is trial 51 with value: 0.4960458104166546. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.483533 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3719642337170449, 'ffn_dropout': 0.1521286504855443, 'lr': 0.0007356980480054816, 'weight_decay': 0.007651810738369785, 'batch_size': 32} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 16:07:35,561] Trial 92 finished with value: 0.48492679469640865 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3890193563287839, 'ffn_dropout': 0.14238429312598122, 'lr': 0.0007453628490743121, 'weight_decay': 0.01165308784942211, 'batch_size': 32}. Best is trial 51 with value: 0.4960458104166546. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.484927 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3890193563287839, 'ffn_dropout': 0.14238429312598122, 'lr': 0.0007453628490743121, 'weight_decay': 0.01165308784942211, 'batch_size': 32} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 16:11:08,508] Trial 93 finished with value: 0.4821037618562549 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3897073380382652, 'ffn_dropout': 0.13865237434908162, 'lr': 0.0008139640169396708, 'weight_decay': 0.011056588823901217, 'batch_size': 32}. Best is trial 51 with value: 0.4960458104166546. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.482104 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3897073380382652, 'ffn_dropout': 0.13865237434908162, 'lr': 0.0008139640169396708, 'weight_decay': 0.011056588823901217, 'batch_size': 32} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 16:11:43,933] Trial 94 pruned. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.361673 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3918534255353679, 'ffn_dropout': 0.1711094411336314, 'lr': 0.0008060925295025305, 'weight_decay': 0.011502400215589714, 'batch_size': 32} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 16:12:30,932] Trial 95 pruned. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.417740 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3867480208321956, 'ffn_dropout': 0.14396019899578133, 'lr': 0.0006778582835764893, 'weight_decay': 0.006286591872999541, 'batch_size': 32} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 16:13:03,685] Trial 96 pruned. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.134660 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39944971009444413, 'ffn_dropout': 0.156470790720399, 'lr': 0.001370922450391433, 'weight_decay': 0.00511975091309368, 'batch_size': 32} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 16:13:53,224] Trial 97 pruned. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.402250 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.38216065392000453, 'ffn_dropout': 0.13784298384231627, 'lr': 0.0011681415595628931, 'weight_decay': 0.013086207668760732, 'batch_size': 32} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.2421505376344086, 1: 1.1364571982080156, 2: 0.7604464159121752} (클래스별 샘플 수: {0: 10075, 1: 11012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.244002650762094, 1: 1.1330617172174438, 2: 0.7612790721252306} (클래스별 샘플 수: {0: 10060, 1: 11045, 2: 16439}) -[I 2025-12-28 16:17:46,159] Trial 98 finished with value: 0.482250152053455 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.39253876688219974, 'ffn_dropout': 0.16459959583645678, 'lr': 0.0008032641460999773, 'weight_decay': 0.010575196237729921, 'batch_size': 32}. Best is trial 51 with value: 0.4960458104166546. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.482250 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.39253876688219974, 'ffn_dropout': 0.16459959583645678, 'lr': 0.0008032641460999773, 'weight_decay': 0.010575196237729921, 'batch_size': 32} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.244073079346132, 1: 1.1395596051632497, 2: 0.758347481607244} (클래스별 샘플 수: {0: 10053, 1: 10975, 2: 16492}) -[I 2025-12-28 16:18:32,101] Trial 99 pruned. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.411504 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.361561104405005, 'ffn_dropout': 0.12301382321024466, 'lr': 0.0007250806306714704, 'weight_decay': 0.006693394628608259, 'batch_size': 32} - Best Value (CSI): 0.496046 - Best Trial: 51 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.4960 -Best Hyperparameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3873943566967484, 'ffn_dropout': 0.14296280926606936, 'lr': 0.0007665967810279031, 'weight_decay': 0.00878158688959246, 'batch_size': 32} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.2937 - - 최종 CSI: 0.4115 - - 최고 CSI: 0.5021 - - 최저 CSI: 0.0000 - - 평균 CSI: 0.3875 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/ft_transformer_ctgan10000_busan_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 30, Best CSI: 0.4803 - Fold 1 학습 완료 (검증 CSI: 0.4803) -Fold 2 학습 중... - Early stopping at epoch 29, Best CSI: 0.4923 - Fold 2 학습 완료 (검증 CSI: 0.4923) -Fold 3 학습 중... - Early stopping at epoch 31, Best CSI: 0.4888 - Fold 3 학습 완료 (검증 CSI: 0.4888) - -모든 모델 저장 완료: ../save_model/ft_transformer_optima/ft_transformer_ctgan10000_busan.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/ft_transformer_optima/scaler/ft_transformer_ctgan10000_busan_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: ../save_model/ft_transformer_optima/ft_transformer_ctgan10000_busan.pkl - -✓ 완료: ft_transformer_ctgan10000/ft_transformer_ctgan10000_busan.py (소요 시간: 13596초) - ----------------------------------------- -실행 중: ft_transformer_ctgan10000/ft_transformer_ctgan10000_daegu.py -시작 시간: 2025-12-28 16:22:58 ----------------------------------------- -[I 2025-12-28 16:22:59,553] A new study created in memory with name: no-name-ba0f68be-ffb5-47eb-8851-48a161add0c7 - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 16:27:37,724] Trial 0 finished with value: 0.2778810650700827 and parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3701467009841284, 'ffn_dropout': 0.34426462320006423, 'lr': 1.3109360467028999e-05, 'weight_decay': 0.02423566308912537, 'batch_size': 64}. Best is trial 0 with value: 0.2778810650700827. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.277881 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3701467009841284, 'ffn_dropout': 0.34426462320006423, 'lr': 1.3109360467028999e-05, 'weight_decay': 0.02423566308912537, 'batch_size': 64} - Best Value (CSI): 0.277881 - Best Trial: 0 - Best Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3701467009841284, 'ffn_dropout': 0.34426462320006423, 'lr': 1.3109360467028999e-05, 'weight_decay': 0.02423566308912537, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 16:33:19,450] Trial 1 finished with value: 0.38877054282869344 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3923824967760874, 'ffn_dropout': 0.366372620834721, 'lr': 7.008528604913917e-05, 'weight_decay': 0.0018675228609619104, 'batch_size': 32}. Best is trial 1 with value: 0.38877054282869344. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.388771 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3923824967760874, 'ffn_dropout': 0.366372620834721, 'lr': 7.008528604913917e-05, 'weight_decay': 0.0018675228609619104, 'batch_size': 32} - Best Value (CSI): 0.388771 - Best Trial: 1 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3923824967760874, 'ffn_dropout': 0.366372620834721, 'lr': 7.008528604913917e-05, 'weight_decay': 0.0018675228609619104, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 16:34:09,727] Trial 2 finished with value: 0.20377099349222924 and parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.26753797601240537, 'ffn_dropout': 0.3271404027274428, 'lr': 0.0036042968905664234, 'weight_decay': 0.010232940484755502, 'batch_size': 128}. Best is trial 1 with value: 0.38877054282869344. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.203771 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.26753797601240537, 'ffn_dropout': 0.3271404027274428, 'lr': 0.0036042968905664234, 'weight_decay': 0.010232940484755502, 'batch_size': 128} - Best Value (CSI): 0.388771 - Best Trial: 1 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3923824967760874, 'ffn_dropout': 0.366372620834721, 'lr': 7.008528604913917e-05, 'weight_decay': 0.0018675228609619104, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 16:42:13,846] Trial 3 finished with value: 0.39652656875481224 and parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.32948318116036757, 'ffn_dropout': 0.16821397984058944, 'lr': 3.332753256113301e-05, 'weight_decay': 0.0001802089324120185, 'batch_size': 32}. Best is trial 3 with value: 0.39652656875481224. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.396527 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.32948318116036757, 'ffn_dropout': 0.16821397984058944, 'lr': 3.332753256113301e-05, 'weight_decay': 0.0001802089324120185, 'batch_size': 32} - Best Value (CSI): 0.396527 - Best Trial: 3 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.32948318116036757, 'ffn_dropout': 0.16821397984058944, 'lr': 3.332753256113301e-05, 'weight_decay': 0.0001802089324120185, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 16:47:38,475] Trial 4 finished with value: 0.4410366955005478 and parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28149479497858065, 'ffn_dropout': 0.17739961891493267, 'lr': 0.00011721284975607486, 'weight_decay': 0.002095918030208876, 'batch_size': 32}. Best is trial 4 with value: 0.4410366955005478. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.441037 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28149479497858065, 'ffn_dropout': 0.17739961891493267, 'lr': 0.00011721284975607486, 'weight_decay': 0.002095918030208876, 'batch_size': 32} - Best Value (CSI): 0.441037 - Best Trial: 4 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28149479497858065, 'ffn_dropout': 0.17739961891493267, 'lr': 0.00011721284975607486, 'weight_decay': 0.002095918030208876, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 16:49:23,863] Trial 5 finished with value: 0.4167220709912521 and parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.36944100174298133, 'ffn_dropout': 0.2718846156695268, 'lr': 0.0016406077621457548, 'weight_decay': 0.003318831477091509, 'batch_size': 128}. Best is trial 4 with value: 0.4410366955005478. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.416722 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.36944100174298133, 'ffn_dropout': 0.2718846156695268, 'lr': 0.0016406077621457548, 'weight_decay': 0.003318831477091509, 'batch_size': 128} - Best Value (CSI): 0.441037 - Best Trial: 4 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28149479497858065, 'ffn_dropout': 0.17739961891493267, 'lr': 0.00011721284975607486, 'weight_decay': 0.002095918030208876, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 16:50:34,348] Trial 6 pruned. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.16185476576351565, 'ffn_dropout': 0.1678240171917521, 'lr': 0.001615971637617205, 'weight_decay': 0.041108070508839516, 'batch_size': 32} - Best Value (CSI): 0.441037 - Best Trial: 4 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28149479497858065, 'ffn_dropout': 0.17739961891493267, 'lr': 0.00011721284975607486, 'weight_decay': 0.002095918030208876, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 16:51:16,423] Trial 7 pruned. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.210345 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3252415669042098, 'ffn_dropout': 0.16169577174503838, 'lr': 2.5283965640193944e-05, 'weight_decay': 0.0018320496723356848, 'batch_size': 32} - Best Value (CSI): 0.441037 - Best Trial: 4 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28149479497858065, 'ffn_dropout': 0.17739961891493267, 'lr': 0.00011721284975607486, 'weight_decay': 0.002095918030208876, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 16:55:02,901] Trial 8 finished with value: 0.42372346160540614 and parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.32982919884014783, 'ffn_dropout': 0.11139095180519151, 'lr': 0.0006007911455383494, 'weight_decay': 0.0003596767220767154, 'batch_size': 64}. Best is trial 4 with value: 0.4410366955005478. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.423723 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.32982919884014783, 'ffn_dropout': 0.11139095180519151, 'lr': 0.0006007911455383494, 'weight_decay': 0.0003596767220767154, 'batch_size': 64} - Best Value (CSI): 0.441037 - Best Trial: 4 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28149479497858065, 'ffn_dropout': 0.17739961891493267, 'lr': 0.00011721284975607486, 'weight_decay': 0.002095918030208876, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 16:55:29,140] Trial 9 pruned. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.057243 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.38866032747452317, 'ffn_dropout': 0.2045138309129935, 'lr': 0.0009033782888554393, 'weight_decay': 0.0037844093813659916, 'batch_size': 64} - Best Value (CSI): 0.441037 - Best Trial: 4 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28149479497858065, 'ffn_dropout': 0.17739961891493267, 'lr': 0.00011721284975607486, 'weight_decay': 0.002095918030208876, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 16:55:40,025] Trial 10 pruned. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.098012 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.20093928279986067, 'ffn_dropout': 0.25603738269056797, 'lr': 0.0001425327108931291, 'weight_decay': 0.06477598259866986, 'batch_size': 256} - Best Value (CSI): 0.441037 - Best Trial: 4 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28149479497858065, 'ffn_dropout': 0.17739961891493267, 'lr': 0.00011721284975607486, 'weight_decay': 0.002095918030208876, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 16:59:34,031] Trial 11 finished with value: 0.42113167696589243 and parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.2681726705516485, 'ffn_dropout': 0.12422923954998787, 'lr': 0.00032414744740194394, 'weight_decay': 0.0003062275289856915, 'batch_size': 64}. Best is trial 4 with value: 0.4410366955005478. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.421132 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.2681726705516485, 'ffn_dropout': 0.12422923954998787, 'lr': 0.00032414744740194394, 'weight_decay': 0.0003062275289856915, 'batch_size': 64} - Best Value (CSI): 0.441037 - Best Trial: 4 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28149479497858065, 'ffn_dropout': 0.17739961891493267, 'lr': 0.00011721284975607486, 'weight_decay': 0.002095918030208876, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 17:00:06,917] Trial 12 pruned. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.360887 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.29914156961221017, 'ffn_dropout': 0.10095807426228082, 'lr': 0.0002890374276537757, 'weight_decay': 0.0006024297700590324, 'batch_size': 256} - Best Value (CSI): 0.441037 - Best Trial: 4 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28149479497858065, 'ffn_dropout': 0.17739961891493267, 'lr': 0.00011721284975607486, 'weight_decay': 0.002095918030208876, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 17:03:50,261] Trial 13 finished with value: 0.4364802844187287 and parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.10812121199780253, 'ffn_dropout': 0.10099119275616791, 'lr': 0.00042037574098368377, 'weight_decay': 0.0006794997511097631, 'batch_size': 64}. Best is trial 4 with value: 0.4410366955005478. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.436480 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.10812121199780253, 'ffn_dropout': 0.10099119275616791, 'lr': 0.00042037574098368377, 'weight_decay': 0.0006794997511097631, 'batch_size': 64} - Best Value (CSI): 0.441037 - Best Trial: 4 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28149479497858065, 'ffn_dropout': 0.17739961891493267, 'lr': 0.00011721284975607486, 'weight_decay': 0.002095918030208876, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 17:04:46,506] Trial 14 pruned. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10091839574773706, 'ffn_dropout': 0.20998567524708406, 'lr': 0.009297216714080368, 'weight_decay': 0.00010393929184419674, 'batch_size': 32} - Best Value (CSI): 0.441037 - Best Trial: 4 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28149479497858065, 'ffn_dropout': 0.17739961891493267, 'lr': 0.00011721284975607486, 'weight_decay': 0.002095918030208876, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 17:05:27,716] Trial 15 pruned. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.339827 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.21151647860428308, 'ffn_dropout': 0.13881680677224553, 'lr': 0.00011739530328211201, 'weight_decay': 0.0007217565325261509, 'batch_size': 64} - Best Value (CSI): 0.441037 - Best Trial: 4 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28149479497858065, 'ffn_dropout': 0.17739961891493267, 'lr': 0.00011721284975607486, 'weight_decay': 0.002095918030208876, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 17:05:46,154] Trial 16 pruned. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.368653 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.10984560242647123, 'ffn_dropout': 0.10018030775961752, 'lr': 0.00028070714229719984, 'weight_decay': 0.0008867163544360894, 'batch_size': 256} - Best Value (CSI): 0.441037 - Best Trial: 4 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28149479497858065, 'ffn_dropout': 0.17739961891493267, 'lr': 0.00011721284975607486, 'weight_decay': 0.002095918030208876, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 17:05:57,400] Trial 17 pruned. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.078691 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.23858937227457216, 'ffn_dropout': 0.20720987930572723, 'lr': 8.71878147562777e-05, 'weight_decay': 0.010531684125290508, 'batch_size': 128} - Best Value (CSI): 0.441037 - Best Trial: 4 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28149479497858065, 'ffn_dropout': 0.17739961891493267, 'lr': 0.00011721284975607486, 'weight_decay': 0.002095918030208876, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 17:06:38,122] Trial 18 pruned. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.306620 - Parameters: {'d_token': 224, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.15370925792654455, 'ffn_dropout': 0.14238132059748346, 'lr': 5.4306182646121885e-05, 'weight_decay': 0.001075734073261604, 'batch_size': 64} - Best Value (CSI): 0.441037 - Best Trial: 4 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28149479497858065, 'ffn_dropout': 0.17739961891493267, 'lr': 0.00011721284975607486, 'weight_decay': 0.002095918030208876, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 17:12:58,600] Trial 19 finished with value: 0.43692922420067787 and parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.21503912723424526, 'ffn_dropout': 0.14097372155620447, 'lr': 0.00018317359898890786, 'weight_decay': 0.0059170113583524656, 'batch_size': 32}. Best is trial 4 with value: 0.4410366955005478. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.436929 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.21503912723424526, 'ffn_dropout': 0.14097372155620447, 'lr': 0.00018317359898890786, 'weight_decay': 0.0059170113583524656, 'batch_size': 32} - Best Value (CSI): 0.441037 - Best Trial: 4 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28149479497858065, 'ffn_dropout': 0.17739961891493267, 'lr': 0.00011721284975607486, 'weight_decay': 0.002095918030208876, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 17:17:55,572] Trial 20 finished with value: 0.43432573221224785 and parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2385513012130085, 'ffn_dropout': 0.18269155408995588, 'lr': 0.00015956194228066413, 'weight_decay': 0.005924410902479277, 'batch_size': 32}. Best is trial 4 with value: 0.4410366955005478. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.434326 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2385513012130085, 'ffn_dropout': 0.18269155408995588, 'lr': 0.00015956194228066413, 'weight_decay': 0.005924410902479277, 'batch_size': 32} - Best Value (CSI): 0.441037 - Best Trial: 4 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28149479497858065, 'ffn_dropout': 0.17739961891493267, 'lr': 0.00011721284975607486, 'weight_decay': 0.002095918030208876, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 17:23:59,437] Trial 21 finished with value: 0.42600751953396715 and parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1402722670929168, 'ffn_dropout': 0.1475850064017891, 'lr': 0.0001863195703407688, 'weight_decay': 0.00277082718665622, 'batch_size': 32}. Best is trial 4 with value: 0.4410366955005478. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.426008 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1402722670929168, 'ffn_dropout': 0.1475850064017891, 'lr': 0.0001863195703407688, 'weight_decay': 0.00277082718665622, 'batch_size': 32} - Best Value (CSI): 0.441037 - Best Trial: 4 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28149479497858065, 'ffn_dropout': 0.17739961891493267, 'lr': 0.00011721284975607486, 'weight_decay': 0.002095918030208876, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 17:32:16,629] Trial 22 finished with value: 0.41353256500551744 and parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.19720492218749186, 'ffn_dropout': 0.12797651400816107, 'lr': 0.000495178758657061, 'weight_decay': 0.0015586334783531895, 'batch_size': 32}. Best is trial 4 with value: 0.4410366955005478. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.413533 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.19720492218749186, 'ffn_dropout': 0.12797651400816107, 'lr': 0.000495178758657061, 'weight_decay': 0.0015586334783531895, 'batch_size': 32} - Best Value (CSI): 0.441037 - Best Trial: 4 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28149479497858065, 'ffn_dropout': 0.17739961891493267, 'lr': 0.00011721284975607486, 'weight_decay': 0.002095918030208876, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 17:38:00,494] Trial 23 finished with value: 0.4173922855701848 and parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.17930384796010074, 'ffn_dropout': 0.12697276163810145, 'lr': 0.0002077983341525288, 'weight_decay': 0.005688923842675696, 'batch_size': 32}. Best is trial 4 with value: 0.4410366955005478. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.417392 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.17930384796010074, 'ffn_dropout': 0.12697276163810145, 'lr': 0.0002077983341525288, 'weight_decay': 0.005688923842675696, 'batch_size': 32} - Best Value (CSI): 0.441037 - Best Trial: 4 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28149479497858065, 'ffn_dropout': 0.17739961891493267, 'lr': 0.00011721284975607486, 'weight_decay': 0.002095918030208876, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 17:44:41,677] Trial 24 finished with value: 0.4270196526799979 and parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1305489220308568, 'ffn_dropout': 0.14707842034889101, 'lr': 0.00010074242146200202, 'weight_decay': 0.0012618637790405114, 'batch_size': 32}. Best is trial 4 with value: 0.4410366955005478. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.427020 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1305489220308568, 'ffn_dropout': 0.14707842034889101, 'lr': 0.00010074242146200202, 'weight_decay': 0.0012618637790405114, 'batch_size': 32} - Best Value (CSI): 0.441037 - Best Trial: 4 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28149479497858065, 'ffn_dropout': 0.17739961891493267, 'lr': 0.00011721284975607486, 'weight_decay': 0.002095918030208876, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 17:47:14,033] Trial 25 finished with value: 0.43164657438152854 and parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.17379594662419506, 'ffn_dropout': 0.18478909173009345, 'lr': 0.00044544989303464243, 'weight_decay': 0.0005054991023566345, 'batch_size': 64}. Best is trial 4 with value: 0.4410366955005478. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.431647 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.17379594662419506, 'ffn_dropout': 0.18478909173009345, 'lr': 0.00044544989303464243, 'weight_decay': 0.0005054991023566345, 'batch_size': 64} - Best Value (CSI): 0.441037 - Best Trial: 4 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28149479497858065, 'ffn_dropout': 0.17739961891493267, 'lr': 0.00011721284975607486, 'weight_decay': 0.002095918030208876, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 17:47:29,002] Trial 26 pruned. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.187016 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.22088417480497952, 'ffn_dropout': 0.11625574369543377, 'lr': 5.592297297582552e-05, 'weight_decay': 0.0019541343950212854, 'batch_size': 256} - Best Value (CSI): 0.441037 - Best Trial: 4 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28149479497858065, 'ffn_dropout': 0.17739961891493267, 'lr': 0.00011721284975607486, 'weight_decay': 0.002095918030208876, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 17:47:51,214] Trial 27 pruned. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.313297 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.13256132285394256, 'ffn_dropout': 0.22810700035390155, 'lr': 0.00014989052089656936, 'weight_decay': 0.0008678055373563038, 'batch_size': 128} - Best Value (CSI): 0.441037 - Best Trial: 4 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28149479497858065, 'ffn_dropout': 0.17739961891493267, 'lr': 0.00011721284975607486, 'weight_decay': 0.002095918030208876, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 17:54:41,185] Trial 28 finished with value: 0.4252268679431384 and parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.19001315087120063, 'ffn_dropout': 0.15614607708422013, 'lr': 0.0002654527590801228, 'weight_decay': 0.002573465027448971, 'batch_size': 32}. Best is trial 4 with value: 0.4410366955005478. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.425227 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.19001315087120063, 'ffn_dropout': 0.15614607708422013, 'lr': 0.0002654527590801228, 'weight_decay': 0.002573465027448971, 'batch_size': 32} - Best Value (CSI): 0.441037 - Best Trial: 4 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28149479497858065, 'ffn_dropout': 0.17739961891493267, 'lr': 0.00011721284975607486, 'weight_decay': 0.002095918030208876, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 17:55:09,779] Trial 29 pruned. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.227102 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.17348723074832184, 'ffn_dropout': 0.10018473858642078, 'lr': 1.6090750235341957e-05, 'weight_decay': 0.017946357754710474, 'batch_size': 64} - Best Value (CSI): 0.441037 - Best Trial: 4 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28149479497858065, 'ffn_dropout': 0.17739961891493267, 'lr': 0.00011721284975607486, 'weight_decay': 0.002095918030208876, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 17:55:35,028] Trial 30 pruned. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.291045 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2212145267074257, 'ffn_dropout': 0.13526300446824732, 'lr': 9.433966517880381e-05, 'weight_decay': 0.0011518173872887916, 'batch_size': 64} - Best Value (CSI): 0.441037 - Best Trial: 4 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28149479497858065, 'ffn_dropout': 0.17739961891493267, 'lr': 0.00011721284975607486, 'weight_decay': 0.002095918030208876, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 17:59:28,805] Trial 31 finished with value: 0.4174178706993557 and parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24048536547188604, 'ffn_dropout': 0.17878178804673248, 'lr': 0.00015235865551818068, 'weight_decay': 0.004796727863596373, 'batch_size': 32}. Best is trial 4 with value: 0.4410366955005478. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.417418 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24048536547188604, 'ffn_dropout': 0.17878178804673248, 'lr': 0.00015235865551818068, 'weight_decay': 0.004796727863596373, 'batch_size': 32} - Best Value (CSI): 0.441037 - Best Trial: 4 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28149479497858065, 'ffn_dropout': 0.17739961891493267, 'lr': 0.00011721284975607486, 'weight_decay': 0.002095918030208876, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 18:03:12,257] Trial 32 finished with value: 0.41701615999466024 and parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.25332940256998526, 'ffn_dropout': 0.18591533761726112, 'lr': 0.00019048421655226425, 'weight_decay': 0.007636466609754598, 'batch_size': 32}. Best is trial 4 with value: 0.4410366955005478. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.417016 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.25332940256998526, 'ffn_dropout': 0.18591533761726112, 'lr': 0.00019048421655226425, 'weight_decay': 0.007636466609754598, 'batch_size': 32} - Best Value (CSI): 0.441037 - Best Trial: 4 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28149479497858065, 'ffn_dropout': 0.17739961891493267, 'lr': 0.00011721284975607486, 'weight_decay': 0.002095918030208876, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 18:03:59,859] Trial 33 pruned. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.301184 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.277357626435737, 'ffn_dropout': 0.15530634965097306, 'lr': 4.526814702422805e-05, 'weight_decay': 0.005190336304289837, 'batch_size': 32} - Best Value (CSI): 0.441037 - Best Trial: 4 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28149479497858065, 'ffn_dropout': 0.17739961891493267, 'lr': 0.00011721284975607486, 'weight_decay': 0.002095918030208876, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 18:04:33,389] Trial 34 pruned. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.262794 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2226300009687655, 'ffn_dropout': 0.11997795303382583, 'lr': 0.00011267138880272823, 'weight_decay': 0.016262237150809038, 'batch_size': 32} - Best Value (CSI): 0.441037 - Best Trial: 4 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28149479497858065, 'ffn_dropout': 0.17739961891493267, 'lr': 0.00011721284975607486, 'weight_decay': 0.002095918030208876, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 18:10:54,070] Trial 35 finished with value: 0.43517580034057524 and parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2471485456410509, 'ffn_dropout': 0.17617170894663353, 'lr': 7.751791898412974e-05, 'weight_decay': 0.002536006307165387, 'batch_size': 32}. Best is trial 4 with value: 0.4410366955005478. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.435176 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2471485456410509, 'ffn_dropout': 0.17617170894663353, 'lr': 7.751791898412974e-05, 'weight_decay': 0.002536006307165387, 'batch_size': 32} - Best Value (CSI): 0.441037 - Best Trial: 4 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28149479497858065, 'ffn_dropout': 0.17739961891493267, 'lr': 0.00011721284975607486, 'weight_decay': 0.002095918030208876, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 18:11:12,918] Trial 36 pruned. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.291519 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2908913120813284, 'ffn_dropout': 0.16515512627448653, 'lr': 8.210408773614566e-05, 'weight_decay': 0.0027277184725345055, 'batch_size': 128} - Best Value (CSI): 0.441037 - Best Trial: 4 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28149479497858065, 'ffn_dropout': 0.17739961891493267, 'lr': 0.00011721284975607486, 'weight_decay': 0.002095918030208876, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 18:20:37,046] Trial 37 finished with value: 0.4240695794218001 and parameters: {'d_token': 256, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.26092772989371105, 'ffn_dropout': 0.136825659477604, 'lr': 6.500846396521682e-05, 'weight_decay': 0.001971050216091294, 'batch_size': 32}. Best is trial 4 with value: 0.4410366955005478. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.424070 - Parameters: {'d_token': 256, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.26092772989371105, 'ffn_dropout': 0.136825659477604, 'lr': 6.500846396521682e-05, 'weight_decay': 0.001971050216091294, 'batch_size': 32} - Best Value (CSI): 0.441037 - Best Trial: 4 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28149479497858065, 'ffn_dropout': 0.17739961891493267, 'lr': 0.00011721284975607486, 'weight_decay': 0.002095918030208876, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 18:21:09,876] Trial 38 pruned. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.152595 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2441950476193616, 'ffn_dropout': 0.2868835205646733, 'lr': 3.1496752342310546e-05, 'weight_decay': 0.003389399270824248, 'batch_size': 32} - Best Value (CSI): 0.441037 - Best Trial: 4 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28149479497858065, 'ffn_dropout': 0.17739961891493267, 'lr': 0.00011721284975607486, 'weight_decay': 0.002095918030208876, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 18:21:52,380] Trial 39 pruned. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.245283 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1172512730086474, 'ffn_dropout': 0.3905775495921092, 'lr': 4.177661882470523e-05, 'weight_decay': 0.0014672429013298004, 'batch_size': 32} - Best Value (CSI): 0.441037 - Best Trial: 4 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28149479497858065, 'ffn_dropout': 0.17739961891493267, 'lr': 0.00011721284975607486, 'weight_decay': 0.002095918030208876, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 18:24:21,692] Trial 40 finished with value: 0.4414200029420164 and parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1556353802013698, 'ffn_dropout': 0.16208534456557933, 'lr': 0.0007496145596734645, 'weight_decay': 0.008780582140665853, 'batch_size': 128}. Best is trial 40 with value: 0.4414200029420164. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.441420 - Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1556353802013698, 'ffn_dropout': 0.16208534456557933, 'lr': 0.0007496145596734645, 'weight_decay': 0.008780582140665853, 'batch_size': 128} - Best Value (CSI): 0.441420 - Best Trial: 40 - Best Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1556353802013698, 'ffn_dropout': 0.16208534456557933, 'lr': 0.0007496145596734645, 'weight_decay': 0.008780582140665853, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 18:26:28,837] Trial 41 finished with value: 0.40821319028067854 and parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.11380741759786872, 'ffn_dropout': 0.17045346842793277, 'lr': 0.0008278682117330897, 'weight_decay': 0.009287643392166362, 'batch_size': 128}. Best is trial 40 with value: 0.4414200029420164. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.408213 - Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.11380741759786872, 'ffn_dropout': 0.17045346842793277, 'lr': 0.0008278682117330897, 'weight_decay': 0.009287643392166362, 'batch_size': 128} - Best Value (CSI): 0.441420 - Best Trial: 40 - Best Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1556353802013698, 'ffn_dropout': 0.16208534456557933, 'lr': 0.0007496145596734645, 'weight_decay': 0.008780582140665853, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 18:29:02,436] Trial 42 finished with value: 0.43116866945239735 and parameters: {'d_token': 224, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.14155923997016856, 'ffn_dropout': 0.15612469395539055, 'lr': 0.0007106629281613418, 'weight_decay': 0.004127294067055026, 'batch_size': 128}. Best is trial 40 with value: 0.4414200029420164. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.431169 - Parameters: {'d_token': 224, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.14155923997016856, 'ffn_dropout': 0.15612469395539055, 'lr': 0.0007106629281613418, 'weight_decay': 0.004127294067055026, 'batch_size': 128} - Best Value (CSI): 0.441420 - Best Trial: 40 - Best Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1556353802013698, 'ffn_dropout': 0.16208534456557933, 'lr': 0.0007496145596734645, 'weight_decay': 0.008780582140665853, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 18:31:32,482] Trial 43 finished with value: 0.43628994954246325 and parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.158485265303198, 'ffn_dropout': 0.1948554239438959, 'lr': 0.0003886845603145932, 'weight_decay': 0.0020910166437049463, 'batch_size': 128}. Best is trial 40 with value: 0.4414200029420164. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.436290 - Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.158485265303198, 'ffn_dropout': 0.1948554239438959, 'lr': 0.0003886845603145932, 'weight_decay': 0.0020910166437049463, 'batch_size': 128} - Best Value (CSI): 0.441420 - Best Trial: 40 - Best Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1556353802013698, 'ffn_dropout': 0.16208534456557933, 'lr': 0.0007496145596734645, 'weight_decay': 0.008780582140665853, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 18:33:22,350] Trial 44 finished with value: 0.40674682199865614 and parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.15291946337901252, 'ffn_dropout': 0.19768801929691726, 'lr': 0.0011338342463576556, 'weight_decay': 0.00369996902521847, 'batch_size': 128}. Best is trial 40 with value: 0.4414200029420164. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.406747 - Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.15291946337901252, 'ffn_dropout': 0.19768801929691726, 'lr': 0.0011338342463576556, 'weight_decay': 0.00369996902521847, 'batch_size': 128} - Best Value (CSI): 0.441420 - Best Trial: 40 - Best Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1556353802013698, 'ffn_dropout': 0.16208534456557933, 'lr': 0.0007496145596734645, 'weight_decay': 0.008780582140665853, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 18:36:34,033] Trial 45 finished with value: 0.42766893605926964 and parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.15934208840399025, 'ffn_dropout': 0.2272607462537528, 'lr': 0.0004657110496285893, 'weight_decay': 0.00692192893003497, 'batch_size': 128}. Best is trial 40 with value: 0.4414200029420164. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.427669 - Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.15934208840399025, 'ffn_dropout': 0.2272607462537528, 'lr': 0.0004657110496285893, 'weight_decay': 0.00692192893003497, 'batch_size': 128} - Best Value (CSI): 0.441420 - Best Trial: 40 - Best Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1556353802013698, 'ffn_dropout': 0.16208534456557933, 'lr': 0.0007496145596734645, 'weight_decay': 0.008780582140665853, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 18:38:54,495] Trial 46 finished with value: 0.41398727836554156 and parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.12087274464840478, 'ffn_dropout': 0.12135616935495028, 'lr': 0.00034238500243035996, 'weight_decay': 0.002092155408082985, 'batch_size': 128}. Best is trial 40 with value: 0.4414200029420164. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.413987 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.12087274464840478, 'ffn_dropout': 0.12135616935495028, 'lr': 0.00034238500243035996, 'weight_decay': 0.002092155408082985, 'batch_size': 128} - Best Value (CSI): 0.441420 - Best Trial: 40 - Best Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1556353802013698, 'ffn_dropout': 0.16208534456557933, 'lr': 0.0007496145596734645, 'weight_decay': 0.008780582140665853, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 18:39:27,972] Trial 47 pruned. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.364629 - Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.101331451260982, 'ffn_dropout': 0.11262176105916095, 'lr': 0.0006420092180808236, 'weight_decay': 0.003945287571753858, 'batch_size': 128} - Best Value (CSI): 0.441420 - Best Trial: 40 - Best Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1556353802013698, 'ffn_dropout': 0.16208534456557933, 'lr': 0.0007496145596734645, 'weight_decay': 0.008780582140665853, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 18:40:50,421] Trial 48 finished with value: 0.3930885634383961 and parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.16844787111446488, 'ffn_dropout': 0.16220069590992453, 'lr': 0.0010667698021979508, 'weight_decay': 0.01107175087779283, 'batch_size': 128}. Best is trial 40 with value: 0.4414200029420164. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.393089 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.16844787111446488, 'ffn_dropout': 0.16220069590992453, 'lr': 0.0010667698021979508, 'weight_decay': 0.01107175087779283, 'batch_size': 128} - Best Value (CSI): 0.441420 - Best Trial: 40 - Best Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1556353802013698, 'ffn_dropout': 0.16208534456557933, 'lr': 0.0007496145596734645, 'weight_decay': 0.008780582140665853, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 18:41:54,798] Trial 49 pruned. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.366071 - Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.186889128498951, 'ffn_dropout': 0.19357609419693145, 'lr': 0.00022611814481767533, 'weight_decay': 0.0004627903298386736, 'batch_size': 64} - Best Value (CSI): 0.441420 - Best Trial: 40 - Best Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1556353802013698, 'ffn_dropout': 0.16208534456557933, 'lr': 0.0007496145596734645, 'weight_decay': 0.008780582140665853, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 18:44:25,772] Trial 50 finished with value: 0.43668175181800956 and parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.1518201551781169, 'ffn_dropout': 0.14685664561297185, 'lr': 0.0003506868170730323, 'weight_decay': 0.0009054143173436034, 'batch_size': 256}. Best is trial 40 with value: 0.4414200029420164. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.436682 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.1518201551781169, 'ffn_dropout': 0.14685664561297185, 'lr': 0.0003506868170730323, 'weight_decay': 0.0009054143173436034, 'batch_size': 256} - Best Value (CSI): 0.441420 - Best Trial: 40 - Best Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1556353802013698, 'ffn_dropout': 0.16208534456557933, 'lr': 0.0007496145596734645, 'weight_decay': 0.008780582140665853, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 18:44:45,548] Trial 51 pruned. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.356838 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.1484801143814788, 'ffn_dropout': 0.14382823767962546, 'lr': 0.00036287085350915956, 'weight_decay': 0.0008554656323528077, 'batch_size': 256} - Best Value (CSI): 0.441420 - Best Trial: 40 - Best Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1556353802013698, 'ffn_dropout': 0.16208534456557933, 'lr': 0.0007496145596734645, 'weight_decay': 0.008780582140665853, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 18:46:59,162] Trial 52 finished with value: 0.4379298071713558 and parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.1601666767646172, 'ffn_dropout': 0.17156274236570754, 'lr': 0.000391827225278508, 'weight_decay': 0.0015144711926276676, 'batch_size': 256}. Best is trial 40 with value: 0.4414200029420164. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.437930 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.1601666767646172, 'ffn_dropout': 0.17156274236570754, 'lr': 0.000391827225278508, 'weight_decay': 0.0015144711926276676, 'batch_size': 256} - Best Value (CSI): 0.441420 - Best Trial: 40 - Best Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1556353802013698, 'ffn_dropout': 0.16208534456557933, 'lr': 0.0007496145596734645, 'weight_decay': 0.008780582140665853, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 18:47:33,047] Trial 53 pruned. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.359596 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.12925519172699754, 'ffn_dropout': 0.1707227907164825, 'lr': 0.0005783478484232665, 'weight_decay': 0.0007458088538710941, 'batch_size': 256} - Best Value (CSI): 0.441420 - Best Trial: 40 - Best Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1556353802013698, 'ffn_dropout': 0.16208534456557933, 'lr': 0.0007496145596734645, 'weight_decay': 0.008780582140665853, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 18:47:49,206] Trial 54 pruned. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.352342 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.18312804282897227, 'ffn_dropout': 0.13174521065987496, 'lr': 0.00027775969113076024, 'weight_decay': 0.0014546947160609855, 'batch_size': 256} - Best Value (CSI): 0.441420 - Best Trial: 40 - Best Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1556353802013698, 'ffn_dropout': 0.16208534456557933, 'lr': 0.0007496145596734645, 'weight_decay': 0.008780582140665853, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 18:48:12,654] Trial 55 pruned. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.338115 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.16560956294095042, 'ffn_dropout': 0.10892657153958425, 'lr': 0.000535584887452813, 'weight_decay': 0.0010309816539916476, 'batch_size': 256} - Best Value (CSI): 0.441420 - Best Trial: 40 - Best Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1556353802013698, 'ffn_dropout': 0.16208534456557933, 'lr': 0.0007496145596734645, 'weight_decay': 0.008780582140665853, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 18:50:30,159] Trial 56 finished with value: 0.4215606952038758 and parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.1415709674621142, 'ffn_dropout': 0.14865399402704152, 'lr': 0.00023744338176008272, 'weight_decay': 0.0006606749020254069, 'batch_size': 256}. Best is trial 40 with value: 0.4414200029420164. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.421561 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.1415709674621142, 'ffn_dropout': 0.14865399402704152, 'lr': 0.00023744338176008272, 'weight_decay': 0.0006606749020254069, 'batch_size': 256} - Best Value (CSI): 0.441420 - Best Trial: 40 - Best Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1556353802013698, 'ffn_dropout': 0.16208534456557933, 'lr': 0.0007496145596734645, 'weight_decay': 0.008780582140665853, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 18:51:05,855] Trial 57 pruned. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.370763 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.19947496063571546, 'ffn_dropout': 0.12938786534384153, 'lr': 0.0003676285877543154, 'weight_decay': 0.00038537532383469737, 'batch_size': 256} - Best Value (CSI): 0.441420 - Best Trial: 40 - Best Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1556353802013698, 'ffn_dropout': 0.16208534456557933, 'lr': 0.0007496145596734645, 'weight_decay': 0.008780582140665853, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 18:51:28,089] Trial 58 pruned. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.294400 - Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.17046375006303202, 'ffn_dropout': 0.1624687126833142, 'lr': 0.00012259062633890306, 'weight_decay': 0.0015711935449833978, 'batch_size': 256} - Best Value (CSI): 0.441420 - Best Trial: 40 - Best Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1556353802013698, 'ffn_dropout': 0.16208534456557933, 'lr': 0.0007496145596734645, 'weight_decay': 0.008780582140665853, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 18:55:07,926] Trial 59 finished with value: 0.4268494956568521 and parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.12227775694630182, 'ffn_dropout': 0.14035312682128326, 'lr': 0.0001961835162982108, 'weight_decay': 0.0011306724784946893, 'batch_size': 64}. Best is trial 40 with value: 0.4414200029420164. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.426849 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.12227775694630182, 'ffn_dropout': 0.14035312682128326, 'lr': 0.0001961835162982108, 'weight_decay': 0.0011306724784946893, 'batch_size': 64} - Best Value (CSI): 0.441420 - Best Trial: 40 - Best Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1556353802013698, 'ffn_dropout': 0.16208534456557933, 'lr': 0.0007496145596734645, 'weight_decay': 0.008780582140665853, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 18:55:22,213] Trial 60 pruned. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.234867 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.14738163162100482, 'ffn_dropout': 0.11035243668803918, 'lr': 0.00030344492212457667, 'weight_decay': 0.0005381824805471099, 'batch_size': 256} - Best Value (CSI): 0.441420 - Best Trial: 40 - Best Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1556353802013698, 'ffn_dropout': 0.16208534456557933, 'lr': 0.0007496145596734645, 'weight_decay': 0.008780582140665853, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 18:57:37,154] Trial 61 finished with value: 0.42434148574158215 and parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1618324906198552, 'ffn_dropout': 0.16972991540214574, 'lr': 0.00040064306856915535, 'weight_decay': 0.0022176667679372677, 'batch_size': 128}. Best is trial 40 with value: 0.4414200029420164. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.424341 - Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1618324906198552, 'ffn_dropout': 0.16972991540214574, 'lr': 0.00040064306856915535, 'weight_decay': 0.0022176667679372677, 'batch_size': 128} - Best Value (CSI): 0.441420 - Best Trial: 40 - Best Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1556353802013698, 'ffn_dropout': 0.16208534456557933, 'lr': 0.0007496145596734645, 'weight_decay': 0.008780582140665853, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 19:02:38,683] Trial 62 finished with value: 0.4306726222233921 and parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.15531911365798245, 'ffn_dropout': 0.14841974083141266, 'lr': 0.0004354097706023698, 'weight_decay': 0.0030311940515041855, 'batch_size': 64}. Best is trial 40 with value: 0.4414200029420164. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.430673 - Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.15531911365798245, 'ffn_dropout': 0.14841974083141266, 'lr': 0.0004354097706023698, 'weight_decay': 0.0030311940515041855, 'batch_size': 64} - Best Value (CSI): 0.441420 - Best Trial: 40 - Best Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1556353802013698, 'ffn_dropout': 0.16208534456557933, 'lr': 0.0007496145596734645, 'weight_decay': 0.008780582140665853, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 19:03:16,779] Trial 63 pruned. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.353846 - Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.13399888854527425, 'ffn_dropout': 0.18612436481955713, 'lr': 0.0002589953027207309, 'weight_decay': 0.0017574512841025413, 'batch_size': 256} - Best Value (CSI): 0.441420 - Best Trial: 40 - Best Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1556353802013698, 'ffn_dropout': 0.16208534456557933, 'lr': 0.0007496145596734645, 'weight_decay': 0.008780582140665853, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 19:05:26,995] Trial 64 finished with value: 0.4171097536811994 and parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1768568151838165, 'ffn_dropout': 0.15478515614876204, 'lr': 0.0005588875477666259, 'weight_decay': 0.0013077979895293028, 'batch_size': 128}. Best is trial 40 with value: 0.4414200029420164. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.417110 - Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1768568151838165, 'ffn_dropout': 0.15478515614876204, 'lr': 0.0005588875477666259, 'weight_decay': 0.0013077979895293028, 'batch_size': 128} - Best Value (CSI): 0.441420 - Best Trial: 40 - Best Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1556353802013698, 'ffn_dropout': 0.16208534456557933, 'lr': 0.0007496145596734645, 'weight_decay': 0.008780582140665853, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 19:06:00,787] Trial 65 pruned. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.347722 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1937437342711599, 'ffn_dropout': 0.179493072950223, 'lr': 0.0001608599354514207, 'weight_decay': 0.0009522080274236417, 'batch_size': 64} - Best Value (CSI): 0.441420 - Best Trial: 40 - Best Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1556353802013698, 'ffn_dropout': 0.16208534456557933, 'lr': 0.0007496145596734645, 'weight_decay': 0.008780582140665853, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 19:09:12,148] Trial 66 finished with value: 0.4253455382972498 and parameters: {'d_token': 256, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.1829266273626336, 'ffn_dropout': 0.13135931840257387, 'lr': 0.0007336456743598867, 'weight_decay': 0.000673853053209739, 'batch_size': 256}. Best is trial 40 with value: 0.4414200029420164. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.425346 - Parameters: {'d_token': 256, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.1829266273626336, 'ffn_dropout': 0.13135931840257387, 'lr': 0.0007336456743598867, 'weight_decay': 0.000673853053209739, 'batch_size': 256} - Best Value (CSI): 0.441420 - Best Trial: 40 - Best Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1556353802013698, 'ffn_dropout': 0.16208534456557933, 'lr': 0.0007496145596734645, 'weight_decay': 0.008780582140665853, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 19:09:51,354] Trial 67 pruned. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.363636 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.15504062242650196, 'ffn_dropout': 0.197143131197394, 'lr': 0.00031771024965177204, 'weight_decay': 0.0023441523271843586, 'batch_size': 128} - Best Value (CSI): 0.441420 - Best Trial: 40 - Best Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1556353802013698, 'ffn_dropout': 0.16208534456557933, 'lr': 0.0007496145596734645, 'weight_decay': 0.008780582140665853, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 19:11:41,737] Trial 68 pruned. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.357564 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.1095408727676423, 'ffn_dropout': 0.1727437198805319, 'lr': 0.0004430360440253659, 'weight_decay': 0.00469007692822832, 'batch_size': 32} - Best Value (CSI): 0.441420 - Best Trial: 40 - Best Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1556353802013698, 'ffn_dropout': 0.16208534456557933, 'lr': 0.0007496145596734645, 'weight_decay': 0.008780582140665853, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 19:15:42,398] Trial 69 finished with value: 0.4431741248703596 and parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.16403219128792793, 'ffn_dropout': 0.12389945690707567, 'lr': 0.0002171309467375011, 'weight_decay': 0.0017934889765604998, 'batch_size': 64}. Best is trial 69 with value: 0.4431741248703596. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.443174 - Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.16403219128792793, 'ffn_dropout': 0.12389945690707567, 'lr': 0.0002171309467375011, 'weight_decay': 0.0017934889765604998, 'batch_size': 64} - Best Value (CSI): 0.443174 - Best Trial: 69 - Best Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.16403219128792793, 'ffn_dropout': 0.12389945690707567, 'lr': 0.0002171309467375011, 'weight_decay': 0.0017934889765604998, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 19:19:41,439] Trial 70 finished with value: 0.4196754395078465 and parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.2055732124683943, 'ffn_dropout': 0.12360387450684893, 'lr': 0.00012191830288681153, 'weight_decay': 0.003159863292954228, 'batch_size': 64}. Best is trial 69 with value: 0.4431741248703596. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.419675 - Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.2055732124683943, 'ffn_dropout': 0.12360387450684893, 'lr': 0.00012191830288681153, 'weight_decay': 0.003159863292954228, 'batch_size': 64} - Best Value (CSI): 0.443174 - Best Trial: 69 - Best Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.16403219128792793, 'ffn_dropout': 0.12389945690707567, 'lr': 0.0002171309467375011, 'weight_decay': 0.0017934889765604998, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 19:23:39,461] Trial 71 finished with value: 0.4204887383965752 and parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.16403341479815875, 'ffn_dropout': 0.13958081240736597, 'lr': 0.00023035280209805352, 'weight_decay': 0.0017788389197751068, 'batch_size': 64}. Best is trial 69 with value: 0.4431741248703596. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.420489 - Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.16403341479815875, 'ffn_dropout': 0.13958081240736597, 'lr': 0.00023035280209805352, 'weight_decay': 0.0017788389197751068, 'batch_size': 64} - Best Value (CSI): 0.443174 - Best Trial: 69 - Best Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.16403219128792793, 'ffn_dropout': 0.12389945690707567, 'lr': 0.0002171309467375011, 'weight_decay': 0.0017934889765604998, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 19:26:54,566] Trial 72 finished with value: 0.4300861950358712 and parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.14178259417799075, 'ffn_dropout': 0.10601497995132242, 'lr': 0.00017974206318143438, 'weight_decay': 0.0013829533626075142, 'batch_size': 64}. Best is trial 69 with value: 0.4431741248703596. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.430086 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.14178259417799075, 'ffn_dropout': 0.10601497995132242, 'lr': 0.00017974206318143438, 'weight_decay': 0.0013829533626075142, 'batch_size': 64} - Best Value (CSI): 0.443174 - Best Trial: 69 - Best Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.16403219128792793, 'ffn_dropout': 0.12389945690707567, 'lr': 0.0002171309467375011, 'weight_decay': 0.0017934889765604998, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 19:30:51,014] Trial 73 finished with value: 0.43437788253710635 and parameters: {'d_token': 224, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.17435240403767915, 'ffn_dropout': 0.1184008817958567, 'lr': 0.00037441260460655196, 'weight_decay': 0.0011027074952704244, 'batch_size': 64}. Best is trial 69 with value: 0.4431741248703596. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.434378 - Parameters: {'d_token': 224, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.17435240403767915, 'ffn_dropout': 0.1184008817958567, 'lr': 0.00037441260460655196, 'weight_decay': 0.0011027074952704244, 'batch_size': 64} - Best Value (CSI): 0.443174 - Best Trial: 69 - Best Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.16403219128792793, 'ffn_dropout': 0.12389945690707567, 'lr': 0.0002171309467375011, 'weight_decay': 0.0017934889765604998, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 19:32:00,900] Trial 74 pruned. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.017208 - Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.12731653987602387, 'ffn_dropout': 0.1515501729584194, 'lr': 0.0005285236199010238, 'weight_decay': 0.002418961894724857, 'batch_size': 32} - Best Value (CSI): 0.443174 - Best Trial: 69 - Best Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.16403219128792793, 'ffn_dropout': 0.12389945690707567, 'lr': 0.0002171309467375011, 'weight_decay': 0.0017934889765604998, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 19:33:06,192] Trial 75 pruned. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.367483 - Parameters: {'d_token': 224, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.18647066952118696, 'ffn_dropout': 0.16046344640671834, 'lr': 0.00014390368388044635, 'weight_decay': 0.0018984357045423708, 'batch_size': 64} - Best Value (CSI): 0.443174 - Best Trial: 69 - Best Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.16403219128792793, 'ffn_dropout': 0.12389945690707567, 'lr': 0.0002171309467375011, 'weight_decay': 0.0017934889765604998, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 19:33:47,093] Trial 76 pruned. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.373576 - Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.1343568783199494, 'ffn_dropout': 0.13412112266573673, 'lr': 0.0002958944519899403, 'weight_decay': 0.000835877698940035, 'batch_size': 256} - Best Value (CSI): 0.443174 - Best Trial: 69 - Best Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.16403219128792793, 'ffn_dropout': 0.12389945690707567, 'lr': 0.0002171309467375011, 'weight_decay': 0.0017934889765604998, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 19:34:01,752] Trial 77 pruned. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.327345 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.14735778164386165, 'ffn_dropout': 0.11725152093659434, 'lr': 0.00020102065510181985, 'weight_decay': 0.0012774312600350324, 'batch_size': 128} - Best Value (CSI): 0.443174 - Best Trial: 69 - Best Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.16403219128792793, 'ffn_dropout': 0.12389945690707567, 'lr': 0.0002171309467375011, 'weight_decay': 0.0017934889765604998, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 19:39:46,982] Trial 78 finished with value: 0.44918319157422554 and parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1615322006432558, 'ffn_dropout': 0.14353691142809796, 'lr': 0.00025225999310114116, 'weight_decay': 0.002948085679186959, 'batch_size': 32}. Best is trial 78 with value: 0.44918319157422554. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.449183 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1615322006432558, 'ffn_dropout': 0.14353691142809796, 'lr': 0.00025225999310114116, 'weight_decay': 0.002948085679186959, 'batch_size': 32} - Best Value (CSI): 0.449183 - Best Trial: 78 - Best Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1615322006432558, 'ffn_dropout': 0.14353691142809796, 'lr': 0.00025225999310114116, 'weight_decay': 0.002948085679186959, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 19:44:15,125] Trial 79 finished with value: 0.41077999210910804 and parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.16867100957054396, 'ffn_dropout': 0.12607406092029955, 'lr': 0.0002463472406391484, 'weight_decay': 0.003069763560343024, 'batch_size': 32}. Best is trial 78 with value: 0.44918319157422554. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.410780 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.16867100957054396, 'ffn_dropout': 0.12607406092029955, 'lr': 0.0002463472406391484, 'weight_decay': 0.003069763560343024, 'batch_size': 32} - Best Value (CSI): 0.449183 - Best Trial: 78 - Best Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1615322006432558, 'ffn_dropout': 0.14353691142809796, 'lr': 0.00025225999310114116, 'weight_decay': 0.002948085679186959, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 19:45:41,199] Trial 80 pruned. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.358051 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1811049257405468, 'ffn_dropout': 0.1454676274524241, 'lr': 0.00013992724247680573, 'weight_decay': 0.006163531217760437, 'batch_size': 32} - Best Value (CSI): 0.449183 - Best Trial: 78 - Best Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1615322006432558, 'ffn_dropout': 0.14353691142809796, 'lr': 0.00025225999310114116, 'weight_decay': 0.002948085679186959, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 19:50:42,000] Trial 81 finished with value: 0.4420117302971501 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.16040871939953077, 'ffn_dropout': 0.16367735877215775, 'lr': 0.0003327621798319041, 'weight_decay': 0.004645945169993859, 'batch_size': 32}. Best is trial 78 with value: 0.44918319157422554. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.442012 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.16040871939953077, 'ffn_dropout': 0.16367735877215775, 'lr': 0.0003327621798319041, 'weight_decay': 0.004645945169993859, 'batch_size': 32} - Best Value (CSI): 0.449183 - Best Trial: 78 - Best Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1615322006432558, 'ffn_dropout': 0.14353691142809796, 'lr': 0.00025225999310114116, 'weight_decay': 0.002948085679186959, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 19:51:33,735] Trial 82 pruned. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.329730 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1635470980524377, 'ffn_dropout': 0.15926548758387668, 'lr': 0.0003137323155267198, 'weight_decay': 0.00402301647510049, 'batch_size': 32} - Best Value (CSI): 0.449183 - Best Trial: 78 - Best Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1615322006432558, 'ffn_dropout': 0.14353691142809796, 'lr': 0.00025225999310114116, 'weight_decay': 0.002948085679186959, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 19:52:59,566] Trial 83 pruned. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.348269 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19529197167907367, 'ffn_dropout': 0.13824790418933847, 'lr': 0.00017644782749934415, 'weight_decay': 0.0034124911632735337, 'batch_size': 32} - Best Value (CSI): 0.449183 - Best Trial: 78 - Best Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1615322006432558, 'ffn_dropout': 0.14353691142809796, 'lr': 0.00025225999310114116, 'weight_decay': 0.002948085679186959, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 19:54:27,227] Trial 84 pruned. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.319419 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.14865115806371734, 'ffn_dropout': 0.15069977993817893, 'lr': 0.00022610838468533088, 'weight_decay': 0.004763659044386419, 'batch_size': 32} - Best Value (CSI): 0.449183 - Best Trial: 78 - Best Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1615322006432558, 'ffn_dropout': 0.14353691142809796, 'lr': 0.00025225999310114116, 'weight_decay': 0.002948085679186959, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 19:59:28,151] Trial 85 finished with value: 0.44052616442516523 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.17400292846833323, 'ffn_dropout': 0.10556144588768568, 'lr': 0.0005005052915230868, 'weight_decay': 0.0027131388409398997, 'batch_size': 32}. Best is trial 78 with value: 0.44918319157422554. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.440526 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.17400292846833323, 'ffn_dropout': 0.10556144588768568, 'lr': 0.0005005052915230868, 'weight_decay': 0.0027131388409398997, 'batch_size': 32} - Best Value (CSI): 0.449183 - Best Trial: 78 - Best Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1615322006432558, 'ffn_dropout': 0.14353691142809796, 'lr': 0.00025225999310114116, 'weight_decay': 0.002948085679186959, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 20:04:53,564] Trial 86 finished with value: 0.44178844339108014 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1712906287602601, 'ffn_dropout': 0.1238482631111626, 'lr': 0.000482944657085638, 'weight_decay': 0.0026962646562749535, 'batch_size': 32}. Best is trial 78 with value: 0.44918319157422554. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.441788 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1712906287602601, 'ffn_dropout': 0.1238482631111626, 'lr': 0.000482944657085638, 'weight_decay': 0.0026962646562749535, 'batch_size': 32} - Best Value (CSI): 0.449183 - Best Trial: 78 - Best Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1615322006432558, 'ffn_dropout': 0.14353691142809796, 'lr': 0.00025225999310114116, 'weight_decay': 0.002948085679186959, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 20:10:05,008] Trial 87 finished with value: 0.44260934523432666 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.17168181393330476, 'ffn_dropout': 0.12562169578849877, 'lr': 0.0006450790370654633, 'weight_decay': 0.0028769137213888445, 'batch_size': 32}. Best is trial 78 with value: 0.44918319157422554. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.442609 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.17168181393330476, 'ffn_dropout': 0.12562169578849877, 'lr': 0.0006450790370654633, 'weight_decay': 0.0028769137213888445, 'batch_size': 32} - Best Value (CSI): 0.449183 - Best Trial: 78 - Best Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1615322006432558, 'ffn_dropout': 0.14353691142809796, 'lr': 0.00025225999310114116, 'weight_decay': 0.002948085679186959, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 20:15:21,974] Trial 88 finished with value: 0.4225039235934051 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.17716253733065707, 'ffn_dropout': 0.10373222813602012, 'lr': 0.0008060110550786684, 'weight_decay': 0.002762115349932314, 'batch_size': 32}. Best is trial 78 with value: 0.44918319157422554. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.422504 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.17716253733065707, 'ffn_dropout': 0.10373222813602012, 'lr': 0.0008060110550786684, 'weight_decay': 0.002762115349932314, 'batch_size': 32} - Best Value (CSI): 0.449183 - Best Trial: 78 - Best Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1615322006432558, 'ffn_dropout': 0.14353691142809796, 'lr': 0.00025225999310114116, 'weight_decay': 0.002948085679186959, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 20:20:38,940] Trial 89 finished with value: 0.4331833072119837 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1890056926716874, 'ffn_dropout': 0.11396396282861, 'lr': 0.0005075379826556228, 'weight_decay': 0.0024884935711004977, 'batch_size': 32}. Best is trial 78 with value: 0.44918319157422554. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.433183 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1890056926716874, 'ffn_dropout': 0.11396396282861, 'lr': 0.0005075379826556228, 'weight_decay': 0.0024884935711004977, 'batch_size': 32} - Best Value (CSI): 0.449183 - Best Trial: 78 - Best Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1615322006432558, 'ffn_dropout': 0.14353691142809796, 'lr': 0.00025225999310114116, 'weight_decay': 0.002948085679186959, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 20:25:52,652] Trial 90 finished with value: 0.434780381610878 and parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.15925184932964423, 'ffn_dropout': 0.12349497213164552, 'lr': 0.0006309746054727753, 'weight_decay': 0.0037050439827611397, 'batch_size': 32}. Best is trial 78 with value: 0.44918319157422554. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.434780 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.15925184932964423, 'ffn_dropout': 0.12349497213164552, 'lr': 0.0006309746054727753, 'weight_decay': 0.0037050439827611397, 'batch_size': 32} - Best Value (CSI): 0.449183 - Best Trial: 78 - Best Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1615322006432558, 'ffn_dropout': 0.14353691142809796, 'lr': 0.00025225999310114116, 'weight_decay': 0.002948085679186959, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 20:30:49,451] Trial 91 finished with value: 0.4099034866820849 and parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.17264366410927948, 'ffn_dropout': 0.1317296908253193, 'lr': 0.0010044852010196881, 'weight_decay': 0.005478366456452128, 'batch_size': 32}. Best is trial 78 with value: 0.44918319157422554. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.409903 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.17264366410927948, 'ffn_dropout': 0.1317296908253193, 'lr': 0.0010044852010196881, 'weight_decay': 0.005478366456452128, 'batch_size': 32} - Best Value (CSI): 0.449183 - Best Trial: 78 - Best Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1615322006432558, 'ffn_dropout': 0.14353691142809796, 'lr': 0.00025225999310114116, 'weight_decay': 0.002948085679186959, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 20:35:59,004] Trial 92 finished with value: 0.41962453309776165 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.20777980930487486, 'ffn_dropout': 0.14179592016430473, 'lr': 0.0006598511598691256, 'weight_decay': 0.002868843656715645, 'batch_size': 32}. Best is trial 78 with value: 0.44918319157422554. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.419625 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.20777980930487486, 'ffn_dropout': 0.14179592016430473, 'lr': 0.0006598511598691256, 'weight_decay': 0.002868843656715645, 'batch_size': 32} - Best Value (CSI): 0.449183 - Best Trial: 78 - Best Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1615322006432558, 'ffn_dropout': 0.14353691142809796, 'lr': 0.00025225999310114116, 'weight_decay': 0.002948085679186959, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 20:39:58,711] Trial 93 finished with value: 0.4201215018677731 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1687561161704828, 'ffn_dropout': 0.11209935167464238, 'lr': 0.0004611785229799356, 'weight_decay': 0.004381972393210843, 'batch_size': 32}. Best is trial 78 with value: 0.44918319157422554. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.420122 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1687561161704828, 'ffn_dropout': 0.11209935167464238, 'lr': 0.0004611785229799356, 'weight_decay': 0.004381972393210843, 'batch_size': 32} - Best Value (CSI): 0.449183 - Best Trial: 78 - Best Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1615322006432558, 'ffn_dropout': 0.14353691142809796, 'lr': 0.00025225999310114116, 'weight_decay': 0.002948085679186959, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 20:40:46,449] Trial 94 pruned. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.366013 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.17926851582710424, 'ffn_dropout': 0.12645963096261686, 'lr': 0.00027446837330017006, 'weight_decay': 0.0017033773078440023, 'batch_size': 32} - Best Value (CSI): 0.449183 - Best Trial: 78 - Best Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1615322006432558, 'ffn_dropout': 0.14353691142809796, 'lr': 0.00025225999310114116, 'weight_decay': 0.002948085679186959, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) -[I 2025-12-28 20:41:36,397] Trial 95 pruned. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.180041 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.16214201024242458, 'ffn_dropout': 0.167265015445544, 'lr': 0.0012821343910400659, 'weight_decay': 0.0022352506919120336, 'batch_size': 32} - Best Value (CSI): 0.449183 - Best Trial: 78 - Best Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1615322006432558, 'ffn_dropout': 0.14353691142809796, 'lr': 0.00025225999310114116, 'weight_decay': 0.002948085679186959, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 20:47:32,305] Trial 96 finished with value: 0.4388926315929929 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1912236184330946, 'ffn_dropout': 0.12009565204016064, 'lr': 0.0007288495141506138, 'weight_decay': 0.0033976339837676274, 'batch_size': 32}. Best is trial 78 with value: 0.44918319157422554. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.438893 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1912236184330946, 'ffn_dropout': 0.12009565204016064, 'lr': 0.0007288495141506138, 'weight_decay': 0.0033976339837676274, 'batch_size': 32} - Best Value (CSI): 0.449183 - Best Trial: 78 - Best Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1615322006432558, 'ffn_dropout': 0.14353691142809796, 'lr': 0.00025225999310114116, 'weight_decay': 0.002948085679186959, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 20:52:54,984] Trial 97 finished with value: 0.4274120121183942 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19035338143141867, 'ffn_dropout': 0.12092017089876318, 'lr': 0.0009174887374745283, 'weight_decay': 0.003374267126255662, 'batch_size': 32}. Best is trial 78 with value: 0.44918319157422554. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.427412 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19035338143141867, 'ffn_dropout': 0.12092017089876318, 'lr': 0.0009174887374745283, 'weight_decay': 0.003374267126255662, 'batch_size': 32} - Best Value (CSI): 0.449183 - Best Trial: 78 - Best Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1615322006432558, 'ffn_dropout': 0.14353691142809796, 'lr': 0.00025225999310114116, 'weight_decay': 0.002948085679186959, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 20:56:33,825] Trial 98 finished with value: 0.4347028957094918 and parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.15863340622012126, 'ffn_dropout': 0.10997161681174206, 'lr': 0.0007445219008485975, 'weight_decay': 0.004219024001386447, 'batch_size': 32}. Best is trial 78 with value: 0.44918319157422554. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.434703 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.15863340622012126, 'ffn_dropout': 0.10997161681174206, 'lr': 0.0007445219008485975, 'weight_decay': 0.004219024001386447, 'batch_size': 32} - Best Value (CSI): 0.449183 - Best Trial: 78 - Best Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1615322006432558, 'ffn_dropout': 0.14353691142809796, 'lr': 0.00025225999310114116, 'weight_decay': 0.002948085679186959, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2464288087170288, 1: 1.1469797016385423, 2: 0.7542314959996783} (클래스별 샘플 수: {0: 10034, 1: 10904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.168284789644013, 2: 0.7447876371282905} (클래스별 샘플 수: {0: 10029, 1: 10712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.247350410312635, 1: 1.1808517330313895, 2: 0.7399436331027415} (클래스별 샘플 수: {0: 10033, 1: 10598, 2: 16913}) -[I 2025-12-28 21:02:10,347] Trial 99 finished with value: 0.4191712639007423 and parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1718070721666482, 'ffn_dropout': 0.10358805464232193, 'lr': 0.0005550459078643854, 'weight_decay': 0.002587835766959848, 'batch_size': 32}. Best is trial 78 with value: 0.44918319157422554. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.419171 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1718070721666482, 'ffn_dropout': 0.10358805464232193, 'lr': 0.0005550459078643854, 'weight_decay': 0.002587835766959848, 'batch_size': 32} - Best Value (CSI): 0.449183 - Best Trial: 78 - Best Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1615322006432558, 'ffn_dropout': 0.14353691142809796, 'lr': 0.00025225999310114116, 'weight_decay': 0.002948085679186959, 'batch_size': 32} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.4492 -Best Hyperparameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1615322006432558, 'ffn_dropout': 0.14353691142809796, 'lr': 0.00025225999310114116, 'weight_decay': 0.002948085679186959, 'batch_size': 32} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.2779 - - 최종 CSI: 0.4192 - - 최고 CSI: 0.4492 - - 최저 CSI: 0.0000 - - 평균 CSI: 0.3587 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/ft_transformer_ctgan10000_daegu_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 17, Best CSI: 0.3962 - Fold 1 학습 완료 (검증 CSI: 0.3962) -Fold 2 학습 중... - Early stopping at epoch 38, Best CSI: 0.4349 - Fold 2 학습 완료 (검증 CSI: 0.4349) -Fold 3 학습 중... - Early stopping at epoch 28, Best CSI: 0.4252 - Fold 3 학습 완료 (검증 CSI: 0.4252) - -모든 모델 저장 완료: ../save_model/ft_transformer_optima/ft_transformer_ctgan10000_daegu.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/ft_transformer_optima/scaler/ft_transformer_ctgan10000_daegu_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: ../save_model/ft_transformer_optima/ft_transformer_ctgan10000_daegu.pkl - -✓ 완료: ft_transformer_ctgan10000/ft_transformer_ctgan10000_daegu.py (소요 시간: 17131초) - ----------------------------------------- -실행 중: ft_transformer_ctgan10000/ft_transformer_ctgan10000_daejeon.py -시작 시간: 2025-12-28 21:08:29 ----------------------------------------- -[I 2025-12-28 21:08:30,933] A new study created in memory with name: no-name-3f3c81fc-a71e-4897-bb9d-8d2f14daf07b - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 21:10:45,843] Trial 0 finished with value: 0.3515107336046827 and parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.2910103348211043, 'ffn_dropout': 0.36754899903896976, 'lr': 2.3405541509068347e-05, 'weight_decay': 0.0001511155501594832, 'batch_size': 256}. Best is trial 0 with value: 0.3515107336046827. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.351511 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.2910103348211043, 'ffn_dropout': 0.36754899903896976, 'lr': 2.3405541509068347e-05, 'weight_decay': 0.0001511155501594832, 'batch_size': 256} - Best Value (CSI): 0.351511 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.2910103348211043, 'ffn_dropout': 0.36754899903896976, 'lr': 2.3405541509068347e-05, 'weight_decay': 0.0001511155501594832, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 21:12:53,317] Trial 1 finished with value: 0.48268241236605886 and parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.2829185571256843, 'ffn_dropout': 0.29864292887671456, 'lr': 0.00023191180470194834, 'weight_decay': 0.000992272744848878, 'batch_size': 128}. Best is trial 1 with value: 0.48268241236605886. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.482682 - Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.2829185571256843, 'ffn_dropout': 0.29864292887671456, 'lr': 0.00023191180470194834, 'weight_decay': 0.000992272744848878, 'batch_size': 128} - Best Value (CSI): 0.482682 - Best Trial: 1 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.2829185571256843, 'ffn_dropout': 0.29864292887671456, 'lr': 0.00023191180470194834, 'weight_decay': 0.000992272744848878, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 21:15:44,597] Trial 2 finished with value: 0.5013219159497612 and parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.10565268869135563, 'ffn_dropout': 0.1512220025238161, 'lr': 0.0015391779544413461, 'weight_decay': 0.0034351346365071294, 'batch_size': 64}. Best is trial 2 with value: 0.5013219159497612. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.501322 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.10565268869135563, 'ffn_dropout': 0.1512220025238161, 'lr': 0.0015391779544413461, 'weight_decay': 0.0034351346365071294, 'batch_size': 64} - Best Value (CSI): 0.501322 - Best Trial: 2 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.10565268869135563, 'ffn_dropout': 0.1512220025238161, 'lr': 0.0015391779544413461, 'weight_decay': 0.0034351346365071294, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 21:16:50,130] Trial 3 finished with value: 0.3093077976149397 and parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.14840952108238487, 'ffn_dropout': 0.1453854539724981, 'lr': 1.238707618652678e-05, 'weight_decay': 0.025335452633787264, 'batch_size': 128}. Best is trial 2 with value: 0.5013219159497612. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.309308 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.14840952108238487, 'ffn_dropout': 0.1453854539724981, 'lr': 1.238707618652678e-05, 'weight_decay': 0.025335452633787264, 'batch_size': 128} - Best Value (CSI): 0.501322 - Best Trial: 2 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.10565268869135563, 'ffn_dropout': 0.1512220025238161, 'lr': 0.0015391779544413461, 'weight_decay': 0.0034351346365071294, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 21:19:27,380] Trial 4 finished with value: 0.46030731800690755 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.17276075571553545, 'ffn_dropout': 0.3474022903607733, 'lr': 0.0001584714987491879, 'weight_decay': 0.0006814440446575935, 'batch_size': 64}. Best is trial 2 with value: 0.5013219159497612. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.460307 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.17276075571553545, 'ffn_dropout': 0.3474022903607733, 'lr': 0.0001584714987491879, 'weight_decay': 0.0006814440446575935, 'batch_size': 64} - Best Value (CSI): 0.501322 - Best Trial: 2 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.10565268869135563, 'ffn_dropout': 0.1512220025238161, 'lr': 0.0015391779544413461, 'weight_decay': 0.0034351346365071294, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 21:20:20,632] Trial 5 finished with value: 0.4987061635154914 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3713927388668614, 'ffn_dropout': 0.3197649291495102, 'lr': 0.0009720779545266859, 'weight_decay': 0.0024427548553668595, 'batch_size': 128}. Best is trial 2 with value: 0.5013219159497612. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.498706 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3713927388668614, 'ffn_dropout': 0.3197649291495102, 'lr': 0.0009720779545266859, 'weight_decay': 0.0024427548553668595, 'batch_size': 128} - Best Value (CSI): 0.501322 - Best Trial: 2 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.10565268869135563, 'ffn_dropout': 0.1512220025238161, 'lr': 0.0015391779544413461, 'weight_decay': 0.0034351346365071294, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:21:59,694] Trial 6 pruned. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.365305 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.15076091579590556, 'ffn_dropout': 0.30415455879227615, 'lr': 2.1431908212236976e-05, 'weight_decay': 0.0005184691476675433, 'batch_size': 32} - Best Value (CSI): 0.501322 - Best Trial: 2 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.10565268869135563, 'ffn_dropout': 0.1512220025238161, 'lr': 0.0015391779544413461, 'weight_decay': 0.0034351346365071294, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:22:35,075] Trial 7 pruned. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1361494845743928, 'ffn_dropout': 0.10745031387126859, 'lr': 0.008474590982147583, 'weight_decay': 0.02996632985549609, 'batch_size': 64} - Best Value (CSI): 0.501322 - Best Trial: 2 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.10565268869135563, 'ffn_dropout': 0.1512220025238161, 'lr': 0.0015391779544413461, 'weight_decay': 0.0034351346365071294, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:22:44,846] Trial 8 pruned. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.142573 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3967395136156501, 'ffn_dropout': 0.3876093034675808, 'lr': 1.6615662574198014e-05, 'weight_decay': 0.0006295034375823504, 'batch_size': 256} - Best Value (CSI): 0.501322 - Best Trial: 2 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.10565268869135563, 'ffn_dropout': 0.1512220025238161, 'lr': 0.0015391779544413461, 'weight_decay': 0.0034351346365071294, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 21:26:05,945] Trial 9 finished with value: 0.49564702440561703 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.32835210822772365, 'ffn_dropout': 0.1774733759381295, 'lr': 7.267523155451432e-05, 'weight_decay': 0.0011692465877522508, 'batch_size': 32}. Best is trial 2 with value: 0.5013219159497612. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.495647 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.32835210822772365, 'ffn_dropout': 0.1774733759381295, 'lr': 7.267523155451432e-05, 'weight_decay': 0.0011692465877522508, 'batch_size': 32} - Best Value (CSI): 0.501322 - Best Trial: 2 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.10565268869135563, 'ffn_dropout': 0.1512220025238161, 'lr': 0.0015391779544413461, 'weight_decay': 0.0034351346365071294, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:26:35,904] Trial 10 pruned. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.20990584109636984, 'ffn_dropout': 0.21857764222635895, 'lr': 0.0012364894857675441, 'weight_decay': 0.00662271549445519, 'batch_size': 64} - Best Value (CSI): 0.501322 - Best Trial: 2 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.10565268869135563, 'ffn_dropout': 0.1512220025238161, 'lr': 0.0015391779544413461, 'weight_decay': 0.0034351346365071294, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 21:27:44,087] Trial 11 finished with value: 0.4917700703665459 and parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.11029183690839856, 'ffn_dropout': 0.2526676915697925, 'lr': 0.0012736609612595687, 'weight_decay': 0.004865858775688092, 'batch_size': 128}. Best is trial 2 with value: 0.5013219159497612. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.491770 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.11029183690839856, 'ffn_dropout': 0.2526676915697925, 'lr': 0.0012736609612595687, 'weight_decay': 0.004865858775688092, 'batch_size': 128} - Best Value (CSI): 0.501322 - Best Trial: 2 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.10565268869135563, 'ffn_dropout': 0.1512220025238161, 'lr': 0.0015391779544413461, 'weight_decay': 0.0034351346365071294, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:28:40,886] Trial 12 pruned. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.453509 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2125488418345018, 'ffn_dropout': 0.21702726593221097, 'lr': 0.0008933109721431462, 'weight_decay': 0.003538699326323409, 'batch_size': 64} - Best Value (CSI): 0.501322 - Best Trial: 2 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.10565268869135563, 'ffn_dropout': 0.1512220025238161, 'lr': 0.0015391779544413461, 'weight_decay': 0.0034351346365071294, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:29:05,311] Trial 13 pruned. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.439394 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.1054738506617745, 'ffn_dropout': 0.12192189326601019, 'lr': 0.0024070517609002355, 'weight_decay': 0.009393528589689108, 'batch_size': 128} - Best Value (CSI): 0.501322 - Best Trial: 2 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.10565268869135563, 'ffn_dropout': 0.1512220025238161, 'lr': 0.0015391779544413461, 'weight_decay': 0.0034351346365071294, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 21:31:05,683] Trial 14 finished with value: 0.5026041056392309 and parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128}. Best is trial 14 with value: 0.5026041056392309. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.502604 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:32:03,006] Trial 15 pruned. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.401718 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.2499398319377708, 'ffn_dropout': 0.15989392516588427, 'lr': 0.0003236232054018821, 'weight_decay': 0.09619251418964923, 'batch_size': 64} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:33:04,025] Trial 16 pruned. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.34362470050957933, 'ffn_dropout': 0.10075486039854117, 'lr': 0.004018723029757962, 'weight_decay': 0.013157509850258141, 'batch_size': 32} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:33:22,186] Trial 17 pruned. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.392644 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.20565665060175314, 'ffn_dropout': 0.17811910410728996, 'lr': 0.0006387547861781145, 'weight_decay': 0.09698879829924102, 'batch_size': 256} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 21:34:57,018] Trial 18 finished with value: 0.4941770913736554 and parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.39249792924519195, 'ffn_dropout': 0.14120337052036003, 'lr': 0.0005190718069112197, 'weight_decay': 0.01829550455255961, 'batch_size': 128}. Best is trial 14 with value: 0.5026041056392309. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.494177 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.39249792924519195, 'ffn_dropout': 0.14120337052036003, 'lr': 0.0005190718069112197, 'weight_decay': 0.01829550455255961, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:35:32,603] Trial 19 pruned. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.2492674716467032, 'ffn_dropout': 0.18993060196715997, 'lr': 0.0022903006526314024, 'weight_decay': 0.04298668487060687, 'batch_size': 64} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:36:10,040] Trial 20 pruned. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.406854 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3244487197097661, 'ffn_dropout': 0.13060537613725406, 'lr': 0.0004065826720290648, 'weight_decay': 0.010029330910050725, 'batch_size': 64} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:36:36,174] Trial 21 pruned. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.411304 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3677426936343995, 'ffn_dropout': 0.1580412151566468, 'lr': 0.0008496330702481001, 'weight_decay': 0.0020726867847233087, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 21:37:35,253] Trial 22 finished with value: 0.49875739273390646 and parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3542877777742037, 'ffn_dropout': 0.2460692956445881, 'lr': 0.001472427431370659, 'weight_decay': 0.003285940974074307, 'batch_size': 128}. Best is trial 14 with value: 0.5026041056392309. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.498757 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3542877777742037, 'ffn_dropout': 0.2460692956445881, 'lr': 0.001472427431370659, 'weight_decay': 0.003285940974074307, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:37:48,980] Trial 23 pruned. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.358862 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.35564032325385153, 'ffn_dropout': 0.23594284415411612, 'lr': 0.0022085021077608916, 'weight_decay': 0.0064032153627335085, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:37:59,422] Trial 24 pruned. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.387668 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3985602367797292, 'ffn_dropout': 0.2631548337992453, 'lr': 0.0005004521696077459, 'weight_decay': 0.003399743644493096, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:38:17,322] Trial 25 pruned. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.082650 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.31052494314229745, 'ffn_dropout': 0.2088412675644749, 'lr': 0.004390479209791537, 'weight_decay': 0.04677165064189165, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:38:58,207] Trial 26 pruned. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.057236 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.36912851683126746, 'ffn_dropout': 0.19691261949120098, 'lr': 0.0015559169987432939, 'weight_decay': 0.015435394035251434, 'batch_size': 32} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:39:28,201] Trial 27 pruned. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.433849 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.34368707966964024, 'ffn_dropout': 0.1728717862583832, 'lr': 0.0007186420135024457, 'weight_decay': 0.007955432604678436, 'batch_size': 256} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:39:37,914] Trial 28 pruned. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.292836 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2776459334353187, 'ffn_dropout': 0.1524554772207722, 'lr': 0.00022334670402665232, 'weight_decay': 0.004206578048017745, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:39:54,510] Trial 29 pruned. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.225598 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.30470697138666925, 'ffn_dropout': 0.23513303174167588, 'lr': 0.00010266013877038994, 'weight_decay': 0.000262085661526064, 'batch_size': 256} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:40:25,169] Trial 30 pruned. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.405123 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.267457712044999, 'ffn_dropout': 0.12374488813804471, 'lr': 0.0003558986388240892, 'weight_decay': 0.001747441667056421, 'batch_size': 64} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:40:36,493] Trial 31 pruned. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.396484 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.37584916598718954, 'ffn_dropout': 0.2694108829907798, 'lr': 0.0011213259159563631, 'weight_decay': 0.0023956216980094763, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 21:41:41,946] Trial 32 finished with value: 0.49591783564901526 and parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.35314992631609726, 'ffn_dropout': 0.32978910030022957, 'lr': 0.0006096988428593991, 'weight_decay': 0.0026893810504803025, 'batch_size': 128}. Best is trial 14 with value: 0.5026041056392309. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.495918 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.35314992631609726, 'ffn_dropout': 0.32978910030022957, 'lr': 0.0006096988428593991, 'weight_decay': 0.0026893810504803025, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:42:00,458] Trial 33 pruned. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.423009 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.38017144468210534, 'ffn_dropout': 0.28472842108333657, 'lr': 0.0015429396280446262, 'weight_decay': 0.0015217547008547867, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:42:11,841] Trial 34 pruned. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.391867 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.38169369565381134, 'ffn_dropout': 0.3142207084881544, 'lr': 0.0008694883297162419, 'weight_decay': 0.004028795601264474, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:42:25,131] Trial 35 pruned. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.346614 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3586603633484885, 'ffn_dropout': 0.35078014827688264, 'lr': 0.00023199493693819677, 'weight_decay': 0.0013909771723235847, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:42:47,806] Trial 36 pruned. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.394221 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3327587060427215, 'ffn_dropout': 0.30455745947096213, 'lr': 0.0016959290025939783, 'weight_decay': 0.0008948118686046056, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:43:06,049] Trial 37 pruned. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.428300 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.399155228196549, 'ffn_dropout': 0.2832916149539943, 'lr': 0.0010146204054581878, 'weight_decay': 0.002808513081241631, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:44:06,720] Trial 38 pruned. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.429104 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.29767874892345975, 'ffn_dropout': 0.23612626042558887, 'lr': 0.0006319263484298835, 'weight_decay': 0.005459650297328778, 'batch_size': 32} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:44:28,446] Trial 39 pruned. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.37955220178179155, 'ffn_dropout': 0.36478353641755257, 'lr': 0.0034276076215243993, 'weight_decay': 0.00011243883532956182, 'batch_size': 64} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:44:42,681] Trial 40 pruned. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.3643136506230742, 'ffn_dropout': 0.14051477410992014, 'lr': 0.006349979396458491, 'weight_decay': 0.0008433932628501213, 'batch_size': 256} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:45:00,997] Trial 41 pruned. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.433980 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.34616787726431775, 'ffn_dropout': 0.3159080195023359, 'lr': 0.0005080600923839421, 'weight_decay': 0.0025555157104543884, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:45:19,481] Trial 42 pruned. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.412931 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3561814010611708, 'ffn_dropout': 0.33422496030519633, 'lr': 0.0011699146384217525, 'weight_decay': 0.0018801678207811022, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:45:29,947] Trial 43 pruned. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.388410 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3224479127568032, 'ffn_dropout': 0.3402329690182905, 'lr': 0.0007228391419247939, 'weight_decay': 0.0011911349873560914, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:45:48,291] Trial 44 pruned. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.416316 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.38709835627554073, 'ffn_dropout': 0.3994342256007215, 'lr': 0.00043833767359392853, 'weight_decay': 0.004818086425654556, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:46:29,473] Trial 45 pruned. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.430865 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.12659611651144798, 'ffn_dropout': 0.32607102624881745, 'lr': 0.002034543458756047, 'weight_decay': 0.003149787410563841, 'batch_size': 64} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:46:48,037] Trial 46 pruned. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.442593 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.17359990974929396, 'ffn_dropout': 0.29509720702954306, 'lr': 0.0013789563225031604, 'weight_decay': 0.0005476356471574887, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) -[I 2025-12-28 21:48:54,537] Trial 47 pruned. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.473862 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3353963539538535, 'ffn_dropout': 0.3554934988966506, 'lr': 0.0010313342594078995, 'weight_decay': 0.007271917526062417, 'batch_size': 32} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:49:16,046] Trial 48 pruned. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.192003 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38771268593017516, 'ffn_dropout': 0.38155517642387754, 'lr': 0.002846663377088448, 'weight_decay': 0.0026271191035313305, 'batch_size': 64} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:49:34,090] Trial 49 pruned. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.391026 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3569629550852389, 'ffn_dropout': 0.1623815444512328, 'lr': 0.0018052307344522424, 'weight_decay': 0.011941913524678527, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:49:51,228] Trial 50 pruned. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.359105 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.36985723078733546, 'ffn_dropout': 0.3281323842739015, 'lr': 0.0005855974849549153, 'weight_decay': 0.005307948419336565, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:50:25,690] Trial 51 pruned. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.392157 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3158093630462354, 'ffn_dropout': 0.17519705277780875, 'lr': 3.9476621197482796e-05, 'weight_decay': 0.0011615958868990786, 'batch_size': 32} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:51:01,931] Trial 52 pruned. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.394068 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3326067820124891, 'ffn_dropout': 0.19054448568110172, 'lr': 0.0008376667228978081, 'weight_decay': 0.0020766535524811137, 'batch_size': 32} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:52:02,048] Trial 53 pruned. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.425265 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.34922003532826523, 'ffn_dropout': 0.1096389840789711, 'lr': 0.0013292637699121057, 'weight_decay': 0.003454639021209991, 'batch_size': 32} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) -[I 2025-12-28 21:54:06,260] Trial 54 pruned. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.455945 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3699930071841796, 'ffn_dropout': 0.14235980736103676, 'lr': 0.00037920091078743733, 'weight_decay': 0.001441788397419719, 'batch_size': 32} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:54:47,872] Trial 55 pruned. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.403263 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.10320806102268956, 'ffn_dropout': 0.20094253666451284, 'lr': 0.0007391130379886442, 'weight_decay': 0.0006681877382356347, 'batch_size': 64} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:55:06,486] Trial 56 pruned. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.443630 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3916426821962267, 'ffn_dropout': 0.18303405829345676, 'lr': 0.002488196044812075, 'weight_decay': 0.008844392367418616, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:55:23,868] Trial 57 pruned. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.403604 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.33908371343242466, 'ffn_dropout': 0.1668786339058096, 'lr': 0.0005792657099834926, 'weight_decay': 0.02488842177476815, 'batch_size': 256} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:56:22,602] Trial 58 pruned. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.421933 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.32473265507728605, 'ffn_dropout': 0.14977315571684574, 'lr': 0.00027944521712988316, 'weight_decay': 0.006206785631725239, 'batch_size': 32} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:56:51,273] Trial 59 pruned. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.404199 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.35504941019122477, 'ffn_dropout': 0.21716095486291476, 'lr': 0.00016514797041883663, 'weight_decay': 0.0021991470942317928, 'batch_size': 64} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:57:01,799] Trial 60 pruned. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.321154 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.37514920863848794, 'ffn_dropout': 0.16684354556917638, 'lr': 0.0004887068907532713, 'weight_decay': 0.004165144081633466, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:57:19,861] Trial 61 pruned. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.407447 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.39085618761924856, 'ffn_dropout': 0.1327227231970394, 'lr': 0.000931920219140957, 'weight_decay': 0.06447921001036785, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) -[I 2025-12-28 21:58:27,691] Trial 62 pruned. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.441331 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.36248932678716794, 'ffn_dropout': 0.15279045626358187, 'lr': 0.0002923397710636246, 'weight_decay': 0.01651820895349918, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:59:01,075] Trial 63 pruned. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.443820 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3845126780585659, 'ffn_dropout': 0.14150886442378036, 'lr': 0.00041385813794535893, 'weight_decay': 0.0017030347501990352, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 21:59:14,456] Trial 64 pruned. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.404902 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.39608407881426566, 'ffn_dropout': 0.18582277408441594, 'lr': 0.0012371514755540366, 'weight_decay': 0.0035061646640506673, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) -[I 2025-12-28 21:59:50,078] Trial 65 pruned. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.439929 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.37468182989004906, 'ffn_dropout': 0.17696022925393243, 'lr': 0.00172641510383182, 'weight_decay': 0.019468063499820557, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) -[I 2025-12-28 22:00:36,864] Trial 66 pruned. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.451907 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.34732274775533084, 'ffn_dropout': 0.161536852029162, 'lr': 0.0007368969734184046, 'weight_decay': 0.033249677988333094, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) -[I 2025-12-28 22:02:47,880] Trial 67 pruned. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.448663 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.3657419601143125, 'ffn_dropout': 0.11951832158139404, 'lr': 0.0010527814437938788, 'weight_decay': 0.0029369821562984415, 'batch_size': 64} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 22:03:13,843] Trial 68 pruned. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.380851 - Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3988055509612349, 'ffn_dropout': 0.15525300928339614, 'lr': 0.000564817636098151, 'weight_decay': 0.01074115020290595, 'batch_size': 256} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 22:03:24,451] Trial 69 pruned. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.345487 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.290186967892228, 'ffn_dropout': 0.24927857773199208, 'lr': 0.0003413806629306943, 'weight_decay': 0.008653283107142463, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 22:03:36,264] Trial 70 pruned. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.404339 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.35094481955345497, 'ffn_dropout': 0.20808595753321998, 'lr': 0.0008570847763093429, 'weight_decay': 0.0068339091917421395, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 22:03:58,394] Trial 71 pruned. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.408253 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.1198680387247807, 'ffn_dropout': 0.26961840983738394, 'lr': 0.0015209417732697755, 'weight_decay': 0.004504098948542499, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 22:04:12,234] Trial 72 pruned. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.411215 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.10927201880991169, 'ffn_dropout': 0.13612573739433703, 'lr': 0.0020333872229633372, 'weight_decay': 0.002265476951681874, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 22:04:22,871] Trial 73 pruned. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.360697 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.1480606012467573, 'ffn_dropout': 0.14620924696964935, 'lr': 0.0006741599423051107, 'weight_decay': 0.003796710980546308, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 22:04:39,887] Trial 74 pruned. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.405291 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.38024380973275806, 'ffn_dropout': 0.22765326842757222, 'lr': 0.001286292298604475, 'weight_decay': 0.0028806217162041514, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 22:05:39,369] Trial 75 pruned. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.416944 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3603872528710351, 'ffn_dropout': 0.19541552198280238, 'lr': 0.00048527339046402666, 'weight_decay': 0.0017370597613519446, 'batch_size': 32} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 22:06:29,583] Trial 76 finished with value: 0.49394858586906015 and parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3881244862768132, 'ffn_dropout': 0.17017775882110805, 'lr': 0.001079391824478875, 'weight_decay': 0.004814755859249107, 'batch_size': 128}. Best is trial 14 with value: 0.5026041056392309. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.493949 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3881244862768132, 'ffn_dropout': 0.17017775882110805, 'lr': 0.001079391824478875, 'weight_decay': 0.004814755859249107, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 22:06:47,724] Trial 77 pruned. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.434199 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3868400151004187, 'ffn_dropout': 0.17299576236645445, 'lr': 0.0008181055907429058, 'weight_decay': 0.005717022654903751, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 22:07:20,083] Trial 78 pruned. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.447177 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.37444959968655794, 'ffn_dropout': 0.1266228230320316, 'lr': 0.0010516478657094893, 'weight_decay': 0.0025107616832460147, 'batch_size': 64} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 22:07:38,737] Trial 79 pruned. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.418025 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3660551763568543, 'ffn_dropout': 0.18448542998786427, 'lr': 0.0014187394276588183, 'weight_decay': 0.00477879207937681, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 22:07:49,934] Trial 80 pruned. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.418882 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3822630932452248, 'ffn_dropout': 0.16681631542122274, 'lr': 0.0006650093370076611, 'weight_decay': 0.0011798303513801513, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) -[I 2025-12-28 22:08:26,092] Trial 81 pruned. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.490694 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.392156948685362, 'ffn_dropout': 0.15614378742747972, 'lr': 0.0010975406127280497, 'weight_decay': 0.0036007910733382993, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 22:09:48,875] Trial 82 finished with value: 0.49418024970628993 and parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2373559361034919, 'ffn_dropout': 0.20239764318595713, 'lr': 0.0009504068554256145, 'weight_decay': 0.004508710577828345, 'batch_size': 128}. Best is trial 14 with value: 0.5026041056392309. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.494180 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2373559361034919, 'ffn_dropout': 0.20239764318595713, 'lr': 0.0009504068554256145, 'weight_decay': 0.004508710577828345, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.240918856387374, 1: 1.07192005710207, 2: 0.7928704173002197} (클래스별 샘플 수: {0: 10085, 1: 11675, 2: 15784}) -[I 2025-12-28 22:11:00,309] Trial 83 finished with value: 0.49819287954649605 and parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21878187910929067, 'ffn_dropout': 0.1473864176158939, 'lr': 0.0009030310046924134, 'weight_decay': 0.007771188015928922, 'batch_size': 128}. Best is trial 14 with value: 0.5026041056392309. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.498193 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21878187910929067, 'ffn_dropout': 0.1473864176158939, 'lr': 0.0009030310046924134, 'weight_decay': 0.007771188015928922, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 22:11:26,359] Trial 84 pruned. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.414327 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.22716334693976697, 'ffn_dropout': 0.1468869901305848, 'lr': 0.0005551955375175151, 'weight_decay': 0.006769149574937204, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 22:11:38,154] Trial 85 pruned. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.348003 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2600316876520279, 'ffn_dropout': 0.17979839489120042, 'lr': 0.00042484608271293594, 'weight_decay': 0.00995306939630061, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) -[I 2025-12-28 22:14:41,293] Trial 86 pruned. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.443478 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2336223965590215, 'ffn_dropout': 0.160465544928828, 'lr': 0.0009122157703412441, 'weight_decay': 0.0030784258464602345, 'batch_size': 32} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 22:14:54,482] Trial 87 pruned. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.399163 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.19071457736005384, 'ffn_dropout': 0.13535742359860606, 'lr': 0.0007904563163174866, 'weight_decay': 0.0073981839819809, 'batch_size': 256} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.2371161196783973, 1: 1.0686249395155552, 2: 0.7962503446374414} (클래스별 샘플 수: {0: 10116, 1: 11711, 2: 15717}) -[I 2025-12-28 22:16:14,848] Trial 88 pruned. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.461538 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13910169279455387, 'ffn_dropout': 0.14924255100103456, 'lr': 0.0006394418458321396, 'weight_decay': 0.005536435492531891, 'batch_size': 64} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 22:16:38,231] Trial 89 pruned. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.415094 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.34035370337862636, 'ffn_dropout': 0.19116339067933386, 'lr': 0.001499978472548167, 'weight_decay': 0.012957618630418827, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 22:16:49,085] Trial 90 pruned. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.383699 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.16106227633524878, 'ffn_dropout': 0.20580835227392907, 'lr': 0.0004931414888703649, 'weight_decay': 0.0018751997872073704, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 22:17:06,930] Trial 91 pruned. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.453875 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.245525154146777, 'ffn_dropout': 0.1672492729628541, 'lr': 0.0011717576162025424, 'weight_decay': 0.004254525223372229, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 22:17:25,536] Trial 92 pruned. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.439614 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3996853322671304, 'ffn_dropout': 0.171879387014887, 'lr': 0.0018114367322291276, 'weight_decay': 0.005097082133074525, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 22:17:36,173] Trial 93 pruned. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.342301 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.27219858664747326, 'ffn_dropout': 0.1551487324433049, 'lr': 0.0007385784272149927, 'weight_decay': 0.008039255899523989, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 22:17:55,802] Trial 94 pruned. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.399015 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.35326333923400705, 'ffn_dropout': 0.20078686506419616, 'lr': 0.0008936180198610464, 'weight_decay': 0.002585353764523342, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 22:18:07,252] Trial 95 pruned. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.426618 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.37489883378705896, 'ffn_dropout': 0.18037850190251226, 'lr': 0.001077649116806185, 'weight_decay': 0.0038749915945665435, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 22:19:03,436] Trial 96 pruned. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.428571 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2114159733284789, 'ffn_dropout': 0.14138325078465772, 'lr': 0.0005999376929795218, 'weight_decay': 0.005999710846949739, 'batch_size': 32} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 22:19:20,999] Trial 97 pruned. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.425723 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3072505767682264, 'ffn_dropout': 0.34537956728108543, 'lr': 0.0009562772057381145, 'weight_decay': 0.0030063086696620277, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 22:20:00,400] Trial 98 pruned. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.426195 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.38757747785496344, 'ffn_dropout': 0.18803207881264233, 'lr': 0.0013034441147882065, 'weight_decay': 0.004816764263709723, 'batch_size': 64} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2327911943486118, 1: 1.0479861460253617, 2: 0.8099648122962675} (클래스별 샘플 수: {0: 10145, 1: 11934, 2: 15441}) -[I 2025-12-28 22:20:10,740] Trial 99 pruned. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.406297 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.365098772570804, 'ffn_dropout': 0.17289328415765787, 'lr': 0.00034651454356218785, 'weight_decay': 0.002116148456919586, 'batch_size': 128} - Best Value (CSI): 0.502604 - Best Trial: 14 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.5026 -Best Hyperparameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39639878146052787, 'ffn_dropout': 0.16243660840447227, 'lr': 0.0005258652715359098, 'weight_decay': 0.06319928258911829, 'batch_size': 128} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.3515 - - 최종 CSI: 0.4063 - - 최고 CSI: 0.5026 - - 최저 CSI: 0.0000 - - 평균 CSI: 0.3814 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/ft_transformer_ctgan10000_daejeon_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 27, Best CSI: 0.4417 - Fold 1 학습 완료 (검증 CSI: 0.4417) -Fold 2 학습 중... - Early stopping at epoch 22, Best CSI: 0.5159 - Fold 2 학습 완료 (검증 CSI: 0.5159) -Fold 3 학습 중... - Early stopping at epoch 34, Best CSI: 0.5334 - Fold 3 학습 완료 (검증 CSI: 0.5334) - -모든 모델 저장 완료: ../save_model/ft_transformer_optima/ft_transformer_ctgan10000_daejeon.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/ft_transformer_optima/scaler/ft_transformer_ctgan10000_daejeon_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: ../save_model/ft_transformer_optima/ft_transformer_ctgan10000_daejeon.pkl - -✓ 완료: ft_transformer_ctgan10000/ft_transformer_ctgan10000_daejeon.py (소요 시간: 4428초) - ----------------------------------------- -실행 중: ft_transformer_ctgan10000/ft_transformer_ctgan10000_gwangju.py -시작 시간: 2025-12-28 22:22:17 ----------------------------------------- -[I 2025-12-28 22:22:18,736] A new study created in memory with name: no-name-4864b88c-1265-49ab-bc7d-bad5a92fe5a7 - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 22:24:43,148] Trial 0 finished with value: 0.30355860091147063 and parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.1744549040386172, 'ffn_dropout': 0.3845778191742626, 'lr': 1.1416482526812583e-05, 'weight_decay': 0.033663094335532405, 'batch_size': 64}. Best is trial 0 with value: 0.30355860091147063. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.303559 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.1744549040386172, 'ffn_dropout': 0.3845778191742626, 'lr': 1.1416482526812583e-05, 'weight_decay': 0.033663094335532405, 'batch_size': 64} - Best Value (CSI): 0.303559 - Best Trial: 0 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.1744549040386172, 'ffn_dropout': 0.3845778191742626, 'lr': 1.1416482526812583e-05, 'weight_decay': 0.033663094335532405, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 22:27:42,051] Trial 1 finished with value: 0.09806344498277031 and parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.17032841745359167, 'ffn_dropout': 0.2334634215576455, 'lr': 0.005839455349348195, 'weight_decay': 0.03884347556796034, 'batch_size': 32}. Best is trial 0 with value: 0.30355860091147063. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.098063 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.17032841745359167, 'ffn_dropout': 0.2334634215576455, 'lr': 0.005839455349348195, 'weight_decay': 0.03884347556796034, 'batch_size': 32} - Best Value (CSI): 0.303559 - Best Trial: 0 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.1744549040386172, 'ffn_dropout': 0.3845778191742626, 'lr': 1.1416482526812583e-05, 'weight_decay': 0.033663094335532405, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 22:30:33,179] Trial 2 finished with value: 0.459070633697188 and parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.13072872167536764, 'ffn_dropout': 0.1140845675514245, 'lr': 0.0012126801600609715, 'weight_decay': 0.005827068786727869, 'batch_size': 64}. Best is trial 2 with value: 0.459070633697188. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.459071 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.13072872167536764, 'ffn_dropout': 0.1140845675514245, 'lr': 0.0012126801600609715, 'weight_decay': 0.005827068786727869, 'batch_size': 64} - Best Value (CSI): 0.459071 - Best Trial: 2 - Best Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.13072872167536764, 'ffn_dropout': 0.1140845675514245, 'lr': 0.0012126801600609715, 'weight_decay': 0.005827068786727869, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 22:32:06,257] Trial 3 finished with value: 0.4837955602953958 and parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.13417611437554622, 'ffn_dropout': 0.101642562315039, 'lr': 0.0006671901431392045, 'weight_decay': 0.0252392379246892, 'batch_size': 256}. Best is trial 3 with value: 0.4837955602953958. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.483796 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.13417611437554622, 'ffn_dropout': 0.101642562315039, 'lr': 0.0006671901431392045, 'weight_decay': 0.0252392379246892, 'batch_size': 256} - Best Value (CSI): 0.483796 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.13417611437554622, 'ffn_dropout': 0.101642562315039, 'lr': 0.0006671901431392045, 'weight_decay': 0.0252392379246892, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 22:32:59,884] Trial 4 finished with value: 0.09167591968793302 and parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.15909672442187694, 'ffn_dropout': 0.3717921952562553, 'lr': 0.005985171792316229, 'weight_decay': 0.0009709989182516932, 'batch_size': 256}. Best is trial 3 with value: 0.4837955602953958. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.091676 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.15909672442187694, 'ffn_dropout': 0.3717921952562553, 'lr': 0.005985171792316229, 'weight_decay': 0.0009709989182516932, 'batch_size': 256} - Best Value (CSI): 0.483796 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.13417611437554622, 'ffn_dropout': 0.101642562315039, 'lr': 0.0006671901431392045, 'weight_decay': 0.0252392379246892, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 22:35:28,413] Trial 5 finished with value: 0.39117419231477824 and parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.39548683926693073, 'ffn_dropout': 0.24640408844891987, 'lr': 3.823039307863025e-05, 'weight_decay': 0.0002952964524635349, 'batch_size': 128}. Best is trial 3 with value: 0.4837955602953958. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.391174 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.39548683926693073, 'ffn_dropout': 0.24640408844891987, 'lr': 3.823039307863025e-05, 'weight_decay': 0.0002952964524635349, 'batch_size': 128} - Best Value (CSI): 0.483796 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.13417611437554622, 'ffn_dropout': 0.101642562315039, 'lr': 0.0006671901431392045, 'weight_decay': 0.0252392379246892, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 22:35:45,971] Trial 6 pruned. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.407279 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.10787546013535586, 'ffn_dropout': 0.20269570904753575, 'lr': 0.0008350155464408088, 'weight_decay': 0.0005291762021911083, 'batch_size': 256} - Best Value (CSI): 0.483796 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.13417611437554622, 'ffn_dropout': 0.101642562315039, 'lr': 0.0006671901431392045, 'weight_decay': 0.0252392379246892, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 22:36:25,931] Trial 7 pruned. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.073201 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.30887545723357024, 'ffn_dropout': 0.39787040746232605, 'lr': 0.008957114036168577, 'weight_decay': 0.0018031616376532479, 'batch_size': 32} - Best Value (CSI): 0.483796 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.13417611437554622, 'ffn_dropout': 0.101642562315039, 'lr': 0.0006671901431392045, 'weight_decay': 0.0252392379246892, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 22:37:23,908] Trial 8 finished with value: 0.4962456778342523 and parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2427549664804898, 'ffn_dropout': 0.16526714996641406, 'lr': 0.004003287639796112, 'weight_decay': 0.00039140197253343913, 'batch_size': 256}. Best is trial 8 with value: 0.4962456778342523. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.496246 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2427549664804898, 'ffn_dropout': 0.16526714996641406, 'lr': 0.004003287639796112, 'weight_decay': 0.00039140197253343913, 'batch_size': 256} - Best Value (CSI): 0.496246 - Best Trial: 8 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2427549664804898, 'ffn_dropout': 0.16526714996641406, 'lr': 0.004003287639796112, 'weight_decay': 0.00039140197253343913, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 22:38:04,514] Trial 9 pruned. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.370732 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.2591490653886718, 'ffn_dropout': 0.10574968794215048, 'lr': 9.775118420469087e-05, 'weight_decay': 0.00017499013641922043, 'batch_size': 256} - Best Value (CSI): 0.496246 - Best Trial: 8 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2427549664804898, 'ffn_dropout': 0.16526714996641406, 'lr': 0.004003287639796112, 'weight_decay': 0.00039140197253343913, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 22:38:46,972] Trial 10 pruned. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.375000 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.23001732499596575, 'ffn_dropout': 0.1692137877502867, 'lr': 0.0025311727803787364, 'weight_decay': 0.00012230507505704623, 'batch_size': 128} - Best Value (CSI): 0.496246 - Best Trial: 8 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2427549664804898, 'ffn_dropout': 0.16526714996641406, 'lr': 0.004003287639796112, 'weight_decay': 0.00039140197253343913, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 22:38:53,094] Trial 11 pruned. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.197179 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.10251961469272192, 'ffn_dropout': 0.14783375038099805, 'lr': 0.00039142875037926196, 'weight_decay': 0.00683189698280882, 'batch_size': 256} - Best Value (CSI): 0.496246 - Best Trial: 8 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2427549664804898, 'ffn_dropout': 0.16526714996641406, 'lr': 0.004003287639796112, 'weight_decay': 0.00039140197253343913, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 22:40:15,857] Trial 12 finished with value: 0.4887356291415484 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.21451183634540438, 'ffn_dropout': 0.1696037775564281, 'lr': 0.0018943596581716322, 'weight_decay': 0.08085910067281002, 'batch_size': 256}. Best is trial 8 with value: 0.4962456778342523. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.488736 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.21451183634540438, 'ffn_dropout': 0.1696037775564281, 'lr': 0.0018943596581716322, 'weight_decay': 0.08085910067281002, 'batch_size': 256} - Best Value (CSI): 0.496246 - Best Trial: 8 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2427549664804898, 'ffn_dropout': 0.16526714996641406, 'lr': 0.004003287639796112, 'weight_decay': 0.00039140197253343913, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 22:40:45,024] Trial 13 pruned. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.324427 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.2214074976487779, 'ffn_dropout': 0.18123065483509015, 'lr': 0.0014631621805475724, 'weight_decay': 0.07830910675016767, 'batch_size': 256} - Best Value (CSI): 0.496246 - Best Trial: 8 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2427549664804898, 'ffn_dropout': 0.16526714996641406, 'lr': 0.004003287639796112, 'weight_decay': 0.00039140197253343913, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 22:41:51,247] Trial 14 finished with value: 0.5001066701078627 and parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2776549176345562, 'ffn_dropout': 0.2073819204835327, 'lr': 0.0017492735615692344, 'weight_decay': 0.0023623967295935363, 'batch_size': 256}. Best is trial 14 with value: 0.5001066701078627. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.500107 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2776549176345562, 'ffn_dropout': 0.2073819204835327, 'lr': 0.0017492735615692344, 'weight_decay': 0.0023623967295935363, 'batch_size': 256} - Best Value (CSI): 0.500107 - Best Trial: 14 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2776549176345562, 'ffn_dropout': 0.2073819204835327, 'lr': 0.0017492735615692344, 'weight_decay': 0.0023623967295935363, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 22:42:10,738] Trial 15 pruned. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.373063 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28236438023078103, 'ffn_dropout': 0.26781169969815066, 'lr': 0.00282033439405969, 'weight_decay': 0.0007357217243206521, 'batch_size': 256} - Best Value (CSI): 0.500107 - Best Trial: 14 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2776549176345562, 'ffn_dropout': 0.2073819204835327, 'lr': 0.0017492735615692344, 'weight_decay': 0.0023623967295935363, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 22:43:13,135] Trial 16 pruned. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.398559 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.32594838996754927, 'ffn_dropout': 0.20210232078133653, 'lr': 0.0003193468849435769, 'weight_decay': 0.0020729762525110674, 'batch_size': 32} - Best Value (CSI): 0.500107 - Best Trial: 14 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2776549176345562, 'ffn_dropout': 0.2073819204835327, 'lr': 0.0017492735615692344, 'weight_decay': 0.0023623967295935363, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 22:43:34,825] Trial 17 pruned. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2589613929991434, 'ffn_dropout': 0.2887930431420088, 'lr': 0.0038432203023356748, 'weight_decay': 0.00044623393047431525, 'batch_size': 64} - Best Value (CSI): 0.500107 - Best Trial: 14 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2776549176345562, 'ffn_dropout': 0.2073819204835327, 'lr': 0.0017492735615692344, 'weight_decay': 0.0023623967295935363, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 22:43:53,635] Trial 18 pruned. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.375297 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.1984614586364219, 'ffn_dropout': 0.14263672594909627, 'lr': 0.0034446941689181675, 'weight_decay': 0.00022421823579855528, 'batch_size': 128} - Best Value (CSI): 0.500107 - Best Trial: 14 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2776549176345562, 'ffn_dropout': 0.2073819204835327, 'lr': 0.0017492735615692344, 'weight_decay': 0.0023623967295935363, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 22:44:03,522] Trial 19 pruned. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2883263005658156, 'ffn_dropout': 0.21616130640562767, 'lr': 0.00823323375328018, 'weight_decay': 0.0010373564061809165, 'batch_size': 256} - Best Value (CSI): 0.500107 - Best Trial: 14 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2776549176345562, 'ffn_dropout': 0.2073819204835327, 'lr': 0.0017492735615692344, 'weight_decay': 0.0023623967295935363, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 22:45:52,523] Trial 20 finished with value: 0.48444765777873006 and parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.24484920110323144, 'ffn_dropout': 0.2828868762985322, 'lr': 0.0007713408804542852, 'weight_decay': 0.00010125118763892607, 'batch_size': 256}. Best is trial 14 with value: 0.5001066701078627. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.484448 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.24484920110323144, 'ffn_dropout': 0.2828868762985322, 'lr': 0.0007713408804542852, 'weight_decay': 0.00010125118763892607, 'batch_size': 256} - Best Value (CSI): 0.500107 - Best Trial: 14 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2776549176345562, 'ffn_dropout': 0.2073819204835327, 'lr': 0.0017492735615692344, 'weight_decay': 0.0023623967295935363, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) -[I 2025-12-28 22:46:37,235] Trial 21 pruned. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.474252 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.20795133100172977, 'ffn_dropout': 0.17425397547284796, 'lr': 0.001594031642863458, 'weight_decay': 0.004878996258385458, 'batch_size': 256} - Best Value (CSI): 0.500107 - Best Trial: 14 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2776549176345562, 'ffn_dropout': 0.2073819204835327, 'lr': 0.0017492735615692344, 'weight_decay': 0.0023623967295935363, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 22:47:45,837] Trial 22 finished with value: 0.493836799397319 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.20004826003642076, 'ffn_dropout': 0.14348259573171573, 'lr': 0.002175165628458849, 'weight_decay': 0.012375227652865986, 'batch_size': 256}. Best is trial 14 with value: 0.5001066701078627. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.493837 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.20004826003642076, 'ffn_dropout': 0.14348259573171573, 'lr': 0.002175165628458849, 'weight_decay': 0.012375227652865986, 'batch_size': 256} - Best Value (CSI): 0.500107 - Best Trial: 14 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2776549176345562, 'ffn_dropout': 0.2073819204835327, 'lr': 0.0017492735615692344, 'weight_decay': 0.0023623967295935363, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 22:48:05,328] Trial 23 pruned. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.407320 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.19541684200349002, 'ffn_dropout': 0.14849340783950735, 'lr': 0.0040876867415894904, 'weight_decay': 0.010300959587378518, 'batch_size': 256} - Best Value (CSI): 0.500107 - Best Trial: 14 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2776549176345562, 'ffn_dropout': 0.2073819204835327, 'lr': 0.0017492735615692344, 'weight_decay': 0.0023623967295935363, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 22:48:33,658] Trial 24 pruned. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.422535 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.2397898644805776, 'ffn_dropout': 0.13043230853213322, 'lr': 0.0020728845123684295, 'weight_decay': 0.0024919705179691502, 'batch_size': 256} - Best Value (CSI): 0.500107 - Best Trial: 14 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2776549176345562, 'ffn_dropout': 0.2073819204835327, 'lr': 0.0017492735615692344, 'weight_decay': 0.0023623967295935363, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 22:50:19,699] Trial 25 finished with value: 0.44927154165643507 and parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.26062758267942754, 'ffn_dropout': 0.12948723936417045, 'lr': 0.0045272217475245905, 'weight_decay': 0.0014046972618234252, 'batch_size': 256}. Best is trial 14 with value: 0.5001066701078627. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.449272 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.26062758267942754, 'ffn_dropout': 0.12948723936417045, 'lr': 0.0045272217475245905, 'weight_decay': 0.0014046972618234252, 'batch_size': 256} - Best Value (CSI): 0.500107 - Best Trial: 14 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2776549176345562, 'ffn_dropout': 0.2073819204835327, 'lr': 0.0017492735615692344, 'weight_decay': 0.0023623967295935363, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 22:51:23,375] Trial 26 pruned. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.486907 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.19537457846352377, 'ffn_dropout': 0.19950138967902994, 'lr': 0.001139501246004423, 'weight_decay': 0.0034806737502214805, 'batch_size': 128} - Best Value (CSI): 0.500107 - Best Trial: 14 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2776549176345562, 'ffn_dropout': 0.2073819204835327, 'lr': 0.0017492735615692344, 'weight_decay': 0.0023623967295935363, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 22:52:10,669] Trial 27 pruned. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.073201 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2300903455113604, 'ffn_dropout': 0.16057503887382626, 'lr': 0.009932825092885943, 'weight_decay': 0.0012032312597511328, 'batch_size': 32} - Best Value (CSI): 0.500107 - Best Trial: 14 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2776549176345562, 'ffn_dropout': 0.2073819204835327, 'lr': 0.0017492735615692344, 'weight_decay': 0.0023623967295935363, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 22:52:42,735] Trial 28 pruned. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.393462 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2831612792151492, 'ffn_dropout': 0.188045527953837, 'lr': 0.0026549374073146685, 'weight_decay': 0.011642809062383366, 'batch_size': 64} - Best Value (CSI): 0.500107 - Best Trial: 14 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2776549176345562, 'ffn_dropout': 0.2073819204835327, 'lr': 0.0017492735615692344, 'weight_decay': 0.0023623967295935363, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 22:54:46,905] Trial 29 finished with value: 0.49754604321956447 and parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.19493447109604495, 'ffn_dropout': 0.22307411149666334, 'lr': 0.0005505583305283389, 'weight_decay': 0.0033284605779323436, 'batch_size': 64}. Best is trial 14 with value: 0.5001066701078627. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.497546 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.19493447109604495, 'ffn_dropout': 0.22307411149666334, 'lr': 0.0005505583305283389, 'weight_decay': 0.0033284605779323436, 'batch_size': 64} - Best Value (CSI): 0.500107 - Best Trial: 14 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2776549176345562, 'ffn_dropout': 0.2073819204835327, 'lr': 0.0017492735615692344, 'weight_decay': 0.0023623967295935363, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 22:55:33,173] Trial 30 pruned. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.366629 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.1726057958392631, 'ffn_dropout': 0.22227277625174308, 'lr': 0.0005672156835071591, 'weight_decay': 0.0024937014614530477, 'batch_size': 64} - Best Value (CSI): 0.500107 - Best Trial: 14 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2776549176345562, 'ffn_dropout': 0.2073819204835327, 'lr': 0.0017492735615692344, 'weight_decay': 0.0023623967295935363, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 22:56:16,556] Trial 31 pruned. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.390156 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.1908205918905234, 'ffn_dropout': 0.18869333030522734, 'lr': 0.001036010040708237, 'weight_decay': 0.003307410563802071, 'batch_size': 64} - Best Value (CSI): 0.500107 - Best Trial: 14 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2776549176345562, 'ffn_dropout': 0.2073819204835327, 'lr': 0.0017492735615692344, 'weight_decay': 0.0023623967295935363, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 22:58:09,974] Trial 32 finished with value: 0.4977312410829639 and parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.213740741544501, 'ffn_dropout': 0.21845009975877583, 'lr': 0.0015630138398552303, 'weight_decay': 0.000685523600920735, 'batch_size': 64}. Best is trial 14 with value: 0.5001066701078627. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.497731 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.213740741544501, 'ffn_dropout': 0.21845009975877583, 'lr': 0.0015630138398552303, 'weight_decay': 0.000685523600920735, 'batch_size': 64} - Best Value (CSI): 0.500107 - Best Trial: 14 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2776549176345562, 'ffn_dropout': 0.2073819204835327, 'lr': 0.0017492735615692344, 'weight_decay': 0.0023623967295935363, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 22:58:42,439] Trial 33 pruned. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.414141 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2150945389082463, 'ffn_dropout': 0.23794295415084643, 'lr': 0.0004688807992686707, 'weight_decay': 0.0006928205565085322, 'batch_size': 64} - Best Value (CSI): 0.500107 - Best Trial: 14 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2776549176345562, 'ffn_dropout': 0.2073819204835327, 'lr': 0.0017492735615692344, 'weight_decay': 0.0023623967295935363, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 22:59:15,656] Trial 34 pruned. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.409389 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.1728383002676006, 'ffn_dropout': 0.21209568802467998, 'lr': 0.0010771337309337828, 'weight_decay': 0.00044604722818240313, 'batch_size': 64} - Best Value (CSI): 0.500107 - Best Trial: 14 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2776549176345562, 'ffn_dropout': 0.2073819204835327, 'lr': 0.0017492735615692344, 'weight_decay': 0.0023623967295935363, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 22:59:47,944] Trial 35 pruned. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.429796 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.15095830209416888, 'ffn_dropout': 0.22023469521178715, 'lr': 0.00022651010646390513, 'weight_decay': 0.0016052441684229095, 'batch_size': 64} - Best Value (CSI): 0.500107 - Best Trial: 14 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2776549176345562, 'ffn_dropout': 0.2073819204835327, 'lr': 0.0017492735615692344, 'weight_decay': 0.0023623967295935363, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:00:08,853] Trial 36 pruned. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.307292 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.236865488044541, 'ffn_dropout': 0.23155622008342217, 'lr': 0.0014689681811972863, 'weight_decay': 0.0003402551144924845, 'batch_size': 64} - Best Value (CSI): 0.500107 - Best Trial: 14 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2776549176345562, 'ffn_dropout': 0.2073819204835327, 'lr': 0.0017492735615692344, 'weight_decay': 0.0023623967295935363, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:00:25,441] Trial 37 pruned. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.031587 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.21893104835569907, 'ffn_dropout': 0.25423999387034074, 'lr': 0.005564802285039306, 'weight_decay': 0.0007982851563507056, 'batch_size': 64} - Best Value (CSI): 0.500107 - Best Trial: 14 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2776549176345562, 'ffn_dropout': 0.2073819204835327, 'lr': 0.0017492735615692344, 'weight_decay': 0.0023623967295935363, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:01:06,659] Trial 38 pruned. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.390960 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.18716410839842074, 'ffn_dropout': 0.19415345710592774, 'lr': 0.000701048579507398, 'weight_decay': 0.0013409891742012228, 'batch_size': 64} - Best Value (CSI): 0.500107 - Best Trial: 14 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2776549176345562, 'ffn_dropout': 0.2073819204835327, 'lr': 0.0017492735615692344, 'weight_decay': 0.0023623967295935363, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:01:37,065] Trial 39 pruned. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.086041 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2516404130694109, 'ffn_dropout': 0.2341006969713482, 'lr': 0.006431610382192338, 'weight_decay': 0.0006515579176368732, 'batch_size': 32} - Best Value (CSI): 0.500107 - Best Trial: 14 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2776549176345562, 'ffn_dropout': 0.2073819204835327, 'lr': 0.0017492735615692344, 'weight_decay': 0.0023623967295935363, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:01:58,490] Trial 40 pruned. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2269692653532709, 'ffn_dropout': 0.20679215181105004, 'lr': 0.0029838890416435905, 'weight_decay': 0.0009798599700912216, 'batch_size': 64} - Best Value (CSI): 0.500107 - Best Trial: 14 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2776549176345562, 'ffn_dropout': 0.2073819204835327, 'lr': 0.0017492735615692344, 'weight_decay': 0.0023623967295935363, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 23:02:50,876] Trial 41 finished with value: 0.49817309664825915 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.18640263261436377, 'ffn_dropout': 0.16122032663611224, 'lr': 0.0021231277257470946, 'weight_decay': 0.01688572475573524, 'batch_size': 256}. Best is trial 14 with value: 0.5001066701078627. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.498173 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.18640263261436377, 'ffn_dropout': 0.16122032663611224, 'lr': 0.0021231277257470946, 'weight_decay': 0.01688572475573524, 'batch_size': 256} - Best Value (CSI): 0.500107 - Best Trial: 14 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2776549176345562, 'ffn_dropout': 0.2073819204835327, 'lr': 0.0017492735615692344, 'weight_decay': 0.0023623967295935363, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:03:15,624] Trial 42 pruned. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.365269 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.15405778746423404, 'ffn_dropout': 0.17952606619386152, 'lr': 0.0017890333818619064, 'weight_decay': 0.018635011852634466, 'batch_size': 256} - Best Value (CSI): 0.500107 - Best Trial: 14 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2776549176345562, 'ffn_dropout': 0.2073819204835327, 'lr': 0.0017492735615692344, 'weight_decay': 0.0023623967295935363, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:03:43,095] Trial 43 pruned. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.389850 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.17920659778666367, 'ffn_dropout': 0.17051235941910464, 'lr': 0.0009233631758119583, 'weight_decay': 0.004776348210741444, 'batch_size': 128} - Best Value (CSI): 0.500107 - Best Trial: 14 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2776549176345562, 'ffn_dropout': 0.2073819204835327, 'lr': 0.0017492735615692344, 'weight_decay': 0.0023623967295935363, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:03:58,880] Trial 44 pruned. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.376993 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.16455219603813523, 'ffn_dropout': 0.16287670978236635, 'lr': 0.0012632386144249806, 'weight_decay': 0.030895530146561694, 'batch_size': 256} - Best Value (CSI): 0.500107 - Best Trial: 14 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2776549176345562, 'ffn_dropout': 0.2073819204835327, 'lr': 0.0017492735615692344, 'weight_decay': 0.0023623967295935363, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 23:04:53,331] Trial 45 finished with value: 0.48428792236162393 and parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.13693275726090168, 'ffn_dropout': 0.19167065155210405, 'lr': 0.002039887112659745, 'weight_decay': 0.007738404653461596, 'batch_size': 256}. Best is trial 14 with value: 0.5001066701078627. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.484288 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.13693275726090168, 'ffn_dropout': 0.19167065155210405, 'lr': 0.002039887112659745, 'weight_decay': 0.007738404653461596, 'batch_size': 256} - Best Value (CSI): 0.500107 - Best Trial: 14 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2776549176345562, 'ffn_dropout': 0.2073819204835327, 'lr': 0.0017492735615692344, 'weight_decay': 0.0023623967295935363, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:05:32,389] Trial 46 pruned. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2123719000500617, 'ffn_dropout': 0.2066227968338971, 'lr': 0.0032340357024603144, 'weight_decay': 0.001764298779913322, 'batch_size': 32} - Best Value (CSI): 0.500107 - Best Trial: 14 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2776549176345562, 'ffn_dropout': 0.2073819204835327, 'lr': 0.0017492735615692344, 'weight_decay': 0.0023623967295935363, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:05:50,406] Trial 47 pruned. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.353482 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.1818014109171604, 'ffn_dropout': 0.2489586538881031, 'lr': 0.004710573705223361, 'weight_decay': 0.0002958088423358973, 'batch_size': 256} - Best Value (CSI): 0.500107 - Best Trial: 14 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2776549176345562, 'ffn_dropout': 0.2073819204835327, 'lr': 0.0017492735615692344, 'weight_decay': 0.0023623967295935363, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:06:23,454] Trial 48 pruned. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.403670 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.20911044808136287, 'ffn_dropout': 0.10067260791044297, 'lr': 0.0014452556494008153, 'weight_decay': 0.0005064115797420447, 'batch_size': 64} - Best Value (CSI): 0.500107 - Best Trial: 14 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2776549176345562, 'ffn_dropout': 0.2073819204835327, 'lr': 0.0017492735615692344, 'weight_decay': 0.0023623967295935363, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 23:07:22,437] Trial 49 finished with value: 0.500955876255065 and parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22595662460184046, 'ffn_dropout': 0.18072426018543497, 'lr': 0.00233421501453318, 'weight_decay': 0.0001873978639928311, 'batch_size': 256}. Best is trial 49 with value: 0.500955876255065. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.500956 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22595662460184046, 'ffn_dropout': 0.18072426018543497, 'lr': 0.00233421501453318, 'weight_decay': 0.0001873978639928311, 'batch_size': 256} - Best Value (CSI): 0.500956 - Best Trial: 49 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22595662460184046, 'ffn_dropout': 0.18072426018543497, 'lr': 0.00233421501453318, 'weight_decay': 0.0001873978639928311, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) -[I 2025-12-28 23:08:07,882] Trial 50 pruned. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.493480 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.18237838074463372, 'ffn_dropout': 0.18241034624732622, 'lr': 0.0006746426196008369, 'weight_decay': 0.00014618701761166458, 'batch_size': 128} - Best Value (CSI): 0.500956 - Best Trial: 49 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22595662460184046, 'ffn_dropout': 0.18072426018543497, 'lr': 0.00233421501453318, 'weight_decay': 0.0001873978639928311, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:08:29,345] Trial 51 pruned. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.374562 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22169374723206992, 'ffn_dropout': 0.1997662848958918, 'lr': 0.002503010590667555, 'weight_decay': 0.00021551991169730015, 'batch_size': 256} - Best Value (CSI): 0.500956 - Best Trial: 49 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22595662460184046, 'ffn_dropout': 0.18072426018543497, 'lr': 0.00233421501453318, 'weight_decay': 0.0001873978639928311, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:08:41,508] Trial 52 pruned. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.24634900278319083, 'ffn_dropout': 0.15436805724223415, 'lr': 0.003347029659416572, 'weight_decay': 0.0001706727222444742, 'batch_size': 256} - Best Value (CSI): 0.500956 - Best Trial: 49 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22595662460184046, 'ffn_dropout': 0.18072426018543497, 'lr': 0.00233421501453318, 'weight_decay': 0.0001873978639928311, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 23:09:23,421] Trial 53 finished with value: 0.48762834509332986 and parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2660804679686664, 'ffn_dropout': 0.16827319909748595, 'lr': 0.0017567766402478964, 'weight_decay': 0.0002329108103257573, 'batch_size': 256}. Best is trial 49 with value: 0.500955876255065. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.487628 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2660804679686664, 'ffn_dropout': 0.16827319909748595, 'lr': 0.0017567766402478964, 'weight_decay': 0.0002329108103257573, 'batch_size': 256} - Best Value (CSI): 0.500956 - Best Trial: 49 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22595662460184046, 'ffn_dropout': 0.18072426018543497, 'lr': 0.00233421501453318, 'weight_decay': 0.0001873978639928311, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:09:47,208] Trial 54 pruned. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.041186 - Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.2028991447901797, 'ffn_dropout': 0.17842433038241115, 'lr': 0.0025439054955018296, 'weight_decay': 0.0003705109855800235, 'batch_size': 256} - Best Value (CSI): 0.500956 - Best Trial: 49 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22595662460184046, 'ffn_dropout': 0.18072426018543497, 'lr': 0.00233421501453318, 'weight_decay': 0.0001873978639928311, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:10:10,040] Trial 55 pruned. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.420225 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.23113495377384968, 'ffn_dropout': 0.2180161264745915, 'lr': 0.0012579888210722666, 'weight_decay': 0.000551238644273327, 'batch_size': 256} - Best Value (CSI): 0.500956 - Best Trial: 49 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22595662460184046, 'ffn_dropout': 0.18072426018543497, 'lr': 0.00233421501453318, 'weight_decay': 0.0001873978639928311, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:10:23,595] Trial 56 pruned. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.446833 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.23852137461664685, 'ffn_dropout': 0.15358530662157838, 'lr': 0.0008800414174104112, 'weight_decay': 0.0008745308747049414, 'batch_size': 256} - Best Value (CSI): 0.500956 - Best Trial: 49 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22595662460184046, 'ffn_dropout': 0.18072426018543497, 'lr': 0.00233421501453318, 'weight_decay': 0.0001873978639928311, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:10:54,040] Trial 57 pruned. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.363286 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.2051821731821433, 'ffn_dropout': 0.1919634291113097, 'lr': 0.0037707014017494696, 'weight_decay': 0.0011724753850994264, 'batch_size': 256} - Best Value (CSI): 0.500956 - Best Trial: 49 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22595662460184046, 'ffn_dropout': 0.18072426018543497, 'lr': 0.00233421501453318, 'weight_decay': 0.0001873978639928311, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:11:05,544] Trial 58 pruned. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.419522 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2728658092886924, 'ffn_dropout': 0.13648294079132645, 'lr': 0.0022405748605553435, 'weight_decay': 0.0021725687202815945, 'batch_size': 256} - Best Value (CSI): 0.500956 - Best Trial: 49 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22595662460184046, 'ffn_dropout': 0.18072426018543497, 'lr': 0.00233421501453318, 'weight_decay': 0.0001873978639928311, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:12:24,228] Trial 59 pruned. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.373541 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.22255961472236965, 'ffn_dropout': 0.1180496420466749, 'lr': 0.0017377240801767912, 'weight_decay': 0.06425982092571389, 'batch_size': 32} - Best Value (CSI): 0.500956 - Best Trial: 49 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22595662460184046, 'ffn_dropout': 0.18072426018543497, 'lr': 0.00233421501453318, 'weight_decay': 0.0001873978639928311, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:12:49,419] Trial 60 pruned. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.25535433708338734, 'ffn_dropout': 0.1596546884928284, 'lr': 0.005710100780388977, 'weight_decay': 0.004482614877122853, 'batch_size': 64} - Best Value (CSI): 0.500956 - Best Trial: 49 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22595662460184046, 'ffn_dropout': 0.18072426018543497, 'lr': 0.00233421501453318, 'weight_decay': 0.0001873978639928311, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 23:14:00,627] Trial 61 finished with value: 0.5013875965799505 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19828426115038106, 'ffn_dropout': 0.14321602580528056, 'lr': 0.00218720274175351, 'weight_decay': 0.01739688286070899, 'batch_size': 256}. Best is trial 61 with value: 0.5013875965799505. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.501388 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19828426115038106, 'ffn_dropout': 0.14321602580528056, 'lr': 0.00218720274175351, 'weight_decay': 0.01739688286070899, 'batch_size': 256} - Best Value (CSI): 0.501388 - Best Trial: 61 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19828426115038106, 'ffn_dropout': 0.14321602580528056, 'lr': 0.00218720274175351, 'weight_decay': 0.01739688286070899, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:14:28,318] Trial 62 pruned. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.398437 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.19010527013785894, 'ffn_dropout': 0.14760021593643738, 'lr': 0.003077712132696288, 'weight_decay': 0.007637730361597706, 'batch_size': 256} - Best Value (CSI): 0.501388 - Best Trial: 61 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19828426115038106, 'ffn_dropout': 0.14321602580528056, 'lr': 0.00218720274175351, 'weight_decay': 0.01739688286070899, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:14:51,083] Trial 63 pruned. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.368485 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19575346235661628, 'ffn_dropout': 0.17475242560346416, 'lr': 0.0020275501504749965, 'weight_decay': 0.023683198811449067, 'batch_size': 256} - Best Value (CSI): 0.501388 - Best Trial: 61 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19828426115038106, 'ffn_dropout': 0.14321602580528056, 'lr': 0.00218720274175351, 'weight_decay': 0.01739688286070899, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:15:10,648] Trial 64 pruned. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.420086 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2121005009887643, 'ffn_dropout': 0.16105245272359592, 'lr': 0.0014743737567357983, 'weight_decay': 0.016293260584767866, 'batch_size': 256} - Best Value (CSI): 0.501388 - Best Trial: 61 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19828426115038106, 'ffn_dropout': 0.14321602580528056, 'lr': 0.00218720274175351, 'weight_decay': 0.01739688286070899, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 23:16:06,791] Trial 65 finished with value: 0.49243876298257144 and parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.23437717998982613, 'ffn_dropout': 0.13842942804786482, 'lr': 0.004573049662470003, 'weight_decay': 0.009957506837230588, 'batch_size': 256}. Best is trial 61 with value: 0.5013875965799505. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.492439 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.23437717998982613, 'ffn_dropout': 0.13842942804786482, 'lr': 0.004573049662470003, 'weight_decay': 0.009957506837230588, 'batch_size': 256} - Best Value (CSI): 0.501388 - Best Trial: 61 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19828426115038106, 'ffn_dropout': 0.14321602580528056, 'lr': 0.00218720274175351, 'weight_decay': 0.01739688286070899, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:16:34,319] Trial 66 pruned. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.370513 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.16863935092390567, 'ffn_dropout': 0.21209372533464382, 'lr': 0.0024983669923680893, 'weight_decay': 0.0032279442840474847, 'batch_size': 128} - Best Value (CSI): 0.501388 - Best Trial: 61 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19828426115038106, 'ffn_dropout': 0.14321602580528056, 'lr': 0.00218720274175351, 'weight_decay': 0.01739688286070899, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:16:49,633] Trial 67 pruned. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.451302 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24485946320396842, 'ffn_dropout': 0.1846905801480751, 'lr': 0.0009713380634149733, 'weight_decay': 0.002516826681300192, 'batch_size': 256} - Best Value (CSI): 0.501388 - Best Trial: 61 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19828426115038106, 'ffn_dropout': 0.14321602580528056, 'lr': 0.00218720274175351, 'weight_decay': 0.01739688286070899, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:17:10,512] Trial 68 pruned. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.20076063842224695, 'ffn_dropout': 0.1989018766916691, 'lr': 0.007243659623447381, 'weight_decay': 0.0061993348443998356, 'batch_size': 64} - Best Value (CSI): 0.501388 - Best Trial: 61 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19828426115038106, 'ffn_dropout': 0.14321602580528056, 'lr': 0.00218720274175351, 'weight_decay': 0.01739688286070899, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:17:18,206] Trial 69 pruned. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.286802 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.22060617322167925, 'ffn_dropout': 0.22862580006854297, 'lr': 0.003595391780531467, 'weight_decay': 0.0015018084403389516, 'batch_size': 256} - Best Value (CSI): 0.501388 - Best Trial: 61 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19828426115038106, 'ffn_dropout': 0.14321602580528056, 'lr': 0.00218720274175351, 'weight_decay': 0.01739688286070899, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:18:07,973] Trial 70 pruned. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.421348 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1888613183262093, 'ffn_dropout': 0.16913271178644232, 'lr': 0.0012918841753341076, 'weight_decay': 0.0006448145777512577, 'batch_size': 64} - Best Value (CSI): 0.501388 - Best Trial: 61 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19828426115038106, 'ffn_dropout': 0.14321602580528056, 'lr': 0.00218720274175351, 'weight_decay': 0.01739688286070899, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 23:19:30,194] Trial 71 finished with value: 0.4947363505746171 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.204744852458924, 'ffn_dropout': 0.1279721805878679, 'lr': 0.002207732032827607, 'weight_decay': 0.014266081446455367, 'batch_size': 256}. Best is trial 61 with value: 0.5013875965799505. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.494736 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.204744852458924, 'ffn_dropout': 0.1279721805878679, 'lr': 0.002207732032827607, 'weight_decay': 0.014266081446455367, 'batch_size': 256} - Best Value (CSI): 0.501388 - Best Trial: 61 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19828426115038106, 'ffn_dropout': 0.14321602580528056, 'lr': 0.00218720274175351, 'weight_decay': 0.01739688286070899, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:19:52,900] Trial 72 pruned. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.427796 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2055131802182044, 'ffn_dropout': 0.12634896266696083, 'lr': 0.0017526736307685773, 'weight_decay': 0.013824169046047932, 'batch_size': 256} - Best Value (CSI): 0.501388 - Best Trial: 61 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19828426115038106, 'ffn_dropout': 0.14321602580528056, 'lr': 0.00218720274175351, 'weight_decay': 0.01739688286070899, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:20:20,524] Trial 73 pruned. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.351582 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.22946151257017075, 'ffn_dropout': 0.11830708485933376, 'lr': 0.002298997694773247, 'weight_decay': 0.009110737014005034, 'batch_size': 256} - Best Value (CSI): 0.501388 - Best Trial: 61 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19828426115038106, 'ffn_dropout': 0.14321602580528056, 'lr': 0.00218720274175351, 'weight_decay': 0.01739688286070899, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 23:21:33,657] Trial 74 finished with value: 0.4992919156401956 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1782984853538817, 'ffn_dropout': 0.11022349336541981, 'lr': 0.0028451960181233504, 'weight_decay': 0.018193450041975326, 'batch_size': 256}. Best is trial 61 with value: 0.5013875965799505. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.499292 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1782984853538817, 'ffn_dropout': 0.11022349336541981, 'lr': 0.0028451960181233504, 'weight_decay': 0.018193450041975326, 'batch_size': 256} - Best Value (CSI): 0.501388 - Best Trial: 61 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19828426115038106, 'ffn_dropout': 0.14321602580528056, 'lr': 0.00218720274175351, 'weight_decay': 0.01739688286070899, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:21:55,602] Trial 75 pruned. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.397770 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1808859444528016, 'ffn_dropout': 0.14415345476015878, 'lr': 0.002765941830488035, 'weight_decay': 0.018043506549232913, 'batch_size': 256} - Best Value (CSI): 0.501388 - Best Trial: 61 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19828426115038106, 'ffn_dropout': 0.14321602580528056, 'lr': 0.00218720274175351, 'weight_decay': 0.01739688286070899, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:22:05,961] Trial 76 pruned. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.17328298467210929, 'ffn_dropout': 0.11024934012463894, 'lr': 0.005275484331557514, 'weight_decay': 0.021463794992675374, 'batch_size': 256} - Best Value (CSI): 0.501388 - Best Trial: 61 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19828426115038106, 'ffn_dropout': 0.14321602580528056, 'lr': 0.00218720274175351, 'weight_decay': 0.01739688286070899, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:22:46,418] Trial 77 pruned. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.367901 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.16099482551181665, 'ffn_dropout': 0.15297353488863297, 'lr': 0.00107676655962284, 'weight_decay': 0.03433704916529691, 'batch_size': 64} - Best Value (CSI): 0.501388 - Best Trial: 61 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19828426115038106, 'ffn_dropout': 0.14321602580528056, 'lr': 0.00218720274175351, 'weight_decay': 0.01739688286070899, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:23:46,806] Trial 78 pruned. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.396396 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2152702302087926, 'ffn_dropout': 0.10883553954662918, 'lr': 0.003961185454049697, 'weight_decay': 0.02740645980795988, 'batch_size': 32} - Best Value (CSI): 0.501388 - Best Trial: 61 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19828426115038106, 'ffn_dropout': 0.14321602580528056, 'lr': 0.00218720274175351, 'weight_decay': 0.01739688286070899, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:24:02,826] Trial 79 pruned. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.405952 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19532442842301123, 'ffn_dropout': 0.1375330036783151, 'lr': 0.002976880384000001, 'weight_decay': 0.011997044104301618, 'batch_size': 256} - Best Value (CSI): 0.501388 - Best Trial: 61 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19828426115038106, 'ffn_dropout': 0.14321602580528056, 'lr': 0.00218720274175351, 'weight_decay': 0.01739688286070899, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 23:25:28,743] Trial 80 finished with value: 0.4980693078653548 and parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22449747582521493, 'ffn_dropout': 0.20669896978515856, 'lr': 0.0007957641965844268, 'weight_decay': 0.048889848942813015, 'batch_size': 128}. Best is trial 61 with value: 0.5013875965799505. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.498069 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22449747582521493, 'ffn_dropout': 0.20669896978515856, 'lr': 0.0007957641965844268, 'weight_decay': 0.048889848942813015, 'batch_size': 128} - Best Value (CSI): 0.501388 - Best Trial: 61 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19828426115038106, 'ffn_dropout': 0.14321602580528056, 'lr': 0.00218720274175351, 'weight_decay': 0.01739688286070899, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:25:56,471] Trial 81 pruned. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.423651 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22405046939496254, 'ffn_dropout': 0.21108138290965373, 'lr': 0.0014897288499596763, 'weight_decay': 0.0475172208698025, 'batch_size': 128} - Best Value (CSI): 0.501388 - Best Trial: 61 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19828426115038106, 'ffn_dropout': 0.14321602580528056, 'lr': 0.00218720274175351, 'weight_decay': 0.01739688286070899, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:26:24,234] Trial 82 pruned. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.372842 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.24944695749258378, 'ffn_dropout': 0.2026586865779086, 'lr': 0.0006114274682924321, 'weight_decay': 0.043004622805300624, 'batch_size': 128} - Best Value (CSI): 0.501388 - Best Trial: 61 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19828426115038106, 'ffn_dropout': 0.14321602580528056, 'lr': 0.00218720274175351, 'weight_decay': 0.01739688286070899, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 23:27:48,456] Trial 83 finished with value: 0.486987919595208 and parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.24078883891391925, 'ffn_dropout': 0.22153739027121797, 'lr': 0.000767517958336242, 'weight_decay': 0.023627084385686687, 'batch_size': 128}. Best is trial 61 with value: 0.5013875965799505. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.486988 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.24078883891391925, 'ffn_dropout': 0.22153739027121797, 'lr': 0.000767517958336242, 'weight_decay': 0.023627084385686687, 'batch_size': 128} - Best Value (CSI): 0.501388 - Best Trial: 61 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19828426115038106, 'ffn_dropout': 0.14321602580528056, 'lr': 0.00218720274175351, 'weight_decay': 0.01739688286070899, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 23:29:11,066] Trial 84 finished with value: 0.5052817328725289 and parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21128609103276186, 'ffn_dropout': 0.18610731195171396, 'lr': 0.0019139767886005993, 'weight_decay': 0.03127877612669642, 'batch_size': 128}. Best is trial 84 with value: 0.5052817328725289. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.505282 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21128609103276186, 'ffn_dropout': 0.18610731195171396, 'lr': 0.0019139767886005993, 'weight_decay': 0.03127877612669642, 'batch_size': 128} - Best Value (CSI): 0.505282 - Best Trial: 84 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21128609103276186, 'ffn_dropout': 0.18610731195171396, 'lr': 0.0019139767886005993, 'weight_decay': 0.03127877612669642, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 23:30:14,199] Trial 85 pruned. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.486239 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21364624203038216, 'ffn_dropout': 0.1869596517584163, 'lr': 0.0019142264955753193, 'weight_decay': 0.027011044901116082, 'batch_size': 128} - Best Value (CSI): 0.505282 - Best Trial: 84 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21128609103276186, 'ffn_dropout': 0.18610731195171396, 'lr': 0.0019139767886005993, 'weight_decay': 0.03127877612669642, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 23:31:28,310] Trial 86 finished with value: 0.4937566261594135 and parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.1950396127127738, 'ffn_dropout': 0.195164433568025, 'lr': 0.0008970031661372964, 'weight_decay': 0.03265615515284464, 'batch_size': 128}. Best is trial 84 with value: 0.5052817328725289. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.493757 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.1950396127127738, 'ffn_dropout': 0.195164433568025, 'lr': 0.0008970031661372964, 'weight_decay': 0.03265615515284464, 'batch_size': 128} - Best Value (CSI): 0.505282 - Best Trial: 84 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21128609103276186, 'ffn_dropout': 0.18610731195171396, 'lr': 0.0019139767886005993, 'weight_decay': 0.03127877612669642, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) -[I 2025-12-28 23:32:01,311] Trial 87 pruned. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.481964 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.17716180990839395, 'ffn_dropout': 0.20606298319351526, 'lr': 0.0011609782029478946, 'weight_decay': 0.0038968153664484958, 'batch_size': 128} - Best Value (CSI): 0.505282 - Best Trial: 84 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21128609103276186, 'ffn_dropout': 0.18610731195171396, 'lr': 0.0019139767886005993, 'weight_decay': 0.03127877612669642, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:32:20,059] Trial 88 pruned. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.18547118031728013, 'ffn_dropout': 0.17562652152681163, 'lr': 0.0016406679962412021, 'weight_decay': 0.019400778821703775, 'batch_size': 128} - Best Value (CSI): 0.505282 - Best Trial: 84 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21128609103276186, 'ffn_dropout': 0.18610731195171396, 'lr': 0.0019139767886005993, 'weight_decay': 0.03127877612669642, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:32:43,045] Trial 89 pruned. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.407119 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.20803433905130264, 'ffn_dropout': 0.24025994211830787, 'lr': 0.0005441178548353954, 'weight_decay': 0.05125926990384529, 'batch_size': 128} - Best Value (CSI): 0.505282 - Best Trial: 84 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21128609103276186, 'ffn_dropout': 0.18610731195171396, 'lr': 0.0019139767886005993, 'weight_decay': 0.03127877612669642, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 23:33:40,971] Trial 90 finished with value: 0.4948383962339948 and parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.19986354036801487, 'ffn_dropout': 0.18580076009483934, 'lr': 0.0007811522916767445, 'weight_decay': 0.005678587648692619, 'batch_size': 128}. Best is trial 84 with value: 0.5052817328725289. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.494838 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.19986354036801487, 'ffn_dropout': 0.18580076009483934, 'lr': 0.0007811522916767445, 'weight_decay': 0.005678587648692619, 'batch_size': 128} - Best Value (CSI): 0.505282 - Best Trial: 84 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21128609103276186, 'ffn_dropout': 0.18610731195171396, 'lr': 0.0019139767886005993, 'weight_decay': 0.03127877612669642, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:34:21,964] Trial 91 pruned. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.388398 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.23150336371131483, 'ffn_dropout': 0.1676580515506743, 'lr': 0.0028960759873974855, 'weight_decay': 0.039881485037680464, 'batch_size': 64} - Best Value (CSI): 0.505282 - Best Trial: 84 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21128609103276186, 'ffn_dropout': 0.18610731195171396, 'lr': 0.0019139767886005993, 'weight_decay': 0.03127877612669642, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:34:40,474] Trial 92 pruned. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.383220 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21752452045176462, 'ffn_dropout': 0.1799835538959502, 'lr': 0.0019529870047801138, 'weight_decay': 0.0008628585887442941, 'batch_size': 256} - Best Value (CSI): 0.505282 - Best Trial: 84 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21128609103276186, 'ffn_dropout': 0.18610731195171396, 'lr': 0.0019139767886005993, 'weight_decay': 0.03127877612669642, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:34:50,654] Trial 93 pruned. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.405192 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22647814851654224, 'ffn_dropout': 0.19809027820887315, 'lr': 0.0013274499678661198, 'weight_decay': 0.09787615428518671, 'batch_size': 256} - Best Value (CSI): 0.505282 - Best Trial: 84 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21128609103276186, 'ffn_dropout': 0.18610731195171396, 'lr': 0.0019139767886005993, 'weight_decay': 0.03127877612669642, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:35:15,940] Trial 94 pruned. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.18940042688901407, 'ffn_dropout': 0.22490778790388583, 'lr': 0.003389406033099836, 'weight_decay': 0.0003922349133094853, 'batch_size': 64} - Best Value (CSI): 0.505282 - Best Trial: 84 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21128609103276186, 'ffn_dropout': 0.18610731195171396, 'lr': 0.0019139767886005993, 'weight_decay': 0.03127877612669642, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.241657571849059, 1: 1.0691727182115904, 2: 0.7940778341793571} (클래스별 샘플 수: {0: 10079, 1: 11705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.2451165721487083, 1: 1.1027109583810615, 2: 0.7751899570531879} (클래스별 샘플 수: {0: 10051, 1: 11349, 2: 16144}) -[I 2025-12-28 23:36:02,227] Trial 95 finished with value: 0.4957523957124577 and parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.23801731382579366, 'ffn_dropout': 0.2171479623425568, 'lr': 0.001564709525674296, 'weight_decay': 0.01602921456848865, 'batch_size': 256}. Best is trial 84 with value: 0.5052817328725289. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.495752 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.23801731382579366, 'ffn_dropout': 0.2171479623425568, 'lr': 0.001564709525674296, 'weight_decay': 0.01602921456848865, 'batch_size': 256} - Best Value (CSI): 0.505282 - Best Trial: 84 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21128609103276186, 'ffn_dropout': 0.18610731195171396, 'lr': 0.0019139767886005993, 'weight_decay': 0.03127877612669642, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:36:41,081] Trial 96 pruned. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2081682559647492, 'ffn_dropout': 0.1916114404057045, 'lr': 0.002457280668526897, 'weight_decay': 0.0011541661753339553, 'batch_size': 32} - Best Value (CSI): 0.505282 - Best Trial: 84 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21128609103276186, 'ffn_dropout': 0.18610731195171396, 'lr': 0.0019139767886005993, 'weight_decay': 0.03127877612669642, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:36:55,064] Trial 97 pruned. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.034229 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2177110385364753, 'ffn_dropout': 0.211113230930637, 'lr': 0.004208437356842814, 'weight_decay': 0.021110179156677178, 'batch_size': 256} - Best Value (CSI): 0.505282 - Best Trial: 84 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21128609103276186, 'ffn_dropout': 0.18610731195171396, 'lr': 0.0019139767886005993, 'weight_decay': 0.03127877612669642, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:37:45,541] Trial 98 pruned. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.395466 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.25538258180866397, 'ffn_dropout': 0.18080055269367168, 'lr': 0.0021568035159304625, 'weight_decay': 0.00026077864873069, 'batch_size': 64} - Best Value (CSI): 0.505282 - Best Trial: 84 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21128609103276186, 'ffn_dropout': 0.18610731195171396, 'lr': 0.0019139767886005993, 'weight_decay': 0.03127877612669642, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2432074221338636, 1: 1.0627690913210968, 2: 0.7970090916815362} (클래스별 샘플 수: {0: 10060, 1: 11768, 2: 15692}) -[I 2025-12-28 23:38:03,764] Trial 99 pruned. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.414712 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.18436782224804477, 'ffn_dropout': 0.1582756113214427, 'lr': 0.0010440759507552013, 'weight_decay': 0.00031600073662022525, 'batch_size': 256} - Best Value (CSI): 0.505282 - Best Trial: 84 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21128609103276186, 'ffn_dropout': 0.18610731195171396, 'lr': 0.0019139767886005993, 'weight_decay': 0.03127877612669642, 'batch_size': 128} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.5053 -Best Hyperparameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21128609103276186, 'ffn_dropout': 0.18610731195171396, 'lr': 0.0019139767886005993, 'weight_decay': 0.03127877612669642, 'batch_size': 128} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.3036 - - 최종 CSI: 0.4147 - - 최고 CSI: 0.5053 - - 최저 CSI: 0.0000 - - 평균 CSI: 0.3473 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/ft_transformer_ctgan10000_gwangju_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 16, Best CSI: 0.4397 - Fold 1 학습 완료 (검증 CSI: 0.4397) -Fold 2 학습 중... - Early stopping at epoch 26, Best CSI: 0.5254 - Fold 2 학습 완료 (검증 CSI: 0.5254) -Fold 3 학습 중... - Early stopping at epoch 25, Best CSI: 0.5187 - Fold 3 학습 완료 (검증 CSI: 0.5187) - -모든 모델 저장 완료: ../save_model/ft_transformer_optima/ft_transformer_ctgan10000_gwangju.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/ft_transformer_optima/scaler/ft_transformer_ctgan10000_gwangju_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: ../save_model/ft_transformer_optima/ft_transformer_ctgan10000_gwangju.pkl - -✓ 완료: ft_transformer_ctgan10000/ft_transformer_ctgan10000_gwangju.py (소요 시간: 4618초) - ----------------------------------------- -실행 중: ft_transformer_ctgan10000/ft_transformer_ctgan10000_incheon.py -시작 시간: 2025-12-28 23:39:15 ----------------------------------------- -[I 2025-12-28 23:39:17,014] A new study created in memory with name: no-name-a5b67fde-dd1a-4b35-8708-081520102ec1 - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 23:42:23,103] Trial 0 finished with value: 0.5462797172926566 and parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3510578172433737, 'ffn_dropout': 0.3165398010379043, 'lr': 0.0002464326184428672, 'weight_decay': 0.0021581132202383307, 'batch_size': 64}. Best is trial 0 with value: 0.5462797172926566. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.546280 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3510578172433737, 'ffn_dropout': 0.3165398010379043, 'lr': 0.0002464326184428672, 'weight_decay': 0.0021581132202383307, 'batch_size': 64} - Best Value (CSI): 0.546280 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3510578172433737, 'ffn_dropout': 0.3165398010379043, 'lr': 0.0002464326184428672, 'weight_decay': 0.0021581132202383307, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 23:49:36,930] Trial 1 finished with value: 0.5464301254312375 and parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2352796863064692, 'ffn_dropout': 0.36022215897032983, 'lr': 0.0010946082821419853, 'weight_decay': 0.007054410467014514, 'batch_size': 32}. Best is trial 1 with value: 0.5464301254312375. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.546430 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2352796863064692, 'ffn_dropout': 0.36022215897032983, 'lr': 0.0010946082821419853, 'weight_decay': 0.007054410467014514, 'batch_size': 32} - Best Value (CSI): 0.546430 - Best Trial: 1 - Best Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2352796863064692, 'ffn_dropout': 0.36022215897032983, 'lr': 0.0010946082821419853, 'weight_decay': 0.007054410467014514, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 23:52:53,593] Trial 2 finished with value: 0.5176309198936521 and parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.32693833818166396, 'ffn_dropout': 0.3329104229929004, 'lr': 9.531124017565615e-05, 'weight_decay': 0.0014548712158556664, 'batch_size': 64}. Best is trial 1 with value: 0.5464301254312375. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.517631 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.32693833818166396, 'ffn_dropout': 0.3329104229929004, 'lr': 9.531124017565615e-05, 'weight_decay': 0.0014548712158556664, 'batch_size': 64} - Best Value (CSI): 0.546430 - Best Trial: 1 - Best Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2352796863064692, 'ffn_dropout': 0.36022215897032983, 'lr': 0.0010946082821419853, 'weight_decay': 0.007054410467014514, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 23:54:37,223] Trial 3 finished with value: 0.5370048614998882 and parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1744414651718707, 'ffn_dropout': 0.39689610586116497, 'lr': 0.00029908950950459617, 'weight_decay': 0.0014636452494366332, 'batch_size': 64}. Best is trial 1 with value: 0.5464301254312375. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.537005 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1744414651718707, 'ffn_dropout': 0.39689610586116497, 'lr': 0.00029908950950459617, 'weight_decay': 0.0014636452494366332, 'batch_size': 64} - Best Value (CSI): 0.546430 - Best Trial: 1 - Best Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2352796863064692, 'ffn_dropout': 0.36022215897032983, 'lr': 0.0010946082821419853, 'weight_decay': 0.007054410467014514, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-28 23:56:04,086] Trial 4 finished with value: 0.437454940659255 and parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21300642605036968, 'ffn_dropout': 0.1505749801818388, 'lr': 4.7399689186158254e-05, 'weight_decay': 0.01212058668322202, 'batch_size': 128}. Best is trial 1 with value: 0.5464301254312375. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.437455 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21300642605036968, 'ffn_dropout': 0.1505749801818388, 'lr': 4.7399689186158254e-05, 'weight_decay': 0.01212058668322202, 'batch_size': 128} - Best Value (CSI): 0.546430 - Best Trial: 1 - Best Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2352796863064692, 'ffn_dropout': 0.36022215897032983, 'lr': 0.0010946082821419853, 'weight_decay': 0.007054410467014514, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 23:56:21,765] Trial 5 pruned. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.366454 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.17447741332140246, 'ffn_dropout': 0.2452934851930991, 'lr': 2.7897643402814155e-05, 'weight_decay': 0.00047731779370732756, 'batch_size': 64} - Best Value (CSI): 0.546430 - Best Trial: 1 - Best Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2352796863064692, 'ffn_dropout': 0.36022215897032983, 'lr': 0.0010946082821419853, 'weight_decay': 0.007054410467014514, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-28 23:56:30,112] Trial 6 pruned. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.199245 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.10537557476906195, 'ffn_dropout': 0.1410387756704381, 'lr': 5.933039783426547e-05, 'weight_decay': 0.0001072532913548624, 'batch_size': 256} - Best Value (CSI): 0.546430 - Best Trial: 1 - Best Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2352796863064692, 'ffn_dropout': 0.36022215897032983, 'lr': 0.0010946082821419853, 'weight_decay': 0.007054410467014514, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-29 00:02:58,992] Trial 7 finished with value: 0.5482335521221479 and parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.11120869422981193, 'ffn_dropout': 0.12617347554183356, 'lr': 0.00015776266193100045, 'weight_decay': 0.001820829144600586, 'batch_size': 32}. Best is trial 7 with value: 0.5482335521221479. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.548234 - Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.11120869422981193, 'ffn_dropout': 0.12617347554183356, 'lr': 0.00015776266193100045, 'weight_decay': 0.001820829144600586, 'batch_size': 32} - Best Value (CSI): 0.548234 - Best Trial: 7 - Best Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.11120869422981193, 'ffn_dropout': 0.12617347554183356, 'lr': 0.00015776266193100045, 'weight_decay': 0.001820829144600586, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 00:03:19,388] Trial 8 pruned. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.435490 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.24230920279189036, 'ffn_dropout': 0.12438456961443337, 'lr': 2.8385518438793184e-05, 'weight_decay': 0.03309078421669175, 'batch_size': 128} - Best Value (CSI): 0.548234 - Best Trial: 7 - Best Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.11120869422981193, 'ffn_dropout': 0.12617347554183356, 'lr': 0.00015776266193100045, 'weight_decay': 0.001820829144600586, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 00:04:16,260] Trial 9 pruned. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3929595994118318, 'ffn_dropout': 0.3108415177081977, 'lr': 0.002373889830295486, 'weight_decay': 0.00710212083580161, 'batch_size': 32} - Best Value (CSI): 0.548234 - Best Trial: 7 - Best Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.11120869422981193, 'ffn_dropout': 0.12617347554183356, 'lr': 0.00015776266193100045, 'weight_decay': 0.001820829144600586, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 00:05:32,157] Trial 10 pruned. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.147427 - Parameters: {'d_token': 256, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.11972846958028585, 'ffn_dropout': 0.1972941509831399, 'lr': 0.0075603924732496755, 'weight_decay': 0.06883168473442167, 'batch_size': 32} - Best Value (CSI): 0.548234 - Best Trial: 7 - Best Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.11120869422981193, 'ffn_dropout': 0.12617347554183356, 'lr': 0.00015776266193100045, 'weight_decay': 0.001820829144600586, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 00:06:26,273] Trial 11 pruned. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.28976331019395996, 'ffn_dropout': 0.10046102154516451, 'lr': 0.0010957127755507245, 'weight_decay': 0.0067622542171069154, 'batch_size': 32} - Best Value (CSI): 0.548234 - Best Trial: 7 - Best Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.11120869422981193, 'ffn_dropout': 0.12617347554183356, 'lr': 0.00015776266193100045, 'weight_decay': 0.001820829144600586, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 00:07:41,542] Trial 12 pruned. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.099383 - Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.270853924462793, 'ffn_dropout': 0.20096324957038045, 'lr': 0.0007817805141926115, 'weight_decay': 0.015460338023660657, 'batch_size': 32} - Best Value (CSI): 0.548234 - Best Trial: 7 - Best Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.11120869422981193, 'ffn_dropout': 0.12617347554183356, 'lr': 0.00015776266193100045, 'weight_decay': 0.001820829144600586, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 00:08:47,160] Trial 13 pruned. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.390043 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.15482396554564729, 'ffn_dropout': 0.260433248472379, 'lr': 1.2640391637559996e-05, 'weight_decay': 0.0034591324820598427, 'batch_size': 32} - Best Value (CSI): 0.548234 - Best Trial: 7 - Best Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.11120869422981193, 'ffn_dropout': 0.12617347554183356, 'lr': 0.00015776266193100045, 'weight_decay': 0.001820829144600586, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-29 00:11:05,854] Trial 14 finished with value: 0.5141720701802868 and parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.2403904204380791, 'ffn_dropout': 0.38140466429794534, 'lr': 0.00017455095805766422, 'weight_decay': 0.08960125142951682, 'batch_size': 256}. Best is trial 7 with value: 0.5482335521221479. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.514172 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.2403904204380791, 'ffn_dropout': 0.38140466429794534, 'lr': 0.00017455095805766422, 'weight_decay': 0.08960125142951682, 'batch_size': 256} - Best Value (CSI): 0.548234 - Best Trial: 7 - Best Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.11120869422981193, 'ffn_dropout': 0.12617347554183356, 'lr': 0.00015776266193100045, 'weight_decay': 0.001820829144600586, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 00:12:01,595] Trial 15 pruned. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.147427 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19943515826116465, 'ffn_dropout': 0.18133413105636048, 'lr': 0.0009616034287122157, 'weight_decay': 0.0007159513200565918, 'batch_size': 32} - Best Value (CSI): 0.548234 - Best Trial: 7 - Best Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.11120869422981193, 'ffn_dropout': 0.12617347554183356, 'lr': 0.00015776266193100045, 'weight_decay': 0.001820829144600586, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-29 00:18:52,166] Trial 16 finished with value: 0.5615761316445699 and parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1380493586467473, 'ffn_dropout': 0.24358844962569826, 'lr': 0.0004894899689411649, 'weight_decay': 0.004098449384519225, 'batch_size': 32}. Best is trial 16 with value: 0.5615761316445699. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.561576 - Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1380493586467473, 'ffn_dropout': 0.24358844962569826, 'lr': 0.0004894899689411649, 'weight_decay': 0.004098449384519225, 'batch_size': 32} - Best Value (CSI): 0.561576 - Best Trial: 16 - Best Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1380493586467473, 'ffn_dropout': 0.24358844962569826, 'lr': 0.0004894899689411649, 'weight_decay': 0.004098449384519225, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 00:20:51,495] Trial 17 pruned. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.490083 - Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.13400388386582784, 'ffn_dropout': 0.23885592609765183, 'lr': 0.00014383085817323593, 'weight_decay': 0.0037793176325993318, 'batch_size': 32} - Best Value (CSI): 0.561576 - Best Trial: 16 - Best Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1380493586467473, 'ffn_dropout': 0.24358844962569826, 'lr': 0.0004894899689411649, 'weight_decay': 0.004098449384519225, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-29 00:23:12,276] Trial 18 finished with value: 0.5643832267965512 and parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256}. Best is trial 18 with value: 0.5643832267965512. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.564383 - Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-29 00:24:51,000] Trial 19 pruned. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.509234 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.14957954967348686, 'ffn_dropout': 0.2800870794477315, 'lr': 0.0005319785577291643, 'weight_decay': 0.0006412975874320264, 'batch_size': 256} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-29 00:25:53,325] Trial 20 finished with value: 0.5264481381947264 and parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.10089007890601638, 'ffn_dropout': 0.22243490483196152, 'lr': 0.00043524164569292014, 'weight_decay': 0.00026857826793736246, 'batch_size': 256}. Best is trial 18 with value: 0.5643832267965512. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.526448 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.10089007890601638, 'ffn_dropout': 0.22243490483196152, 'lr': 0.00043524164569292014, 'weight_decay': 0.00026857826793736246, 'batch_size': 256} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-29 00:28:04,641] Trial 21 pruned. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.477580 - Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.12587702091007322, 'ffn_dropout': 0.171769138114872, 'lr': 0.00027810456590594726, 'weight_decay': 0.0012867254274542095, 'batch_size': 256} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 00:28:49,124] Trial 22 pruned. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.549041 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.14034425867940936, 'ffn_dropout': 0.1637852601775704, 'lr': 0.00014788804132516523, 'weight_decay': 0.0025419095030742144, 'batch_size': 128} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) -[I 2025-12-29 00:30:08,054] Trial 23 pruned. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.576567 - Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.10132696074937578, 'ffn_dropout': 0.11838863742701045, 'lr': 0.00048375297059161706, 'weight_decay': 0.000982606423297445, 'batch_size': 256} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-29 00:37:57,647] Trial 24 finished with value: 0.5452319781737195 and parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.16979016934560456, 'ffn_dropout': 0.15038072988185297, 'lr': 0.00011500819385513623, 'weight_decay': 0.0003696986954667127, 'batch_size': 32}. Best is trial 18 with value: 0.5643832267965512. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.545232 - Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.16979016934560456, 'ffn_dropout': 0.15038072988185297, 'lr': 0.00011500819385513623, 'weight_decay': 0.0003696986954667127, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 00:39:25,047] Trial 25 pruned. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.506422 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.12356542388230375, 'ffn_dropout': 0.2141113010735353, 'lr': 0.0002514440541562182, 'weight_decay': 0.0018424789539535846, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 00:39:42,393] Trial 26 pruned. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.362331 - Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1985323349101837, 'ffn_dropout': 0.1841158137450152, 'lr': 9.375521429618026e-05, 'weight_decay': 0.0009918336446864385, 'batch_size': 256} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-29 00:41:51,854] Trial 27 finished with value: 0.5523076108441733 and parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.13130877181998685, 'ffn_dropout': 0.16801967383763183, 'lr': 0.00020982994508162084, 'weight_decay': 0.0036049157731073123, 'batch_size': 128}. Best is trial 18 with value: 0.5643832267965512. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.552308 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.13130877181998685, 'ffn_dropout': 0.16801967383763183, 'lr': 0.00020982994508162084, 'weight_decay': 0.0036049157731073123, 'batch_size': 128} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-29 00:43:37,714] Trial 28 pruned. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.540420 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.15663569176095848, 'ffn_dropout': 0.22357225971691325, 'lr': 0.0004056937105550292, 'weight_decay': 0.004196219342154379, 'batch_size': 128} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 00:44:21,484] Trial 29 pruned. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.537367 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.13825230132267136, 'ffn_dropout': 0.20082399428944703, 'lr': 0.0002175853527812361, 'weight_decay': 0.0022474023401324356, 'batch_size': 128} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-29 00:46:01,509] Trial 30 pruned. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.531825 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.15512065281194876, 'ffn_dropout': 0.16872809060271243, 'lr': 0.0006777026148565629, 'weight_decay': 0.0029149259395310225, 'batch_size': 128} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-29 00:48:28,578] Trial 31 pruned. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.515233 - Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.12017243720235452, 'ffn_dropout': 0.13445131546928224, 'lr': 0.00019987726465314456, 'weight_decay': 0.002164062932968941, 'batch_size': 128} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 00:49:51,763] Trial 32 pruned. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.453292 - Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.11729625762413762, 'ffn_dropout': 0.10277943559013536, 'lr': 0.000258276941044599, 'weight_decay': 0.005090692893771197, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 00:50:44,312] Trial 33 pruned. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.448900 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.13805123523139862, 'ffn_dropout': 0.15013617176449412, 'lr': 0.00035652314214680277, 'weight_decay': 0.001975910400366289, 'batch_size': 64} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-29 00:57:19,748] Trial 34 finished with value: 0.5526226590348261 and parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.17822697178187646, 'ffn_dropout': 0.16239233794709368, 'lr': 9.8948657760547e-05, 'weight_decay': 0.0013179676713396845, 'batch_size': 32}. Best is trial 18 with value: 0.5643832267965512. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.552623 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.17822697178187646, 'ffn_dropout': 0.16239233794709368, 'lr': 9.8948657760547e-05, 'weight_decay': 0.0013179676713396845, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 00:57:40,592] Trial 35 pruned. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.448471 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.1775633042953697, 'ffn_dropout': 0.18434482937480196, 'lr': 7.939534366246458e-05, 'weight_decay': 0.0013018722931509364, 'batch_size': 128} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 00:58:26,633] Trial 36 pruned. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.494864 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.18756376006064038, 'ffn_dropout': 0.1491303741607855, 'lr': 0.00011715445856402639, 'weight_decay': 0.0052004952280321525, 'batch_size': 64} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 00:58:48,887] Trial 37 pruned. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.538505 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2201909760053963, 'ffn_dropout': 0.16562300977175326, 'lr': 0.0003639311793465039, 'weight_decay': 0.0033750476564611124, 'batch_size': 256} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 00:59:23,229] Trial 38 pruned. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.467086 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1651150601039373, 'ffn_dropout': 0.20977987006228813, 'lr': 6.95017313408398e-05, 'weight_decay': 0.010042484944057472, 'batch_size': 64} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 01:00:40,088] Trial 39 pruned. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.519093 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.1773130090235038, 'ffn_dropout': 0.23536522710957605, 'lr': 0.00021484650929151007, 'weight_decay': 0.0014362896688472364, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) -[I 2025-12-29 01:02:04,272] Trial 40 pruned. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.541386 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.14608759547348982, 'ffn_dropout': 0.2563168568723006, 'lr': 0.0001213425504160212, 'weight_decay': 0.002651002341320549, 'batch_size': 128} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 01:03:46,624] Trial 41 pruned. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.503071 - Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.11759514848670445, 'ffn_dropout': 0.1312498827447781, 'lr': 0.00017585132728941089, 'weight_decay': 0.0015747445896388903, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-29 01:11:28,898] Trial 42 finished with value: 0.5591557623722259 and parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1328778764751705, 'ffn_dropout': 0.1222859064671967, 'lr': 5.4408215906146685e-05, 'weight_decay': 0.0010212712036367943, 'batch_size': 32}. Best is trial 18 with value: 0.5643832267965512. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.559156 - Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1328778764751705, 'ffn_dropout': 0.1222859064671967, 'lr': 5.4408215906146685e-05, 'weight_decay': 0.0010212712036367943, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 01:13:14,803] Trial 43 pruned. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.496921 - Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.161131252874405, 'ffn_dropout': 0.15616650087799774, 'lr': 5.4343323363981646e-05, 'weight_decay': 0.0009404587718160067, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 01:16:08,624] Trial 44 pruned. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.515188 - Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.13121322223822776, 'ffn_dropout': 0.14053149897339584, 'lr': 3.8385743918216924e-05, 'weight_decay': 0.0005587549021746302, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 01:18:44,873] Trial 45 pruned. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.508177 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.14398264544705586, 'ffn_dropout': 0.11515393373204819, 'lr': 4.480248511612693e-05, 'weight_decay': 0.00038870570059338245, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 01:20:32,797] Trial 46 pruned. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.506242 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.1084269413379796, 'ffn_dropout': 0.13550581147327595, 'lr': 8.878353905558894e-05, 'weight_decay': 0.0007381223389466994, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 01:20:46,409] Trial 47 pruned. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.288837 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.13075847136344396, 'ffn_dropout': 0.19331088301551502, 'lr': 6.339790025948526e-05, 'weight_decay': 0.0010741211141414974, 'batch_size': 256} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 01:22:09,585] Trial 48 pruned. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.469349 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.16457222274891387, 'ffn_dropout': 0.17582066036302907, 'lr': 0.00029719417264965117, 'weight_decay': 0.001759079541398814, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 01:22:53,043] Trial 49 pruned. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.017077 - Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.18375308813694813, 'ffn_dropout': 0.1576603252870394, 'lr': 0.0012849111511400186, 'weight_decay': 0.002933562482816141, 'batch_size': 64} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 01:24:56,520] Trial 50 pruned. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.528695 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.14994934150580436, 'ffn_dropout': 0.12036010488584449, 'lr': 2.8849493235188442e-05, 'weight_decay': 0.007959992788597797, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 01:26:55,375] Trial 51 pruned. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.494678 - Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.11139695325026643, 'ffn_dropout': 0.1402597802185082, 'lr': 0.00015898431903922707, 'weight_decay': 0.0016835136359699676, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-29 01:34:47,913] Trial 52 pruned. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.539526 - Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.10054385392614736, 'ffn_dropout': 0.10547076147603708, 'lr': 9.421887063399697e-05, 'weight_decay': 0.0007978168408181234, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 01:36:58,214] Trial 53 pruned. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.499688 - Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.13031920960313817, 'ffn_dropout': 0.12059613125394011, 'lr': 0.00031082253091144717, 'weight_decay': 0.0012402360570501585, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-29 01:43:38,592] Trial 54 finished with value: 0.551710375421777 and parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.12243005076664129, 'ffn_dropout': 0.1288444763745584, 'lr': 0.000601126530477638, 'weight_decay': 0.00423966027385117, 'batch_size': 32}. Best is trial 18 with value: 0.5643832267965512. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.551710 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.12243005076664129, 'ffn_dropout': 0.1288444763745584, 'lr': 0.000601126530477638, 'weight_decay': 0.00423966027385117, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 01:44:26,542] Trial 55 pruned. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.470260 - Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.14800819499266915, 'ffn_dropout': 0.1623276439785605, 'lr': 0.0005709928186422164, 'weight_decay': 0.00399822712327428, 'batch_size': 256} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-29 01:48:36,596] Trial 56 finished with value: 0.49118031111281696 and parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.11265059719117237, 'ffn_dropout': 0.1769276931236695, 'lr': 0.0006733322518482248, 'weight_decay': 0.005720651807583956, 'batch_size': 32}. Best is trial 18 with value: 0.5643832267965512. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.491180 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.11265059719117237, 'ffn_dropout': 0.1769276931236695, 'lr': 0.0006733322518482248, 'weight_decay': 0.005720651807583956, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 01:49:13,914] Trial 57 pruned. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.503056 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.12720094541459576, 'ffn_dropout': 0.1294672021085732, 'lr': 0.0004128748227254106, 'weight_decay': 0.0023769657096122526, 'batch_size': 128} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 01:50:02,862] Trial 58 pruned. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.508115 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.16471730684547087, 'ffn_dropout': 0.14743856744947034, 'lr': 0.0009480749798316357, 'weight_decay': 0.0031631583025376214, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 01:50:39,974] Trial 59 pruned. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.530814 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.14277665883065147, 'ffn_dropout': 0.19420345566058644, 'lr': 0.0002398823123829807, 'weight_decay': 0.004429821264610799, 'batch_size': 256} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-29 01:55:50,971] Trial 60 finished with value: 0.5468393054370795 and parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.15724910010373874, 'ffn_dropout': 0.10928514775108408, 'lr': 0.0005048676561633345, 'weight_decay': 0.01362819348817963, 'batch_size': 32}. Best is trial 18 with value: 0.5643832267965512. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.546839 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.15724910010373874, 'ffn_dropout': 0.10928514775108408, 'lr': 0.0005048676561633345, 'weight_decay': 0.01362819348817963, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 01:57:24,307] Trial 61 pruned. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.457143 - Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.11126207171006505, 'ffn_dropout': 0.1280061076917386, 'lr': 0.00012623528651466964, 'weight_decay': 0.001922736930672293, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 01:58:47,908] Trial 62 pruned. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.467803 - Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1219521748757495, 'ffn_dropout': 0.11114971583257492, 'lr': 0.00017571539737284977, 'weight_decay': 0.0066715937549738326, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 02:00:45,525] Trial 63 pruned. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.488540 - Parameters: {'d_token': 256, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.13516614795874016, 'ffn_dropout': 0.14330543081324593, 'lr': 0.00030328618845788585, 'weight_decay': 0.0035183493083197417, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-29 02:03:00,197] Trial 64 pruned. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.518965 - Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1260288740100909, 'ffn_dropout': 0.15656658076171365, 'lr': 0.00015372187684879247, 'weight_decay': 0.002481824317685139, 'batch_size': 128} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 02:05:48,775] Trial 65 pruned. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.500000 - Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.10734359414184927, 'ffn_dropout': 0.12252180332169352, 'lr': 7.294398541435345e-05, 'weight_decay': 0.0011426704710325013, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 02:06:25,763] Trial 66 pruned. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.496615 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.1414452528667507, 'ffn_dropout': 0.1715158961580739, 'lr': 0.0004268213510793753, 'weight_decay': 0.0015242835354650599, 'batch_size': 256} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 02:07:41,117] Trial 67 pruned. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.522975 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.11652401308232883, 'ffn_dropout': 0.1868235732511662, 'lr': 0.00010823157718656925, 'weight_decay': 0.0009080870019577153, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-29 02:11:10,002] Trial 68 pruned. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.515107 - Parameters: {'d_token': 256, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.1526896427419394, 'ffn_dropout': 0.10191060853890357, 'lr': 0.00021029965699925508, 'weight_decay': 0.000612929701843668, 'batch_size': 128} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 02:13:21,628] Trial 69 pruned. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.490123 - Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.13536761547012877, 'ffn_dropout': 0.14006899025705527, 'lr': 0.00035161465569575663, 'weight_decay': 0.002083127600029381, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-29 02:16:12,281] Trial 70 finished with value: 0.5443605652632723 and parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.10052381846130058, 'ffn_dropout': 0.1699446826256683, 'lr': 0.0002750223134701451, 'weight_decay': 0.00427161233039884, 'batch_size': 64}. Best is trial 18 with value: 0.5643832267965512. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.544361 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.10052381846130058, 'ffn_dropout': 0.1699446826256683, 'lr': 0.0002750223134701451, 'weight_decay': 0.00427161233039884, 'batch_size': 64} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 02:17:38,793] Trial 71 pruned. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.513497 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.15705726030287262, 'ffn_dropout': 0.11496696924824318, 'lr': 0.00048314472620145956, 'weight_decay': 0.013903301993387527, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 02:19:35,601] Trial 72 pruned. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.504926 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.12114851850750076, 'ffn_dropout': 0.1275246101576053, 'lr': 0.0005493998068400294, 'weight_decay': 0.03550651912674199, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 02:20:50,827] Trial 73 pruned. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.497342 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.1727605375760804, 'ffn_dropout': 0.11244759751945095, 'lr': 0.000682120998931394, 'weight_decay': 0.008347055954910884, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 02:22:18,514] Trial 74 pruned. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.526102 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.14802037279166366, 'ffn_dropout': 0.13356660986361782, 'lr': 0.00038551727892383145, 'weight_decay': 0.0013717336899351962, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 02:23:46,638] Trial 75 pruned. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.494479 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.1596173262842347, 'ffn_dropout': 0.14981544426307608, 'lr': 0.000137159045818321, 'weight_decay': 0.0029413589942313967, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 02:23:57,735] Trial 76 pruned. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.380472 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.13347188459450113, 'ffn_dropout': 0.10732748336045642, 'lr': 0.00018492382374384568, 'weight_decay': 0.0008515724884633574, 'batch_size': 256} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 02:24:27,393] Trial 77 pruned. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.526229 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.12507757716508608, 'ffn_dropout': 0.15982659941414, 'lr': 0.00023374888252350107, 'weight_decay': 0.005625368837237321, 'batch_size': 128} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 02:26:09,810] Trial 78 pruned. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.490136 - Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.14042636486523313, 'ffn_dropout': 0.12093017296260274, 'lr': 0.0003188204950081463, 'weight_decay': 0.001077573974636095, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 02:27:24,466] Trial 79 pruned. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.526754 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.15306436366098672, 'ffn_dropout': 0.10081046699775781, 'lr': 8.476491417673307e-05, 'weight_decay': 0.00234832856682374, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 02:28:47,675] Trial 80 pruned. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.446154 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.1692188929787728, 'ffn_dropout': 0.13786665360625644, 'lr': 0.00048180307602545524, 'weight_decay': 0.0016949233785873952, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 02:29:35,206] Trial 81 pruned. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.498141 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2288172760053352, 'ffn_dropout': 0.27889871497197316, 'lr': 0.0008645306269682021, 'weight_decay': 0.009837973408712552, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 02:30:19,962] Trial 82 pruned. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.294456 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.19727717111484516, 'ffn_dropout': 0.396349307622322, 'lr': 0.0012998987357782103, 'weight_decay': 0.003720774254327264, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 02:31:21,343] Trial 83 pruned. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.483871 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.10955880960407603, 'ffn_dropout': 0.36312906768795217, 'lr': 0.0005922267416131876, 'weight_decay': 0.004823423670198022, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 02:31:39,518] Trial 84 pruned. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.467762 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.25022650565347765, 'ffn_dropout': 0.32503966175211096, 'lr': 0.0007793136807075203, 'weight_decay': 0.017245360892372698, 'batch_size': 256} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-29 02:34:44,175] Trial 85 finished with value: 0.5567263224724469 and parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.1195142150753754, 'ffn_dropout': 0.20485175493792943, 'lr': 0.00010449506975161863, 'weight_decay': 0.0068670422769548985, 'batch_size': 64}. Best is trial 18 with value: 0.5643832267965512. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.556726 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.1195142150753754, 'ffn_dropout': 0.20485175493792943, 'lr': 0.00010449506975161863, 'weight_decay': 0.0068670422769548985, 'batch_size': 64} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 02:35:24,657] Trial 86 pruned. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.501531 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.11897206157882803, 'ffn_dropout': 0.21170067527105896, 'lr': 0.00014368305858029076, 'weight_decay': 0.006475731335381718, 'batch_size': 64} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 02:36:05,158] Trial 87 pruned. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.507754 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.1283153969343001, 'ffn_dropout': 0.16612440653798136, 'lr': 0.00010476102421687655, 'weight_decay': 0.0028147428386043265, 'batch_size': 64} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 02:36:31,791] Trial 88 pruned. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.384663 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.1390035577366695, 'ffn_dropout': 0.14653953168715994, 'lr': 6.347006895519652e-05, 'weight_decay': 0.00356343101567134, 'batch_size': 64} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 02:37:18,400] Trial 89 pruned. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.462611 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.1129361105423105, 'ffn_dropout': 0.17853714064563014, 'lr': 0.00019025334891864082, 'weight_decay': 0.00510689662259767, 'batch_size': 64} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 02:38:46,554] Trial 90 pruned. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.537866 - Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.14867016963215005, 'ffn_dropout': 0.15484813659396807, 'lr': 8.000034343293483e-05, 'weight_decay': 0.002010552368835503, 'batch_size': 64} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 02:39:47,901] Trial 91 pruned. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.483118 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13157542666056743, 'ffn_dropout': 0.18850506380661813, 'lr': 0.00034755755506706546, 'weight_decay': 0.007083768226416792, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) -[I 2025-12-29 02:41:00,196] Trial 92 pruned. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.559091 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.12350200171914191, 'ffn_dropout': 0.23102812496229302, 'lr': 0.00026606798188590785, 'weight_decay': 0.004047499294300202, 'batch_size': 128} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 02:42:31,662] Trial 93 pruned. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.516697 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.10586118038060947, 'ffn_dropout': 0.19656956457953234, 'lr': 0.00010196569592521579, 'weight_decay': 0.0012746211851924563, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 02:43:50,042] Trial 94 pruned. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.415405 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.15643780051442444, 'ffn_dropout': 0.24532794565787674, 'lr': 0.0004740733237809556, 'weight_decay': 0.006290953007007396, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 02:44:16,681] Trial 95 pruned. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.510070 - Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1431511861753134, 'ffn_dropout': 0.20545245309209145, 'lr': 0.0001344080033631852, 'weight_decay': 0.004559317578369444, 'batch_size': 256} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 02:46:57,386] Trial 96 pruned. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.517346 - Parameters: {'d_token': 224, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.11432318316474932, 'ffn_dropout': 0.21792276875044492, 'lr': 5.505897101999206e-05, 'weight_decay': 0.0031531514373563823, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.2077462523322395, 1: 0.9975820379965458, 2: 0.8550021634670129} (클래스별 샘플 수: {0: 10362, 1: 12545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.2141910028783027, 1: 0.9899277540473553, 2: 0.8574626013474934} (클래스별 샘플 수: {0: 10307, 1: 12642, 2: 14595}) -[I 2025-12-29 02:49:22,023] Trial 97 pruned. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.532840 - Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.13307953023487068, 'ffn_dropout': 0.12445022691399608, 'lr': 0.00016354271660700285, 'weight_decay': 0.005543919940951279, 'batch_size': 128} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 02:51:03,331] Trial 98 pruned. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.505063 - Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.18112096949966985, 'ffn_dropout': 0.20361572905354947, 'lr': 0.00023312057927042648, 'weight_decay': 0.007806076538260478, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.2061593853473496, 1: 0.9928289804450795, 2: 0.8593284778525949} (클래스별 샘플 수: {0: 10369, 1: 12597, 2: 14554}) -[I 2025-12-29 02:52:18,433] Trial 99 pruned. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.512104 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.16739910791392276, 'ffn_dropout': 0.13299706143126586, 'lr': 0.0004017517571328272, 'weight_decay': 0.0025762049777413353, 'batch_size': 32} - Best Value (CSI): 0.564383 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.5644 -Best Hyperparameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1369145590780379, 'ffn_dropout': 0.16996780951611673, 'lr': 0.0003662598943307626, 'weight_decay': 0.000729119254134465, 'batch_size': 256} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.5463 - - 최종 CSI: 0.5121 - - 최고 CSI: 0.5766 - - 최저 CSI: 0.0000 - - 평균 CSI: 0.4693 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/ft_transformer_ctgan10000_incheon_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 29, Best CSI: 0.5478 - Fold 1 학습 완료 (검증 CSI: 0.5478) -Fold 2 학습 중... - Early stopping at epoch 39, Best CSI: 0.5743 - Fold 2 학습 완료 (검증 CSI: 0.5743) -Fold 3 학습 중... - Early stopping at epoch 28, Best CSI: 0.5100 - Fold 3 학습 완료 (검증 CSI: 0.5100) - -모든 모델 저장 완료: ../save_model/ft_transformer_optima/ft_transformer_ctgan10000_incheon.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/ft_transformer_optima/scaler/ft_transformer_ctgan10000_incheon_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: ../save_model/ft_transformer_optima/ft_transformer_ctgan10000_incheon.pkl - -✓ 완료: ft_transformer_ctgan10000/ft_transformer_ctgan10000_incheon.py (소요 시간: 11710초) - ----------------------------------------- -실행 중: ft_transformer_ctgan10000/ft_transformer_ctgan10000_seoul.py -시작 시간: 2025-12-29 02:54:25 ----------------------------------------- -[I 2025-12-29 02:54:26,928] A new study created in memory with name: no-name-cfc479f4-72df-4a6d-bfe2-c73a36ce6936 - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-29 02:56:56,130] Trial 0 finished with value: 0.5579049839306286 and parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.31795400561331116, 'ffn_dropout': 0.30735230899827337, 'lr': 0.00023961964055182848, 'weight_decay': 0.021219153663130146, 'batch_size': 128}. Best is trial 0 with value: 0.5579049839306286. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.557905 - Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.31795400561331116, 'ffn_dropout': 0.30735230899827337, 'lr': 0.00023961964055182848, 'weight_decay': 0.021219153663130146, 'batch_size': 128} - Best Value (CSI): 0.557905 - Best Trial: 0 - Best Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.31795400561331116, 'ffn_dropout': 0.30735230899827337, 'lr': 0.00023961964055182848, 'weight_decay': 0.021219153663130146, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-29 02:58:58,029] Trial 1 finished with value: 0.5467262445555292 and parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.11909806403334228, 'ffn_dropout': 0.13639481788905272, 'lr': 0.0006551105132270649, 'weight_decay': 0.0007667624170607032, 'batch_size': 128}. Best is trial 0 with value: 0.5579049839306286. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.546726 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.11909806403334228, 'ffn_dropout': 0.13639481788905272, 'lr': 0.0006551105132270649, 'weight_decay': 0.0007667624170607032, 'batch_size': 128} - Best Value (CSI): 0.557905 - Best Trial: 0 - Best Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.31795400561331116, 'ffn_dropout': 0.30735230899827337, 'lr': 0.00023961964055182848, 'weight_decay': 0.021219153663130146, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-29 02:59:49,871] Trial 2 finished with value: 0.3864559980847096 and parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.11263559437447485, 'ffn_dropout': 0.27517152473074846, 'lr': 1.7380463950187136e-05, 'weight_decay': 0.006545579805835805, 'batch_size': 128}. Best is trial 0 with value: 0.5579049839306286. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.386456 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.11263559437447485, 'ffn_dropout': 0.27517152473074846, 'lr': 1.7380463950187136e-05, 'weight_decay': 0.006545579805835805, 'batch_size': 128} - Best Value (CSI): 0.557905 - Best Trial: 0 - Best Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.31795400561331116, 'ffn_dropout': 0.30735230899827337, 'lr': 0.00023961964055182848, 'weight_decay': 0.021219153663130146, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-29 03:02:28,192] Trial 3 finished with value: 0.09805561793547309 and parameters: {'d_token': 224, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.18168718401907408, 'ffn_dropout': 0.20410979838156046, 'lr': 0.0016164240937481325, 'weight_decay': 0.0014196037996539723, 'batch_size': 64}. Best is trial 0 with value: 0.5579049839306286. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.098056 - Parameters: {'d_token': 224, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.18168718401907408, 'ffn_dropout': 0.20410979838156046, 'lr': 0.0016164240937481325, 'weight_decay': 0.0014196037996539723, 'batch_size': 64} - Best Value (CSI): 0.557905 - Best Trial: 0 - Best Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.31795400561331116, 'ffn_dropout': 0.30735230899827337, 'lr': 0.00023961964055182848, 'weight_decay': 0.021219153663130146, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-29 03:11:31,407] Trial 4 finished with value: 0.5725894886897501 and parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.21693351790691612, 'ffn_dropout': 0.28366608615803063, 'lr': 4.624919806815511e-05, 'weight_decay': 0.019396895465195362, 'batch_size': 32}. Best is trial 4 with value: 0.5725894886897501. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.572589 - Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.21693351790691612, 'ffn_dropout': 0.28366608615803063, 'lr': 4.624919806815511e-05, 'weight_decay': 0.019396895465195362, 'batch_size': 32} - Best Value (CSI): 0.572589 - Best Trial: 4 - Best Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.21693351790691612, 'ffn_dropout': 0.28366608615803063, 'lr': 4.624919806815511e-05, 'weight_decay': 0.019396895465195362, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 03:11:43,097] Trial 5 pruned. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.140701 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.17062336854442037, 'ffn_dropout': 0.20579089383914406, 'lr': 2.506129524013788e-05, 'weight_decay': 0.004492904748965555, 'batch_size': 128} - Best Value (CSI): 0.572589 - Best Trial: 4 - Best Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.21693351790691612, 'ffn_dropout': 0.28366608615803063, 'lr': 4.624919806815511e-05, 'weight_decay': 0.019396895465195362, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 03:12:22,697] Trial 6 pruned. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.10207073250615734, 'ffn_dropout': 0.29690310611505, 'lr': 0.009656268309818652, 'weight_decay': 0.0014546192126293862, 'batch_size': 32} - Best Value (CSI): 0.572589 - Best Trial: 4 - Best Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.21693351790691612, 'ffn_dropout': 0.28366608615803063, 'lr': 4.624919806815511e-05, 'weight_decay': 0.019396895465195362, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 03:12:39,751] Trial 7 pruned. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.016741 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3295872195178423, 'ffn_dropout': 0.17756885112938722, 'lr': 0.004859822891995932, 'weight_decay': 0.0017263949348336745, 'batch_size': 64} - Best Value (CSI): 0.572589 - Best Trial: 4 - Best Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.21693351790691612, 'ffn_dropout': 0.28366608615803063, 'lr': 4.624919806815511e-05, 'weight_decay': 0.019396895465195362, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 03:12:49,078] Trial 8 pruned. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.274917 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2217329543480606, 'ffn_dropout': 0.27781370622021306, 'lr': 6.963644832947678e-05, 'weight_decay': 0.030179047730342516, 'batch_size': 128} - Best Value (CSI): 0.572589 - Best Trial: 4 - Best Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.21693351790691612, 'ffn_dropout': 0.28366608615803063, 'lr': 4.624919806815511e-05, 'weight_decay': 0.019396895465195362, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 03:13:08,792] Trial 9 pruned. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.38306233888478025, 'ffn_dropout': 0.10995227482973959, 'lr': 0.008065184798294404, 'weight_decay': 0.00011352903271818957, 'batch_size': 128} - Best Value (CSI): 0.572589 - Best Trial: 4 - Best Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.21693351790691612, 'ffn_dropout': 0.28366608615803063, 'lr': 4.624919806815511e-05, 'weight_decay': 0.019396895465195362, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 03:14:10,542] Trial 10 pruned. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.310973 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.2597368590806157, 'ffn_dropout': 0.3977758216412729, 'lr': 1.0048739962758657e-05, 'weight_decay': 0.08730986665800299, 'batch_size': 32} - Best Value (CSI): 0.572589 - Best Trial: 4 - Best Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.21693351790691612, 'ffn_dropout': 0.28366608615803063, 'lr': 4.624919806815511e-05, 'weight_decay': 0.019396895465195362, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 03:14:27,678] Trial 11 pruned. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.286210 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.285749719359101, 'ffn_dropout': 0.32694390805598683, 'lr': 0.00015267879702870508, 'weight_decay': 0.015323620339219567, 'batch_size': 256} - Best Value (CSI): 0.572589 - Best Trial: 4 - Best Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.21693351790691612, 'ffn_dropout': 0.28366608615803063, 'lr': 4.624919806815511e-05, 'weight_decay': 0.019396895465195362, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-29 03:20:06,251] Trial 12 finished with value: 0.5672164910898182 and parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.2976224591819775, 'ffn_dropout': 0.3361044960918732, 'lr': 0.00017425335506144425, 'weight_decay': 0.023645411885796466, 'batch_size': 32}. Best is trial 4 with value: 0.5725894886897501. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.567216 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.2976224591819775, 'ffn_dropout': 0.3361044960918732, 'lr': 0.00017425335506144425, 'weight_decay': 0.023645411885796466, 'batch_size': 32} - Best Value (CSI): 0.572589 - Best Trial: 4 - Best Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.21693351790691612, 'ffn_dropout': 0.28366608615803063, 'lr': 4.624919806815511e-05, 'weight_decay': 0.019396895465195362, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 03:21:33,690] Trial 13 pruned. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.445783 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.2321795836727086, 'ffn_dropout': 0.3363290636408807, 'lr': 6.42124147086052e-05, 'weight_decay': 0.09619023699959023, 'batch_size': 32} - Best Value (CSI): 0.572589 - Best Trial: 4 - Best Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.21693351790691612, 'ffn_dropout': 0.28366608615803063, 'lr': 4.624919806815511e-05, 'weight_decay': 0.019396895465195362, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-29 03:27:38,678] Trial 14 finished with value: 0.571643543151814 and parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2697960009937791, 'ffn_dropout': 0.24660136888593615, 'lr': 0.00010552571107046037, 'weight_decay': 0.009900681595458921, 'batch_size': 32}. Best is trial 4 with value: 0.5725894886897501. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.571644 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2697960009937791, 'ffn_dropout': 0.24660136888593615, 'lr': 0.00010552571107046037, 'weight_decay': 0.009900681595458921, 'batch_size': 32} - Best Value (CSI): 0.572589 - Best Trial: 4 - Best Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.21693351790691612, 'ffn_dropout': 0.28366608615803063, 'lr': 4.624919806815511e-05, 'weight_decay': 0.019396895465195362, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) -[I 2025-12-29 03:32:10,750] Trial 15 pruned. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.599809 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.25491446318232, 'ffn_dropout': 0.2418176728685899, 'lr': 4.681308129647074e-05, 'weight_decay': 0.008619004185613652, 'batch_size': 32} - Best Value (CSI): 0.572589 - Best Trial: 4 - Best Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.21693351790691612, 'ffn_dropout': 0.28366608615803063, 'lr': 4.624919806815511e-05, 'weight_decay': 0.019396895465195362, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 03:32:49,493] Trial 16 pruned. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.440933 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.21428712193808533, 'ffn_dropout': 0.245348029094218, 'lr': 0.0004950446686988365, 'weight_decay': 0.04065653412603421, 'batch_size': 256} - Best Value (CSI): 0.572589 - Best Trial: 4 - Best Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.21693351790691612, 'ffn_dropout': 0.28366608615803063, 'lr': 4.624919806815511e-05, 'weight_decay': 0.019396895465195362, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 03:33:29,056] Trial 17 pruned. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.337432 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.18818600124077917, 'ffn_dropout': 0.2277747169158896, 'lr': 7.869068402677907e-05, 'weight_decay': 0.010562171852071317, 'batch_size': 32} - Best Value (CSI): 0.572589 - Best Trial: 4 - Best Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.21693351790691612, 'ffn_dropout': 0.28366608615803063, 'lr': 4.624919806815511e-05, 'weight_decay': 0.019396895465195362, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 03:34:18,736] Trial 18 pruned. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.321859 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2694319076765506, 'ffn_dropout': 0.27068687555165083, 'lr': 3.359304406488655e-05, 'weight_decay': 0.005217120838257398, 'batch_size': 32} - Best Value (CSI): 0.572589 - Best Trial: 4 - Best Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.21693351790691612, 'ffn_dropout': 0.28366608615803063, 'lr': 4.624919806815511e-05, 'weight_decay': 0.019396895465195362, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) -[I 2025-12-29 03:37:56,964] Trial 19 pruned. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.587302 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2347602940713037, 'ffn_dropout': 0.19089315650019492, 'lr': 0.00012324335712764707, 'weight_decay': 0.011568811507437745, 'batch_size': 32} - Best Value (CSI): 0.572589 - Best Trial: 4 - Best Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.21693351790691612, 'ffn_dropout': 0.28366608615803063, 'lr': 4.624919806815511e-05, 'weight_decay': 0.019396895465195362, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-29 03:40:53,619] Trial 20 finished with value: 0.5840041121927088 and parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.15138336650637607, 'ffn_dropout': 0.2209876231731353, 'lr': 0.0003384467661077483, 'weight_decay': 0.04790408424933305, 'batch_size': 64}. Best is trial 20 with value: 0.5840041121927088. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.584004 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.15138336650637607, 'ffn_dropout': 0.2209876231731353, 'lr': 0.0003384467661077483, 'weight_decay': 0.04790408424933305, 'batch_size': 64} - Best Value (CSI): 0.584004 - Best Trial: 20 - Best Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.15138336650637607, 'ffn_dropout': 0.2209876231731353, 'lr': 0.0003384467661077483, 'weight_decay': 0.04790408424933305, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-29 03:44:21,509] Trial 21 finished with value: 0.5692611869504968 and parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.15260200801027626, 'ffn_dropout': 0.2299506016341118, 'lr': 0.00038648182971781327, 'weight_decay': 0.04521377059350505, 'batch_size': 64}. Best is trial 20 with value: 0.5840041121927088. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.569261 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.15260200801027626, 'ffn_dropout': 0.2299506016341118, 'lr': 0.00038648182971781327, 'weight_decay': 0.04521377059350505, 'batch_size': 64} - Best Value (CSI): 0.584004 - Best Trial: 20 - Best Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.15138336650637607, 'ffn_dropout': 0.2209876231731353, 'lr': 0.0003384467661077483, 'weight_decay': 0.04790408424933305, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-29 03:47:34,905] Trial 22 finished with value: 0.5750868235368252 and parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.20213073075325172, 'ffn_dropout': 0.25276633710336677, 'lr': 0.0002699922387287163, 'weight_decay': 0.04848142422795926, 'batch_size': 64}. Best is trial 20 with value: 0.5840041121927088. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.575087 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.20213073075325172, 'ffn_dropout': 0.25276633710336677, 'lr': 0.0002699922387287163, 'weight_decay': 0.04848142422795926, 'batch_size': 64} - Best Value (CSI): 0.584004 - Best Trial: 20 - Best Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.15138336650637607, 'ffn_dropout': 0.2209876231731353, 'lr': 0.0003384467661077483, 'weight_decay': 0.04790408424933305, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 03:48:10,171] Trial 23 pruned. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.029363 - Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.14473548544540732, 'ffn_dropout': 0.17297357140834846, 'lr': 0.0008652956534740518, 'weight_decay': 0.043336825146245116, 'batch_size': 64} - Best Value (CSI): 0.584004 - Best Trial: 20 - Best Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.15138336650637607, 'ffn_dropout': 0.2209876231731353, 'lr': 0.0003384467661077483, 'weight_decay': 0.04790408424933305, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-29 03:51:23,418] Trial 24 finished with value: 0.5734361421451473 and parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.20759771548090097, 'ffn_dropout': 0.21468123752398455, 'lr': 0.00025420553866967237, 'weight_decay': 0.0647083701609805, 'batch_size': 64}. Best is trial 20 with value: 0.5840041121927088. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.573436 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.20759771548090097, 'ffn_dropout': 0.21468123752398455, 'lr': 0.00025420553866967237, 'weight_decay': 0.0647083701609805, 'batch_size': 64} - Best Value (CSI): 0.584004 - Best Trial: 20 - Best Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.15138336650637607, 'ffn_dropout': 0.2209876231731353, 'lr': 0.0003384467661077483, 'weight_decay': 0.04790408424933305, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-29 03:54:54,345] Trial 25 finished with value: 0.5728761684696874 and parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.19531877018222105, 'ffn_dropout': 0.2163469352356568, 'lr': 0.00026793978788309766, 'weight_decay': 0.060526039597060335, 'batch_size': 64}. Best is trial 20 with value: 0.5840041121927088. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.572876 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.19531877018222105, 'ffn_dropout': 0.2163469352356568, 'lr': 0.00026793978788309766, 'weight_decay': 0.060526039597060335, 'batch_size': 64} - Best Value (CSI): 0.584004 - Best Trial: 20 - Best Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.15138336650637607, 'ffn_dropout': 0.2209876231731353, 'lr': 0.0003384467661077483, 'weight_decay': 0.04790408424933305, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-29 03:58:59,379] Trial 26 pruned. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.554714 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.14623903107326944, 'ffn_dropout': 0.15917179323107283, 'lr': 0.00027793459460336066, 'weight_decay': 0.06752963459670294, 'batch_size': 64} - Best Value (CSI): 0.584004 - Best Trial: 20 - Best Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.15138336650637607, 'ffn_dropout': 0.2209876231731353, 'lr': 0.0003384467661077483, 'weight_decay': 0.04790408424933305, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 03:59:48,224] Trial 27 pruned. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.032840 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.16950012418427002, 'ffn_dropout': 0.20288908347600293, 'lr': 0.0010034527978017675, 'weight_decay': 0.09965754029836332, 'batch_size': 64} - Best Value (CSI): 0.584004 - Best Trial: 20 - Best Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.15138336650637607, 'ffn_dropout': 0.2209876231731353, 'lr': 0.0003384467661077483, 'weight_decay': 0.04790408424933305, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-29 04:02:26,780] Trial 28 finished with value: 0.5788872867819307 and parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2016068251445053, 'ffn_dropout': 0.2575884819768468, 'lr': 0.00043879747382487755, 'weight_decay': 0.03143945377816023, 'batch_size': 64}. Best is trial 20 with value: 0.5840041121927088. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.578887 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2016068251445053, 'ffn_dropout': 0.2575884819768468, 'lr': 0.00043879747382487755, 'weight_decay': 0.03143945377816023, 'batch_size': 64} - Best Value (CSI): 0.584004 - Best Trial: 20 - Best Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.15138336650637607, 'ffn_dropout': 0.2209876231731353, 'lr': 0.0003384467661077483, 'weight_decay': 0.04790408424933305, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-29 04:05:29,066] Trial 29 finished with value: 0.5767424500570838 and parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.1881056951475832, 'ffn_dropout': 0.2479988546153217, 'lr': 0.00048283484068757567, 'weight_decay': 0.025649327935511782, 'batch_size': 64}. Best is trial 20 with value: 0.5840041121927088. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.576742 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.1881056951475832, 'ffn_dropout': 0.2479988546153217, 'lr': 0.00048283484068757567, 'weight_decay': 0.025649327935511782, 'batch_size': 64} - Best Value (CSI): 0.584004 - Best Trial: 20 - Best Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.15138336650637607, 'ffn_dropout': 0.2209876231731353, 'lr': 0.0003384467661077483, 'weight_decay': 0.04790408424933305, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-29 04:08:45,077] Trial 30 finished with value: 0.5871801671613369 and parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.13029659543170038, 'ffn_dropout': 0.26314272832988106, 'lr': 0.0004555995067335758, 'weight_decay': 0.02699427292151179, 'batch_size': 64}. Best is trial 30 with value: 0.5871801671613369. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.587180 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.13029659543170038, 'ffn_dropout': 0.26314272832988106, 'lr': 0.0004555995067335758, 'weight_decay': 0.02699427292151179, 'batch_size': 64} - Best Value (CSI): 0.587180 - Best Trial: 30 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.13029659543170038, 'ffn_dropout': 0.26314272832988106, 'lr': 0.0004555995067335758, 'weight_decay': 0.02699427292151179, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 04:09:31,644] Trial 31 pruned. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.488751 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.13051867347068974, 'ffn_dropout': 0.260281554563409, 'lr': 0.000429693868905566, 'weight_decay': 0.026803669176562836, 'batch_size': 64} - Best Value (CSI): 0.587180 - Best Trial: 30 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.13029659543170038, 'ffn_dropout': 0.26314272832988106, 'lr': 0.0004555995067335758, 'weight_decay': 0.02699427292151179, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 04:10:17,810] Trial 32 pruned. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.470204 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12757790062608004, 'ffn_dropout': 0.2331033463086535, 'lr': 0.0005328271924469928, 'weight_decay': 0.016758772543039376, 'batch_size': 64} - Best Value (CSI): 0.587180 - Best Trial: 30 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.13029659543170038, 'ffn_dropout': 0.26314272832988106, 'lr': 0.0004555995067335758, 'weight_decay': 0.02699427292151179, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 04:11:16,877] Trial 33 pruned. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.1754021243433097, 'ffn_dropout': 0.25237838050557104, 'lr': 0.0007074769302769029, 'weight_decay': 0.03149193571375503, 'batch_size': 64} - Best Value (CSI): 0.587180 - Best Trial: 30 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.13029659543170038, 'ffn_dropout': 0.26314272832988106, 'lr': 0.0004555995067335758, 'weight_decay': 0.02699427292151179, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 04:11:38,842] Trial 34 pruned. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.169155 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.1603374066104922, 'ffn_dropout': 0.26162791042510625, 'lr': 0.001330667342379479, 'weight_decay': 0.020322353307538312, 'batch_size': 64} - Best Value (CSI): 0.587180 - Best Trial: 30 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.13029659543170038, 'ffn_dropout': 0.26314272832988106, 'lr': 0.0004555995067335758, 'weight_decay': 0.02699427292151179, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 04:11:59,061] Trial 35 pruned. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.395439 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.18679409326783822, 'ffn_dropout': 0.22612479088663734, 'lr': 0.0001920615443389492, 'weight_decay': 0.031826385232525095, 'batch_size': 256} - Best Value (CSI): 0.587180 - Best Trial: 30 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.13029659543170038, 'ffn_dropout': 0.26314272832988106, 'lr': 0.0004555995067335758, 'weight_decay': 0.02699427292151179, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-29 04:14:51,811] Trial 36 finished with value: 0.5766925878416213 and parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.11299131009819986, 'ffn_dropout': 0.28165584565671, 'lr': 0.00036423548077642363, 'weight_decay': 0.014944008461314653, 'batch_size': 64}. Best is trial 30 with value: 0.5871801671613369. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.576693 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.11299131009819986, 'ffn_dropout': 0.28165584565671, 'lr': 0.00036423548077642363, 'weight_decay': 0.014944008461314653, 'batch_size': 64} - Best Value (CSI): 0.587180 - Best Trial: 30 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.13029659543170038, 'ffn_dropout': 0.26314272832988106, 'lr': 0.0004555995067335758, 'weight_decay': 0.02699427292151179, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 04:15:33,307] Trial 37 pruned. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.485759 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13169794429282083, 'ffn_dropout': 0.2653366138640552, 'lr': 0.0005417823714042152, 'weight_decay': 0.021105546799304115, 'batch_size': 64} - Best Value (CSI): 0.587180 - Best Trial: 30 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.13029659543170038, 'ffn_dropout': 0.26314272832988106, 'lr': 0.0004555995067335758, 'weight_decay': 0.02699427292151179, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 04:16:02,263] Trial 38 pruned. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.013898 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.1583171447334046, 'ffn_dropout': 0.28859050840028894, 'lr': 0.0017588952803970746, 'weight_decay': 0.0074232370696753975, 'batch_size': 64} - Best Value (CSI): 0.587180 - Best Trial: 30 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.13029659543170038, 'ffn_dropout': 0.26314272832988106, 'lr': 0.0004555995067335758, 'weight_decay': 0.02699427292151179, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 04:16:45,429] Trial 39 pruned. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.482400 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.17821616132165277, 'ffn_dropout': 0.3014862592759043, 'lr': 0.0007926725729142426, 'weight_decay': 0.03653475589452454, 'batch_size': 64} - Best Value (CSI): 0.587180 - Best Trial: 30 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.13029659543170038, 'ffn_dropout': 0.26314272832988106, 'lr': 0.0004555995067335758, 'weight_decay': 0.02699427292151179, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 04:17:18,551] Trial 40 pruned. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.462548 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.1006318173978627, 'ffn_dropout': 0.19740064024336465, 'lr': 0.0003553565594700732, 'weight_decay': 0.012848431876657362, 'batch_size': 128} - Best Value (CSI): 0.587180 - Best Trial: 30 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.13029659543170038, 'ffn_dropout': 0.26314272832988106, 'lr': 0.0004555995067335758, 'weight_decay': 0.02699427292151179, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-29 04:20:11,445] Trial 41 finished with value: 0.5820980514045591 and parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.11513504544675668, 'ffn_dropout': 0.2856617378633517, 'lr': 0.0003387630992399779, 'weight_decay': 0.015063109005040497, 'batch_size': 64}. Best is trial 30 with value: 0.5871801671613369. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.582098 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.11513504544675668, 'ffn_dropout': 0.2856617378633517, 'lr': 0.0003387630992399779, 'weight_decay': 0.015063109005040497, 'batch_size': 64} - Best Value (CSI): 0.587180 - Best Trial: 30 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.13029659543170038, 'ffn_dropout': 0.26314272832988106, 'lr': 0.0004555995067335758, 'weight_decay': 0.02699427292151179, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-29 04:22:52,073] Trial 42 finished with value: 0.5826088856623229 and parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.11829574259077641, 'ffn_dropout': 0.27786123422526277, 'lr': 0.00020436288643566148, 'weight_decay': 0.02724252332885922, 'batch_size': 64}. Best is trial 30 with value: 0.5871801671613369. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.582609 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.11829574259077641, 'ffn_dropout': 0.27786123422526277, 'lr': 0.00020436288643566148, 'weight_decay': 0.02724252332885922, 'batch_size': 64} - Best Value (CSI): 0.587180 - Best Trial: 30 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.13029659543170038, 'ffn_dropout': 0.26314272832988106, 'lr': 0.0004555995067335758, 'weight_decay': 0.02699427292151179, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-29 04:25:31,929] Trial 43 finished with value: 0.5885711803137631 and parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12221399429185369, 'ffn_dropout': 0.27723467741432656, 'lr': 0.0002004737157808501, 'weight_decay': 0.017798768457349907, 'batch_size': 64}. Best is trial 43 with value: 0.5885711803137631. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.588571 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12221399429185369, 'ffn_dropout': 0.27723467741432656, 'lr': 0.0002004737157808501, 'weight_decay': 0.017798768457349907, 'batch_size': 64} - Best Value (CSI): 0.588571 - Best Trial: 43 - Best Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12221399429185369, 'ffn_dropout': 0.27723467741432656, 'lr': 0.0002004737157808501, 'weight_decay': 0.017798768457349907, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 04:25:57,129] Trial 44 pruned. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.440318 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.11584640365787176, 'ffn_dropout': 0.3124092221918302, 'lr': 0.0002047257510557689, 'weight_decay': 0.018458053146143304, 'batch_size': 64} - Best Value (CSI): 0.588571 - Best Trial: 43 - Best Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12221399429185369, 'ffn_dropout': 0.27723467741432656, 'lr': 0.0002004737157808501, 'weight_decay': 0.017798768457349907, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 04:26:20,280] Trial 45 pruned. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.369430 - Parameters: {'d_token': 224, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.10098182860557439, 'ffn_dropout': 0.277769112110723, 'lr': 0.0001484778189344276, 'weight_decay': 0.006325728418314964, 'batch_size': 256} - Best Value (CSI): 0.588571 - Best Trial: 43 - Best Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12221399429185369, 'ffn_dropout': 0.27723467741432656, 'lr': 0.0002004737157808501, 'weight_decay': 0.017798768457349907, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 04:26:41,776] Trial 46 pruned. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.430407 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.13759369907107238, 'ffn_dropout': 0.29152350266355476, 'lr': 0.00022651303159974983, 'weight_decay': 0.015595806785966313, 'batch_size': 128} - Best Value (CSI): 0.588571 - Best Trial: 43 - Best Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12221399429185369, 'ffn_dropout': 0.27723467741432656, 'lr': 0.0002004737157808501, 'weight_decay': 0.017798768457349907, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 04:27:25,188] Trial 47 pruned. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.475162 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.12109774498400552, 'ffn_dropout': 0.2745289628119233, 'lr': 0.00010345681716254672, 'weight_decay': 0.024383757729480055, 'batch_size': 64} - Best Value (CSI): 0.588571 - Best Trial: 43 - Best Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12221399429185369, 'ffn_dropout': 0.27723467741432656, 'lr': 0.0002004737157808501, 'weight_decay': 0.017798768457349907, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 04:27:42,372] Trial 48 pruned. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.325000 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.11654831088109424, 'ffn_dropout': 0.3147730944906184, 'lr': 0.00016085671842261403, 'weight_decay': 0.00351422848731665, 'batch_size': 64} - Best Value (CSI): 0.588571 - Best Trial: 43 - Best Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12221399429185369, 'ffn_dropout': 0.27723467741432656, 'lr': 0.0002004737157808501, 'weight_decay': 0.017798768457349907, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 04:28:22,295] Trial 49 pruned. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.418746 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.14076986155892818, 'ffn_dropout': 0.2960943334899248, 'lr': 0.0003050899124188452, 'weight_decay': 0.00910371467047018, 'batch_size': 64} - Best Value (CSI): 0.588571 - Best Trial: 43 - Best Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12221399429185369, 'ffn_dropout': 0.27723467741432656, 'lr': 0.0002004737157808501, 'weight_decay': 0.017798768457349907, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 04:29:02,738] Trial 50 pruned. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.474814 - Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.12738092712833432, 'ffn_dropout': 0.280369610149275, 'lr': 0.000632816329457544, 'weight_decay': 0.05484601218268662, 'batch_size': 128} - Best Value (CSI): 0.588571 - Best Trial: 43 - Best Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12221399429185369, 'ffn_dropout': 0.27723467741432656, 'lr': 0.0002004737157808501, 'weight_decay': 0.017798768457349907, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) -[I 2025-12-29 04:30:45,687] Trial 51 pruned. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.595285 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.15874607498139368, 'ffn_dropout': 0.2633384217805401, 'lr': 0.00036649007898842693, 'weight_decay': 0.03350392478165871, 'batch_size': 64} - Best Value (CSI): 0.588571 - Best Trial: 43 - Best Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12221399429185369, 'ffn_dropout': 0.27723467741432656, 'lr': 0.0002004737157808501, 'weight_decay': 0.017798768457349907, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-29 04:33:37,213] Trial 52 finished with value: 0.5855357784884214 and parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.11731164574725747, 'ffn_dropout': 0.23816056363935245, 'lr': 0.00022051718562417637, 'weight_decay': 0.037738985225110315, 'batch_size': 64}. Best is trial 43 with value: 0.5885711803137631. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.585536 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.11731164574725747, 'ffn_dropout': 0.23816056363935245, 'lr': 0.00022051718562417637, 'weight_decay': 0.037738985225110315, 'batch_size': 64} - Best Value (CSI): 0.588571 - Best Trial: 43 - Best Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12221399429185369, 'ffn_dropout': 0.27723467741432656, 'lr': 0.0002004737157808501, 'weight_decay': 0.017798768457349907, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-29 04:36:32,924] Trial 53 finished with value: 0.5825601143092648 and parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10813048504945645, 'ffn_dropout': 0.242520963163446, 'lr': 0.00020551838546086957, 'weight_decay': 0.07699102926582083, 'batch_size': 64}. Best is trial 43 with value: 0.5885711803137631. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.582560 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10813048504945645, 'ffn_dropout': 0.242520963163446, 'lr': 0.00020551838546086957, 'weight_decay': 0.07699102926582083, 'batch_size': 64} - Best Value (CSI): 0.588571 - Best Trial: 43 - Best Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12221399429185369, 'ffn_dropout': 0.27723467741432656, 'lr': 0.0002004737157808501, 'weight_decay': 0.017798768457349907, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-29 04:39:17,104] Trial 54 finished with value: 0.5822811640862801 and parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10677239084416629, 'ffn_dropout': 0.23685237483127486, 'lr': 0.00022358015308684168, 'weight_decay': 0.07702848410469723, 'batch_size': 64}. Best is trial 43 with value: 0.5885711803137631. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.582281 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10677239084416629, 'ffn_dropout': 0.23685237483127486, 'lr': 0.00022358015308684168, 'weight_decay': 0.07702848410469723, 'batch_size': 64} - Best Value (CSI): 0.588571 - Best Trial: 43 - Best Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12221399429185369, 'ffn_dropout': 0.27723467741432656, 'lr': 0.0002004737157808501, 'weight_decay': 0.017798768457349907, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 04:39:32,981] Trial 55 pruned. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.318744 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.1382497468923508, 'ffn_dropout': 0.23774639206303022, 'lr': 0.00014177240483837324, 'weight_decay': 0.056107001103240794, 'batch_size': 256} - Best Value (CSI): 0.588571 - Best Trial: 43 - Best Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12221399429185369, 'ffn_dropout': 0.27723467741432656, 'lr': 0.0002004737157808501, 'weight_decay': 0.017798768457349907, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-29 04:43:35,520] Trial 56 finished with value: 0.5786512956901767 and parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.12435888010929234, 'ffn_dropout': 0.22306922947797206, 'lr': 0.00018515400363972018, 'weight_decay': 0.07905435558307217, 'batch_size': 64}. Best is trial 43 with value: 0.5885711803137631. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.578651 - Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.12435888010929234, 'ffn_dropout': 0.22306922947797206, 'lr': 0.00018515400363972018, 'weight_decay': 0.07905435558307217, 'batch_size': 64} - Best Value (CSI): 0.588571 - Best Trial: 43 - Best Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12221399429185369, 'ffn_dropout': 0.27723467741432656, 'lr': 0.0002004737157808501, 'weight_decay': 0.017798768457349907, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) -[I 2025-12-29 04:45:06,285] Trial 57 pruned. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.576427 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10757793396127785, 'ffn_dropout': 0.2141371903919246, 'lr': 0.0001224192730610905, 'weight_decay': 0.04436120454446182, 'batch_size': 64} - Best Value (CSI): 0.588571 - Best Trial: 43 - Best Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12221399429185369, 'ffn_dropout': 0.27723467741432656, 'lr': 0.0002004737157808501, 'weight_decay': 0.017798768457349907, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 04:45:35,641] Trial 58 pruned. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.288565 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.12080037491831641, 'ffn_dropout': 0.24659577238328956, 'lr': 9.033209234643225e-05, 'weight_decay': 0.039622857291108905, 'batch_size': 64} - Best Value (CSI): 0.588571 - Best Trial: 43 - Best Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12221399429185369, 'ffn_dropout': 0.27723467741432656, 'lr': 0.0002004737157808501, 'weight_decay': 0.017798768457349907, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 04:46:00,834] Trial 59 pruned. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.260241 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.14744852855582782, 'ffn_dropout': 0.24006856896700993, 'lr': 6.703217259238753e-05, 'weight_decay': 0.07092868875380011, 'batch_size': 64} - Best Value (CSI): 0.588571 - Best Trial: 43 - Best Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12221399429185369, 'ffn_dropout': 0.27723467741432656, 'lr': 0.0002004737157808501, 'weight_decay': 0.017798768457349907, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-29 04:48:33,077] Trial 60 finished with value: 0.5771309635712614 and parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.1346835159086081, 'ffn_dropout': 0.2714572708095556, 'lr': 0.00023054941246685432, 'weight_decay': 0.051940359954400196, 'batch_size': 64}. Best is trial 43 with value: 0.5885711803137631. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.577131 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.1346835159086081, 'ffn_dropout': 0.2714572708095556, 'lr': 0.00023054941246685432, 'weight_decay': 0.051940359954400196, 'batch_size': 64} - Best Value (CSI): 0.588571 - Best Trial: 43 - Best Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12221399429185369, 'ffn_dropout': 0.27723467741432656, 'lr': 0.0002004737157808501, 'weight_decay': 0.017798768457349907, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-29 04:51:24,211] Trial 61 finished with value: 0.5805523008484407 and parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10688235200661511, 'ffn_dropout': 0.2341942150214136, 'lr': 0.0001902569669852399, 'weight_decay': 0.0828880413798283, 'batch_size': 64}. Best is trial 43 with value: 0.5885711803137631. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.580552 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10688235200661511, 'ffn_dropout': 0.2341942150214136, 'lr': 0.0001902569669852399, 'weight_decay': 0.0828880413798283, 'batch_size': 64} - Best Value (CSI): 0.588571 - Best Trial: 43 - Best Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12221399429185369, 'ffn_dropout': 0.27723467741432656, 'lr': 0.0002004737157808501, 'weight_decay': 0.017798768457349907, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-29 04:53:57,632] Trial 62 finished with value: 0.5902150483032744 and parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10908300747104757, 'ffn_dropout': 0.253484998998862, 'lr': 0.00028652786262047274, 'weight_decay': 0.0765345214426832, 'batch_size': 64}. Best is trial 62 with value: 0.5902150483032744. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.590215 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10908300747104757, 'ffn_dropout': 0.253484998998862, 'lr': 0.00028652786262047274, 'weight_decay': 0.0765345214426832, 'batch_size': 64} - Best Value (CSI): 0.590215 - Best Trial: 62 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10908300747104757, 'ffn_dropout': 0.253484998998862, 'lr': 0.00028652786262047274, 'weight_decay': 0.0765345214426832, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-29 04:56:31,967] Trial 63 finished with value: 0.5761304966321242 and parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12096545013730317, 'ffn_dropout': 0.2546782896684882, 'lr': 0.00031541584194649737, 'weight_decay': 0.051116998835743, 'batch_size': 64}. Best is trial 62 with value: 0.5902150483032744. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.576130 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12096545013730317, 'ffn_dropout': 0.2546782896684882, 'lr': 0.00031541584194649737, 'weight_decay': 0.051116998835743, 'batch_size': 64} - Best Value (CSI): 0.590215 - Best Trial: 62 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10908300747104757, 'ffn_dropout': 0.253484998998862, 'lr': 0.00028652786262047274, 'weight_decay': 0.0765345214426832, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) -[I 2025-12-29 04:58:06,120] Trial 64 pruned. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.583821 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10017653710502612, 'ffn_dropout': 0.26741324277445516, 'lr': 0.00012685038392221408, 'weight_decay': 0.09933725451305633, 'batch_size': 64} - Best Value (CSI): 0.590215 - Best Trial: 62 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10908300747104757, 'ffn_dropout': 0.253484998998862, 'lr': 0.00028652786262047274, 'weight_decay': 0.0765345214426832, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 04:58:57,380] Trial 65 pruned. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.421367 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.14831281617234934, 'ffn_dropout': 0.24683217060438484, 'lr': 0.0002792676196590625, 'weight_decay': 0.02665850119448124, 'batch_size': 64} - Best Value (CSI): 0.590215 - Best Trial: 62 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10908300747104757, 'ffn_dropout': 0.253484998998862, 'lr': 0.00028652786262047274, 'weight_decay': 0.0765345214426832, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) -[I 2025-12-29 05:01:01,890] Trial 66 pruned. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.595216 - Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.1293611674986793, 'ffn_dropout': 0.22477006225140303, 'lr': 0.00017979875442098418, 'weight_decay': 0.038481811830882715, 'batch_size': 64} - Best Value (CSI): 0.590215 - Best Trial: 62 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10908300747104757, 'ffn_dropout': 0.253484998998862, 'lr': 0.00028652786262047274, 'weight_decay': 0.0765345214426832, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 05:01:14,022] Trial 67 pruned. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.329504 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.11472780047346824, 'ffn_dropout': 0.21333210870995709, 'lr': 0.0002474172539387321, 'weight_decay': 0.06429726138634083, 'batch_size': 256} - Best Value (CSI): 0.590215 - Best Trial: 62 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10908300747104757, 'ffn_dropout': 0.253484998998862, 'lr': 0.00028652786262047274, 'weight_decay': 0.0765345214426832, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 05:03:12,573] Trial 68 pruned. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.473045 - Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.16675521856447773, 'ffn_dropout': 0.2560450595649854, 'lr': 0.0004465645646684194, 'weight_decay': 0.023611578198663427, 'batch_size': 32} - Best Value (CSI): 0.590215 - Best Trial: 62 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10908300747104757, 'ffn_dropout': 0.253484998998862, 'lr': 0.00028652786262047274, 'weight_decay': 0.0765345214426832, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 05:03:30,818] Trial 69 pruned. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.339135 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.14063210800796877, 'ffn_dropout': 0.27063906098569096, 'lr': 0.0001499614000064815, 'weight_decay': 0.044467955872826016, 'batch_size': 128} - Best Value (CSI): 0.590215 - Best Trial: 62 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10908300747104757, 'ffn_dropout': 0.253484998998862, 'lr': 0.00028652786262047274, 'weight_decay': 0.0765345214426832, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-29 05:05:55,365] Trial 70 finished with value: 0.5823328307616414 and parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.15360930595994146, 'ffn_dropout': 0.24230138424159062, 'lr': 0.0001024483259337221, 'weight_decay': 0.06030002573700187, 'batch_size': 64}. Best is trial 62 with value: 0.5902150483032744. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.582333 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.15360930595994146, 'ffn_dropout': 0.24230138424159062, 'lr': 0.0001024483259337221, 'weight_decay': 0.06030002573700187, 'batch_size': 64} - Best Value (CSI): 0.590215 - Best Trial: 62 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10908300747104757, 'ffn_dropout': 0.253484998998862, 'lr': 0.00028652786262047274, 'weight_decay': 0.0765345214426832, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) -[I 2025-12-29 05:06:55,860] Trial 71 pruned. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.602980 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.15203814701138024, 'ffn_dropout': 0.2430930681806338, 'lr': 0.00011091474741207093, 'weight_decay': 0.06653768840583758, 'batch_size': 64} - Best Value (CSI): 0.590215 - Best Trial: 62 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10908300747104757, 'ffn_dropout': 0.253484998998862, 'lr': 0.00028652786262047274, 'weight_decay': 0.0765345214426832, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 05:07:32,758] Trial 72 pruned. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.422105 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.12573660427253677, 'ffn_dropout': 0.25964629826940444, 'lr': 8.54189070699916e-05, 'weight_decay': 0.03547852627177405, 'batch_size': 64} - Best Value (CSI): 0.590215 - Best Trial: 62 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10908300747104757, 'ffn_dropout': 0.253484998998862, 'lr': 0.00028652786262047274, 'weight_decay': 0.0765345214426832, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-29 05:09:40,237] Trial 73 finished with value: 0.5728515985023669 and parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.10942705800688653, 'ffn_dropout': 0.2300452021848057, 'lr': 0.0002892666055680068, 'weight_decay': 0.05704902722685733, 'batch_size': 64}. Best is trial 62 with value: 0.5902150483032744. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.572852 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.10942705800688653, 'ffn_dropout': 0.2300452021848057, 'lr': 0.0002892666055680068, 'weight_decay': 0.05704902722685733, 'batch_size': 64} - Best Value (CSI): 0.590215 - Best Trial: 62 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10908300747104757, 'ffn_dropout': 0.253484998998862, 'lr': 0.00028652786262047274, 'weight_decay': 0.0765345214426832, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) -[I 2025-12-29 05:11:22,517] Trial 74 pruned. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.587488 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.13908456339849215, 'ffn_dropout': 0.25594781485281626, 'lr': 0.00021826036422696197, 'weight_decay': 0.07798666723959523, 'batch_size': 64} - Best Value (CSI): 0.590215 - Best Trial: 62 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10908300747104757, 'ffn_dropout': 0.253484998998862, 'lr': 0.00028652786262047274, 'weight_decay': 0.0765345214426832, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 05:12:20,429] Trial 75 pruned. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.437042 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.13211634361608926, 'ffn_dropout': 0.2212168665246504, 'lr': 0.00016728373918987349, 'weight_decay': 0.04408488976547518, 'batch_size': 64} - Best Value (CSI): 0.590215 - Best Trial: 62 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10908300747104757, 'ffn_dropout': 0.253484998998862, 'lr': 0.00028652786262047274, 'weight_decay': 0.0765345214426832, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) -[I 2025-12-29 05:14:02,880] Trial 76 pruned. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.599412 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.1517109686842802, 'ffn_dropout': 0.24967440573368807, 'lr': 0.0004183723127483666, 'weight_decay': 0.02851147482324035, 'batch_size': 64} - Best Value (CSI): 0.590215 - Best Trial: 62 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10908300747104757, 'ffn_dropout': 0.253484998998862, 'lr': 0.00028652786262047274, 'weight_decay': 0.0765345214426832, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 05:14:19,926] Trial 77 pruned. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.327571 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.11037771074907918, 'ffn_dropout': 0.20678846877997326, 'lr': 0.00013459968027379216, 'weight_decay': 0.09332382514522398, 'batch_size': 64} - Best Value (CSI): 0.590215 - Best Trial: 62 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10908300747104757, 'ffn_dropout': 0.253484998998862, 'lr': 0.00028652786262047274, 'weight_decay': 0.0765345214426832, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) -[I 2025-12-29 05:15:37,873] Trial 78 pruned. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.610536 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.12146641640644601, 'ffn_dropout': 0.23789436331991326, 'lr': 0.00031924509726042043, 'weight_decay': 0.019934426047364052, 'batch_size': 64} - Best Value (CSI): 0.590215 - Best Trial: 62 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10908300747104757, 'ffn_dropout': 0.253484998998862, 'lr': 0.00028652786262047274, 'weight_decay': 0.0765345214426832, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 05:16:42,782] Trial 79 pruned. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.449222 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.17107662061001871, 'ffn_dropout': 0.275952953779324, 'lr': 5.3078213949806096e-05, 'weight_decay': 0.03180543809107208, 'batch_size': 32} - Best Value (CSI): 0.590215 - Best Trial: 62 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10908300747104757, 'ffn_dropout': 0.253484998998862, 'lr': 0.00028652786262047274, 'weight_decay': 0.0765345214426832, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 05:17:03,798] Trial 80 pruned. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.420601 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.16298545282238547, 'ffn_dropout': 0.2670184113208191, 'lr': 0.00024789366090929144, 'weight_decay': 0.06222291373745851, 'batch_size': 64} - Best Value (CSI): 0.590215 - Best Trial: 62 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10908300747104757, 'ffn_dropout': 0.253484998998862, 'lr': 0.00028652786262047274, 'weight_decay': 0.0765345214426832, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 05:17:50,738] Trial 81 pruned. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.480125 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10881599624108843, 'ffn_dropout': 0.23055890424707653, 'lr': 0.00018783938344469822, 'weight_decay': 0.07755427091175272, 'batch_size': 64} - Best Value (CSI): 0.590215 - Best Trial: 62 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10908300747104757, 'ffn_dropout': 0.253484998998862, 'lr': 0.00028652786262047274, 'weight_decay': 0.0765345214426832, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) -[I 2025-12-29 05:19:30,156] Trial 82 pruned. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.585390 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10038281962591575, 'ffn_dropout': 0.24028858056728497, 'lr': 0.00021332151287445762, 'weight_decay': 0.04728373319341611, 'batch_size': 64} - Best Value (CSI): 0.590215 - Best Trial: 62 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10908300747104757, 'ffn_dropout': 0.253484998998862, 'lr': 0.00028652786262047274, 'weight_decay': 0.0765345214426832, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) -[I 2025-12-29 05:21:13,109] Trial 83 pruned. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.607619 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.13312136615921247, 'ffn_dropout': 0.23378428584048425, 'lr': 0.00039210785204485084, 'weight_decay': 0.07553547869369046, 'batch_size': 64} - Best Value (CSI): 0.590215 - Best Trial: 62 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10908300747104757, 'ffn_dropout': 0.253484998998862, 'lr': 0.00028652786262047274, 'weight_decay': 0.0765345214426832, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-29 05:23:43,670] Trial 84 finished with value: 0.5698066378405643 and parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.11958995152624513, 'ffn_dropout': 0.2524170860645722, 'lr': 9.929962087270417e-05, 'weight_decay': 0.037442205872462525, 'batch_size': 64}. Best is trial 62 with value: 0.5902150483032744. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.569807 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.11958995152624513, 'ffn_dropout': 0.2524170860645722, 'lr': 9.929962087270417e-05, 'weight_decay': 0.037442205872462525, 'batch_size': 64} - Best Value (CSI): 0.590215 - Best Trial: 62 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10908300747104757, 'ffn_dropout': 0.253484998998862, 'lr': 0.00028652786262047274, 'weight_decay': 0.0765345214426832, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-29 05:26:35,707] Trial 85 finished with value: 0.5813084162281533 and parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.11125319716064018, 'ffn_dropout': 0.28561983502752886, 'lr': 0.00025584770257392435, 'weight_decay': 0.08726024119690849, 'batch_size': 64}. Best is trial 62 with value: 0.5902150483032744. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.581308 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.11125319716064018, 'ffn_dropout': 0.28561983502752886, 'lr': 0.00025584770257392435, 'weight_decay': 0.08726024119690849, 'batch_size': 64} - Best Value (CSI): 0.590215 - Best Trial: 62 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10908300747104757, 'ffn_dropout': 0.253484998998862, 'lr': 0.00028652786262047274, 'weight_decay': 0.0765345214426832, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) -[I 2025-12-29 05:28:17,385] Trial 86 pruned. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.585700 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.14556830671400348, 'ffn_dropout': 0.2643943009940297, 'lr': 0.00015977018799567377, 'weight_decay': 0.06026190580643869, 'batch_size': 64} - Best Value (CSI): 0.590215 - Best Trial: 62 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10908300747104757, 'ffn_dropout': 0.253484998998862, 'lr': 0.00028652786262047274, 'weight_decay': 0.0765345214426832, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) -[I 2025-12-29 05:29:47,474] Trial 87 pruned. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.595930 - Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.1283647803196793, 'ffn_dropout': 0.2468824135839423, 'lr': 0.0005502312009717997, 'weight_decay': 0.05114471586901889, 'batch_size': 128} - Best Value (CSI): 0.590215 - Best Trial: 62 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10908300747104757, 'ffn_dropout': 0.253484998998862, 'lr': 0.00028652786262047274, 'weight_decay': 0.0765345214426832, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 05:29:59,561] Trial 88 pruned. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.398967 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10719128423118103, 'ffn_dropout': 0.22381310285198575, 'lr': 0.00033424510400721755, 'weight_decay': 0.022960715233175312, 'batch_size': 256} - Best Value (CSI): 0.590215 - Best Trial: 62 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10908300747104757, 'ffn_dropout': 0.253484998998862, 'lr': 0.00028652786262047274, 'weight_decay': 0.0765345214426832, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-29 05:32:42,164] Trial 89 finished with value: 0.5837434608728763 and parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.1549131596412708, 'ffn_dropout': 0.279386170889448, 'lr': 0.00012528789840496432, 'weight_decay': 0.029491179677383857, 'batch_size': 64}. Best is trial 62 with value: 0.5902150483032744. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.583743 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.1549131596412708, 'ffn_dropout': 0.279386170889448, 'lr': 0.00012528789840496432, 'weight_decay': 0.029491179677383857, 'batch_size': 64} - Best Value (CSI): 0.590215 - Best Trial: 62 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10908300747104757, 'ffn_dropout': 0.253484998998862, 'lr': 0.00028652786262047274, 'weight_decay': 0.0765345214426832, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-29 05:35:43,739] Trial 90 finished with value: 0.5936576575682742 and parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.15689079322421481, 'ffn_dropout': 0.27970845546044715, 'lr': 0.00011858823893766563, 'weight_decay': 0.02942637540327823, 'batch_size': 64}. Best is trial 90 with value: 0.5936576575682742. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.593658 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.15689079322421481, 'ffn_dropout': 0.27970845546044715, 'lr': 0.00011858823893766563, 'weight_decay': 0.02942637540327823, 'batch_size': 64} - Best Value (CSI): 0.593658 - Best Trial: 90 - Best Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.15689079322421481, 'ffn_dropout': 0.27970845546044715, 'lr': 0.00011858823893766563, 'weight_decay': 0.02942637540327823, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 05:36:10,517] Trial 91 pruned. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.333333 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1598610563184279, 'ffn_dropout': 0.28145271575862263, 'lr': 7.697713543246169e-05, 'weight_decay': 0.030015902236366993, 'batch_size': 64} - Best Value (CSI): 0.593658 - Best Trial: 90 - Best Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.15689079322421481, 'ffn_dropout': 0.27970845546044715, 'lr': 0.00011858823893766563, 'weight_decay': 0.02942637540327823, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 05:36:54,624] Trial 92 pruned. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.448544 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.15582214283051204, 'ffn_dropout': 0.2927477479282527, 'lr': 0.00010947537998356849, 'weight_decay': 0.018691160709088876, 'batch_size': 64} - Best Value (CSI): 0.593658 - Best Trial: 90 - Best Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.15689079322421481, 'ffn_dropout': 0.27970845546044715, 'lr': 0.00011858823893766563, 'weight_decay': 0.02942637540327823, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 05:37:41,410] Trial 93 pruned. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.403498 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.14225563017621035, 'ffn_dropout': 0.3028678517514851, 'lr': 0.00014287765329235475, 'weight_decay': 0.038728006548534206, 'batch_size': 64} - Best Value (CSI): 0.593658 - Best Trial: 90 - Best Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.15689079322421481, 'ffn_dropout': 0.27970845546044715, 'lr': 0.00011858823893766563, 'weight_decay': 0.02942637540327823, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-29 05:40:05,716] Trial 94 finished with value: 0.5789642828373208 and parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.13446390801781316, 'ffn_dropout': 0.2751389696501385, 'lr': 0.00012279379067272055, 'weight_decay': 0.02615411408014481, 'batch_size': 64}. Best is trial 90 with value: 0.5936576575682742. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.578964 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.13446390801781316, 'ffn_dropout': 0.2751389696501385, 'lr': 0.00012279379067272055, 'weight_decay': 0.02615411408014481, 'batch_size': 64} - Best Value (CSI): 0.593658 - Best Trial: 90 - Best Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.15689079322421481, 'ffn_dropout': 0.27970845546044715, 'lr': 0.00011858823893766563, 'weight_decay': 0.02942637540327823, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-29 05:42:57,914] Trial 95 finished with value: 0.5846675374753975 and parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1530043983274827, 'ffn_dropout': 0.2881867651786676, 'lr': 0.0001700874664617842, 'weight_decay': 0.033379049976407546, 'batch_size': 64}. Best is trial 90 with value: 0.5936576575682742. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.584668 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1530043983274827, 'ffn_dropout': 0.2881867651786676, 'lr': 0.0001700874664617842, 'weight_decay': 0.033379049976407546, 'batch_size': 64} - Best Value (CSI): 0.593658 - Best Trial: 90 - Best Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.15689079322421481, 'ffn_dropout': 0.27970845546044715, 'lr': 0.00011858823893766563, 'weight_decay': 0.02942637540327823, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.2494675186368478, 1: 1.0737594737594738, 2: 0.7884247884247885} (클래스별 샘플 수: {0: 10016, 1: 11655, 2: 15873}) -[I 2025-12-29 05:45:10,924] Trial 96 pruned. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.579038 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.17285487875653333, 'ffn_dropout': 0.2962554931642661, 'lr': 0.00017088254580087918, 'weight_decay': 0.022659897944009497, 'batch_size': 64} - Best Value (CSI): 0.593658 - Best Trial: 90 - Best Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.15689079322421481, 'ffn_dropout': 0.27970845546044715, 'lr': 0.00011858823893766563, 'weight_decay': 0.02942637540327823, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) -[I 2025-12-29 05:46:42,375] Trial 97 pruned. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.588813 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.1816655638004124, 'ffn_dropout': 0.285345968404239, 'lr': 0.0002135626759827049, 'weight_decay': 0.01307917837419845, 'batch_size': 64} - Best Value (CSI): 0.593658 - Best Trial: 90 - Best Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.15689079322421481, 'ffn_dropout': 0.27970845546044715, 'lr': 0.00011858823893766563, 'weight_decay': 0.02942637540327823, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.2478479077342375, 1: 1.0703615007412475, 2: 0.7909161768733278} (클래스별 샘플 수: {0: 10029, 1: 11692, 2: 15823}) -[I 2025-12-29 05:48:17,539] Trial 98 pruned. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.583665 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.16608408233895347, 'ffn_dropout': 0.2900561254330309, 'lr': 0.0002809138175271737, 'weight_decay': 0.028304694978962264, 'batch_size': 64} - Best Value (CSI): 0.593658 - Best Trial: 90 - Best Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.15689079322421481, 'ffn_dropout': 0.27970845546044715, 'lr': 0.00011858823893766563, 'weight_decay': 0.02942637540327823, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.24655304162929, 1: 1.058899895577569, 2: 0.7978225737858298} (클래스별 샘플 수: {0: 10033, 1: 11811, 2: 15676}) -[I 2025-12-29 05:49:52,737] Trial 99 pruned. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.451685 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.11832376199069997, 'ffn_dropout': 0.27140107497959304, 'lr': 0.00019517907474982205, 'weight_decay': 0.0410477497510017, 'batch_size': 32} - Best Value (CSI): 0.593658 - Best Trial: 90 - Best Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.15689079322421481, 'ffn_dropout': 0.27970845546044715, 'lr': 0.00011858823893766563, 'weight_decay': 0.02942637540327823, 'batch_size': 64} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.5937 -Best Hyperparameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.15689079322421481, 'ffn_dropout': 0.27970845546044715, 'lr': 0.00011858823893766563, 'weight_decay': 0.02942637540327823, 'batch_size': 64} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.5579 - - 최종 CSI: 0.4517 - - 최고 CSI: 0.6105 - - 최저 CSI: 0.0000 - - 평균 CSI: 0.4571 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/ft_transformer_ctgan10000_seoul_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 19, Best CSI: 0.5223 - Fold 1 학습 완료 (검증 CSI: 0.5223) -Fold 2 학습 중... - Early stopping at epoch 36, Best CSI: 0.6397 - Fold 2 학습 완료 (검증 CSI: 0.6397) -Fold 3 학습 중... - Early stopping at epoch 19, Best CSI: 0.5893 - Fold 3 학습 완료 (검증 CSI: 0.5893) - -모든 모델 저장 완료: ../save_model/ft_transformer_optima/ft_transformer_ctgan10000_seoul.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/ft_transformer_optima/scaler/ft_transformer_ctgan10000_seoul_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: ../save_model/ft_transformer_optima/ft_transformer_ctgan10000_seoul.pkl - -✓ 완료: ft_transformer_ctgan10000/ft_transformer_ctgan10000_seoul.py (소요 시간: 10708초) - -========================================== -FT-Transformer CTGAN10000 파일 실행 완료 -종료 시간: 2025-12-29 05:52:53 -총 소요 시간: 17시간 16분 31초 -성공: 6개 -실패: 0개 -========================================== diff --git a/Analysis_code/5.optima/run_bash/ft_transformer/ft_transformer_pure.log b/Analysis_code/5.optima/run_bash/ft_transformer/ft_transformer_pure.log deleted file mode 100644 index 505e25f6361ef25fc5997f3c8f53051ba68cd2d8..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/run_bash/ft_transformer/ft_transformer_pure.log +++ /dev/null @@ -1,8314 +0,0 @@ -nohup: ignoring input -/bin/bash: /opt/conda/lib/libtinfo.so.6: no version information available (required by /bin/bash) -========================================== -FT-Transformer Pure 파일 실행 시작 -시작 시간: 2025-12-24 21:05:51 -GPU: 0번 (CUDA_VISIBLE_DEVICES=0) -========================================== - ----------------------------------------- -실행 중: ft_transformer_pure/ft_transforemer_pure_busan.py -시작 시간: 2025-12-24 21:05:51 ----------------------------------------- -[I 2025-12-24 21:05:52,186] A new study created in memory with name: no-name-cbbdd308-9187-4fe4-981c-c22eafca869e - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 21:07:15,828] Trial 0 finished with value: 0.2716562081953138 and parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.11161146376561665, 'ffn_dropout': 0.16539029606255945, 'lr': 0.0005298408753759566, 'weight_decay': 0.017614939068221567, 'batch_size': 64}. Best is trial 0 with value: 0.2716562081953138. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.271656 - Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.11161146376561665, 'ffn_dropout': 0.16539029606255945, 'lr': 0.0005298408753759566, 'weight_decay': 0.017614939068221567, 'batch_size': 64} - Best Value (CSI): 0.271656 - Best Trial: 0 - Best Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.11161146376561665, 'ffn_dropout': 0.16539029606255945, 'lr': 0.0005298408753759566, 'weight_decay': 0.017614939068221567, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 21:08:29,449] Trial 1 finished with value: 0.40681736446514954 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.15540270176323806, 'ffn_dropout': 0.27253625623596467, 'lr': 0.00044929186520826483, 'weight_decay': 0.003390384966471146, 'batch_size': 128}. Best is trial 1 with value: 0.40681736446514954. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.406817 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.15540270176323806, 'ffn_dropout': 0.27253625623596467, 'lr': 0.00044929186520826483, 'weight_decay': 0.003390384966471146, 'batch_size': 128} - Best Value (CSI): 0.406817 - Best Trial: 1 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.15540270176323806, 'ffn_dropout': 0.27253625623596467, 'lr': 0.00044929186520826483, 'weight_decay': 0.003390384966471146, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 21:11:06,686] Trial 2 finished with value: 0.3573276604690426 and parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3601098829646031, 'ffn_dropout': 0.3490416201648363, 'lr': 6.163844995114048e-05, 'weight_decay': 0.00019208795174567497, 'batch_size': 64}. Best is trial 1 with value: 0.40681736446514954. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.357328 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3601098829646031, 'ffn_dropout': 0.3490416201648363, 'lr': 6.163844995114048e-05, 'weight_decay': 0.00019208795174567497, 'batch_size': 64} - Best Value (CSI): 0.406817 - Best Trial: 1 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.15540270176323806, 'ffn_dropout': 0.27253625623596467, 'lr': 0.00044929186520826483, 'weight_decay': 0.003390384966471146, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 21:12:26,059] Trial 3 finished with value: 0.40546390841173974 and parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.35874568857982514, 'ffn_dropout': 0.12393618693450768, 'lr': 0.00025016844156483965, 'weight_decay': 0.004002829955614525, 'batch_size': 128}. Best is trial 1 with value: 0.40681736446514954. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.405464 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.35874568857982514, 'ffn_dropout': 0.12393618693450768, 'lr': 0.00025016844156483965, 'weight_decay': 0.004002829955614525, 'batch_size': 128} - Best Value (CSI): 0.406817 - Best Trial: 1 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.15540270176323806, 'ffn_dropout': 0.27253625623596467, 'lr': 0.00044929186520826483, 'weight_decay': 0.003390384966471146, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 21:14:11,922] Trial 4 finished with value: 0.05763020768354185 and parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.22163904998551381, 'ffn_dropout': 0.3470697330323391, 'lr': 0.008230613887251468, 'weight_decay': 0.0003203157082813393, 'batch_size': 128}. Best is trial 1 with value: 0.40681736446514954. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.057630 - Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.22163904998551381, 'ffn_dropout': 0.3470697330323391, 'lr': 0.008230613887251468, 'weight_decay': 0.0003203157082813393, 'batch_size': 128} - Best Value (CSI): 0.406817 - Best Trial: 1 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.15540270176323806, 'ffn_dropout': 0.27253625623596467, 'lr': 0.00044929186520826483, 'weight_decay': 0.003390384966471146, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 21:19:34,052] Trial 5 finished with value: 0.4206899061123088 and parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.1352387756644564, 'ffn_dropout': 0.14472440440380052, 'lr': 9.340289562157445e-05, 'weight_decay': 0.0002938915951634303, 'batch_size': 32}. Best is trial 5 with value: 0.4206899061123088. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.420690 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.1352387756644564, 'ffn_dropout': 0.14472440440380052, 'lr': 9.340289562157445e-05, 'weight_decay': 0.0002938915951634303, 'batch_size': 32} - Best Value (CSI): 0.420690 - Best Trial: 5 - Best Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.1352387756644564, 'ffn_dropout': 0.14472440440380052, 'lr': 9.340289562157445e-05, 'weight_decay': 0.0002938915951634303, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-24 21:19:42,321] Trial 6 pruned. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.353480 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.39594917797466855, 'ffn_dropout': 0.3203346716186153, 'lr': 0.000781676547670931, 'weight_decay': 0.008307922629229626, 'batch_size': 256} - Best Value (CSI): 0.420690 - Best Trial: 5 - Best Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.1352387756644564, 'ffn_dropout': 0.14472440440380052, 'lr': 9.340289562157445e-05, 'weight_decay': 0.0002938915951634303, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) -[I 2025-12-24 21:20:32,465] Trial 7 pruned. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.401852 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3668265618216233, 'ffn_dropout': 0.3925083503096971, 'lr': 0.00037367521501284066, 'weight_decay': 0.011598232677155231, 'batch_size': 128} - Best Value (CSI): 0.420690 - Best Trial: 5 - Best Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.1352387756644564, 'ffn_dropout': 0.14472440440380052, 'lr': 9.340289562157445e-05, 'weight_decay': 0.0002938915951634303, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 21:28:18,884] Trial 8 finished with value: 0.41158589732941925 and parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.37209712351706214, 'ffn_dropout': 0.20731899678017, 'lr': 0.000218138503538878, 'weight_decay': 0.0001184931303641176, 'batch_size': 32}. Best is trial 5 with value: 0.4206899061123088. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.411586 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.37209712351706214, 'ffn_dropout': 0.20731899678017, 'lr': 0.000218138503538878, 'weight_decay': 0.0001184931303641176, 'batch_size': 32} - Best Value (CSI): 0.420690 - Best Trial: 5 - Best Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.1352387756644564, 'ffn_dropout': 0.14472440440380052, 'lr': 9.340289562157445e-05, 'weight_decay': 0.0002938915951634303, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-24 21:28:29,737] Trial 9 pruned. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.369433 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2803024777911396, 'ffn_dropout': 0.12857578173351294, 'lr': 0.0007189895940006559, 'weight_decay': 0.00019844456080760276, 'batch_size': 256} - Best Value (CSI): 0.420690 - Best Trial: 5 - Best Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.1352387756644564, 'ffn_dropout': 0.14472440440380052, 'lr': 9.340289562157445e-05, 'weight_decay': 0.0002938915951634303, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-24 21:29:17,323] Trial 10 pruned. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.361136 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.10226527035464761, 'ffn_dropout': 0.21168172867208787, 'lr': 1.0382931622997178e-05, 'weight_decay': 0.0008351894612281936, 'batch_size': 32} - Best Value (CSI): 0.420690 - Best Trial: 5 - Best Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.1352387756644564, 'ffn_dropout': 0.14472440440380052, 'lr': 9.340289562157445e-05, 'weight_decay': 0.0002938915951634303, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 21:38:12,793] Trial 11 finished with value: 0.4099823120630448 and parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.2854965392430121, 'ffn_dropout': 0.19524179027271088, 'lr': 7.023186682543279e-05, 'weight_decay': 0.0001024857249200319, 'batch_size': 32}. Best is trial 5 with value: 0.4206899061123088. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.409982 - Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.2854965392430121, 'ffn_dropout': 0.19524179027271088, 'lr': 7.023186682543279e-05, 'weight_decay': 0.0001024857249200319, 'batch_size': 32} - Best Value (CSI): 0.420690 - Best Trial: 5 - Best Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.1352387756644564, 'ffn_dropout': 0.14472440440380052, 'lr': 9.340289562157445e-05, 'weight_decay': 0.0002938915951634303, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 21:43:17,311] Trial 12 finished with value: 0.43285145179010937 and parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.19629762465883627, 'ffn_dropout': 0.10602886629880709, 'lr': 0.00010096393518563076, 'weight_decay': 0.0008082976530795957, 'batch_size': 32}. Best is trial 12 with value: 0.43285145179010937. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.432851 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.19629762465883627, 'ffn_dropout': 0.10602886629880709, 'lr': 0.00010096393518563076, 'weight_decay': 0.0008082976530795957, 'batch_size': 32} - Best Value (CSI): 0.432851 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.19629762465883627, 'ffn_dropout': 0.10602886629880709, 'lr': 0.00010096393518563076, 'weight_decay': 0.0008082976530795957, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 21:49:12,072] Trial 13 finished with value: 0.42530117027192066 and parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.18041728686941927, 'ffn_dropout': 0.11264108754126853, 'lr': 4.962079194793984e-05, 'weight_decay': 0.0008626335334910986, 'batch_size': 32}. Best is trial 12 with value: 0.43285145179010937. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.425301 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.18041728686941927, 'ffn_dropout': 0.11264108754126853, 'lr': 4.962079194793984e-05, 'weight_decay': 0.0008626335334910986, 'batch_size': 32} - Best Value (CSI): 0.432851 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.19629762465883627, 'ffn_dropout': 0.10602886629880709, 'lr': 0.00010096393518563076, 'weight_decay': 0.0008082976530795957, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 21:54:46,722] Trial 14 finished with value: 0.3972831331277789 and parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19067532756157915, 'ffn_dropout': 0.10979003854169951, 'lr': 1.8114802502367554e-05, 'weight_decay': 0.001204940422568156, 'batch_size': 32}. Best is trial 12 with value: 0.43285145179010937. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.397283 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19067532756157915, 'ffn_dropout': 0.10979003854169951, 'lr': 1.8114802502367554e-05, 'weight_decay': 0.001204940422568156, 'batch_size': 32} - Best Value (CSI): 0.432851 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.19629762465883627, 'ffn_dropout': 0.10602886629880709, 'lr': 0.00010096393518563076, 'weight_decay': 0.0008082976530795957, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 21:57:49,444] Trial 15 finished with value: 0.3794355947774739 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.18548075704642356, 'ffn_dropout': 0.1693140844425441, 'lr': 2.9510008201866402e-05, 'weight_decay': 0.07698800691804498, 'batch_size': 32}. Best is trial 12 with value: 0.43285145179010937. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.379436 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.18548075704642356, 'ffn_dropout': 0.1693140844425441, 'lr': 2.9510008201866402e-05, 'weight_decay': 0.07698800691804498, 'batch_size': 32} - Best Value (CSI): 0.432851 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.19629762465883627, 'ffn_dropout': 0.10602886629880709, 'lr': 0.00010096393518563076, 'weight_decay': 0.0008082976530795957, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 22:01:24,558] Trial 16 finished with value: 0.3727053563934914 and parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2290667457024898, 'ffn_dropout': 0.10549807703167577, 'lr': 3.326386548838545e-05, 'weight_decay': 0.000903196427161907, 'batch_size': 32}. Best is trial 12 with value: 0.43285145179010937. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.372705 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2290667457024898, 'ffn_dropout': 0.10549807703167577, 'lr': 3.326386548838545e-05, 'weight_decay': 0.000903196427161907, 'batch_size': 32} - Best Value (CSI): 0.432851 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.19629762465883627, 'ffn_dropout': 0.10602886629880709, 'lr': 0.00010096393518563076, 'weight_decay': 0.0008082976530795957, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 22:07:14,782] Trial 17 finished with value: 0.44057343009096755 and parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.16944490355028666, 'ffn_dropout': 0.14932148150310504, 'lr': 0.00012797632667353558, 'weight_decay': 0.0006203480378658751, 'batch_size': 32}. Best is trial 17 with value: 0.44057343009096755. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.440573 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.16944490355028666, 'ffn_dropout': 0.14932148150310504, 'lr': 0.00012797632667353558, 'weight_decay': 0.0006203480378658751, 'batch_size': 32} - Best Value (CSI): 0.440573 - Best Trial: 17 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.16944490355028666, 'ffn_dropout': 0.14932148150310504, 'lr': 0.00012797632667353558, 'weight_decay': 0.0006203480378658751, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 22:08:55,414] Trial 18 finished with value: 0.42534156192096617 and parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.15722836504645515, 'ffn_dropout': 0.15300674331169764, 'lr': 0.00013224064929378727, 'weight_decay': 0.0017291531999271655, 'batch_size': 256}. Best is trial 17 with value: 0.44057343009096755. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.425342 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.15722836504645515, 'ffn_dropout': 0.15300674331169764, 'lr': 0.00013224064929378727, 'weight_decay': 0.0017291531999271655, 'batch_size': 256} - Best Value (CSI): 0.440573 - Best Trial: 17 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.16944490355028666, 'ffn_dropout': 0.14932148150310504, 'lr': 0.00012797632667353558, 'weight_decay': 0.0006203480378658751, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 22:11:35,396] Trial 19 finished with value: 0.42547680691531214 and parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.21492770100564465, 'ffn_dropout': 0.17765308865183607, 'lr': 0.00013337847789394913, 'weight_decay': 0.000589014061788355, 'batch_size': 64}. Best is trial 17 with value: 0.44057343009096755. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.425477 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.21492770100564465, 'ffn_dropout': 0.17765308865183607, 'lr': 0.00013337847789394913, 'weight_decay': 0.000589014061788355, 'batch_size': 64} - Best Value (CSI): 0.440573 - Best Trial: 17 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.16944490355028666, 'ffn_dropout': 0.14932148150310504, 'lr': 0.00012797632667353558, 'weight_decay': 0.0006203480378658751, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 22:16:02,522] Trial 20 finished with value: 0.4199478691190693 and parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2551109743812424, 'ffn_dropout': 0.10005925493428475, 'lr': 0.0001446248966798091, 'weight_decay': 0.00044713327479039156, 'batch_size': 32}. Best is trial 17 with value: 0.44057343009096755. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.419948 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2551109743812424, 'ffn_dropout': 0.10005925493428475, 'lr': 0.0001446248966798091, 'weight_decay': 0.00044713327479039156, 'batch_size': 32} - Best Value (CSI): 0.440573 - Best Trial: 17 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.16944490355028666, 'ffn_dropout': 0.14932148150310504, 'lr': 0.00012797632667353558, 'weight_decay': 0.0006203480378658751, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 22:18:00,371] Trial 21 finished with value: 0.43292068719707527 and parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.21781385759759414, 'ffn_dropout': 0.18050520653533988, 'lr': 0.00011348629783939886, 'weight_decay': 0.0005283771455974894, 'batch_size': 64}. Best is trial 17 with value: 0.44057343009096755. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.432921 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.21781385759759414, 'ffn_dropout': 0.18050520653533988, 'lr': 0.00011348629783939886, 'weight_decay': 0.0005283771455974894, 'batch_size': 64} - Best Value (CSI): 0.440573 - Best Trial: 17 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.16944490355028666, 'ffn_dropout': 0.14932148150310504, 'lr': 0.00012797632667353558, 'weight_decay': 0.0006203480378658751, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 22:20:51,247] Trial 22 finished with value: 0.40580589408929885 and parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.20087117562256218, 'ffn_dropout': 0.14540865302065994, 'lr': 8.141490879403435e-05, 'weight_decay': 0.0017277855852907455, 'batch_size': 64}. Best is trial 17 with value: 0.44057343009096755. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.405806 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.20087117562256218, 'ffn_dropout': 0.14540865302065994, 'lr': 8.141490879403435e-05, 'weight_decay': 0.0017277855852907455, 'batch_size': 64} - Best Value (CSI): 0.440573 - Best Trial: 17 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.16944490355028666, 'ffn_dropout': 0.14932148150310504, 'lr': 0.00012797632667353558, 'weight_decay': 0.0006203480378658751, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 22:23:15,268] Trial 23 finished with value: 0.4408859654528239 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.16661944788187644, 'ffn_dropout': 0.1365300998885908, 'lr': 0.0002222655324389348, 'weight_decay': 0.0004932155242453681, 'batch_size': 64}. Best is trial 23 with value: 0.4408859654528239. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.440886 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.16661944788187644, 'ffn_dropout': 0.1365300998885908, 'lr': 0.0002222655324389348, 'weight_decay': 0.0004932155242453681, 'batch_size': 64} - Best Value (CSI): 0.440886 - Best Trial: 23 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.16661944788187644, 'ffn_dropout': 0.1365300998885908, 'lr': 0.0002222655324389348, 'weight_decay': 0.0004932155242453681, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-24 22:23:42,348] Trial 24 pruned. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.434590 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.14705689182560458, 'ffn_dropout': 0.2301422825067694, 'lr': 0.00020816470971717925, 'weight_decay': 0.0004033713902101654, 'batch_size': 64} - Best Value (CSI): 0.440886 - Best Trial: 23 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.16661944788187644, 'ffn_dropout': 0.1365300998885908, 'lr': 0.0002222655324389348, 'weight_decay': 0.0004932155242453681, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-24 22:24:07,160] Trial 25 pruned. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.370331 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.1685338645409166, 'ffn_dropout': 0.18788010363660446, 'lr': 0.0003041672280291468, 'weight_decay': 0.0004445217662058431, 'batch_size': 64} - Best Value (CSI): 0.440886 - Best Trial: 23 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.16661944788187644, 'ffn_dropout': 0.1365300998885908, 'lr': 0.0002222655324389348, 'weight_decay': 0.0004932155242453681, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-24 22:24:20,835] Trial 26 pruned. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.365556 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.13169377571165716, 'ffn_dropout': 0.14046492811902309, 'lr': 4.2113462512600025e-05, 'weight_decay': 0.0002049665233559899, 'batch_size': 64} - Best Value (CSI): 0.440886 - Best Trial: 23 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.16661944788187644, 'ffn_dropout': 0.1365300998885908, 'lr': 0.0002222655324389348, 'weight_decay': 0.0004932155242453681, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-24 22:24:37,528] Trial 27 pruned. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.072703 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.170471740004805, 'ffn_dropout': 0.1740898576481405, 'lr': 0.0010139822728750698, 'weight_decay': 0.0015293463948971167, 'batch_size': 64} - Best Value (CSI): 0.440886 - Best Trial: 23 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.16661944788187644, 'ffn_dropout': 0.1365300998885908, 'lr': 0.0002222655324389348, 'weight_decay': 0.0004932155242453681, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 22:27:17,552] Trial 28 pruned. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.407834 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.12683701914949141, 'ffn_dropout': 0.15774549247346611, 'lr': 0.00018737159989240586, 'weight_decay': 0.0005829380100391147, 'batch_size': 64} - Best Value (CSI): 0.440886 - Best Trial: 23 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.16661944788187644, 'ffn_dropout': 0.1365300998885908, 'lr': 0.0002222655324389348, 'weight_decay': 0.0004932155242453681, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 22:29:03,329] Trial 29 finished with value: 0.4396152183492245 and parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.12145056202742249, 'ffn_dropout': 0.13232742929659472, 'lr': 0.00039116251467073395, 'weight_decay': 0.002460668243223156, 'batch_size': 64}. Best is trial 23 with value: 0.4408859654528239. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.439615 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.12145056202742249, 'ffn_dropout': 0.13232742929659472, 'lr': 0.00039116251467073395, 'weight_decay': 0.002460668243223156, 'batch_size': 64} - Best Value (CSI): 0.440886 - Best Trial: 23 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.16661944788187644, 'ffn_dropout': 0.1365300998885908, 'lr': 0.0002222655324389348, 'weight_decay': 0.0004932155242453681, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-24 22:29:23,422] Trial 30 pruned. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.367421 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1142574177320691, 'ffn_dropout': 0.130643704121932, 'lr': 0.000531578567195389, 'weight_decay': 0.0023046646708570753, 'batch_size': 64} - Best Value (CSI): 0.440886 - Best Trial: 23 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.16661944788187644, 'ffn_dropout': 0.1365300998885908, 'lr': 0.0002222655324389348, 'weight_decay': 0.0004932155242453681, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 22:30:57,364] Trial 31 finished with value: 0.42099865366393896 and parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.15166548342855268, 'ffn_dropout': 0.16066114076365856, 'lr': 0.0002701874393601726, 'weight_decay': 0.00117234538978594, 'batch_size': 64}. Best is trial 23 with value: 0.4408859654528239. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.420999 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.15166548342855268, 'ffn_dropout': 0.16066114076365856, 'lr': 0.0002701874393601726, 'weight_decay': 0.00117234538978594, 'batch_size': 64} - Best Value (CSI): 0.440886 - Best Trial: 23 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.16661944788187644, 'ffn_dropout': 0.1365300998885908, 'lr': 0.0002222655324389348, 'weight_decay': 0.0004932155242453681, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 22:33:22,460] Trial 32 finished with value: 0.43915337225108164 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1221769529687865, 'ffn_dropout': 0.16767607964339762, 'lr': 0.00014558794815515584, 'weight_decay': 0.004157011020491038, 'batch_size': 64}. Best is trial 23 with value: 0.4408859654528239. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.439153 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1221769529687865, 'ffn_dropout': 0.16767607964339762, 'lr': 0.00014558794815515584, 'weight_decay': 0.004157011020491038, 'batch_size': 64} - Best Value (CSI): 0.440886 - Best Trial: 23 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.16661944788187644, 'ffn_dropout': 0.1365300998885908, 'lr': 0.0002222655324389348, 'weight_decay': 0.0004932155242453681, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 22:35:13,226] Trial 33 finished with value: 0.43008947421556815 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.10736309598341608, 'ffn_dropout': 0.12980279907750716, 'lr': 0.00040532762714498544, 'weight_decay': 0.0037310271593565957, 'batch_size': 64}. Best is trial 23 with value: 0.4408859654528239. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.430089 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.10736309598341608, 'ffn_dropout': 0.12980279907750716, 'lr': 0.00040532762714498544, 'weight_decay': 0.0037310271593565957, 'batch_size': 64} - Best Value (CSI): 0.440886 - Best Trial: 23 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.16661944788187644, 'ffn_dropout': 0.1365300998885908, 'lr': 0.0002222655324389348, 'weight_decay': 0.0004932155242453681, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 22:37:53,266] Trial 34 finished with value: 0.44685896765010097 and parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64}. Best is trial 34 with value: 0.44685896765010097. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.446859 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-24 22:38:00,660] Trial 35 pruned. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.396004 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.14462296702616304, 'ffn_dropout': 0.1246760481582648, 'lr': 6.105469388743497e-05, 'weight_decay': 0.0028938948699263984, 'batch_size': 128} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-24 22:38:16,915] Trial 36 pruned. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.365191 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.12035079804650102, 'ffn_dropout': 0.149510124200388, 'lr': 0.00047174414036001605, 'weight_decay': 0.0023551475298550285, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 22:39:07,695] Trial 37 finished with value: 0.4223602210445432 and parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.1044373307277818, 'ffn_dropout': 0.14263573465399085, 'lr': 0.000302613226111262, 'weight_decay': 0.006740169967352519, 'batch_size': 256}. Best is trial 34 with value: 0.44685896765010097. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.422360 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.1044373307277818, 'ffn_dropout': 0.14263573465399085, 'lr': 0.000302613226111262, 'weight_decay': 0.006740169967352519, 'batch_size': 256} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-24 22:39:20,977] Trial 38 pruned. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.243961 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13290415702752417, 'ffn_dropout': 0.24727900746308162, 'lr': 0.0012326041722119587, 'weight_decay': 0.00031406212349913685, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 22:40:21,990] Trial 39 finished with value: 0.41469884778442173 and parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.16442188296374266, 'ffn_dropout': 0.16210633970415922, 'lr': 0.000186974792225708, 'weight_decay': 0.001286264250306955, 'batch_size': 128}. Best is trial 34 with value: 0.44685896765010097. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.414699 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.16442188296374266, 'ffn_dropout': 0.16210633970415922, 'lr': 0.000186974792225708, 'weight_decay': 0.001286264250306955, 'batch_size': 128} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-24 22:40:32,679] Trial 40 pruned. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.372744 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.1484605446567468, 'ffn_dropout': 0.20025990884967768, 'lr': 8.575112371582988e-05, 'weight_decay': 0.004599717044616802, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 22:42:14,884] Trial 41 finished with value: 0.43206459687410587 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.12273785426811507, 'ffn_dropout': 0.12118736956983608, 'lr': 0.00015856243255226292, 'weight_decay': 0.005083269704223034, 'batch_size': 64}. Best is trial 34 with value: 0.44685896765010097. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.432065 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.12273785426811507, 'ffn_dropout': 0.12118736956983608, 'lr': 0.00015856243255226292, 'weight_decay': 0.005083269704223034, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 22:44:21,423] Trial 42 finished with value: 0.4446825582887692 and parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.13892275054841433, 'ffn_dropout': 0.1619381505259511, 'lr': 0.0002641210845173141, 'weight_decay': 0.0029389595891957812, 'batch_size': 64}. Best is trial 34 with value: 0.44685896765010097. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.444683 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.13892275054841433, 'ffn_dropout': 0.1619381505259511, 'lr': 0.0002641210845173141, 'weight_decay': 0.0029389595891957812, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 22:46:10,351] Trial 43 finished with value: 0.43266945617122116 and parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.13930046596010037, 'ffn_dropout': 0.13752346272528815, 'lr': 0.0002450579923866201, 'weight_decay': 0.0023122652226731906, 'batch_size': 64}. Best is trial 34 with value: 0.44685896765010097. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.432669 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.13930046596010037, 'ffn_dropout': 0.13752346272528815, 'lr': 0.0002450579923866201, 'weight_decay': 0.0023122652226731906, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-24 22:46:20,895] Trial 44 pruned. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.365179 - Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.15857297194981307, 'ffn_dropout': 0.18772362749618376, 'lr': 0.0003675467030114775, 'weight_decay': 0.0028527944682771346, 'batch_size': 256} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 22:47:20,085] Trial 45 finished with value: 0.433653323906144 and parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.13741300344344057, 'ffn_dropout': 0.12174163946124844, 'lr': 0.00023551225141755434, 'weight_decay': 0.0018218549065596849, 'batch_size': 128}. Best is trial 34 with value: 0.44685896765010097. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.433653 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.13741300344344057, 'ffn_dropout': 0.12174163946124844, 'lr': 0.00023551225141755434, 'weight_decay': 0.0018218549065596849, 'batch_size': 128} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-24 22:47:35,908] Trial 46 pruned. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.371152 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11140605860647304, 'ffn_dropout': 0.14995680233029204, 'lr': 0.0006414506865666999, 'weight_decay': 0.005916597420457188, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-24 22:47:56,796] Trial 47 pruned. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.426773 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10241782277076769, 'ffn_dropout': 0.21581324465994434, 'lr': 9.59311189039552e-05, 'weight_decay': 0.0032458152681815247, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 22:51:40,214] Trial 48 finished with value: 0.4108988981847557 and parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.1766665260205816, 'ffn_dropout': 0.16708583462416718, 'lr': 0.00037018571042276747, 'weight_decay': 0.00906381865144435, 'batch_size': 32}. Best is trial 34 with value: 0.44685896765010097. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.410899 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.1766665260205816, 'ffn_dropout': 0.16708583462416718, 'lr': 0.00037018571042276747, 'weight_decay': 0.00906381865144435, 'batch_size': 32} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-24 22:51:53,997] Trial 49 pruned. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.430528 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.16412432501674917, 'ffn_dropout': 0.13472811453248745, 'lr': 0.000115708873562184, 'weight_decay': 0.000730188816522402, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-24 22:51:58,560] Trial 50 pruned. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.362816 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.17873897097830344, 'ffn_dropout': 0.1969202419055362, 'lr': 0.00018268836856962564, 'weight_decay': 0.0010906775597055035, 'batch_size': 256} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 22:53:53,517] Trial 51 finished with value: 0.43505520810714465 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.11836095934456023, 'ffn_dropout': 0.16729729931532022, 'lr': 0.0001518861250427379, 'weight_decay': 0.003900931709043469, 'batch_size': 64}. Best is trial 34 with value: 0.44685896765010097. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.435055 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.11836095934456023, 'ffn_dropout': 0.16729729931532022, 'lr': 0.0001518861250427379, 'weight_decay': 0.003900931709043469, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 22:55:39,850] Trial 52 finished with value: 0.42993099838054566 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1276642556550645, 'ffn_dropout': 0.11516472013799388, 'lr': 0.00026317842150197864, 'weight_decay': 0.0045182481945233634, 'batch_size': 64}. Best is trial 34 with value: 0.44685896765010097. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.429931 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1276642556550645, 'ffn_dropout': 0.11516472013799388, 'lr': 0.00026317842150197864, 'weight_decay': 0.0045182481945233634, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-24 22:55:54,276] Trial 53 pruned. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.413428 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.14123769766505162, 'ffn_dropout': 0.18205419602763703, 'lr': 0.00010649389516004006, 'weight_decay': 0.013794606390772679, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 22:59:18,037] Trial 54 finished with value: 0.422165865623137 and parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.10046554992944573, 'ffn_dropout': 0.15479480405640608, 'lr': 6.702440851520361e-05, 'weight_decay': 0.0064016116149720245, 'batch_size': 32}. Best is trial 34 with value: 0.44685896765010097. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.422166 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.10046554992944573, 'ffn_dropout': 0.15479480405640608, 'lr': 6.702440851520361e-05, 'weight_decay': 0.0064016116149720245, 'batch_size': 32} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 23:01:05,420] Trial 55 finished with value: 0.42987156262218523 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.15589057881876345, 'ffn_dropout': 0.11321831314617826, 'lr': 0.00015180347427543685, 'weight_decay': 0.001498105803813603, 'batch_size': 64}. Best is trial 34 with value: 0.44685896765010097. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.429872 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.15589057881876345, 'ffn_dropout': 0.11321831314617826, 'lr': 0.00015180347427543685, 'weight_decay': 0.001498105803813603, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-24 23:01:50,069] Trial 56 pruned. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.414938 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.12502416532004454, 'ffn_dropout': 0.17195491618563047, 'lr': 0.00020932360677364286, 'weight_decay': 0.0007618644733752707, 'batch_size': 32} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 23:04:10,696] Trial 57 finished with value: 0.43792688267252666 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.14308764252702494, 'ffn_dropout': 0.13635105515146415, 'lr': 0.0003351061913252913, 'weight_decay': 0.0010446177301177196, 'batch_size': 64}. Best is trial 34 with value: 0.44685896765010097. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.437927 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.14308764252702494, 'ffn_dropout': 0.13635105515146415, 'lr': 0.0003351061913252913, 'weight_decay': 0.0010446177301177196, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 23:05:45,449] Trial 58 finished with value: 0.4314030798769573 and parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.11734004375718132, 'ffn_dropout': 0.15444538716281442, 'lr': 0.0004885988765810802, 'weight_decay': 0.003499031815938539, 'batch_size': 128}. Best is trial 34 with value: 0.44685896765010097. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.431403 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.11734004375718132, 'ffn_dropout': 0.15444538716281442, 'lr': 0.0004885988765810802, 'weight_decay': 0.003499031815938539, 'batch_size': 128} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-24 23:05:56,841] Trial 59 pruned. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.340792 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.13304855500949794, 'ffn_dropout': 0.14371712316118468, 'lr': 0.00012818684309719898, 'weight_decay': 0.002068584440869597, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 23:08:39,563] Trial 60 finished with value: 0.4183339755039925 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.19330983418143388, 'ffn_dropout': 0.10110453974514497, 'lr': 8.583449563416909e-05, 'weight_decay': 0.002721435555248054, 'batch_size': 32}. Best is trial 34 with value: 0.44685896765010097. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.418334 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.19330983418143388, 'ffn_dropout': 0.10110453974514497, 'lr': 8.583449563416909e-05, 'weight_decay': 0.002721435555248054, 'batch_size': 32} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 23:10:39,268] Trial 61 finished with value: 0.4268362832508313 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.14403008537893516, 'ffn_dropout': 0.13629366518715721, 'lr': 0.0002613018566136403, 'weight_decay': 0.0010618237005948106, 'batch_size': 64}. Best is trial 34 with value: 0.44685896765010097. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.426836 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.14403008537893516, 'ffn_dropout': 0.13629366518715721, 'lr': 0.0002613018566136403, 'weight_decay': 0.0010618237005948106, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 23:13:01,847] Trial 62 finished with value: 0.4360677530223788 and parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1503473590815548, 'ffn_dropout': 0.16185994294607334, 'lr': 0.00017752392111640842, 'weight_decay': 0.001394367403221107, 'batch_size': 64}. Best is trial 34 with value: 0.44685896765010097. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.436068 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1503473590815548, 'ffn_dropout': 0.16185994294607334, 'lr': 0.00017752392111640842, 'weight_decay': 0.001394367403221107, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-24 23:13:29,817] Trial 63 pruned. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.443038 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.11065610995348804, 'ffn_dropout': 0.12695571161808028, 'lr': 0.0002885646584172064, 'weight_decay': 0.000679344219588653, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 23:15:23,784] Trial 64 finished with value: 0.437579723259043 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.17119424292801105, 'ffn_dropout': 0.1755835705372324, 'lr': 0.00033355028398536333, 'weight_decay': 0.0009619433383730276, 'batch_size': 64}. Best is trial 34 with value: 0.44685896765010097. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.437580 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.17119424292801105, 'ffn_dropout': 0.1755835705372324, 'lr': 0.00033355028398536333, 'weight_decay': 0.0009619433383730276, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-24 23:15:49,548] Trial 65 pruned. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.414395 - Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.15995244313171714, 'ffn_dropout': 0.1469650849132134, 'lr': 0.00020932639011696742, 'weight_decay': 0.001864522752897311, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-24 23:16:03,308] Trial 66 pruned. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.425864 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1338358315764653, 'ffn_dropout': 0.11643755871045142, 'lr': 0.00012607479252254634, 'weight_decay': 0.0003970226578472575, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 23:18:15,306] Trial 67 finished with value: 0.4377719654479156 and parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11548257721205969, 'ffn_dropout': 0.136160791794505, 'lr': 0.00033324894731611945, 'weight_decay': 0.0015230991516363463, 'batch_size': 64}. Best is trial 34 with value: 0.44685896765010097. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.437772 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11548257721205969, 'ffn_dropout': 0.136160791794505, 'lr': 0.00033324894731611945, 'weight_decay': 0.0015230991516363463, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-24 23:18:49,049] Trial 68 pruned. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.258376 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1833908763547541, 'ffn_dropout': 0.11055988012166172, 'lr': 0.0006009206135324157, 'weight_decay': 0.000953195189727053, 'batch_size': 32} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-24 23:18:58,452] Trial 69 pruned. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.404412 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.15242147407379378, 'ffn_dropout': 0.1540705336246568, 'lr': 0.0005012376140565922, 'weight_decay': 0.0005463731094503438, 'batch_size': 256} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-24 23:19:15,048] Trial 70 pruned. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.373062 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12216833488908127, 'ffn_dropout': 0.1647921326873882, 'lr': 0.0003906610038721315, 'weight_decay': 0.0025535524488692544, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 23:21:27,903] Trial 71 finished with value: 0.435993517682358 and parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11219350448211339, 'ffn_dropout': 0.13654059376463895, 'lr': 0.00022505341172976073, 'weight_decay': 0.0015301267090640357, 'batch_size': 64}. Best is trial 34 with value: 0.44685896765010097. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.435994 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11219350448211339, 'ffn_dropout': 0.13654059376463895, 'lr': 0.00022505341172976073, 'weight_decay': 0.0015301267090640357, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 23:23:47,481] Trial 72 finished with value: 0.4347462872278883 and parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.12930459247642412, 'ffn_dropout': 0.13322573141255908, 'lr': 0.00031843077613118035, 'weight_decay': 0.0012381531015066725, 'batch_size': 64}. Best is trial 34 with value: 0.44685896765010097. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.434746 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.12930459247642412, 'ffn_dropout': 0.13322573141255908, 'lr': 0.00031843077613118035, 'weight_decay': 0.0012381531015066725, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 23:25:50,839] Trial 73 finished with value: 0.43610147759642154 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.13839404989020693, 'ffn_dropout': 0.12690642557506082, 'lr': 0.00016538841091805762, 'weight_decay': 0.0032412212655670886, 'batch_size': 64}. Best is trial 34 with value: 0.44685896765010097. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.436101 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.13839404989020693, 'ffn_dropout': 0.12690642557506082, 'lr': 0.00016538841091805762, 'weight_decay': 0.0032412212655670886, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 23:29:01,507] Trial 74 finished with value: 0.4312383091437722 and parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.11653855622684464, 'ffn_dropout': 0.14275929767641615, 'lr': 0.00028460617114638235, 'weight_decay': 0.002006987988284185, 'batch_size': 64}. Best is trial 34 with value: 0.44685896765010097. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.431238 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.11653855622684464, 'ffn_dropout': 0.14275929767641615, 'lr': 0.00028460617114638235, 'weight_decay': 0.002006987988284185, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 23:30:42,138] Trial 75 finished with value: 0.42427663968001644 and parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.14405291157126954, 'ffn_dropout': 0.147497862375569, 'lr': 0.0004131545606780899, 'weight_decay': 0.0008840203906735652, 'batch_size': 64}. Best is trial 34 with value: 0.44685896765010097. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.424277 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.14405291157126954, 'ffn_dropout': 0.147497862375569, 'lr': 0.0004131545606780899, 'weight_decay': 0.0008840203906735652, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 23:33:00,700] Trial 76 finished with value: 0.42898336743700877 and parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1250015471873365, 'ffn_dropout': 0.15991870248319542, 'lr': 0.00010685658625210783, 'weight_decay': 0.002498587295823636, 'batch_size': 64}. Best is trial 34 with value: 0.44685896765010097. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.428983 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1250015471873365, 'ffn_dropout': 0.15991870248319542, 'lr': 0.00010685658625210783, 'weight_decay': 0.002498587295823636, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-24 23:33:14,606] Trial 77 pruned. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.409297 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.10916975712623853, 'ffn_dropout': 0.12418717001937549, 'lr': 0.00021568999421121357, 'weight_decay': 0.0015752792074903558, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-24 23:33:55,820] Trial 78 pruned. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.335780 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10016287107992053, 'ffn_dropout': 0.17272849593417253, 'lr': 0.0003411300597292981, 'weight_decay': 0.0041576908411654805, 'batch_size': 32} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 23:35:59,362] Trial 79 finished with value: 0.4390793126260876 and parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1550532097382014, 'ffn_dropout': 0.1818794838732973, 'lr': 0.000148253884079043, 'weight_decay': 0.0013142271522298573, 'batch_size': 64}. Best is trial 34 with value: 0.44685896765010097. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.439079 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1550532097382014, 'ffn_dropout': 0.1818794838732973, 'lr': 0.000148253884079043, 'weight_decay': 0.0013142271522298573, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-24 23:36:05,974] Trial 80 pruned. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.377093 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1655555030444613, 'ffn_dropout': 0.18243629556107993, 'lr': 0.00014206535072706176, 'weight_decay': 0.0006840114135102137, 'batch_size': 128} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 23:38:14,837] Trial 81 finished with value: 0.4343994600543056 and parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.15196026906780236, 'ffn_dropout': 0.1396717652358687, 'lr': 0.0001791175945997799, 'weight_decay': 0.002149480908811411, 'batch_size': 64}. Best is trial 34 with value: 0.44685896765010097. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.434399 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.15196026906780236, 'ffn_dropout': 0.1396717652358687, 'lr': 0.0001791175945997799, 'weight_decay': 0.002149480908811411, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-24 23:38:48,142] Trial 82 pruned. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.345076 - Parameters: {'d_token': 256, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.1397416566595478, 'ffn_dropout': 0.1535063865271314, 'lr': 0.00023753423772434744, 'weight_decay': 0.0017162014159020965, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 23:40:39,916] Trial 83 finished with value: 0.42227034403006697 and parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13271606872472977, 'ffn_dropout': 0.13194523085355503, 'lr': 0.0001322145881891085, 'weight_decay': 0.0012002010920918662, 'batch_size': 64}. Best is trial 34 with value: 0.44685896765010097. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.422270 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13271606872472977, 'ffn_dropout': 0.13194523085355503, 'lr': 0.0001322145881891085, 'weight_decay': 0.0012002010920918662, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-24 23:41:02,396] Trial 84 pruned. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.340257 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1579641531734757, 'ffn_dropout': 0.1685644367244534, 'lr': 0.0004262760084174622, 'weight_decay': 0.0013245417955253717, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-24 23:41:19,420] Trial 85 pruned. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.423077 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.12574703884866506, 'ffn_dropout': 0.11856014757578794, 'lr': 7.661706039833143e-05, 'weight_decay': 0.0030229419881972566, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-24 23:41:23,923] Trial 86 pruned. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.402184 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.14658612350938036, 'ffn_dropout': 0.14794954396294077, 'lr': 0.00010586659867601494, 'weight_decay': 0.0019688613523105836, 'batch_size': 256} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-24 23:41:44,870] Trial 87 pruned. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.431214 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.17285217214915596, 'ffn_dropout': 0.1595334198213084, 'lr': 0.0001608793243989159, 'weight_decay': 0.0008323042035421292, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) -[I 2025-12-24 23:42:02,780] Trial 88 pruned. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.415642 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11748267530584228, 'ffn_dropout': 0.19171733739605576, 'lr': 0.00025812722699980017, 'weight_decay': 0.0010580913210353126, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 23:44:29,812] Trial 89 finished with value: 0.40891192863339976 and parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.13725038838012077, 'ffn_dropout': 0.18277621350532858, 'lr': 0.00020032994389305542, 'weight_decay': 0.0034887933999480612, 'batch_size': 32}. Best is trial 34 with value: 0.44685896765010097. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.408912 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.13725038838012077, 'ffn_dropout': 0.18277621350532858, 'lr': 0.00020032994389305542, 'weight_decay': 0.0034887933999480612, 'batch_size': 32} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 23:46:22,137] Trial 90 pruned. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.409722 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1065001382341087, 'ffn_dropout': 0.10891632331387538, 'lr': 0.00031086432567882337, 'weight_decay': 0.0006128406106834008, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 23:48:35,512] Trial 91 finished with value: 0.4388294109525152 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1757127498318602, 'ffn_dropout': 0.17317353223764714, 'lr': 0.00034463574291892493, 'weight_decay': 0.0009371440081303333, 'batch_size': 64}. Best is trial 34 with value: 0.44685896765010097. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.438829 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1757127498318602, 'ffn_dropout': 0.17317353223764714, 'lr': 0.00034463574291892493, 'weight_decay': 0.0009371440081303333, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 23:50:11,888] Trial 92 finished with value: 0.4237766217155063 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.16466070449465317, 'ffn_dropout': 0.17511994782534973, 'lr': 0.0004476506576582681, 'weight_decay': 0.0004670382692755319, 'batch_size': 64}. Best is trial 34 with value: 0.44685896765010097. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.423777 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.16466070449465317, 'ffn_dropout': 0.17511994782534973, 'lr': 0.0004476506576582681, 'weight_decay': 0.0004670382692755319, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 23:52:24,776] Trial 93 pruned. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.412698 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1889739099450263, 'ffn_dropout': 0.14014996902219434, 'lr': 0.00035621865439225105, 'weight_decay': 0.0013901341053616685, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 23:54:19,805] Trial 94 finished with value: 0.42786243764426807 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.20234990861285176, 'ffn_dropout': 0.16680573566616572, 'lr': 0.0002397713518372184, 'weight_decay': 0.001724666556849769, 'batch_size': 64}. Best is trial 34 with value: 0.44685896765010097. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.427862 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.20234990861285176, 'ffn_dropout': 0.16680573566616572, 'lr': 0.0002397713518372184, 'weight_decay': 0.001724666556849769, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 23:55:57,531] Trial 95 finished with value: 0.43135514774246975 and parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1461188107174643, 'ffn_dropout': 0.15633331482440302, 'lr': 0.0001943057787945578, 'weight_decay': 0.0024840617639411058, 'batch_size': 64}. Best is trial 34 with value: 0.44685896765010097. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.431355 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1461188107174643, 'ffn_dropout': 0.15633331482440302, 'lr': 0.0001943057787945578, 'weight_decay': 0.0024840617639411058, 'batch_size': 64} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 23:57:03,852] Trial 96 finished with value: 0.44356656238053443 and parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.17413605614106317, 'ffn_dropout': 0.13008596176993953, 'lr': 0.0002922785952231531, 'weight_decay': 0.0007965811418392027, 'batch_size': 128}. Best is trial 34 with value: 0.44685896765010097. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.443567 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.17413605614106317, 'ffn_dropout': 0.13008596176993953, 'lr': 0.0002922785952231531, 'weight_decay': 0.0007965811418392027, 'batch_size': 128} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 23:58:02,932] Trial 97 finished with value: 0.43062295906473214 and parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.17190352061838166, 'ffn_dropout': 0.146661184021868, 'lr': 0.00016085569673664242, 'weight_decay': 0.0005990250766392707, 'batch_size': 128}. Best is trial 34 with value: 0.44685896765010097. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.430623 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.17190352061838166, 'ffn_dropout': 0.146661184021868, 'lr': 0.00016085569673664242, 'weight_decay': 0.0005990250766392707, 'batch_size': 128} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-24 23:59:08,087] Trial 98 finished with value: 0.42054051764302797 and parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.17888044483600604, 'ffn_dropout': 0.12169457530144016, 'lr': 0.00012237394433629615, 'weight_decay': 0.0007302890920701455, 'batch_size': 128}. Best is trial 34 with value: 0.44685896765010097. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.420541 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.17888044483600604, 'ffn_dropout': 0.12169457530144016, 'lr': 0.00012237394433629615, 'weight_decay': 0.0007302890920701455, 'batch_size': 128} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 110.18867924528301, 1: 5.98974358974359, 2: 0.354111084162018} (클래스별 샘플 수: {0: 53, 1: 975, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 77.97333333333333, 1: 5.778656126482214, 2: 0.3553503068603026} (클래스별 샘플 수: {0: 75, 1: 1012, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 97.46666666666667, 1: 5.5961722488038275, 2: 0.3557394002068252} (클래스별 샘플 수: {0: 60, 1: 1045, 2: 16439}) -[I 2025-12-25 00:00:22,256] Trial 99 finished with value: 0.43343416605689183 and parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.1601821574440112, 'ffn_dropout': 0.12976073895601006, 'lr': 0.00026851535849948567, 'weight_decay': 0.0008776216136817475, 'batch_size': 128}. Best is trial 34 with value: 0.44685896765010097. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.433434 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.1601821574440112, 'ffn_dropout': 0.12976073895601006, 'lr': 0.00026851535849948567, 'weight_decay': 0.0008776216136817475, 'batch_size': 128} - Best Value (CSI): 0.446859 - Best Trial: 34 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.4469 -Best Hyperparameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11973480060658612, 'ffn_dropout': 0.15614454735278546, 'lr': 0.00016413327466283583, 'weight_decay': 0.002548468041818763, 'batch_size': 64} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.2717 - - 최종 CSI: 0.4334 - - 최고 CSI: 0.4469 - - 최저 CSI: 0.0576 - - 평균 CSI: 0.4003 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/ft_transformer_pure_busan_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 40, Best CSI: 0.4700 - Fold 1 학습 완료 (검증 CSI: 0.4700) -Fold 2 학습 중... - Early stopping at epoch 45, Best CSI: 0.4465 - Fold 2 학습 완료 (검증 CSI: 0.4465) -Fold 3 학습 중... - Early stopping at epoch 48, Best CSI: 0.4121 - Fold 3 학습 완료 (검증 CSI: 0.4121) - -모든 모델 저장 완료: ../save_model/ft_transformer_optima/ft_transformer_pure_busan.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/ft_transformer_optima/scaler/ft_transformer_pure_busan_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: - - . - - . - - / - - s - - a - - v - - e - - _ - - m - - o - - d - - e - - l - - / - - f - - t - - _ - - t - - r - - a - - n - - s - - f - - o - - r - - m - - e - - r - - _ - - o - - p - - t - - i - - m - - a - - / - - f - - t - - _ - - t - - r - - a - - n - - s - - f - - o - - r - - m - - e - - r - - _ - - p - - u - - r - - e - - _ - - b - - u - - s - - a - - n - - . - - p - - k - - l - -✓ 완료: ft_transformer_pure/ft_transforemer_pure_busan.py (소요 시간: 10631초) - ----------------------------------------- -실행 중: ft_transformer_pure/ft_transforemer_pure_daegu.py -시작 시간: 2025-12-25 00:03:02 ----------------------------------------- -[I 2025-12-25 00:03:03,477] A new study created in memory with name: no-name-57303f6f-9fca-4a7e-9adb-baf8ef76290d - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 00:04:07,276] Trial 0 finished with value: 0.29640492038291927 and parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3381230287461169, 'ffn_dropout': 0.36757338932332717, 'lr': 0.0014413286388068006, 'weight_decay': 0.010927123335060396, 'batch_size': 128}. Best is trial 0 with value: 0.29640492038291927. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.296405 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3381230287461169, 'ffn_dropout': 0.36757338932332717, 'lr': 0.0014413286388068006, 'weight_decay': 0.010927123335060396, 'batch_size': 128} - Best Value (CSI): 0.296405 - Best Trial: 0 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3381230287461169, 'ffn_dropout': 0.36757338932332717, 'lr': 0.0014413286388068006, 'weight_decay': 0.010927123335060396, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 00:05:25,980] Trial 1 finished with value: 0.05034594666863255 and parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.39087698016863215, 'ffn_dropout': 0.11898414611002428, 'lr': 0.001452510613654026, 'weight_decay': 0.00044599179342484684, 'batch_size': 64}. Best is trial 0 with value: 0.29640492038291927. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.050346 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.39087698016863215, 'ffn_dropout': 0.11898414611002428, 'lr': 0.001452510613654026, 'weight_decay': 0.00044599179342484684, 'batch_size': 64} - Best Value (CSI): 0.296405 - Best Trial: 0 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3381230287461169, 'ffn_dropout': 0.36757338932332717, 'lr': 0.0014413286388068006, 'weight_decay': 0.010927123335060396, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 00:06:10,468] Trial 2 finished with value: 0.3107880741325129 and parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.30512974907178914, 'ffn_dropout': 0.21970635664817653, 'lr': 0.000102852057681668, 'weight_decay': 0.00725358763806132, 'batch_size': 256}. Best is trial 2 with value: 0.3107880741325129. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.310788 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.30512974907178914, 'ffn_dropout': 0.21970635664817653, 'lr': 0.000102852057681668, 'weight_decay': 0.00725358763806132, 'batch_size': 256} - Best Value (CSI): 0.310788 - Best Trial: 2 - Best Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.30512974907178914, 'ffn_dropout': 0.21970635664817653, 'lr': 0.000102852057681668, 'weight_decay': 0.00725358763806132, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 00:06:40,173] Trial 3 finished with value: 0.26297613018764626 and parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.20586011480004948, 'ffn_dropout': 0.1390176554954961, 'lr': 0.0023164398302919172, 'weight_decay': 0.00010225359197346127, 'batch_size': 256}. Best is trial 2 with value: 0.3107880741325129. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.262976 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.20586011480004948, 'ffn_dropout': 0.1390176554954961, 'lr': 0.0023164398302919172, 'weight_decay': 0.00010225359197346127, 'batch_size': 256} - Best Value (CSI): 0.310788 - Best Trial: 2 - Best Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.30512974907178914, 'ffn_dropout': 0.21970635664817653, 'lr': 0.000102852057681668, 'weight_decay': 0.00725358763806132, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 00:11:20,229] Trial 4 finished with value: 0.3668187349867032 and parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2996103926982233, 'ffn_dropout': 0.14832668634755228, 'lr': 0.00010398138036962992, 'weight_decay': 0.06876687719690146, 'batch_size': 32}. Best is trial 4 with value: 0.3668187349867032. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.366819 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2996103926982233, 'ffn_dropout': 0.14832668634755228, 'lr': 0.00010398138036962992, 'weight_decay': 0.06876687719690146, 'batch_size': 32} - Best Value (CSI): 0.366819 - Best Trial: 4 - Best Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2996103926982233, 'ffn_dropout': 0.14832668634755228, 'lr': 0.00010398138036962992, 'weight_decay': 0.06876687719690146, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 00:11:57,332] Trial 5 pruned. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.192882 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.19950733516044453, 'ffn_dropout': 0.39764852055930777, 'lr': 1.0395846888169699e-05, 'weight_decay': 0.01769995069845971, 'batch_size': 32} - Best Value (CSI): 0.366819 - Best Trial: 4 - Best Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2996103926982233, 'ffn_dropout': 0.14832668634755228, 'lr': 0.00010398138036962992, 'weight_decay': 0.06876687719690146, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 00:13:04,756] Trial 6 finished with value: 0.3462053462346258 and parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3575813950382517, 'ffn_dropout': 0.17269873041744793, 'lr': 0.0001942566524715374, 'weight_decay': 0.020579710525079314, 'batch_size': 64}. Best is trial 4 with value: 0.3668187349867032. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.346205 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3575813950382517, 'ffn_dropout': 0.17269873041744793, 'lr': 0.0001942566524715374, 'weight_decay': 0.020579710525079314, 'batch_size': 64} - Best Value (CSI): 0.366819 - Best Trial: 4 - Best Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2996103926982233, 'ffn_dropout': 0.14832668634755228, 'lr': 0.00010398138036962992, 'weight_decay': 0.06876687719690146, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 00:13:52,372] Trial 7 finished with value: 0.3099725192421742 and parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.35672743118683026, 'ffn_dropout': 0.22696902030481328, 'lr': 0.0006125718433535596, 'weight_decay': 0.02082658000555602, 'batch_size': 256}. Best is trial 4 with value: 0.3668187349867032. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.309973 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.35672743118683026, 'ffn_dropout': 0.22696902030481328, 'lr': 0.0006125718433535596, 'weight_decay': 0.02082658000555602, 'batch_size': 256} - Best Value (CSI): 0.366819 - Best Trial: 4 - Best Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2996103926982233, 'ffn_dropout': 0.14832668634755228, 'lr': 0.00010398138036962992, 'weight_decay': 0.06876687719690146, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 00:14:04,109] Trial 8 pruned. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.177920 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.29473027671342156, 'ffn_dropout': 0.3300111152470837, 'lr': 5.3303470397916326e-05, 'weight_decay': 0.0023553640053748074, 'batch_size': 128} - Best Value (CSI): 0.366819 - Best Trial: 4 - Best Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2996103926982233, 'ffn_dropout': 0.14832668634755228, 'lr': 0.00010398138036962992, 'weight_decay': 0.06876687719690146, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 00:14:26,537] Trial 9 pruned. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.231765 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.31398045289883136, 'ffn_dropout': 0.21280289961488602, 'lr': 0.0004801779351694766, 'weight_decay': 0.010403740920260276, 'batch_size': 64} - Best Value (CSI): 0.366819 - Best Trial: 4 - Best Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2996103926982233, 'ffn_dropout': 0.14832668634755228, 'lr': 0.00010398138036962992, 'weight_decay': 0.06876687719690146, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 00:14:56,862] Trial 10 pruned. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.11410982397162447, 'ffn_dropout': 0.10811820161463548, 'lr': 0.004628623232471164, 'weight_decay': 0.0683400981411213, 'batch_size': 32} - Best Value (CSI): 0.366819 - Best Trial: 4 - Best Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2996103926982233, 'ffn_dropout': 0.14832668634755228, 'lr': 0.00010398138036962992, 'weight_decay': 0.06876687719690146, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 00:16:25,548] Trial 11 finished with value: 0.3418081636360529 and parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3995247187345581, 'ffn_dropout': 0.16263785361632307, 'lr': 0.00013852752835741633, 'weight_decay': 0.09258009920110537, 'batch_size': 64}. Best is trial 4 with value: 0.3668187349867032. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.341808 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3995247187345581, 'ffn_dropout': 0.16263785361632307, 'lr': 0.00013852752835741633, 'weight_decay': 0.09258009920110537, 'batch_size': 64} - Best Value (CSI): 0.366819 - Best Trial: 4 - Best Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2996103926982233, 'ffn_dropout': 0.14832668634755228, 'lr': 0.00010398138036962992, 'weight_decay': 0.06876687719690146, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 00:20:53,752] Trial 12 finished with value: 0.37102097275562435 and parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2515300932635287, 'ffn_dropout': 0.17239289985688716, 'lr': 0.00022084072000306073, 'weight_decay': 0.042215460556657966, 'batch_size': 32}. Best is trial 12 with value: 0.37102097275562435. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.371021 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2515300932635287, 'ffn_dropout': 0.17239289985688716, 'lr': 0.00022084072000306073, 'weight_decay': 0.042215460556657966, 'batch_size': 32} - Best Value (CSI): 0.371021 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2515300932635287, 'ffn_dropout': 0.17239289985688716, 'lr': 0.00022084072000306073, 'weight_decay': 0.042215460556657966, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 00:21:39,057] Trial 13 pruned. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.265217 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2546998253110153, 'ffn_dropout': 0.16393792606071905, 'lr': 4.768664499417311e-05, 'weight_decay': 0.059712910940831226, 'batch_size': 32} - Best Value (CSI): 0.371021 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2515300932635287, 'ffn_dropout': 0.17239289985688716, 'lr': 0.00022084072000306073, 'weight_decay': 0.042215460556657966, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 00:26:03,977] Trial 14 finished with value: 0.3604774056077337 and parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.2600901689614381, 'ffn_dropout': 0.258394378319389, 'lr': 0.0002987047063970269, 'weight_decay': 0.03910245029990228, 'batch_size': 32}. Best is trial 12 with value: 0.37102097275562435. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.360477 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.2600901689614381, 'ffn_dropout': 0.258394378319389, 'lr': 0.0002987047063970269, 'weight_decay': 0.03910245029990228, 'batch_size': 32} - Best Value (CSI): 0.371021 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2515300932635287, 'ffn_dropout': 0.17239289985688716, 'lr': 0.00022084072000306073, 'weight_decay': 0.042215460556657966, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 00:26:36,796] Trial 15 pruned. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2194669942019723, 'ffn_dropout': 0.10661868034076227, 'lr': 0.009441917837163808, 'weight_decay': 0.03947590595319887, 'batch_size': 32} - Best Value (CSI): 0.371021 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2515300932635287, 'ffn_dropout': 0.17239289985688716, 'lr': 0.00022084072000306073, 'weight_decay': 0.042215460556657966, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 00:28:55,247] Trial 16 finished with value: 0.33785353335346757 and parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.27463888766994204, 'ffn_dropout': 0.1851949543419541, 'lr': 0.0006303182901778837, 'weight_decay': 0.08604434356624223, 'batch_size': 32}. Best is trial 12 with value: 0.37102097275562435. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.337854 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.27463888766994204, 'ffn_dropout': 0.1851949543419541, 'lr': 0.0006303182901778837, 'weight_decay': 0.08604434356624223, 'batch_size': 32} - Best Value (CSI): 0.371021 - Best Trial: 12 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2515300932635287, 'ffn_dropout': 0.17239289985688716, 'lr': 0.00022084072000306073, 'weight_decay': 0.042215460556657966, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 00:33:41,546] Trial 17 finished with value: 0.3781935514399195 and parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.22468349766909257, 'ffn_dropout': 0.13603983401789904, 'lr': 7.722413778980943e-05, 'weight_decay': 0.004254290539938868, 'batch_size': 32}. Best is trial 17 with value: 0.3781935514399195. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.378194 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.22468349766909257, 'ffn_dropout': 0.13603983401789904, 'lr': 7.722413778980943e-05, 'weight_decay': 0.004254290539938868, 'batch_size': 32} - Best Value (CSI): 0.378194 - Best Trial: 17 - Best Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.22468349766909257, 'ffn_dropout': 0.13603983401789904, 'lr': 7.722413778980943e-05, 'weight_decay': 0.004254290539938868, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 00:38:21,165] Trial 18 finished with value: 0.3635361833263781 and parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.23005551233327268, 'ffn_dropout': 0.1371591619205612, 'lr': 3.394993471775902e-05, 'weight_decay': 0.0038194955307940333, 'batch_size': 32}. Best is trial 17 with value: 0.3781935514399195. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.363536 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.23005551233327268, 'ffn_dropout': 0.1371591619205612, 'lr': 3.394993471775902e-05, 'weight_decay': 0.0038194955307940333, 'batch_size': 32} - Best Value (CSI): 0.378194 - Best Trial: 17 - Best Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.22468349766909257, 'ffn_dropout': 0.13603983401789904, 'lr': 7.722413778980943e-05, 'weight_decay': 0.004254290539938868, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 00:38:34,237] Trial 19 pruned. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.216017 - Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.16701450542264093, 'ffn_dropout': 0.1913927816359933, 'lr': 0.00026869812422733387, 'weight_decay': 0.001520190460413396, 'batch_size': 128} - Best Value (CSI): 0.378194 - Best Trial: 17 - Best Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.22468349766909257, 'ffn_dropout': 0.13603983401789904, 'lr': 7.722413778980943e-05, 'weight_decay': 0.004254290539938868, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 00:43:03,216] Trial 20 pruned. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.378989 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.24027697569103826, 'ffn_dropout': 0.2549514754391863, 'lr': 2.712512810162597e-05, 'weight_decay': 0.004753392620564204, 'batch_size': 32} - Best Value (CSI): 0.378194 - Best Trial: 17 - Best Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.22468349766909257, 'ffn_dropout': 0.13603983401789904, 'lr': 7.722413778980943e-05, 'weight_decay': 0.004254290539938868, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 00:46:08,784] Trial 21 pruned. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.398241 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.28955563008050433, 'ffn_dropout': 0.14194676951666715, 'lr': 9.446466866633282e-05, 'weight_decay': 0.03551395818967427, 'batch_size': 32} - Best Value (CSI): 0.378194 - Best Trial: 17 - Best Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.22468349766909257, 'ffn_dropout': 0.13603983401789904, 'lr': 7.722413778980943e-05, 'weight_decay': 0.004254290539938868, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 00:49:44,195] Trial 22 finished with value: 0.37708810870616577 and parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2736667393384993, 'ffn_dropout': 0.15170625593594783, 'lr': 9.659707401306993e-05, 'weight_decay': 0.0298090327084465, 'batch_size': 32}. Best is trial 17 with value: 0.3781935514399195. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.377088 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2736667393384993, 'ffn_dropout': 0.15170625593594783, 'lr': 9.659707401306993e-05, 'weight_decay': 0.0298090327084465, 'batch_size': 32} - Best Value (CSI): 0.378194 - Best Trial: 17 - Best Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.22468349766909257, 'ffn_dropout': 0.13603983401789904, 'lr': 7.722413778980943e-05, 'weight_decay': 0.004254290539938868, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 00:51:07,912] Trial 23 pruned. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.362401 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2649784818886293, 'ffn_dropout': 0.10154704244458997, 'lr': 0.00018658315041770242, 'weight_decay': 0.014961751067695336, 'batch_size': 32} - Best Value (CSI): 0.378194 - Best Trial: 17 - Best Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.22468349766909257, 'ffn_dropout': 0.13603983401789904, 'lr': 7.722413778980943e-05, 'weight_decay': 0.004254290539938868, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 00:53:13,543] Trial 24 pruned. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.357471 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.23997995894306204, 'ffn_dropout': 0.12771001296875512, 'lr': 6.432800311001589e-05, 'weight_decay': 0.007364575003852467, 'batch_size': 32} - Best Value (CSI): 0.378194 - Best Trial: 17 - Best Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.22468349766909257, 'ffn_dropout': 0.13603983401789904, 'lr': 7.722413778980943e-05, 'weight_decay': 0.004254290539938868, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 00:56:02,205] Trial 25 finished with value: 0.3846594392002736 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32}. Best is trial 25 with value: 0.3846594392002736. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.384659 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 00:58:18,811] Trial 26 finished with value: 0.36795760244412906 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.276943901112094, 'ffn_dropout': 0.1853214861823787, 'lr': 0.0001462682045809044, 'weight_decay': 0.022542531674437004, 'batch_size': 32}. Best is trial 25 with value: 0.3846594392002736. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.367958 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.276943901112094, 'ffn_dropout': 0.1853214861823787, 'lr': 0.0001462682045809044, 'weight_decay': 0.022542531674437004, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 00:58:27,408] Trial 27 pruned. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.230683 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1851668595583471, 'ffn_dropout': 0.12819907056823646, 'lr': 7.466186862229132e-05, 'weight_decay': 0.027469178498408763, 'batch_size': 128} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 00:58:32,441] Trial 28 pruned. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.210359 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.22401980641948582, 'ffn_dropout': 0.15375703330088797, 'lr': 0.00039567638254670403, 'weight_decay': 0.01221021811704656, 'batch_size': 256} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 00:58:38,864] Trial 29 pruned. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.159314 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.32564210717116354, 'ffn_dropout': 0.1964478851149662, 'lr': 2.411338810295645e-05, 'weight_decay': 0.009340289027118242, 'batch_size': 128} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 00:59:35,785] Trial 30 pruned. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.356906 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.28174577482011315, 'ffn_dropout': 0.15578645391612983, 'lr': 0.00014306815925175246, 'weight_decay': 0.013644583383725588, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 01:02:42,323] Trial 31 finished with value: 0.3814997399916305 and parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2538965342701613, 'ffn_dropout': 0.1715270645347582, 'lr': 0.00024654793000754744, 'weight_decay': 0.04590813078125738, 'batch_size': 32}. Best is trial 25 with value: 0.3846594392002736. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.381500 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2538965342701613, 'ffn_dropout': 0.1715270645347582, 'lr': 0.00024654793000754744, 'weight_decay': 0.04590813078125738, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 01:03:30,978] Trial 32 pruned. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.112453 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2647336609800726, 'ffn_dropout': 0.14235115699424677, 'lr': 0.00034966277051878966, 'weight_decay': 0.031042471305895013, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 01:06:25,091] Trial 33 finished with value: 0.37126634054290425 and parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24253663844056722, 'ffn_dropout': 0.12447265813235775, 'lr': 9.056471868149548e-05, 'weight_decay': 0.05763534725554885, 'batch_size': 32}. Best is trial 25 with value: 0.3846594392002736. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.371266 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24253663844056722, 'ffn_dropout': 0.12447265813235775, 'lr': 9.056471868149548e-05, 'weight_decay': 0.05763534725554885, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 01:07:17,828] Trial 34 pruned. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.242206 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3131971064643815, 'ffn_dropout': 0.12382386634845254, 'lr': 0.00021940676645817666, 'weight_decay': 0.0059599212067557835, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 01:07:42,355] Trial 35 pruned. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.288212 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2810108559678304, 'ffn_dropout': 0.20523277305860907, 'lr': 0.000985234842015357, 'weight_decay': 0.024779667839241383, 'batch_size': 256} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 01:09:20,279] Trial 36 finished with value: 0.3595546205987475 and parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.29083608242093845, 'ffn_dropout': 0.17455951882678528, 'lr': 0.00011969498229601953, 'weight_decay': 0.01692278511021081, 'batch_size': 64}. Best is trial 25 with value: 0.3846594392002736. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.359555 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.29083608242093845, 'ffn_dropout': 0.17455951882678528, 'lr': 0.00011969498229601953, 'weight_decay': 0.01692278511021081, 'batch_size': 64} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 01:11:35,904] Trial 37 pruned. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.352034 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2155042585332457, 'ffn_dropout': 0.14904695830006562, 'lr': 7.670309549097895e-05, 'weight_decay': 0.008805186841907587, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 01:12:20,514] Trial 38 pruned. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.240000 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.30196495081849317, 'ffn_dropout': 0.22446686766337226, 'lr': 0.000194151028876896, 'weight_decay': 0.09926617301109392, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 01:12:26,212] Trial 39 pruned. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.201226 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3367792034467395, 'ffn_dropout': 0.17426735465844692, 'lr': 0.00010584347078872694, 'weight_decay': 0.05213644608611559, 'batch_size': 256} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 01:12:55,910] Trial 40 pruned. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.216667 - Parameters: {'d_token': 224, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.2670313138916806, 'ffn_dropout': 0.23409115588842277, 'lr': 0.0002990911595192957, 'weight_decay': 0.027939092699228563, 'batch_size': 64} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 01:13:36,309] Trial 41 pruned. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.289474 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24143536587159278, 'ffn_dropout': 0.11845599645802474, 'lr': 8.60145507764918e-05, 'weight_decay': 0.05362156496412405, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 01:16:07,443] Trial 42 finished with value: 0.375512780245531 and parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24794757397861558, 'ffn_dropout': 0.11859775836775327, 'lr': 5.053396197420868e-05, 'weight_decay': 0.05076568133806051, 'batch_size': 32}. Best is trial 25 with value: 0.3846594392002736. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.375513 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24794757397861558, 'ffn_dropout': 0.11859775836775327, 'lr': 5.053396197420868e-05, 'weight_decay': 0.05076568133806051, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 01:18:52,254] Trial 43 finished with value: 0.36168482715052286 and parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.25683030004415575, 'ffn_dropout': 0.1393711695040204, 'lr': 4.002861073931268e-05, 'weight_decay': 0.019340247935675816, 'batch_size': 32}. Best is trial 25 with value: 0.3846594392002736. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.361685 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.25683030004415575, 'ffn_dropout': 0.1393711695040204, 'lr': 4.002861073931268e-05, 'weight_decay': 0.019340247935675816, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 01:19:31,713] Trial 44 pruned. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.221604 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.20590799879258337, 'ffn_dropout': 0.15777470785574413, 'lr': 5.573810967788502e-05, 'weight_decay': 0.0713951408353533, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 01:20:42,393] Trial 45 pruned. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.366385 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.23079177438339005, 'ffn_dropout': 0.11541649633008234, 'lr': 0.0001358451439384273, 'weight_decay': 0.039793600980840935, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 01:24:34,160] Trial 46 finished with value: 0.37646924856967123 and parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.25024327072948416, 'ffn_dropout': 0.10071226240862333, 'lr': 5.038194029056816e-05, 'weight_decay': 0.017013501743789003, 'batch_size': 32}. Best is trial 25 with value: 0.3846594392002736. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.376469 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.25024327072948416, 'ffn_dropout': 0.10071226240862333, 'lr': 5.038194029056816e-05, 'weight_decay': 0.017013501743789003, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 01:24:55,473] Trial 47 pruned. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.368542 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.305066893504488, 'ffn_dropout': 0.10325124755985961, 'lr': 0.0001767758512753313, 'weight_decay': 0.01176027891772478, 'batch_size': 128} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 01:26:26,040] Trial 48 pruned. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.375152 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.29149490260947125, 'ffn_dropout': 0.13313606317894816, 'lr': 6.525215500694195e-05, 'weight_decay': 0.018382060305199118, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 01:26:58,622] Trial 49 pruned. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.287407 - Parameters: {'d_token': 256, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.2698408270873233, 'ffn_dropout': 0.16346983019944672, 'lr': 0.0001038702263688621, 'weight_decay': 0.030442936674810028, 'batch_size': 64} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 01:27:13,708] Trial 50 pruned. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.229095 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.25382057863434565, 'ffn_dropout': 0.14710667511561856, 'lr': 0.000260482215019166, 'weight_decay': 0.015416232554210473, 'batch_size': 256} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 01:28:29,277] Trial 51 pruned. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.382950 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2508465329855773, 'ffn_dropout': 0.11270099004496292, 'lr': 4.774434042567095e-05, 'weight_decay': 0.043112821231246753, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 01:31:34,149] Trial 52 pruned. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.381089 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2289731645958358, 'ffn_dropout': 0.10046906754393926, 'lr': 5.975534203122773e-05, 'weight_decay': 0.023698071107677927, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 01:32:13,306] Trial 53 pruned. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.248424 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.27625114458583655, 'ffn_dropout': 0.11831624623556967, 'lr': 3.117206840839612e-05, 'weight_decay': 0.07855498001882467, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 01:32:49,522] Trial 54 pruned. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.221976 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2468401280343273, 'ffn_dropout': 0.13410069815930403, 'lr': 2.2583802632988417e-05, 'weight_decay': 0.04922226294720182, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 01:33:15,552] Trial 55 pruned. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.209102 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.25821090272750413, 'ffn_dropout': 0.11192072104236607, 'lr': 4.598134508068652e-05, 'weight_decay': 0.0679162463748671, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 01:34:00,898] Trial 56 pruned. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.271858 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.23476335461152986, 'ffn_dropout': 0.1689347650721264, 'lr': 0.0001251306712154929, 'weight_decay': 0.03563571855732425, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 01:36:19,011] Trial 57 finished with value: 0.34532926140481335 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.21274730512779844, 'ffn_dropout': 0.15023180816384787, 'lr': 7.553313758345565e-05, 'weight_decay': 0.020698039970127907, 'batch_size': 32}. Best is trial 25 with value: 0.3846594392002736. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.345329 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.21274730512779844, 'ffn_dropout': 0.15023180816384787, 'lr': 7.553313758345565e-05, 'weight_decay': 0.020698039970127907, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 01:37:28,935] Trial 58 pruned. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.371498 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2201681972822226, 'ffn_dropout': 0.1340370586037815, 'lr': 0.00016677048638332032, 'weight_decay': 0.03241099099461399, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 01:38:17,110] Trial 59 pruned. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.257033 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.26752823764485656, 'ffn_dropout': 0.18219243601550086, 'lr': 2.0584674418846556e-05, 'weight_decay': 0.04606464334219064, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 01:38:25,806] Trial 60 pruned. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.216895 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2818347544330957, 'ffn_dropout': 0.14311614147828705, 'lr': 3.658903235027625e-05, 'weight_decay': 0.01048636994645898, 'batch_size': 128} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 01:39:41,541] Trial 61 pruned. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.377858 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2443987217247292, 'ffn_dropout': 0.12246747070262111, 'lr': 9.221300128520368e-05, 'weight_decay': 0.060060927272184546, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 01:40:20,242] Trial 62 pruned. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.279601 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.23864904468354095, 'ffn_dropout': 0.1253834479666242, 'lr': 9.026806641393389e-05, 'weight_decay': 0.06320761601780531, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 01:41:23,774] Trial 63 pruned. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.361894 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2519566117534627, 'ffn_dropout': 0.15995732491857165, 'lr': 0.00011088019211551819, 'weight_decay': 0.047591649301497514, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 01:42:49,213] Trial 64 pruned. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.381935 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.22761126442851026, 'ffn_dropout': 0.11003836223688264, 'lr': 6.539831130594897e-05, 'weight_decay': 0.08455111462320279, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 01:44:14,885] Trial 65 pruned. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.356751 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2618049516337553, 'ffn_dropout': 0.1296994254043359, 'lr': 0.0002220623289306713, 'weight_decay': 0.024937766359421805, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 01:45:27,065] Trial 66 pruned. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.374831 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24514416906599937, 'ffn_dropout': 0.1515561935607681, 'lr': 0.00016056979526384368, 'weight_decay': 0.039003896438167554, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 01:45:54,567] Trial 67 pruned. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.269022 - Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.2713629171870476, 'ffn_dropout': 0.12058204104810842, 'lr': 5.0396561770973595e-05, 'weight_decay': 0.028173274829699446, 'batch_size': 64} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 01:47:20,551] Trial 68 pruned. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.362269 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.28707751393163905, 'ffn_dropout': 0.11081905299849734, 'lr': 0.0001147335427001085, 'weight_decay': 0.05761019328817282, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 01:47:28,094] Trial 69 pruned. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.224944 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.23501184316258888, 'ffn_dropout': 0.1400635623865405, 'lr': 7.577609294899357e-05, 'weight_decay': 0.014134105176864828, 'batch_size': 256} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 01:48:15,562] Trial 70 pruned. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.276446 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.29675575239778684, 'ffn_dropout': 0.1670891716611272, 'lr': 0.00015287585714840164, 'weight_decay': 0.03365082008007107, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 01:49:56,017] Trial 71 pruned. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.340351 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.25737933703068944, 'ffn_dropout': 0.17796137207868157, 'lr': 0.00022521061691440413, 'weight_decay': 0.04468956383618979, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 01:50:27,129] Trial 72 pruned. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.113223 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24853974273349277, 'ffn_dropout': 0.19029652870010408, 'lr': 0.00040233939157278915, 'weight_decay': 0.0977870594049185, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 01:51:46,714] Trial 73 pruned. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.352732 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2726834830127298, 'ffn_dropout': 0.15823087106128558, 'lr': 0.00013236146186103174, 'weight_decay': 0.020984024511877575, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 01:52:31,249] Trial 74 pruned. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.250649 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.22377538146645015, 'ffn_dropout': 0.10059809317336783, 'lr': 0.00027360910126416645, 'weight_decay': 0.07597054311247373, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 01:53:38,741] Trial 75 pruned. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.353559 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.23795816856951482, 'ffn_dropout': 0.1994553169582546, 'lr': 8.741954469949254e-05, 'weight_decay': 0.03552888814935313, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 01:53:59,230] Trial 76 pruned. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.268392 - Parameters: {'d_token': 224, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.26089392545197554, 'ffn_dropout': 0.17044736921182158, 'lr': 0.00018800930917454542, 'weight_decay': 0.0567672998976659, 'batch_size': 128} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 01:57:31,927] Trial 77 pruned. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.398649 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28246003953154925, 'ffn_dropout': 0.1288602574511914, 'lr': 5.937254097847339e-05, 'weight_decay': 0.026374076447417863, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 01:58:35,700] Trial 78 pruned. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.383313 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2501666795767813, 'ffn_dropout': 0.14423176917594188, 'lr': 0.00010237162637743782, 'weight_decay': 0.0031510867233097055, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 01:58:57,743] Trial 79 pruned. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.245963 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2671314469693315, 'ffn_dropout': 0.1822267758722683, 'lr': 0.00014882341109530802, 'weight_decay': 0.04588757495565786, 'batch_size': 64} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 02:00:36,045] Trial 80 pruned. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.383546 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19833162360201495, 'ffn_dropout': 0.1380597690297294, 'lr': 4.186394989308294e-05, 'weight_decay': 0.01983329347179651, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 02:01:31,822] Trial 81 pruned. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.361355 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2764539983358285, 'ffn_dropout': 0.18866790646872159, 'lr': 0.000131562568097284, 'weight_decay': 0.015421897781673667, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 02:02:27,125] Trial 82 pruned. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.349474 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.26033566195021013, 'ffn_dropout': 0.17650384318029463, 'lr': 0.00024158450054274696, 'weight_decay': 0.02382452245088323, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 02:02:55,620] Trial 83 pruned. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.252513 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2958672527829419, 'ffn_dropout': 0.1649342110104734, 'lr': 0.00016828829515001332, 'weight_decay': 0.029477789168930804, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 02:03:53,269] Trial 84 pruned. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.365408 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.24334446278218236, 'ffn_dropout': 0.1546385285082794, 'lr': 0.00019429838501662638, 'weight_decay': 0.03966097852509651, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 02:04:34,518] Trial 85 pruned. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.284672 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.23337180521386156, 'ffn_dropout': 0.2011715822725904, 'lr': 7.066482628723317e-05, 'weight_decay': 0.017089855050382862, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 02:04:42,044] Trial 86 pruned. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.231867 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.27558109650165885, 'ffn_dropout': 0.20955582217143295, 'lr': 0.00011019567633675305, 'weight_decay': 0.0122839116254214, 'batch_size': 256} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 02:05:17,689] Trial 87 pruned. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.237981 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.28752910034323875, 'ffn_dropout': 0.19396481721062273, 'lr': 5.252093270499447e-05, 'weight_decay': 0.05337234877724441, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 02:05:47,855] Trial 88 pruned. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.198216 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.25365665857383535, 'ffn_dropout': 0.117997228974347, 'lr': 0.0003061670134929325, 'weight_decay': 0.034966758530073645, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 02:06:18,571] Trial 89 pruned. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.336989 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.26261489189037845, 'ffn_dropout': 0.14875894019199726, 'lr': 8.26032224968283e-05, 'weight_decay': 0.07403655957298266, 'batch_size': 128} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 02:06:51,340] Trial 90 pruned. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.114837 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.22609452963278073, 'ffn_dropout': 0.10537285661488736, 'lr': 0.0003461901495593995, 'weight_decay': 0.02251828113503891, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 02:08:28,007] Trial 91 pruned. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.380096 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3025284403584919, 'ffn_dropout': 0.12564494381562907, 'lr': 9.721791504287365e-05, 'weight_decay': 0.06310948408287001, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 02:09:39,336] Trial 92 pruned. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.379147 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3139911193746904, 'ffn_dropout': 0.16205379454717653, 'lr': 0.0001394609257230219, 'weight_decay': 0.04211238081061817, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 02:10:22,388] Trial 93 pruned. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.272601 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.26681972993130537, 'ffn_dropout': 0.1343291688353294, 'lr': 6.615457016506832e-05, 'weight_decay': 0.05180702780280516, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 02:10:57,249] Trial 94 pruned. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.260993 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2782996358791965, 'ffn_dropout': 0.15378044592427076, 'lr': 0.00012275021944088482, 'weight_decay': 0.03164396623629694, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 02:11:53,403] Trial 95 pruned. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.372941 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.24141893745567022, 'ffn_dropout': 0.17175610027786212, 'lr': 8.302066783097746e-05, 'weight_decay': 0.07066763621481499, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 02:12:41,802] Trial 96 pruned. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.252276 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.25036001393024215, 'ffn_dropout': 0.14795508754920153, 'lr': 0.00019038525306239407, 'weight_decay': 0.09240520501938326, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) -[I 2025-12-25 02:13:01,726] Trial 97 pruned. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.275538 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2845467794557007, 'ffn_dropout': 0.11416709168310722, 'lr': 5.656401600299793e-05, 'weight_decay': 0.02727770526964544, 'batch_size': 64} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 177.21212121212122, 1: 9.779264214046822, 2: 0.3457695263998108} (클래스별 샘플 수: {0: 33, 1: 598, 2: 16913}) -[I 2025-12-25 02:16:03,848] Trial 98 pruned. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.387275 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2716837436337158, 'ffn_dropout': 0.18478747522353028, 'lr': 9.772918180337497e-05, 'weight_decay': 0.038987460176003914, 'batch_size': 32} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 171.76470588235293, 1: 6.460176991150442, 2: 0.3521891207333253} (클래스별 샘플 수: {0: 34, 1: 904, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 8.213483146067416, 2: 0.34803308932928645} (클래스별 샘플 수: {0: 29, 1: 712, 2: 16803}) -[I 2025-12-25 02:16:33,144] Trial 99 pruned. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.305944 - Parameters: {'d_token': 224, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.25336969552014654, 'ffn_dropout': 0.14221517883832288, 'lr': 0.00020935430753702875, 'weight_decay': 0.08478436951388278, 'batch_size': 256} - Best Value (CSI): 0.384659 - Best Trial: 25 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.3847 -Best Hyperparameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2747124536980523, 'ffn_dropout': 0.1909754518903343, 'lr': 0.00016739997447268043, 'weight_decay': 0.027811856175591093, 'batch_size': 32} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.2964 - - 최종 CSI: 0.3059 - - 최고 CSI: 0.3986 - - 최저 CSI: 0.0000 - - 평균 CSI: 0.2966 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/ft_transformer_pure_daegu_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 15, Best CSI: 0.2853 - Fold 1 학습 완료 (검증 CSI: 0.2853) -Fold 2 학습 중... - Early stopping at epoch 25, Best CSI: 0.3728 - Fold 2 학습 완료 (검증 CSI: 0.3728) -Fold 3 학습 중... - Early stopping at epoch 28, Best CSI: 0.3885 - Fold 3 학습 완료 (검증 CSI: 0.3885) - -모든 모델 저장 완료: ../save_model/ft_transformer_optima/ft_transformer_pure_daegu.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/ft_transformer_optima/scaler/ft_transformer_pure_daegu_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: - - . - - . - - / - - s - - a - - v - - e - - _ - - m - - o - - d - - e - - l - - / - - f - - t - - _ - - t - - r - - a - - n - - s - - f - - o - - r - - m - - e - - r - - _ - - o - - p - - t - - i - - m - - a - - / - - f - - t - - _ - - t - - r - - a - - n - - s - - f - - o - - r - - m - - e - - r - - _ - - p - - u - - r - - e - - _ - - d - - a - - e - - g - - u - - . - - p - - k - - l - -✓ 완료: ft_transformer_pure/ft_transforemer_pure_daegu.py (소요 시간: 8139초) - ----------------------------------------- -실행 중: ft_transformer_pure/ft_transforemer_pure_daejeon.py -시작 시간: 2025-12-25 02:18:41 ----------------------------------------- -[I 2025-12-25 02:18:42,941] A new study created in memory with name: no-name-4f7668f7-8d36-4c4b-9ba4-8fe54d832213 - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 02:19:13,816] Trial 0 finished with value: 0.13030681079890966 and parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.386205863505391, 'ffn_dropout': 0.2521012318195598, 'lr': 0.0027508036764389253, 'weight_decay': 0.0013064873456425207, 'batch_size': 256}. Best is trial 0 with value: 0.13030681079890966. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.130307 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.386205863505391, 'ffn_dropout': 0.2521012318195598, 'lr': 0.0027508036764389253, 'weight_decay': 0.0013064873456425207, 'batch_size': 256} - Best Value (CSI): 0.130307 - Best Trial: 0 - Best Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.386205863505391, 'ffn_dropout': 0.2521012318195598, 'lr': 0.0027508036764389253, 'weight_decay': 0.0013064873456425207, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 02:19:52,823] Trial 1 finished with value: 0.3391544553633025 and parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.3219789740376229, 'ffn_dropout': 0.25267947395532514, 'lr': 0.0008600496582725825, 'weight_decay': 0.004994230377148241, 'batch_size': 128}. Best is trial 1 with value: 0.3391544553633025. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.339154 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.3219789740376229, 'ffn_dropout': 0.25267947395532514, 'lr': 0.0008600496582725825, 'weight_decay': 0.004994230377148241, 'batch_size': 128} - Best Value (CSI): 0.339154 - Best Trial: 1 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.3219789740376229, 'ffn_dropout': 0.25267947395532514, 'lr': 0.0008600496582725825, 'weight_decay': 0.004994230377148241, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 02:22:38,669] Trial 2 finished with value: 0.30718642597208246 and parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.39398100656571566, 'ffn_dropout': 0.3938950592277768, 'lr': 1.7473639861546465e-05, 'weight_decay': 0.0005937886556325067, 'batch_size': 64}. Best is trial 1 with value: 0.3391544553633025. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.307186 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.39398100656571566, 'ffn_dropout': 0.3938950592277768, 'lr': 1.7473639861546465e-05, 'weight_decay': 0.0005937886556325067, 'batch_size': 64} - Best Value (CSI): 0.339154 - Best Trial: 1 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.3219789740376229, 'ffn_dropout': 0.25267947395532514, 'lr': 0.0008600496582725825, 'weight_decay': 0.004994230377148241, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 02:24:25,039] Trial 3 finished with value: 0.44855934612463416 and parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.22250020483695154, 'ffn_dropout': 0.24855846298418743, 'lr': 0.0009474576937825958, 'weight_decay': 0.003135324345742673, 'batch_size': 64}. Best is trial 3 with value: 0.44855934612463416. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.448559 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.22250020483695154, 'ffn_dropout': 0.24855846298418743, 'lr': 0.0009474576937825958, 'weight_decay': 0.003135324345742673, 'batch_size': 64} - Best Value (CSI): 0.448559 - Best Trial: 3 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.22250020483695154, 'ffn_dropout': 0.24855846298418743, 'lr': 0.0009474576937825958, 'weight_decay': 0.003135324345742673, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 02:27:40,249] Trial 4 finished with value: 0.42406414036846246 and parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.29944198514797504, 'ffn_dropout': 0.17765690689159946, 'lr': 3.306077243763879e-05, 'weight_decay': 0.000780374193213055, 'batch_size': 64}. Best is trial 3 with value: 0.44855934612463416. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.424064 - Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.29944198514797504, 'ffn_dropout': 0.17765690689159946, 'lr': 3.306077243763879e-05, 'weight_decay': 0.000780374193213055, 'batch_size': 64} - Best Value (CSI): 0.448559 - Best Trial: 3 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.22250020483695154, 'ffn_dropout': 0.24855846298418743, 'lr': 0.0009474576937825958, 'weight_decay': 0.003135324345742673, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 02:27:57,810] Trial 5 pruned. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.310465 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.19805755987150375, 'ffn_dropout': 0.1757244411044384, 'lr': 1.556712595249609e-05, 'weight_decay': 0.0007577872222493627, 'batch_size': 128} - Best Value (CSI): 0.448559 - Best Trial: 3 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.22250020483695154, 'ffn_dropout': 0.24855846298418743, 'lr': 0.0009474576937825958, 'weight_decay': 0.003135324345742673, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 02:28:21,428] Trial 6 pruned. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.335178 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.21016204032170777, 'ffn_dropout': 0.27014975084639836, 'lr': 6.875008575947255e-05, 'weight_decay': 0.0006885662915962751, 'batch_size': 64} - Best Value (CSI): 0.448559 - Best Trial: 3 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.22250020483695154, 'ffn_dropout': 0.24855846298418743, 'lr': 0.0009474576937825958, 'weight_decay': 0.003135324345742673, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 02:28:46,223] Trial 7 pruned. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.338322 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.28833099039090293, 'ffn_dropout': 0.12745887007797477, 'lr': 0.001323999389868429, 'weight_decay': 0.02923603888342883, 'batch_size': 128} - Best Value (CSI): 0.448559 - Best Trial: 3 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.22250020483695154, 'ffn_dropout': 0.24855846298418743, 'lr': 0.0009474576937825958, 'weight_decay': 0.003135324345742673, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 02:29:16,474] Trial 8 pruned. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.275100 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3620071144212412, 'ffn_dropout': 0.10877837624069653, 'lr': 0.0004984077953127111, 'weight_decay': 0.008771934343919804, 'batch_size': 64} - Best Value (CSI): 0.448559 - Best Trial: 3 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.22250020483695154, 'ffn_dropout': 0.24855846298418743, 'lr': 0.0009474576937825958, 'weight_decay': 0.003135324345742673, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 02:29:22,016] Trial 9 pruned. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.154831 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.37462323470489955, 'ffn_dropout': 0.21868120187732437, 'lr': 2.0436795328702492e-05, 'weight_decay': 0.0030175359299820493, 'batch_size': 128} - Best Value (CSI): 0.448559 - Best Trial: 3 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.22250020483695154, 'ffn_dropout': 0.24855846298418743, 'lr': 0.0009474576937825958, 'weight_decay': 0.003135324345742673, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 02:29:47,226] Trial 10 pruned. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.1118827660045983, 'ffn_dropout': 0.3173360589175065, 'lr': 0.006415415752176818, 'weight_decay': 0.00010169291389718093, 'batch_size': 32} - Best Value (CSI): 0.448559 - Best Trial: 3 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.22250020483695154, 'ffn_dropout': 0.24855846298418743, 'lr': 0.0009474576937825958, 'weight_decay': 0.003135324345742673, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 02:34:01,612] Trial 11 finished with value: 0.4608644130883877 and parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.25975648216177644, 'ffn_dropout': 0.17542324756869107, 'lr': 0.0001396476058783493, 'weight_decay': 0.09839404123936313, 'batch_size': 64}. Best is trial 11 with value: 0.4608644130883877. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.460864 - Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.25975648216177644, 'ffn_dropout': 0.17542324756869107, 'lr': 0.0001396476058783493, 'weight_decay': 0.09839404123936313, 'batch_size': 64} - Best Value (CSI): 0.460864 - Best Trial: 11 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.25975648216177644, 'ffn_dropout': 0.17542324756869107, 'lr': 0.0001396476058783493, 'weight_decay': 0.09839404123936313, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 02:38:02,074] Trial 12 finished with value: 0.4544232442299096 and parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.24545849623176033, 'ffn_dropout': 0.19251250339764825, 'lr': 0.0001665216869025282, 'weight_decay': 0.09239819754180736, 'batch_size': 64}. Best is trial 11 with value: 0.4608644130883877. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.454423 - Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.24545849623176033, 'ffn_dropout': 0.19251250339764825, 'lr': 0.0001665216869025282, 'weight_decay': 0.09239819754180736, 'batch_size': 64} - Best Value (CSI): 0.460864 - Best Trial: 11 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.25975648216177644, 'ffn_dropout': 0.17542324756869107, 'lr': 0.0001396476058783493, 'weight_decay': 0.09839404123936313, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 02:44:57,228] Trial 13 finished with value: 0.45503965265223134 and parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.2690310855371136, 'ffn_dropout': 0.16561062431898876, 'lr': 0.0001453353396907857, 'weight_decay': 0.07596215382887424, 'batch_size': 32}. Best is trial 11 with value: 0.4608644130883877. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.455040 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.2690310855371136, 'ffn_dropout': 0.16561062431898876, 'lr': 0.0001453353396907857, 'weight_decay': 0.07596215382887424, 'batch_size': 32} - Best Value (CSI): 0.460864 - Best Trial: 11 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.25975648216177644, 'ffn_dropout': 0.17542324756869107, 'lr': 0.0001396476058783493, 'weight_decay': 0.09839404123936313, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) -[I 2025-12-25 02:48:43,893] Trial 14 pruned. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.477273 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.27548623024746627, 'ffn_dropout': 0.15723909007738684, 'lr': 0.00012817458554516893, 'weight_decay': 0.07211967061898854, 'batch_size': 32} - Best Value (CSI): 0.460864 - Best Trial: 11 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.25975648216177644, 'ffn_dropout': 0.17542324756869107, 'lr': 0.0001396476058783493, 'weight_decay': 0.09839404123936313, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 02:54:23,242] Trial 15 pruned. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.468015 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.33666782795390526, 'ffn_dropout': 0.14123400391830365, 'lr': 0.00027647939463135536, 'weight_decay': 0.028441460889922228, 'batch_size': 32} - Best Value (CSI): 0.460864 - Best Trial: 11 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.25975648216177644, 'ffn_dropout': 0.17542324756869107, 'lr': 0.0001396476058783493, 'weight_decay': 0.09839404123936313, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 02:54:29,833] Trial 16 pruned. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.298980 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.2597136985155452, 'ffn_dropout': 0.10306357961808336, 'lr': 6.648547577292476e-05, 'weight_decay': 0.03969365247771782, 'batch_size': 256} - Best Value (CSI): 0.460864 - Best Trial: 11 - Best Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.25975648216177644, 'ffn_dropout': 0.17542324756869107, 'lr': 0.0001396476058783493, 'weight_decay': 0.09839404123936313, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 03:01:34,108] Trial 17 finished with value: 0.46122600267823205 and parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.30795563768884227, 'ffn_dropout': 0.15517610487893013, 'lr': 0.0003222776334143166, 'weight_decay': 0.08132868611741094, 'batch_size': 32}. Best is trial 17 with value: 0.46122600267823205. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.461226 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.30795563768884227, 'ffn_dropout': 0.15517610487893013, 'lr': 0.0003222776334143166, 'weight_decay': 0.08132868611741094, 'batch_size': 32} - Best Value (CSI): 0.461226 - Best Trial: 17 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.30795563768884227, 'ffn_dropout': 0.15517610487893013, 'lr': 0.0003222776334143166, 'weight_decay': 0.08132868611741094, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:02:41,546] Trial 18 pruned. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.350515 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3168485196408837, 'ffn_dropout': 0.13343450116726494, 'lr': 0.0005757295357987116, 'weight_decay': 0.014904174244906926, 'batch_size': 32} - Best Value (CSI): 0.461226 - Best Trial: 17 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.30795563768884227, 'ffn_dropout': 0.15517610487893013, 'lr': 0.0003222776334143166, 'weight_decay': 0.08132868611741094, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:02:48,108] Trial 19 pruned. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.306775 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.35825597872308906, 'ffn_dropout': 0.20074858502807807, 'lr': 0.0003116589866826082, 'weight_decay': 0.017198858782809124, 'batch_size': 256} - Best Value (CSI): 0.461226 - Best Trial: 17 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.30795563768884227, 'ffn_dropout': 0.15517610487893013, 'lr': 0.0003222776334143166, 'weight_decay': 0.08132868611741094, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:04:15,393] Trial 20 pruned. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.362921 - Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3349950282653754, 'ffn_dropout': 0.15312756013636863, 'lr': 5.634856046589454e-05, 'weight_decay': 0.04433450215033534, 'batch_size': 32} - Best Value (CSI): 0.461226 - Best Trial: 17 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.30795563768884227, 'ffn_dropout': 0.15517610487893013, 'lr': 0.0003222776334143166, 'weight_decay': 0.08132868611741094, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 03:10:29,420] Trial 21 finished with value: 0.447830789557824 and parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.2782528079118694, 'ffn_dropout': 0.16037319675253303, 'lr': 0.00014711697045364033, 'weight_decay': 0.09875039751362177, 'batch_size': 32}. Best is trial 17 with value: 0.46122600267823205. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.447831 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.2782528079118694, 'ffn_dropout': 0.16037319675253303, 'lr': 0.00014711697045364033, 'weight_decay': 0.09875039751362177, 'batch_size': 32} - Best Value (CSI): 0.461226 - Best Trial: 17 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.30795563768884227, 'ffn_dropout': 0.15517610487893013, 'lr': 0.0003222776334143166, 'weight_decay': 0.08132868611741094, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:11:43,626] Trial 22 pruned. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.359792 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.249201046305229, 'ffn_dropout': 0.21164493507004215, 'lr': 0.00022113220881700202, 'weight_decay': 0.05205012145541569, 'batch_size': 32} - Best Value (CSI): 0.461226 - Best Trial: 17 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.30795563768884227, 'ffn_dropout': 0.15517610487893013, 'lr': 0.0003222776334143166, 'weight_decay': 0.08132868611741094, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 03:18:27,139] Trial 23 finished with value: 0.4650483385119633 and parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32}. Best is trial 23 with value: 0.4650483385119633. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.465048 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:19:33,055] Trial 24 pruned. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.374922 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3083242923260655, 'ffn_dropout': 0.12875641739552787, 'lr': 0.00037044929466205405, 'weight_decay': 0.052543783586070536, 'batch_size': 32} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:20:33,731] Trial 25 pruned. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.340400 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.29695464430191476, 'ffn_dropout': 0.18140145890848025, 'lr': 7.722357609573937e-05, 'weight_decay': 0.09504432028645285, 'batch_size': 32} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:20:53,245] Trial 26 pruned. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.326159 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3368158295522806, 'ffn_dropout': 0.21841261519222804, 'lr': 0.00010667769129379456, 'weight_decay': 0.021900839706615265, 'batch_size': 64} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:20:59,111] Trial 27 pruned. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.196105 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.29086679444899766, 'ffn_dropout': 0.19209551573668684, 'lr': 3.829192828823051e-05, 'weight_decay': 0.04914597364594219, 'batch_size': 256} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:22:07,010] Trial 28 pruned. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.370044 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.23625560793188388, 'ffn_dropout': 0.11802183847106702, 'lr': 0.00021284049168924664, 'weight_decay': 0.03118335078716931, 'batch_size': 32} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:22:14,280] Trial 29 pruned. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.262770 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.26469890318248807, 'ffn_dropout': 0.1478267110960241, 'lr': 0.00010277233896130291, 'weight_decay': 0.05888817107606561, 'batch_size': 256} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:22:30,707] Trial 30 pruned. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.331861 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.39648666739833827, 'ffn_dropout': 0.14034876522758272, 'lr': 0.00039617690740969365, 'weight_decay': 0.016702442882228948, 'batch_size': 64} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:23:47,690] Trial 31 pruned. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.371935 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.27671875779592975, 'ffn_dropout': 0.17170602666153917, 'lr': 0.0002056998795335358, 'weight_decay': 0.06972595790011288, 'batch_size': 32} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) -[I 2025-12-25 03:28:08,574] Trial 32 pruned. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.479452 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3139333004984618, 'ffn_dropout': 0.16184792190716438, 'lr': 0.00013720637040861447, 'weight_decay': 0.07388944594720782, 'batch_size': 32} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) -[I 2025-12-25 03:32:09,936] Trial 33 pruned. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.484015 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.2560772432994428, 'ffn_dropout': 0.10939491480278664, 'lr': 0.0002684907548100298, 'weight_decay': 0.03316332949972466, 'batch_size': 32} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:32:47,271] Trial 34 pruned. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.277081 - Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3254085183083442, 'ffn_dropout': 0.16345816548842246, 'lr': 0.0006249853373731823, 'weight_decay': 0.09486827853352472, 'batch_size': 32} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:33:00,031] Trial 35 pruned. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.310021 - Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3021966932597069, 'ffn_dropout': 0.14183973781074632, 'lr': 9.48032977101479e-05, 'weight_decay': 0.05691430113336231, 'batch_size': 128} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 03:35:46,712] Trial 36 finished with value: 0.4642646660986382 and parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2267342240802674, 'ffn_dropout': 0.17776218943120453, 'lr': 0.00014945776087991092, 'weight_decay': 0.04209109124699349, 'batch_size': 64}. Best is trial 23 with value: 0.4650483385119633. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.464265 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2267342240802674, 'ffn_dropout': 0.17776218943120453, 'lr': 0.00014945776087991092, 'weight_decay': 0.04209109124699349, 'batch_size': 64} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:36:00,971] Trial 37 pruned. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.340782 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.22310753923366405, 'ffn_dropout': 0.2366885832268742, 'lr': 4.72739974390631e-05, 'weight_decay': 0.0381473757277536, 'batch_size': 64} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:36:16,258] Trial 38 pruned. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.267510 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.23154941805813725, 'ffn_dropout': 0.18007574505785867, 'lr': 0.0007815302366605472, 'weight_decay': 0.024648361380013688, 'batch_size': 64} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:36:32,944] Trial 39 pruned. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.337692 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.18997172703916282, 'ffn_dropout': 0.12269600481738505, 'lr': 8.840676217976613e-05, 'weight_decay': 0.012239733588227808, 'batch_size': 64} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:36:45,969] Trial 40 pruned. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.235294 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2132537142418937, 'ffn_dropout': 0.18948056996187362, 'lr': 1.0277654099186322e-05, 'weight_decay': 0.04198576118747863, 'batch_size': 64} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:37:21,830] Trial 41 pruned. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.377049 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.2688947285786729, 'ffn_dropout': 0.16909607415704322, 'lr': 0.0001686533967450979, 'weight_decay': 0.06880858422708143, 'batch_size': 64} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:37:29,898] Trial 42 pruned. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.281220 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.28376121656142994, 'ffn_dropout': 0.2039230154593726, 'lr': 0.0003846940557574178, 'weight_decay': 0.06732831646904867, 'batch_size': 128} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:37:46,745] Trial 43 pruned. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.289284 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.2922063791799537, 'ffn_dropout': 0.17130344255008872, 'lr': 0.00012896728075348615, 'weight_decay': 0.09387395241889032, 'batch_size': 64} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:39:03,005] Trial 44 pruned. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.368804 - Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.24779733311726734, 'ffn_dropout': 0.1496796279205009, 'lr': 0.00019194665161242235, 'weight_decay': 0.03801390056485421, 'batch_size': 32} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:39:20,293] Trial 45 pruned. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.302181 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3018090314684446, 'ffn_dropout': 0.18430615012418222, 'lr': 0.0002457447444210661, 'weight_decay': 0.06807761318857905, 'batch_size': 64} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:41:32,358] Trial 46 pruned. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.359897 - Parameters: {'d_token': 256, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.26633486691424757, 'ffn_dropout': 0.19250259517936447, 'lr': 7.500280999472191e-05, 'weight_decay': 0.02337184932874585, 'batch_size': 32} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:41:41,479] Trial 47 pruned. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.323324 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2806351346715156, 'ffn_dropout': 0.226624156725439, 'lr': 0.00015568304168309753, 'weight_decay': 0.05164813934853537, 'batch_size': 128} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:42:02,229] Trial 48 pruned. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.273614 - Parameters: {'d_token': 224, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.25786968372896785, 'ffn_dropout': 0.15319509343093857, 'lr': 0.00046108085754404104, 'weight_decay': 0.0058039311496743086, 'batch_size': 64} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:43:25,518] Trial 49 pruned. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.348887 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.32245683685099713, 'ffn_dropout': 0.13266268562229994, 'lr': 0.000274059808714681, 'weight_decay': 0.032735009865683604, 'batch_size': 32} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:43:30,792] Trial 50 pruned. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.250676 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.2355664353006523, 'ffn_dropout': 0.20479045910321175, 'lr': 0.00011761115263079321, 'weight_decay': 0.07926097430809213, 'batch_size': 256} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:43:52,303] Trial 51 pruned. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.324264 - Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.25012746612917475, 'ffn_dropout': 0.17439271051675012, 'lr': 0.00016861565661898862, 'weight_decay': 0.09542170809947026, 'batch_size': 64} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:44:13,877] Trial 52 pruned. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.324161 - Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.2714804182618546, 'ffn_dropout': 0.1977181495745457, 'lr': 0.0003329047428454063, 'weight_decay': 0.04611552003129593, 'batch_size': 64} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:44:35,349] Trial 53 pruned. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.285921 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.2860687540004463, 'ffn_dropout': 0.1860297868175671, 'lr': 5.5885885311342984e-05, 'weight_decay': 0.09815781078408395, 'batch_size': 64} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:44:57,132] Trial 54 pruned. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.330539 - Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.24042973518770833, 'ffn_dropout': 0.1627467129097943, 'lr': 0.00012461258035902429, 'weight_decay': 0.05570639594115275, 'batch_size': 64} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:45:39,360] Trial 55 pruned. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.340473 - Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.19966882373520395, 'ffn_dropout': 0.15571034975654957, 'lr': 0.0001767141784803544, 'weight_decay': 0.07062711898044698, 'batch_size': 32} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:46:30,693] Trial 56 pruned. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.369610 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3009506500304082, 'ffn_dropout': 0.20998784941379028, 'lr': 9.168123099955834e-05, 'weight_decay': 0.04225848645453474, 'batch_size': 32} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:47:03,225] Trial 57 pruned. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.347245 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.2599271083912196, 'ffn_dropout': 0.17786934680411398, 'lr': 0.0002407116435874551, 'weight_decay': 0.07856157509887263, 'batch_size': 64} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 03:50:24,672] Trial 58 pruned. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.441115 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.24503427068562, 'ffn_dropout': 0.19786768781080466, 'lr': 6.914514615963278e-05, 'weight_decay': 0.026846020984466923, 'batch_size': 32} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:50:36,089] Trial 59 pruned. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.304866 - Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.2713899385322525, 'ffn_dropout': 0.1463708110951466, 'lr': 0.00030777945944062687, 'weight_decay': 0.057402331008289835, 'batch_size': 256} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:50:47,557] Trial 60 pruned. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.312400 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3107669270478937, 'ffn_dropout': 0.1325496726545791, 'lr': 0.00014154114043603622, 'weight_decay': 0.035094361370802366, 'batch_size': 128} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:51:01,630] Trial 61 pruned. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.332020 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.23304132726344665, 'ffn_dropout': 0.2652634598153322, 'lr': 0.0010725729988811882, 'weight_decay': 0.07810436958043124, 'batch_size': 64} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:51:14,217] Trial 62 pruned. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.155522 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.22188416187291823, 'ffn_dropout': 0.1673111187969517, 'lr': 0.0019067768628427148, 'weight_decay': 0.0023486968560448365, 'batch_size': 64} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:51:31,161] Trial 63 pruned. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.328714 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.28806932251388995, 'ffn_dropout': 0.21694043201515065, 'lr': 0.00021090188777624395, 'weight_decay': 0.05863602403780413, 'batch_size': 64} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) -[I 2025-12-25 03:54:54,222] Trial 64 pruned. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.475515 - Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.25580926494778866, 'ffn_dropout': 0.1893877174250361, 'lr': 0.0005117996815384344, 'weight_decay': 0.09827447110989218, 'batch_size': 32} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:55:16,788] Trial 65 pruned. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.318079 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.24327397506052878, 'ffn_dropout': 0.2282766586390969, 'lr': 0.00011473685724022373, 'weight_decay': 0.04412703184916589, 'batch_size': 64} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:56:49,942] Trial 66 pruned. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.367548 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2781440562549066, 'ffn_dropout': 0.17927609472545594, 'lr': 0.0001823514967917349, 'weight_decay': 0.018710671992557666, 'batch_size': 32} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:57:16,284] Trial 67 pruned. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.331986 - Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.2247585207775954, 'ffn_dropout': 0.15763024285904298, 'lr': 0.00032469137104025646, 'weight_decay': 0.029378158740838673, 'batch_size': 64} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:58:19,637] Trial 68 pruned. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.348939 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.2095833130230336, 'ffn_dropout': 0.3038196487912499, 'lr': 8.814998763564693e-05, 'weight_decay': 0.08215820979744469, 'batch_size': 32} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:58:41,218] Trial 69 pruned. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.331621 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.2629930125134808, 'ffn_dropout': 0.13976456874887552, 'lr': 0.00040592320621973886, 'weight_decay': 0.049725975156648276, 'batch_size': 64} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 03:58:45,940] Trial 70 pruned. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.252427 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.29519081247493917, 'ffn_dropout': 0.1694399179567708, 'lr': 0.0002516582573227136, 'weight_decay': 0.06351460520348687, 'batch_size': 256} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 04:00:40,606] Trial 71 pruned. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.374476 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.2817266472143714, 'ffn_dropout': 0.16429902684217892, 'lr': 0.00014093098634472743, 'weight_decay': 0.07999560217027929, 'batch_size': 32} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 04:01:21,883] Trial 72 pruned. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.341886 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3079290041872924, 'ffn_dropout': 0.15601313848273946, 'lr': 0.00010563620972163942, 'weight_decay': 0.09640854342029524, 'batch_size': 32} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 04:08:44,734] Trial 73 pruned. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.486863 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.2739261336957577, 'ffn_dropout': 0.17970319493498682, 'lr': 0.0001540692100227186, 'weight_decay': 0.06163027826998439, 'batch_size': 32} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 04:15:05,025] Trial 74 finished with value: 0.45084682206272 and parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.254294788049956, 'ffn_dropout': 0.14426501906887468, 'lr': 0.0006481679430742509, 'weight_decay': 0.08023295949616388, 'batch_size': 32}. Best is trial 23 with value: 0.4650483385119633. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.450847 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.254294788049956, 'ffn_dropout': 0.14426501906887468, 'lr': 0.0006481679430742509, 'weight_decay': 0.08023295949616388, 'batch_size': 32} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 04:16:26,811] Trial 75 pruned. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.356407 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.25183578043329835, 'ffn_dropout': 0.13855450251708706, 'lr': 0.0006060536526459364, 'weight_decay': 0.045816042098822014, 'batch_size': 32} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 04:17:41,772] Trial 76 pruned. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.344933 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.24007507862757438, 'ffn_dropout': 0.12010206429559603, 'lr': 0.0002006325437943349, 'weight_decay': 0.08135095428397322, 'batch_size': 32} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 04:18:10,604] Trial 77 pruned. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.082650 - Parameters: {'d_token': 224, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.2646620155993172, 'ffn_dropout': 0.1488778347770608, 'lr': 0.0007192668584792978, 'weight_decay': 0.05859609933240925, 'batch_size': 64} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 04:18:25,982] Trial 78 pruned. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.082536 - Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.2524945988719568, 'ffn_dropout': 0.1964030675677524, 'lr': 0.0009338675261970192, 'weight_decay': 0.03396228256508752, 'batch_size': 128} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 04:23:16,875] Trial 79 finished with value: 0.45436899533608077 and parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.23049911574490933, 'ffn_dropout': 0.18651180572159953, 'lr': 0.00046304265762119235, 'weight_decay': 0.07104678540529988, 'batch_size': 32}. Best is trial 23 with value: 0.4650483385119633. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.454369 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.23049911574490933, 'ffn_dropout': 0.18651180572159953, 'lr': 0.00046304265762119235, 'weight_decay': 0.07104678540529988, 'batch_size': 32} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 04:28:12,866] Trial 80 finished with value: 0.45703343189295076 and parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.23048347997977794, 'ffn_dropout': 0.18750289268007883, 'lr': 0.0004350734820522211, 'weight_decay': 0.0653742620045878, 'batch_size': 32}. Best is trial 23 with value: 0.4650483385119633. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.457033 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.23048347997977794, 'ffn_dropout': 0.18750289268007883, 'lr': 0.0004350734820522211, 'weight_decay': 0.0653742620045878, 'batch_size': 32} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 04:33:56,196] Trial 81 finished with value: 0.4589362380806823 and parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.23056895756818988, 'ffn_dropout': 0.18363084583665082, 'lr': 0.0003520801513432133, 'weight_decay': 0.06854022758073623, 'batch_size': 32}. Best is trial 23 with value: 0.4650483385119633. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.458936 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.23056895756818988, 'ffn_dropout': 0.18363084583665082, 'lr': 0.0003520801513432133, 'weight_decay': 0.06854022758073623, 'batch_size': 32} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 04:38:22,237] Trial 82 finished with value: 0.45137134090178077 and parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2277988711061078, 'ffn_dropout': 0.18910326729218868, 'lr': 0.00046459903023809507, 'weight_decay': 0.06530866307332514, 'batch_size': 32}. Best is trial 23 with value: 0.4650483385119633. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.451371 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2277988711061078, 'ffn_dropout': 0.18910326729218868, 'lr': 0.00046459903023809507, 'weight_decay': 0.06530866307332514, 'batch_size': 32} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 04:39:11,937] Trial 83 pruned. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.360759 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.21741321677041275, 'ffn_dropout': 0.1742847408178841, 'lr': 0.00031910126285560243, 'weight_decay': 0.03872939404967124, 'batch_size': 32} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 04:40:06,268] Trial 84 pruned. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.368020 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.23038860887623194, 'ffn_dropout': 0.20457748348696742, 'lr': 0.0003886599589877962, 'weight_decay': 0.05026247177175396, 'batch_size': 32} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 04:41:20,190] Trial 85 pruned. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.359302 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.23900258773488933, 'ffn_dropout': 0.1817370371032135, 'lr': 0.00023144407257019077, 'weight_decay': 0.06773121333296692, 'batch_size': 32} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 04:42:05,984] Trial 86 pruned. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.351114 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2440255082736722, 'ffn_dropout': 0.19482772271381382, 'lr': 0.0002897827063436645, 'weight_decay': 0.08526981779290388, 'batch_size': 32} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 04:42:57,196] Trial 87 pruned. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.355063 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2102239351904792, 'ffn_dropout': 0.17238251374068608, 'lr': 0.00018442575735323118, 'weight_decay': 0.05161089413515312, 'batch_size': 32} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 04:43:41,033] Trial 88 pruned. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.347083 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.23591535431740157, 'ffn_dropout': 0.18324525962295476, 'lr': 0.0002684960425505086, 'weight_decay': 0.06823455246625137, 'batch_size': 32} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 04:45:02,178] Trial 89 pruned. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.362025 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.22124391463619042, 'ffn_dropout': 0.16402091374871258, 'lr': 0.0005374059841365807, 'weight_decay': 0.08574377426892478, 'batch_size': 32} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 04:45:37,365] Trial 90 pruned. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.344181 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2294479440288413, 'ffn_dropout': 0.18754713859844455, 'lr': 0.0004556684256290737, 'weight_decay': 0.03922819137266111, 'batch_size': 32} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 04:46:24,972] Trial 91 pruned. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.338005 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.23018718229928498, 'ffn_dropout': 0.19173044585955154, 'lr': 0.0004554765120727365, 'weight_decay': 0.06250498689640645, 'batch_size': 32} - Best Value (CSI): 0.465048 - Best Trial: 23 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3015737494021433, 'ffn_dropout': 0.17734984362677814, 'lr': 0.00013586839992305125, 'weight_decay': 0.09844215442969696, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 50.41379310344828, 1: 3.417884278199883, 2: 0.3720811859769676} (클래스별 샘플 수: {0: 116, 1: 1711, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 68.8, 1: 3.4913432835820895, 2: 0.3705017739483021} (클래스별 샘플 수: {0: 85, 1: 1675, 2: 15784}) -[I 2025-12-25 04:51:37,352] Trial 92 finished with value: 0.4655886251588111 and parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.24759508454949322, 'ffn_dropout': 0.2013907953941948, 'lr': 0.0003711331440914647, 'weight_decay': 0.06954769328501528, 'batch_size': 32}. Best is trial 92 with value: 0.4655886251588111. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.465589 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.24759508454949322, 'ffn_dropout': 0.2013907953941948, 'lr': 0.0003711331440914647, 'weight_decay': 0.06954769328501528, 'batch_size': 32} - Best Value (CSI): 0.465589 - Best Trial: 92 - Best Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.24759508454949322, 'ffn_dropout': 0.2013907953941948, 'lr': 0.0003711331440914647, 'weight_decay': 0.06954769328501528, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 04:52:36,462] Trial 93 pruned. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.356669 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.24695528939520603, 'ffn_dropout': 0.2016898494693985, 'lr': 0.0003733027099291986, 'weight_decay': 0.07429823282039537, 'batch_size': 32} - Best Value (CSI): 0.465589 - Best Trial: 92 - Best Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.24759508454949322, 'ffn_dropout': 0.2013907953941948, 'lr': 0.0003711331440914647, 'weight_decay': 0.06954769328501528, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 04:53:57,074] Trial 94 pruned. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.370327 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.25947391435271694, 'ffn_dropout': 0.1749487831150375, 'lr': 0.0002210614647830701, 'weight_decay': 0.09700864977530034, 'batch_size': 32} - Best Value (CSI): 0.465589 - Best Trial: 92 - Best Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.24759508454949322, 'ffn_dropout': 0.2013907953941948, 'lr': 0.0003711331440914647, 'weight_decay': 0.06954769328501528, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 04:54:58,944] Trial 95 pruned. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.379261 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2698824138408282, 'ffn_dropout': 0.20932226869786041, 'lr': 0.00016027051213687697, 'weight_decay': 0.05149181775473954, 'batch_size': 32} - Best Value (CSI): 0.465589 - Best Trial: 92 - Best Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.24759508454949322, 'ffn_dropout': 0.2013907953941948, 'lr': 0.0003711331440914647, 'weight_decay': 0.06954769328501528, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 04:55:04,775] Trial 96 pruned. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.266927 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.24681916906843834, 'ffn_dropout': 0.15925528603733935, 'lr': 0.00034283130668631386, 'weight_decay': 0.07449417472487424, 'batch_size': 256} - Best Value (CSI): 0.465589 - Best Trial: 92 - Best Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.24759508454949322, 'ffn_dropout': 0.2013907953941948, 'lr': 0.0003711331440914647, 'weight_decay': 0.06954769328501528, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 04:56:28,619] Trial 97 pruned. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.359033 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2377925004208892, 'ffn_dropout': 0.1668042973311131, 'lr': 0.00012959502864005269, 'weight_decay': 0.09953493546155284, 'batch_size': 32} - Best Value (CSI): 0.465589 - Best Trial: 92 - Best Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.24759508454949322, 'ffn_dropout': 0.2013907953941948, 'lr': 0.0003711331440914647, 'weight_decay': 0.06954769328501528, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 04:56:38,850] Trial 98 pruned. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.310256 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2900582142320236, 'ffn_dropout': 0.18577243562412113, 'lr': 0.0002830984196360623, 'weight_decay': 0.043690195208951836, 'batch_size': 128} - Best Value (CSI): 0.465589 - Best Trial: 92 - Best Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.24759508454949322, 'ffn_dropout': 0.2013907953941948, 'lr': 0.0003711331440914647, 'weight_decay': 0.06954769328501528, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 40.275862068965516, 1: 3.0196483971044468, 2: 0.378213846253481} (클래스별 샘플 수: {0: 145, 1: 1934, 2: 15441}) -[I 2025-12-25 04:57:27,231] Trial 99 pruned. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.341162 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.26062911765607766, 'ffn_dropout': 0.1994652189335202, 'lr': 0.00019789603168893626, 'weight_decay': 0.060154853924075054, 'batch_size': 32} - Best Value (CSI): 0.465589 - Best Trial: 92 - Best Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.24759508454949322, 'ffn_dropout': 0.2013907953941948, 'lr': 0.0003711331440914647, 'weight_decay': 0.06954769328501528, 'batch_size': 32} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.4656 -Best Hyperparameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.24759508454949322, 'ffn_dropout': 0.2013907953941948, 'lr': 0.0003711331440914647, 'weight_decay': 0.06954769328501528, 'batch_size': 32} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.1303 - - 최종 CSI: 0.3412 - - 최고 CSI: 0.4869 - - 최저 CSI: 0.0000 - - 평균 CSI: 0.3438 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/ft_transformer_pure_daejeon_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 18, Best CSI: 0.3766 - Fold 1 학습 완료 (검증 CSI: 0.3766) -Fold 2 학습 중... - Early stopping at epoch 37, Best CSI: 0.4943 - Fold 2 학습 완료 (검증 CSI: 0.4943) -Fold 3 학습 중... - Early stopping at epoch 49, Best CSI: 0.4778 - Fold 3 학습 완료 (검증 CSI: 0.4778) - -모든 모델 저장 완료: ../save_model/ft_transformer_optima/ft_transformer_pure_daejeon.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/ft_transformer_optima/scaler/ft_transformer_pure_daejeon_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: - - . - - . - - / - - s - - a - - v - - e - - _ - - m - - o - - d - - e - - l - - / - - f - - t - - _ - - t - - r - - a - - n - - s - - f - - o - - r - - m - - e - - r - - _ - - o - - p - - t - - i - - m - - a - - / - - f - - t - - _ - - t - - r - - a - - n - - s - - f - - o - - r - - m - - e - - r - - _ - - p - - u - - r - - e - - _ - - d - - a - - e - - j - - e - - o - - n - - . - - p - - k - - l - -✓ 완료: ft_transformer_pure/ft_transforemer_pure_daejeon.py (소요 시간: 9802초) - ----------------------------------------- -실행 중: ft_transformer_pure/ft_transforemer_pure_gwangju.py -시작 시간: 2025-12-25 05:02:03 ----------------------------------------- -[I 2025-12-25 05:02:04,162] A new study created in memory with name: no-name-3a09f0a2-83d7-42d2-b634-d45b8354cf66 - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 114.66666666666667, 1: 4.335063009636768, 2: 0.3622398414271556} (클래스별 샘플 수: {0: 51, 1: 1349, 2: 16144}) -[I 2025-12-25 05:02:54,522] Trial 0 finished with value: 0.09711722395057353 and parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.29262855180304015, 'ffn_dropout': 0.19893286521589182, 'lr': 0.0019623690950916596, 'weight_decay': 0.0001793027408356603, 'batch_size': 128}. Best is trial 0 with value: 0.09711722395057353. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.097117 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.29262855180304015, 'ffn_dropout': 0.19893286521589182, 'lr': 0.0019623690950916596, 'weight_decay': 0.0001793027408356603, 'batch_size': 128} - Best Value (CSI): 0.097117 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.29262855180304015, 'ffn_dropout': 0.19893286521589182, 'lr': 0.0019623690950916596, 'weight_decay': 0.0001793027408356603, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 114.66666666666667, 1: 4.335063009636768, 2: 0.3622398414271556} (클래스별 샘플 수: {0: 51, 1: 1349, 2: 16144}) -[I 2025-12-25 05:04:40,253] Trial 1 finished with value: 0.09167591968793302 and parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.2743178890378547, 'ffn_dropout': 0.30092594792497473, 'lr': 0.0020736408681141087, 'weight_decay': 0.0870661299358735, 'batch_size': 64}. Best is trial 0 with value: 0.09711722395057353. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.091676 - Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.2743178890378547, 'ffn_dropout': 0.30092594792497473, 'lr': 0.0020736408681141087, 'weight_decay': 0.0870661299358735, 'batch_size': 64} - Best Value (CSI): 0.097117 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.29262855180304015, 'ffn_dropout': 0.19893286521589182, 'lr': 0.0019623690950916596, 'weight_decay': 0.0001793027408356603, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 114.66666666666667, 1: 4.335063009636768, 2: 0.3622398414271556} (클래스별 샘플 수: {0: 51, 1: 1349, 2: 16144}) -[I 2025-12-25 05:06:06,109] Trial 2 finished with value: 0.027373960548928197 and parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2026868471197999, 'ffn_dropout': 0.3025630197805988, 'lr': 0.003333344593317576, 'weight_decay': 0.03784694529277321, 'batch_size': 32}. Best is trial 0 with value: 0.09711722395057353. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.027374 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2026868471197999, 'ffn_dropout': 0.3025630197805988, 'lr': 0.003333344593317576, 'weight_decay': 0.03784694529277321, 'batch_size': 32} - Best Value (CSI): 0.097117 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.29262855180304015, 'ffn_dropout': 0.19893286521589182, 'lr': 0.0019623690950916596, 'weight_decay': 0.0001793027408356603, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 114.66666666666667, 1: 4.335063009636768, 2: 0.3622398414271556} (클래스별 샘플 수: {0: 51, 1: 1349, 2: 16144}) -[I 2025-12-25 05:07:52,978] Trial 3 finished with value: 0.08981917274635197 and parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12449588652198683, 'ffn_dropout': 0.3429009226079186, 'lr': 0.0022344600807863526, 'weight_decay': 0.0017879678345691476, 'batch_size': 32}. Best is trial 0 with value: 0.09711722395057353. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.089819 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12449588652198683, 'ffn_dropout': 0.3429009226079186, 'lr': 0.0022344600807863526, 'weight_decay': 0.0017879678345691476, 'batch_size': 32} - Best Value (CSI): 0.097117 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.29262855180304015, 'ffn_dropout': 0.19893286521589182, 'lr': 0.0019623690950916596, 'weight_decay': 0.0001793027408356603, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 114.66666666666667, 1: 4.335063009636768, 2: 0.3622398414271556} (클래스별 샘플 수: {0: 51, 1: 1349, 2: 16144}) -[I 2025-12-25 05:11:10,844] Trial 4 finished with value: 0.09167591968793302 and parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39530548107743024, 'ffn_dropout': 0.33160374097830697, 'lr': 0.0069056782512902405, 'weight_decay': 0.04913392440897764, 'batch_size': 32}. Best is trial 0 with value: 0.09711722395057353. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.091676 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39530548107743024, 'ffn_dropout': 0.33160374097830697, 'lr': 0.0069056782512902405, 'weight_decay': 0.04913392440897764, 'batch_size': 32} - Best Value (CSI): 0.097117 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.29262855180304015, 'ffn_dropout': 0.19893286521589182, 'lr': 0.0019623690950916596, 'weight_decay': 0.0001793027408356603, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 114.66666666666667, 1: 4.335063009636768, 2: 0.3622398414271556} (클래스별 샘플 수: {0: 51, 1: 1349, 2: 16144}) -[I 2025-12-25 05:12:53,538] Trial 5 finished with value: 0.22204656660795327 and parameters: {'d_token': 256, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.2914882522894078, 'ffn_dropout': 0.20783178249421266, 'lr': 0.00046747811127472214, 'weight_decay': 0.0772041002784932, 'batch_size': 64}. Best is trial 5 with value: 0.22204656660795327. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.222047 - Parameters: {'d_token': 256, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.2914882522894078, 'ffn_dropout': 0.20783178249421266, 'lr': 0.00046747811127472214, 'weight_decay': 0.0772041002784932, 'batch_size': 64} - Best Value (CSI): 0.222047 - Best Trial: 5 - Best Parameters: {'d_token': 256, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.2914882522894078, 'ffn_dropout': 0.20783178249421266, 'lr': 0.00046747811127472214, 'weight_decay': 0.0772041002784932, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 114.66666666666667, 1: 4.335063009636768, 2: 0.3622398414271556} (클래스별 샘플 수: {0: 51, 1: 1349, 2: 16144}) -[I 2025-12-25 05:15:57,879] Trial 6 finished with value: 0.024400425015178834 and parameters: {'d_token': 224, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.27408776402465795, 'ffn_dropout': 0.11814799828174796, 'lr': 0.0019215476581536828, 'weight_decay': 0.0016069884023401377, 'batch_size': 32}. Best is trial 5 with value: 0.22204656660795327. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.024400 - Parameters: {'d_token': 224, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.27408776402465795, 'ffn_dropout': 0.11814799828174796, 'lr': 0.0019215476581536828, 'weight_decay': 0.0016069884023401377, 'batch_size': 32} - Best Value (CSI): 0.222047 - Best Trial: 5 - Best Parameters: {'d_token': 256, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.2914882522894078, 'ffn_dropout': 0.20783178249421266, 'lr': 0.00046747811127472214, 'weight_decay': 0.0772041002784932, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 114.66666666666667, 1: 4.335063009636768, 2: 0.3622398414271556} (클래스별 샘플 수: {0: 51, 1: 1349, 2: 16144}) -[I 2025-12-25 05:16:49,249] Trial 7 finished with value: 0.4075205630618481 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.39925760866529836, 'ffn_dropout': 0.33973484450671276, 'lr': 0.00016610665721224484, 'weight_decay': 0.0001261438721450454, 'batch_size': 256}. Best is trial 7 with value: 0.4075205630618481. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.407521 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.39925760866529836, 'ffn_dropout': 0.33973484450671276, 'lr': 0.00016610665721224484, 'weight_decay': 0.0001261438721450454, 'batch_size': 256} - Best Value (CSI): 0.407521 - Best Trial: 7 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.39925760866529836, 'ffn_dropout': 0.33973484450671276, 'lr': 0.00016610665721224484, 'weight_decay': 0.0001261438721450454, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 114.66666666666667, 1: 4.335063009636768, 2: 0.3622398414271556} (클래스별 샘플 수: {0: 51, 1: 1349, 2: 16144}) -[I 2025-12-25 05:18:25,276] Trial 8 finished with value: 0.46013157463180815 and parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.1663415378158141, 'ffn_dropout': 0.30898861936978617, 'lr': 0.00036352832902233055, 'weight_decay': 0.002261790524891314, 'batch_size': 128}. Best is trial 8 with value: 0.46013157463180815. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.460132 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.1663415378158141, 'ffn_dropout': 0.30898861936978617, 'lr': 0.00036352832902233055, 'weight_decay': 0.002261790524891314, 'batch_size': 128} - Best Value (CSI): 0.460132 - Best Trial: 8 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.1663415378158141, 'ffn_dropout': 0.30898861936978617, 'lr': 0.00036352832902233055, 'weight_decay': 0.002261790524891314, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 114.66666666666667, 1: 4.335063009636768, 2: 0.3622398414271556} (클래스별 샘플 수: {0: 51, 1: 1349, 2: 16144}) -[I 2025-12-25 05:19:05,894] Trial 9 finished with value: 0.3864056835438296 and parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.2700224417659769, 'ffn_dropout': 0.2602179867754312, 'lr': 0.001876313153377928, 'weight_decay': 0.0025295377327571623, 'batch_size': 256}. Best is trial 8 with value: 0.46013157463180815. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.386406 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.2700224417659769, 'ffn_dropout': 0.2602179867754312, 'lr': 0.001876313153377928, 'weight_decay': 0.0025295377327571623, 'batch_size': 256} - Best Value (CSI): 0.460132 - Best Trial: 8 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.1663415378158141, 'ffn_dropout': 0.30898861936978617, 'lr': 0.00036352832902233055, 'weight_decay': 0.002261790524891314, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:19:19,595] Trial 10 pruned. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.289110 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.1005861961469651, 'ffn_dropout': 0.3868916395381999, 'lr': 1.58864589566609e-05, 'weight_decay': 0.011374196132424614, 'batch_size': 128} - Best Value (CSI): 0.460132 - Best Trial: 8 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.1663415378158141, 'ffn_dropout': 0.30898861936978617, 'lr': 0.00036352832902233055, 'weight_decay': 0.002261790524891314, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:19:29,525] Trial 11 pruned. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.291946 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.3969727802531813, 'ffn_dropout': 0.36461355438984316, 'lr': 0.000124264334040086, 'weight_decay': 0.00012635254515303018, 'batch_size': 256} - Best Value (CSI): 0.460132 - Best Trial: 8 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.1663415378158141, 'ffn_dropout': 0.30898861936978617, 'lr': 0.00036352832902233055, 'weight_decay': 0.002261790524891314, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:19:39,483] Trial 12 pruned. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.371849 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.1801701950985205, 'ffn_dropout': 0.3679847878882928, 'lr': 0.0002084475358430697, 'weight_decay': 0.0004322383296510278, 'batch_size': 256} - Best Value (CSI): 0.460132 - Best Trial: 8 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.1663415378158141, 'ffn_dropout': 0.30898861936978617, 'lr': 0.00036352832902233055, 'weight_decay': 0.002261790524891314, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) -[I 2025-12-25 05:20:16,950] Trial 13 pruned. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.386139 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.33816383601401845, 'ffn_dropout': 0.3946511152846607, 'lr': 8.211769654135713e-05, 'weight_decay': 0.0005907439109310786, 'batch_size': 128} - Best Value (CSI): 0.460132 - Best Trial: 8 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.1663415378158141, 'ffn_dropout': 0.30898861936978617, 'lr': 0.00036352832902233055, 'weight_decay': 0.002261790524891314, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 114.66666666666667, 1: 4.335063009636768, 2: 0.3622398414271556} (클래스별 샘플 수: {0: 51, 1: 1349, 2: 16144}) -[I 2025-12-25 05:21:34,190] Trial 14 finished with value: 0.4471053892943319 and parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.19845745033017642, 'ffn_dropout': 0.3078664006280304, 'lr': 0.0004945624430722741, 'weight_decay': 0.008076961501678102, 'batch_size': 128}. Best is trial 8 with value: 0.46013157463180815. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.447105 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.19845745033017642, 'ffn_dropout': 0.3078664006280304, 'lr': 0.0004945624430722741, 'weight_decay': 0.008076961501678102, 'batch_size': 128} - Best Value (CSI): 0.460132 - Best Trial: 8 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.1663415378158141, 'ffn_dropout': 0.30898861936978617, 'lr': 0.00036352832902233055, 'weight_decay': 0.002261790524891314, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:21:50,190] Trial 15 pruned. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.409370 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.19683441510898547, 'ffn_dropout': 0.2867763607880951, 'lr': 0.0006237685003961505, 'weight_decay': 0.007407819917978954, 'batch_size': 128} - Best Value (CSI): 0.460132 - Best Trial: 8 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.1663415378158141, 'ffn_dropout': 0.30898861936978617, 'lr': 0.00036352832902233055, 'weight_decay': 0.002261790524891314, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 114.66666666666667, 1: 4.335063009636768, 2: 0.3622398414271556} (클래스별 샘플 수: {0: 51, 1: 1349, 2: 16144}) -[I 2025-12-25 05:22:51,437] Trial 16 finished with value: 0.45146154174905967 and parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.16284518012838253, 'ffn_dropout': 0.2522420270144627, 'lr': 0.0007985608493790112, 'weight_decay': 0.005982033150207093, 'batch_size': 128}. Best is trial 8 with value: 0.46013157463180815. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.451462 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.16284518012838253, 'ffn_dropout': 0.2522420270144627, 'lr': 0.0007985608493790112, 'weight_decay': 0.005982033150207093, 'batch_size': 128} - Best Value (CSI): 0.460132 - Best Trial: 8 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.1663415378158141, 'ffn_dropout': 0.30898861936978617, 'lr': 0.00036352832902233055, 'weight_decay': 0.002261790524891314, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:23:07,026] Trial 17 pruned. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.366712 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.15556176869411126, 'ffn_dropout': 0.24490380246951735, 'lr': 0.0007716678761443495, 'weight_decay': 0.004100399837590382, 'batch_size': 128} - Best Value (CSI): 0.460132 - Best Trial: 8 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.1663415378158141, 'ffn_dropout': 0.30898861936978617, 'lr': 0.00036352832902233055, 'weight_decay': 0.002261790524891314, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:23:27,834] Trial 18 pruned. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.370551 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.2278667931985267, 'ffn_dropout': 0.2617217810559588, 'lr': 0.00028393760295564207, 'weight_decay': 0.018238744121195336, 'batch_size': 128} - Best Value (CSI): 0.460132 - Best Trial: 8 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.1663415378158141, 'ffn_dropout': 0.30898861936978617, 'lr': 0.00036352832902233055, 'weight_decay': 0.002261790524891314, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:23:44,530] Trial 19 pruned. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.369475 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.14082126853676113, 'ffn_dropout': 0.2302084572127562, 'lr': 6.960168496596925e-05, 'weight_decay': 0.003464112603788143, 'batch_size': 128} - Best Value (CSI): 0.460132 - Best Trial: 8 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.1663415378158141, 'ffn_dropout': 0.30898861936978617, 'lr': 0.00036352832902233055, 'weight_decay': 0.002261790524891314, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 114.66666666666667, 1: 4.335063009636768, 2: 0.3622398414271556} (클래스별 샘플 수: {0: 51, 1: 1349, 2: 16144}) -[I 2025-12-25 05:24:45,179] Trial 20 finished with value: 0.31936252241261154 and parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.1484117292040626, 'ffn_dropout': 0.2769221786119898, 'lr': 0.0009090109987182563, 'weight_decay': 0.0011252896577516908, 'batch_size': 64}. Best is trial 8 with value: 0.46013157463180815. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.319363 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.1484117292040626, 'ffn_dropout': 0.2769221786119898, 'lr': 0.0009090109987182563, 'weight_decay': 0.0011252896577516908, 'batch_size': 64} - Best Value (CSI): 0.460132 - Best Trial: 8 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.1663415378158141, 'ffn_dropout': 0.30898861936978617, 'lr': 0.00036352832902233055, 'weight_decay': 0.002261790524891314, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) -[I 2025-12-25 05:25:30,366] Trial 21 pruned. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.441022 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.17178129214328822, 'ffn_dropout': 0.3140487814323126, 'lr': 0.0005558914007216449, 'weight_decay': 0.005899356329977749, 'batch_size': 128} - Best Value (CSI): 0.460132 - Best Trial: 8 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.1663415378158141, 'ffn_dropout': 0.30898861936978617, 'lr': 0.00036352832902233055, 'weight_decay': 0.002261790524891314, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:25:52,086] Trial 22 pruned. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.414653 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22487784947661632, 'ffn_dropout': 0.3114583507201134, 'lr': 0.00033577651379597417, 'weight_decay': 0.015402129854042585, 'batch_size': 128} - Best Value (CSI): 0.460132 - Best Trial: 8 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.1663415378158141, 'ffn_dropout': 0.30898861936978617, 'lr': 0.00036352832902233055, 'weight_decay': 0.002261790524891314, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) -[I 2025-12-25 05:26:34,648] Trial 23 pruned. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.433990 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.17363682239766687, 'ffn_dropout': 0.28220341531224363, 'lr': 0.0009079147826912145, 'weight_decay': 0.006364470928914251, 'batch_size': 128} - Best Value (CSI): 0.460132 - Best Trial: 8 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.1663415378158141, 'ffn_dropout': 0.30898861936978617, 'lr': 0.00036352832902233055, 'weight_decay': 0.002261790524891314, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:26:51,196] Trial 24 pruned. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.326639 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2004119772372248, 'ffn_dropout': 0.2769213367210678, 'lr': 0.00030170474913777777, 'weight_decay': 0.003762689346089469, 'batch_size': 128} - Best Value (CSI): 0.460132 - Best Trial: 8 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.1663415378158141, 'ffn_dropout': 0.30898861936978617, 'lr': 0.00036352832902233055, 'weight_decay': 0.002261790524891314, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:27:10,820] Trial 25 pruned. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.408848 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.12288253853654899, 'ffn_dropout': 0.32949439807164144, 'lr': 0.0010585890443665388, 'weight_decay': 0.009962537819236516, 'batch_size': 128} - Best Value (CSI): 0.460132 - Best Trial: 8 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.1663415378158141, 'ffn_dropout': 0.30898861936978617, 'lr': 0.00036352832902233055, 'weight_decay': 0.002261790524891314, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:27:33,818] Trial 26 pruned. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.377241 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.16229383949298243, 'ffn_dropout': 0.23849548374423873, 'lr': 0.0004257198144025464, 'weight_decay': 0.01906723754086527, 'batch_size': 128} - Best Value (CSI): 0.460132 - Best Trial: 8 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.1663415378158141, 'ffn_dropout': 0.30898861936978617, 'lr': 0.00036352832902233055, 'weight_decay': 0.002261790524891314, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:27:57,668] Trial 27 pruned. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.360973 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.18786017019095563, 'ffn_dropout': 0.3168079816519877, 'lr': 0.0002160238363794102, 'weight_decay': 0.004966735364284992, 'batch_size': 128} - Best Value (CSI): 0.460132 - Best Trial: 8 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.1663415378158141, 'ffn_dropout': 0.30898861936978617, 'lr': 0.00036352832902233055, 'weight_decay': 0.002261790524891314, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 114.66666666666667, 1: 4.335063009636768, 2: 0.3622398414271556} (클래스별 샘플 수: {0: 51, 1: 1349, 2: 16144}) -[I 2025-12-25 05:30:31,145] Trial 28 finished with value: 0.46517686569307726 and parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64}. Best is trial 28 with value: 0.46517686569307726. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.465177 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 114.66666666666667, 1: 4.335063009636768, 2: 0.3622398414271556} (클래스별 샘플 수: {0: 51, 1: 1349, 2: 16144}) -[I 2025-12-25 05:31:51,961] Trial 29 finished with value: 0.461071532540925 and parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.22221093325088664, 'ffn_dropout': 0.3572861091380669, 'lr': 0.0012158992947908314, 'weight_decay': 0.002534627693749831, 'batch_size': 64}. Best is trial 28 with value: 0.46517686569307726. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.461072 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.22221093325088664, 'ffn_dropout': 0.3572861091380669, 'lr': 0.0012158992947908314, 'weight_decay': 0.002534627693749831, 'batch_size': 64} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 114.66666666666667, 1: 4.335063009636768, 2: 0.3622398414271556} (클래스별 샘플 수: {0: 51, 1: 1349, 2: 16144}) -[I 2025-12-25 05:34:48,642] Trial 30 finished with value: 0.4520009478793458 and parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.22981557876763814, 'ffn_dropout': 0.36459507802943675, 'lr': 0.0014461516017665384, 'weight_decay': 0.000872091340821586, 'batch_size': 64}. Best is trial 28 with value: 0.46517686569307726. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.452001 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.22981557876763814, 'ffn_dropout': 0.36459507802943675, 'lr': 0.0014461516017665384, 'weight_decay': 0.000872091340821586, 'batch_size': 64} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:35:50,379] Trial 31 pruned. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.391273 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2345111771535317, 'ffn_dropout': 0.3547749501611806, 'lr': 0.0012915401417742903, 'weight_decay': 0.0008760605205286531, 'batch_size': 64} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:36:29,389] Trial 32 pruned. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.386364 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.24746346468511665, 'ffn_dropout': 0.3749218377186346, 'lr': 0.0013765408278672378, 'weight_decay': 0.0022166967860632347, 'batch_size': 64} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:36:41,751] Trial 33 pruned. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.039179 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2081877165034573, 'ffn_dropout': 0.39743411340801094, 'lr': 0.0034549270490634794, 'weight_decay': 0.0013298808970797153, 'batch_size': 64} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:36:56,107] Trial 34 pruned. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.302632 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.21496052350070946, 'ffn_dropout': 0.3495988550509811, 'lr': 0.002855594477575197, 'weight_decay': 0.0023734533382712094, 'batch_size': 64} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:37:09,226] Trial 35 pruned. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.052264 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.25103120996051304, 'ffn_dropout': 0.37829578781816575, 'lr': 0.004544169882755556, 'weight_decay': 0.002664946366427354, 'batch_size': 64} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:37:34,717] Trial 36 pruned. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.243563 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.21676242437737786, 'ffn_dropout': 0.34796452858231725, 'lr': 0.0015240983602085206, 'weight_decay': 0.0016669257621242497, 'batch_size': 64} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:37:46,734] Trial 37 pruned. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.087565 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.18881693326609966, 'ffn_dropout': 0.36094146943466665, 'lr': 0.0023473867033466773, 'weight_decay': 0.0009043190554852143, 'batch_size': 64} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:37:59,733] Trial 38 pruned. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.23891031199799023, 'ffn_dropout': 0.3251640335589496, 'lr': 0.009814686917414805, 'weight_decay': 0.00043360422780191007, 'batch_size': 64} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:38:27,397] Trial 39 pruned. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.073201 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2610336984850971, 'ffn_dropout': 0.33700550506496213, 'lr': 0.0012452778567671706, 'weight_decay': 0.002984376345105177, 'batch_size': 32} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:38:43,532] Trial 40 pruned. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.213375689667259, 'ffn_dropout': 0.3780538007518284, 'lr': 0.001899072396845153, 'weight_decay': 0.001860530970735027, 'batch_size': 64} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:39:12,942] Trial 41 pruned. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.385447 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.16747555755250743, 'ffn_dropout': 0.29880532353135986, 'lr': 0.0006938773377488943, 'weight_decay': 0.0035720364986428083, 'batch_size': 64} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:41:00,726] Trial 42 pruned. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.381663 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.18570198927704246, 'ffn_dropout': 0.3390371917575428, 'lr': 0.0008765654596846273, 'weight_decay': 0.0048811133388722405, 'batch_size': 32} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:41:26,502] Trial 43 pruned. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.2276006084136979, 'ffn_dropout': 0.350422562705314, 'lr': 0.001609754737017845, 'weight_decay': 0.0019436356164982762, 'batch_size': 64} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:41:35,672] Trial 44 pruned. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.372173 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.284989003938103, 'ffn_dropout': 0.3628240658055896, 'lr': 0.0006880215545277704, 'weight_decay': 0.0014012451966706199, 'batch_size': 256} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:41:54,983] Trial 45 pruned. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.20437588011522517, 'ffn_dropout': 0.384340675750214, 'lr': 0.0010986524674709102, 'weight_decay': 0.0029623969358937344, 'batch_size': 64} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:42:51,301] Trial 46 pruned. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.375587 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.1740621890543514, 'ffn_dropout': 0.3242837976995512, 'lr': 0.00044885580132517436, 'weight_decay': 0.0047843500336699025, 'batch_size': 32} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:43:06,694] Trial 47 pruned. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.070515 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2500683816159819, 'ffn_dropout': 0.29737590307281286, 'lr': 0.002333315960631975, 'weight_decay': 0.0011420274607976933, 'batch_size': 64} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:43:14,145] Trial 48 pruned. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.371487 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.19242257009268757, 'ffn_dropout': 0.33955996676252903, 'lr': 0.0007018587840228305, 'weight_decay': 0.0024476402195342767, 'batch_size': 256} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:43:29,309] Trial 49 pruned. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1371215156564099, 'ffn_dropout': 0.37108076005872537, 'lr': 0.0017511665258131168, 'weight_decay': 0.00022126038282386636, 'batch_size': 64} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:43:57,113] Trial 50 pruned. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.383929 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.15738788907729614, 'ffn_dropout': 0.3585968644060297, 'lr': 0.0011279892881025898, 'weight_decay': 0.0019184457141561805, 'batch_size': 64} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 114.66666666666667, 1: 4.335063009636768, 2: 0.3622398414271556} (클래스별 샘플 수: {0: 51, 1: 1349, 2: 16144}) -[I 2025-12-25 05:44:58,948] Trial 51 pruned. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.465940 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.19809818515214467, 'ffn_dropout': 0.3039636458767096, 'lr': 0.0004800113690111531, 'weight_decay': 0.007275858759230468, 'batch_size': 128} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:45:15,166] Trial 52 pruned. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.383523 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.1782194199030736, 'ffn_dropout': 0.3882725662150924, 'lr': 0.0006295300153683286, 'weight_decay': 0.008661762840104599, 'batch_size': 128} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 114.66666666666667, 1: 4.335063009636768, 2: 0.3622398414271556} (클래스별 샘플 수: {0: 51, 1: 1349, 2: 16144}) -[I 2025-12-25 05:46:45,249] Trial 53 finished with value: 0.4542044767929346 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.21901921307226072, 'ffn_dropout': 0.32688892686744137, 'lr': 0.0008702091528213914, 'weight_decay': 0.0037671432118682154, 'batch_size': 128}. Best is trial 28 with value: 0.46517686569307726. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.454204 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.21901921307226072, 'ffn_dropout': 0.32688892686744137, 'lr': 0.0008702091528213914, 'weight_decay': 0.0037671432118682154, 'batch_size': 128} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:46:57,816] Trial 54 pruned. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.366188 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.22072618574089317, 'ffn_dropout': 0.3174444725495746, 'lr': 0.0008891975602638085, 'weight_decay': 0.0038780695570615428, 'batch_size': 128} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:47:09,055] Trial 55 pruned. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.352863 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.23663151614390204, 'ffn_dropout': 0.3339439630294819, 'lr': 0.0014766532550647155, 'weight_decay': 0.005966185994188241, 'batch_size': 128} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:47:22,118] Trial 56 pruned. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.389747 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.21427661525833494, 'ffn_dropout': 0.36786529543080887, 'lr': 0.0003737764092888425, 'weight_decay': 0.0033585971022743666, 'batch_size': 128} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:47:29,274] Trial 57 pruned. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.323804 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.2691526275996794, 'ffn_dropout': 0.34860185887799855, 'lr': 0.0005571043260833596, 'weight_decay': 0.001481446310561865, 'batch_size': 256} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:47:36,181] Trial 58 pruned. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.245392 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.20524896192559924, 'ffn_dropout': 0.3281930539443096, 'lr': 0.0009893064402221694, 'weight_decay': 0.004479506020333192, 'batch_size': 128} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:48:20,494] Trial 59 pruned. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.412804 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.18181018176313696, 'ffn_dropout': 0.2913568337919433, 'lr': 0.0008522402683237674, 'weight_decay': 0.002840467584660579, 'batch_size': 32} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:48:41,159] Trial 60 pruned. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.362745 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.22649371699807494, 'ffn_dropout': 0.26380274372292395, 'lr': 0.0005029539608235313, 'weight_decay': 0.0024025949798825094, 'batch_size': 128} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:48:56,486] Trial 61 pruned. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.404164 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.19523082393837196, 'ffn_dropout': 0.30665671861890154, 'lr': 0.0003772828147012614, 'weight_decay': 0.008050725471452858, 'batch_size': 128} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:49:12,615] Trial 62 pruned. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.386236 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.20582499323739398, 'ffn_dropout': 0.3200554663857304, 'lr': 0.0007193590114586899, 'weight_decay': 0.011927207836846613, 'batch_size': 128} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:49:30,948] Trial 63 pruned. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.369252 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.16400786464751083, 'ffn_dropout': 0.3089941341623069, 'lr': 0.0012049442947190602, 'weight_decay': 0.006495049346872716, 'batch_size': 128} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:49:43,940] Trial 64 pruned. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.393266 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.22146830714751656, 'ffn_dropout': 0.34241158087887413, 'lr': 0.0005857140462077315, 'weight_decay': 0.005046533535908529, 'batch_size': 128} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:49:58,443] Trial 65 pruned. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.391335 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.18148257746371563, 'ffn_dropout': 0.2909150756305158, 'lr': 0.0003021626981653297, 'weight_decay': 0.0036164852898987487, 'batch_size': 128} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:50:21,389] Trial 66 pruned. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.393119 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.23546558256348837, 'ffn_dropout': 0.3580228121555677, 'lr': 0.0010578076378718554, 'weight_decay': 0.005663573099266001, 'batch_size': 64} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:50:34,263] Trial 67 pruned. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.400290 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.19531311866770573, 'ffn_dropout': 0.3304329918864657, 'lr': 0.0013988310746714586, 'weight_decay': 0.0038821942335004697, 'batch_size': 128} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:51:02,379] Trial 68 pruned. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.376833 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.15328439750849324, 'ffn_dropout': 0.2735230099607816, 'lr': 0.0008210779200773781, 'weight_decay': 0.002123764269250208, 'batch_size': 64} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:51:10,679] Trial 69 pruned. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.115039 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.21221501657175712, 'ffn_dropout': 0.39943238805553805, 'lr': 0.0020112673788907427, 'weight_decay': 0.0027708007900058263, 'batch_size': 128} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:51:37,245] Trial 70 pruned. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.365782 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.24508307801893614, 'ffn_dropout': 0.312761501400733, 'lr': 0.0002616712944099542, 'weight_decay': 0.009821263724479366, 'batch_size': 64} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:51:42,615] Trial 71 pruned. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.295052 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.3495938368308896, 'ffn_dropout': 0.3436467109307653, 'lr': 0.0004036337102077431, 'weight_decay': 0.00011759957867519061, 'batch_size': 256} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:51:48,885] Trial 72 pruned. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.313180 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.23162026607027847, 'ffn_dropout': 0.3537557380874828, 'lr': 0.00014884411093250496, 'weight_decay': 0.00022350812096312578, 'batch_size': 256} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:51:58,821] Trial 73 pruned. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.340161 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.21944597997936288, 'ffn_dropout': 0.33505451841021905, 'lr': 0.0004935656588640028, 'weight_decay': 0.0001571931242211524, 'batch_size': 256} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:52:10,889] Trial 74 pruned. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.388100 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.25721194150571974, 'ffn_dropout': 0.37036767102697127, 'lr': 0.000555029323567799, 'weight_decay': 0.0016658297448969963, 'batch_size': 256} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:52:15,281] Trial 75 pruned. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.304090 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.24360549622730884, 'ffn_dropout': 0.318451740789571, 'lr': 0.0002365632669682442, 'weight_decay': 0.0007390131904735075, 'batch_size': 256} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 114.66666666666667, 1: 4.335063009636768, 2: 0.3622398414271556} (클래스별 샘플 수: {0: 51, 1: 1349, 2: 16144}) -[I 2025-12-25 05:54:10,572] Trial 76 pruned. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.484242 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.3849972050663171, 'ffn_dropout': 0.36219424517767623, 'lr': 0.00019980593585168535, 'weight_decay': 0.001086533649143069, 'batch_size': 64} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:54:25,144] Trial 77 pruned. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.375413 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.22710796079928153, 'ffn_dropout': 0.3447564480543577, 'lr': 0.0016550015356752905, 'weight_decay': 0.0005261708526353079, 'batch_size': 128} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:55:07,458] Trial 78 pruned. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.402768 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.20133111357686587, 'ffn_dropout': 0.3262565124850321, 'lr': 0.0007431383509760672, 'weight_decay': 0.004359685368192822, 'batch_size': 32} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) -[I 2025-12-25 05:56:14,644] Trial 79 pruned. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.432028 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.17047730935847139, 'ffn_dropout': 0.35331788824652566, 'lr': 0.00032347448481312945, 'weight_decay': 0.0032925650907495766, 'batch_size': 64} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:56:24,580] Trial 80 pruned. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.064919 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.19283635734199422, 'ffn_dropout': 0.30368065499321434, 'lr': 0.0009826334417181457, 'weight_decay': 0.0003436022532237786, 'batch_size': 128} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:56:32,559] Trial 81 pruned. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.352864 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.309816225707421, 'ffn_dropout': 0.22569486585989065, 'lr': 0.0012386082484920774, 'weight_decay': 0.00217559490473419, 'batch_size': 256} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:56:39,257] Trial 82 pruned. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.186181 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.21035058709435583, 'ffn_dropout': 0.2487511746675919, 'lr': 0.0020830335496524193, 'weight_decay': 0.0018812669631650895, 'batch_size': 256} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:56:46,525] Trial 83 pruned. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.206114 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.1848567498495778, 'ffn_dropout': 0.25892037052134503, 'lr': 0.0015137534420347403, 'weight_decay': 0.00257585668121529, 'batch_size': 256} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:56:55,620] Trial 84 pruned. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.312982 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2403091363846552, 'ffn_dropout': 0.28205608512572355, 'lr': 0.0025347511755171655, 'weight_decay': 0.001285460122674878, 'batch_size': 256} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:57:31,514] Trial 85 pruned. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.371901 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.2345998236091512, 'ffn_dropout': 0.37674695361595506, 'lr': 0.0006407619518640441, 'weight_decay': 0.00010414088658001112, 'batch_size': 64} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:57:42,462] Trial 86 pruned. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.210870 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.2567713963921216, 'ffn_dropout': 0.33543327943163503, 'lr': 0.001903746662861581, 'weight_decay': 0.0015857077181221351, 'batch_size': 128} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 114.66666666666667, 1: 4.335063009636768, 2: 0.3622398414271556} (클래스별 샘플 수: {0: 51, 1: 1349, 2: 16144}) -[I 2025-12-25 05:59:25,717] Trial 87 finished with value: 0.4542621353196135 and parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.22014459601974626, 'ffn_dropout': 0.36659844334591213, 'lr': 0.0007998324941771957, 'weight_decay': 0.0042062275733193944, 'batch_size': 64}. Best is trial 28 with value: 0.46517686569307726. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.454262 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.22014459601974626, 'ffn_dropout': 0.36659844334591213, 'lr': 0.0007998324941771957, 'weight_decay': 0.0042062275733193944, 'batch_size': 64} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 05:59:46,501] Trial 88 pruned. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.380762 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.22986245006022354, 'ffn_dropout': 0.3649718054034906, 'lr': 0.0008141432035146417, 'weight_decay': 0.004179715130208902, 'batch_size': 64} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 06:00:14,770] Trial 89 pruned. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.363897 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.21915273874116184, 'ffn_dropout': 0.3845996608392798, 'lr': 0.0009966443742309128, 'weight_decay': 0.005411218855923533, 'batch_size': 64} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 06:00:40,357] Trial 90 pruned. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.402985 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2106543876426483, 'ffn_dropout': 0.355730458627069, 'lr': 0.00042844820717211573, 'weight_decay': 0.0031947046839435776, 'batch_size': 64} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 06:00:52,179] Trial 91 pruned. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.209264 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.19981917592497048, 'ffn_dropout': 0.3426064494145769, 'lr': 0.0013523901953797967, 'weight_decay': 0.006877258579683283, 'batch_size': 64} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 06:01:22,516] Trial 92 pruned. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.394476 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.22355628560524476, 'ffn_dropout': 0.36816221327440984, 'lr': 0.0011125714472882409, 'weight_decay': 0.0029744934263087205, 'batch_size': 64} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 06:01:42,240] Trial 93 pruned. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.386247 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.18991410476162215, 'ffn_dropout': 0.3210520435095761, 'lr': 0.0007829455069114803, 'weight_decay': 0.0022945090990425378, 'batch_size': 128} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 06:01:50,623] Trial 94 pruned. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.366769 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2048234628706, 'ffn_dropout': 0.3509426305429772, 'lr': 0.0016579506894987372, 'weight_decay': 0.004767001010939034, 'batch_size': 256} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 06:02:13,777] Trial 95 pruned. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.388049 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.17821817465874765, 'ffn_dropout': 0.3139832410519233, 'lr': 0.0005976572308687453, 'weight_decay': 0.006017686746266306, 'batch_size': 64} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 06:02:55,946] Trial 96 pruned. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.073201 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.23884142007375667, 'ffn_dropout': 0.33083844601763823, 'lr': 0.0009213260411406948, 'weight_decay': 0.003912352190526453, 'batch_size': 32} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 74.0253164556962, 1: 3.4299120234604104, 2: 0.3710659898477157} (클래스별 샘플 수: {0: 79, 1: 1705, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 114.66666666666667, 1: 4.335063009636768, 2: 0.3622398414271556} (클래스별 샘플 수: {0: 51, 1: 1349, 2: 16144}) -[I 2025-12-25 06:04:55,085] Trial 97 pruned. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.486800 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.24906224197316087, 'ffn_dropout': 0.29861389261342197, 'lr': 0.0006873520091813965, 'weight_decay': 0.002659948153677358, 'batch_size': 128} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 06:05:22,700] Trial 98 pruned. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.378522 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.21656943991370947, 'ffn_dropout': 0.3909958804656269, 'lr': 0.0012301024257874446, 'weight_decay': 0.0017261201580247617, 'batch_size': 128} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 97.33333333333333, 1: 3.3031674208144794, 2: 0.3721641600815702} (클래스별 샘플 수: {0: 60, 1: 1768, 2: 15692}) -[I 2025-12-25 06:06:18,795] Trial 99 pruned. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.390335 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.16438228655864257, 'ffn_dropout': 0.37961840655094414, 'lr': 0.00035038170096574224, 'weight_decay': 0.0020553505446097575, 'batch_size': 64} - Best Value (CSI): 0.465177 - Best Trial: 28 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.4652 -Best Hyperparameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22191677554696004, 'ffn_dropout': 0.3593673195268826, 'lr': 0.001039914773988631, 'weight_decay': 0.002578609852830777, 'batch_size': 64} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.0971 - - 최종 CSI: 0.3903 - - 최고 CSI: 0.4868 - - 최저 CSI: 0.0000 - - 평균 CSI: 0.3110 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/ft_transformer_pure_gwangju_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 26, Best CSI: 0.3933 - Fold 1 학습 완료 (검증 CSI: 0.3933) -Fold 2 학습 중... - Early stopping at epoch 32, Best CSI: 0.4537 - Fold 2 학습 완료 (검증 CSI: 0.4537) -Fold 3 학습 중... - Early stopping at epoch 44, Best CSI: 0.4828 - Fold 3 학습 완료 (검증 CSI: 0.4828) - -모든 모델 저장 완료: ../save_model/ft_transformer_optima/ft_transformer_pure_gwangju.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/ft_transformer_optima/scaler/ft_transformer_pure_gwangju_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: - - . - - . - - / - - s - - a - - v - - e - - _ - - m - - o - - d - - e - - l - - / - - f - - t - - _ - - t - - r - - a - - n - - s - - f - - o - - r - - m - - e - - r - - _ - - o - - p - - t - - i - - m - - a - - / - - f - - t - - _ - - t - - r - - a - - n - - s - - f - - o - - r - - m - - e - - r - - _ - - p - - u - - r - - e - - _ - - g - - w - - a - - n - - g - - j - - u - - . - - p - - k - - l - -✓ 완료: ft_transformer_pure/ft_transforemer_pure_gwangju.py (소요 시간: 3999초) - ----------------------------------------- -실행 중: ft_transformer_pure/ft_transforemer_pure_incheon.py -시작 시간: 2025-12-25 06:08:42 ----------------------------------------- -[I 2025-12-25 06:08:43,887] A new study created in memory with name: no-name-5c3a1402-974f-4d2c-8636-2a105f12884d - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 06:09:52,419] Trial 0 finished with value: 0.5023864961275578 and parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.15168417589020827, 'ffn_dropout': 0.19782411771466096, 'lr': 5.1831628390418495e-05, 'weight_decay': 0.02318754716845433, 'batch_size': 256}. Best is trial 0 with value: 0.5023864961275578. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.502386 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.15168417589020827, 'ffn_dropout': 0.19782411771466096, 'lr': 5.1831628390418495e-05, 'weight_decay': 0.02318754716845433, 'batch_size': 256} - Best Value (CSI): 0.502386 - Best Trial: 0 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.15168417589020827, 'ffn_dropout': 0.19782411771466096, 'lr': 5.1831628390418495e-05, 'weight_decay': 0.02318754716845433, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 06:11:46,004] Trial 1 finished with value: 0.5331123520411832 and parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.18795117608123107, 'ffn_dropout': 0.10789686828674755, 'lr': 1.9249578885169958e-05, 'weight_decay': 0.00045278114856496656, 'batch_size': 128}. Best is trial 1 with value: 0.5331123520411832. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.533112 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.18795117608123107, 'ffn_dropout': 0.10789686828674755, 'lr': 1.9249578885169958e-05, 'weight_decay': 0.00045278114856496656, 'batch_size': 128} - Best Value (CSI): 0.533112 - Best Trial: 1 - Best Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.18795117608123107, 'ffn_dropout': 0.10789686828674755, 'lr': 1.9249578885169958e-05, 'weight_decay': 0.00045278114856496656, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 06:14:59,906] Trial 2 finished with value: 0.5465607835164977 and parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.20328684851147377, 'ffn_dropout': 0.15608370575338412, 'lr': 0.00015823652235619827, 'weight_decay': 0.028387618010176596, 'batch_size': 64}. Best is trial 2 with value: 0.5465607835164977. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.546561 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.20328684851147377, 'ffn_dropout': 0.15608370575338412, 'lr': 0.00015823652235619827, 'weight_decay': 0.028387618010176596, 'batch_size': 64} - Best Value (CSI): 0.546561 - Best Trial: 2 - Best Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.20328684851147377, 'ffn_dropout': 0.15608370575338412, 'lr': 0.00015823652235619827, 'weight_decay': 0.028387618010176596, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 06:17:52,197] Trial 3 finished with value: 0.46506627509085546 and parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3166023286367327, 'ffn_dropout': 0.2821666562759018, 'lr': 0.0006790552467163069, 'weight_decay': 0.00039395884026432917, 'batch_size': 64}. Best is trial 2 with value: 0.5465607835164977. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.465066 - Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3166023286367327, 'ffn_dropout': 0.2821666562759018, 'lr': 0.0006790552467163069, 'weight_decay': 0.00039395884026432917, 'batch_size': 64} - Best Value (CSI): 0.546561 - Best Trial: 2 - Best Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.20328684851147377, 'ffn_dropout': 0.15608370575338412, 'lr': 0.00015823652235619827, 'weight_decay': 0.028387618010176596, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 06:18:50,744] Trial 4 finished with value: 0.5263598242156682 and parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.21818989575866482, 'ffn_dropout': 0.3413019597759419, 'lr': 8.761146719969165e-05, 'weight_decay': 0.0007511820225075656, 'batch_size': 256}. Best is trial 2 with value: 0.5465607835164977. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.526360 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.21818989575866482, 'ffn_dropout': 0.3413019597759419, 'lr': 8.761146719969165e-05, 'weight_decay': 0.0007511820225075656, 'batch_size': 256} - Best Value (CSI): 0.546561 - Best Trial: 2 - Best Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.20328684851147377, 'ffn_dropout': 0.15608370575338412, 'lr': 0.00015823652235619827, 'weight_decay': 0.028387618010176596, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 06:18:59,299] Trial 5 pruned. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.18035432353009323, 'ffn_dropout': 0.1167007812043586, 'lr': 0.00781554388062254, 'weight_decay': 0.000541609681031691, 'batch_size': 256} - Best Value (CSI): 0.546561 - Best Trial: 2 - Best Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.20328684851147377, 'ffn_dropout': 0.15608370575338412, 'lr': 0.00015823652235619827, 'weight_decay': 0.028387618010176596, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 06:20:51,699] Trial 6 finished with value: 0.5499631272762147 and parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2980506223370139, 'ffn_dropout': 0.13679651535428397, 'lr': 0.00012603488529067887, 'weight_decay': 0.0010789166100312734, 'batch_size': 64}. Best is trial 6 with value: 0.5499631272762147. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.549963 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2980506223370139, 'ffn_dropout': 0.13679651535428397, 'lr': 0.00012603488529067887, 'weight_decay': 0.0010789166100312734, 'batch_size': 64} - Best Value (CSI): 0.549963 - Best Trial: 6 - Best Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2980506223370139, 'ffn_dropout': 0.13679651535428397, 'lr': 0.00012603488529067887, 'weight_decay': 0.0010789166100312734, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 06:21:27,530] Trial 7 pruned. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.489564 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.3826591479524817, 'ffn_dropout': 0.18408141908894138, 'lr': 0.00037132725027798976, 'weight_decay': 0.004432265784488715, 'batch_size': 32} - Best Value (CSI): 0.549963 - Best Trial: 6 - Best Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2980506223370139, 'ffn_dropout': 0.13679651535428397, 'lr': 0.00012603488529067887, 'weight_decay': 0.0010789166100312734, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 06:24:20,732] Trial 8 pruned. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.558231 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2742361626951546, 'ffn_dropout': 0.14848958904783932, 'lr': 2.107202629790357e-05, 'weight_decay': 0.05858071842703583, 'batch_size': 32} - Best Value (CSI): 0.549963 - Best Trial: 6 - Best Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2980506223370139, 'ffn_dropout': 0.13679651535428397, 'lr': 0.00012603488529067887, 'weight_decay': 0.0010789166100312734, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 06:26:27,376] Trial 9 finished with value: 0.5609756000325428 and parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2583449749801112, 'ffn_dropout': 0.24285621080643433, 'lr': 0.0005397035080582344, 'weight_decay': 0.012404006621240261, 'batch_size': 128}. Best is trial 9 with value: 0.5609756000325428. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.560976 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2583449749801112, 'ffn_dropout': 0.24285621080643433, 'lr': 0.0005397035080582344, 'weight_decay': 0.012404006621240261, 'batch_size': 128} - Best Value (CSI): 0.560976 - Best Trial: 9 - Best Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2583449749801112, 'ffn_dropout': 0.24285621080643433, 'lr': 0.0005397035080582344, 'weight_decay': 0.012404006621240261, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 06:27:56,254] Trial 10 finished with value: 0.5605887261807504 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12038133063917736, 'ffn_dropout': 0.24464773024938075, 'lr': 0.0012288262804192869, 'weight_decay': 0.00012680456195291018, 'batch_size': 128}. Best is trial 9 with value: 0.5609756000325428. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.560589 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12038133063917736, 'ffn_dropout': 0.24464773024938075, 'lr': 0.0012288262804192869, 'weight_decay': 0.00012680456195291018, 'batch_size': 128} - Best Value (CSI): 0.560976 - Best Trial: 9 - Best Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2583449749801112, 'ffn_dropout': 0.24285621080643433, 'lr': 0.0005397035080582344, 'weight_decay': 0.012404006621240261, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 06:29:26,206] Trial 11 finished with value: 0.5607844794099125 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10288412634034222, 'ffn_dropout': 0.2457432622836574, 'lr': 0.001108065412885759, 'weight_decay': 0.00019368388896397114, 'batch_size': 128}. Best is trial 9 with value: 0.5609756000325428. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.560784 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10288412634034222, 'ffn_dropout': 0.2457432622836574, 'lr': 0.001108065412885759, 'weight_decay': 0.00019368388896397114, 'batch_size': 128} - Best Value (CSI): 0.560976 - Best Trial: 9 - Best Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2583449749801112, 'ffn_dropout': 0.24285621080643433, 'lr': 0.0005397035080582344, 'weight_decay': 0.012404006621240261, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 06:30:31,255] Trial 12 finished with value: 0.5592901333677839 and parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.10865819152706158, 'ffn_dropout': 0.25847979244877933, 'lr': 0.0013252962886862575, 'weight_decay': 0.004164171163917052, 'batch_size': 128}. Best is trial 9 with value: 0.5609756000325428. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.559290 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.10865819152706158, 'ffn_dropout': 0.25847979244877933, 'lr': 0.0013252962886862575, 'weight_decay': 0.004164171163917052, 'batch_size': 128} - Best Value (CSI): 0.560976 - Best Trial: 9 - Best Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2583449749801112, 'ffn_dropout': 0.24285621080643433, 'lr': 0.0005397035080582344, 'weight_decay': 0.012404006621240261, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 06:30:39,317] Trial 13 pruned. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.028408 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.23950900286649165, 'ffn_dropout': 0.30902884823952853, 'lr': 0.0028492059596172802, 'weight_decay': 0.00010032739743204352, 'batch_size': 128} - Best Value (CSI): 0.560976 - Best Trial: 9 - Best Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2583449749801112, 'ffn_dropout': 0.24285621080643433, 'lr': 0.0005397035080582344, 'weight_decay': 0.012404006621240261, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 06:31:32,760] Trial 14 finished with value: 0.5557059161524593 and parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.25893449513552985, 'ffn_dropout': 0.21840088109891515, 'lr': 0.0003813496214789295, 'weight_decay': 0.010077836206100022, 'batch_size': 128}. Best is trial 9 with value: 0.5609756000325428. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.555706 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.25893449513552985, 'ffn_dropout': 0.21840088109891515, 'lr': 0.0003813496214789295, 'weight_decay': 0.010077836206100022, 'batch_size': 128} - Best Value (CSI): 0.560976 - Best Trial: 9 - Best Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2583449749801112, 'ffn_dropout': 0.24285621080643433, 'lr': 0.0005397035080582344, 'weight_decay': 0.012404006621240261, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 06:31:44,328] Trial 15 pruned. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.525875 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.10294109028202032, 'ffn_dropout': 0.3997769660202033, 'lr': 0.002494996899206077, 'weight_decay': 0.001876698041116484, 'batch_size': 128} - Best Value (CSI): 0.560976 - Best Trial: 9 - Best Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2583449749801112, 'ffn_dropout': 0.24285621080643433, 'lr': 0.0005397035080582344, 'weight_decay': 0.012404006621240261, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 06:32:10,367] Trial 16 pruned. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.531359 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.15774092016431762, 'ffn_dropout': 0.2347317623501348, 'lr': 0.00032968399290091854, 'weight_decay': 0.0077175615895213375, 'batch_size': 128} - Best Value (CSI): 0.560976 - Best Trial: 9 - Best Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2583449749801112, 'ffn_dropout': 0.24285621080643433, 'lr': 0.0005397035080582344, 'weight_decay': 0.012404006621240261, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 06:33:31,247] Trial 17 finished with value: 0.5495731525410316 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.23828650212506322, 'ffn_dropout': 0.20771405799084558, 'lr': 0.0007441831496401034, 'weight_decay': 0.0019797132755250703, 'batch_size': 128}. Best is trial 9 with value: 0.5609756000325428. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.549573 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.23828650212506322, 'ffn_dropout': 0.20771405799084558, 'lr': 0.0007441831496401034, 'weight_decay': 0.0019797132755250703, 'batch_size': 128} - Best Value (CSI): 0.560976 - Best Trial: 9 - Best Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2583449749801112, 'ffn_dropout': 0.24285621080643433, 'lr': 0.0005397035080582344, 'weight_decay': 0.012404006621240261, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 06:39:53,746] Trial 18 finished with value: 0.5600849945244285 and parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.15561174422120433, 'ffn_dropout': 0.275260950668861, 'lr': 0.000222912922404823, 'weight_decay': 0.09632694451434938, 'batch_size': 32}. Best is trial 9 with value: 0.5609756000325428. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.560085 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.15561174422120433, 'ffn_dropout': 0.275260950668861, 'lr': 0.000222912922404823, 'weight_decay': 0.09632694451434938, 'batch_size': 32} - Best Value (CSI): 0.560976 - Best Trial: 9 - Best Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2583449749801112, 'ffn_dropout': 0.24285621080643433, 'lr': 0.0005397035080582344, 'weight_decay': 0.012404006621240261, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 06:40:09,624] Trial 19 pruned. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.21661613222031778, 'ffn_dropout': 0.17153020016207565, 'lr': 0.007529231120839772, 'weight_decay': 0.00025884894456957794, 'batch_size': 128} - Best Value (CSI): 0.560976 - Best Trial: 9 - Best Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2583449749801112, 'ffn_dropout': 0.24285621080643433, 'lr': 0.0005397035080582344, 'weight_decay': 0.012404006621240261, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 06:40:24,290] Trial 20 pruned. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.019516 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.27922152874033723, 'ffn_dropout': 0.21779728298016282, 'lr': 0.0026634242947173063, 'weight_decay': 0.00020887447140232113, 'batch_size': 128} - Best Value (CSI): 0.560976 - Best Trial: 9 - Best Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2583449749801112, 'ffn_dropout': 0.24285621080643433, 'lr': 0.0005397035080582344, 'weight_decay': 0.012404006621240261, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 06:42:03,293] Trial 21 finished with value: 0.5668806602309416 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12823504101007213, 'ffn_dropout': 0.24204039169440933, 'lr': 0.0008968581420613831, 'weight_decay': 0.00013612999017543234, 'batch_size': 128}. Best is trial 21 with value: 0.5668806602309416. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.566881 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12823504101007213, 'ffn_dropout': 0.24204039169440933, 'lr': 0.0008968581420613831, 'weight_decay': 0.00013612999017543234, 'batch_size': 128} - Best Value (CSI): 0.566881 - Best Trial: 21 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12823504101007213, 'ffn_dropout': 0.24204039169440933, 'lr': 0.0008968581420613831, 'weight_decay': 0.00013612999017543234, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 06:42:23,673] Trial 22 pruned. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.536194 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.13129422928279824, 'ffn_dropout': 0.24688408243347557, 'lr': 0.0005902142846066769, 'weight_decay': 0.00024872009990851296, 'batch_size': 128} - Best Value (CSI): 0.566881 - Best Trial: 21 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12823504101007213, 'ffn_dropout': 0.24204039169440933, 'lr': 0.0008968581420613831, 'weight_decay': 0.00013612999017543234, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 06:44:09,244] Trial 23 finished with value: 0.5673234518633549 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128}. Best is trial 23 with value: 0.5673234518633549. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.567323 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 06:44:21,934] Trial 24 pruned. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.506753 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12930931342803847, 'ffn_dropout': 0.20009448267052468, 'lr': 0.00046698198320616063, 'weight_decay': 0.00011393573097561589, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 06:44:29,104] Trial 25 pruned. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.503553 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.1778503166472795, 'ffn_dropout': 0.18199211511259697, 'lr': 0.0002406153197737413, 'weight_decay': 0.0010509368096982261, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 06:45:03,385] Trial 26 pruned. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.13327555309804112, 'ffn_dropout': 0.22886930522275112, 'lr': 0.0007932486436691002, 'weight_decay': 0.00016317047800793708, 'batch_size': 32} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 06:45:10,672] Trial 27 pruned. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.515767 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.14895722211917198, 'ffn_dropout': 0.17325703416848567, 'lr': 0.00177056092563618, 'weight_decay': 0.0002995911478233817, 'batch_size': 256} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 06:45:28,581] Trial 28 pruned. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.17593097163961852, 'ffn_dropout': 0.21693017875622592, 'lr': 0.004250221522374358, 'weight_decay': 0.0001015648020457322, 'batch_size': 64} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 06:45:36,256] Trial 29 pruned. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.480359 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.14786245806659531, 'ffn_dropout': 0.19455262441856833, 'lr': 0.0009446705727542001, 'weight_decay': 0.0003966658643232621, 'batch_size': 256} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 06:45:49,012] Trial 30 pruned. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.544792 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.20032038839491104, 'ffn_dropout': 0.20202422613339893, 'lr': 0.0004928983963896523, 'weight_decay': 0.00019321988967685937, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 06:47:40,045] Trial 31 finished with value: 0.563607369549601 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10260325160493375, 'ffn_dropout': 0.2597310816023563, 'lr': 0.0011424207608275207, 'weight_decay': 0.00016595787716341918, 'batch_size': 128}. Best is trial 23 with value: 0.5673234518633549. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.563607 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10260325160493375, 'ffn_dropout': 0.2597310816023563, 'lr': 0.0011424207608275207, 'weight_decay': 0.00016595787716341918, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 06:47:48,390] Trial 32 pruned. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.492586 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10066782348816578, 'ffn_dropout': 0.2620446181886807, 'lr': 0.0010060616036423158, 'weight_decay': 0.00016235962991251033, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 06:47:57,417] Trial 33 pruned. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.504974 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.11802013391437569, 'ffn_dropout': 0.22938034439063423, 'lr': 0.0014823079555297896, 'weight_decay': 0.0003394316719042018, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 06:48:06,983] Trial 34 pruned. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.492255 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.13535603010069813, 'ffn_dropout': 0.2792611411302509, 'lr': 0.000604505329307539, 'weight_decay': 0.00014685920098230396, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 06:48:22,784] Trial 35 pruned. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.020683 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.11988769842324046, 'ffn_dropout': 0.30026225551815056, 'lr': 0.0016030332212753817, 'weight_decay': 0.0005647924324208686, 'batch_size': 64} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 06:48:31,260] Trial 36 pruned. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.481211 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.16540779870685812, 'ffn_dropout': 0.2670630761056743, 'lr': 0.0008299796869834042, 'weight_decay': 0.0003018483422456579, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 06:48:38,402] Trial 37 pruned. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.523694 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.1951546289703142, 'ffn_dropout': 0.25350360895886237, 'lr': 0.00026953199068110214, 'weight_decay': 0.00047955483375928344, 'batch_size': 256} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 06:49:03,650] Trial 38 pruned. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.532919 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.14483071853779714, 'ffn_dropout': 0.23345477464320977, 'lr': 0.0005107207953273052, 'weight_decay': 0.00014582168064134125, 'batch_size': 64} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 06:49:15,274] Trial 39 pruned. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.523688 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.16661161613366407, 'ffn_dropout': 0.2868370859192786, 'lr': 0.00016217083519655796, 'weight_decay': 0.0006260405898636037, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 06:50:09,171] Trial 40 pruned. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.18378921102510293, 'ffn_dropout': 0.15892158426162734, 'lr': 0.0007259280627875253, 'weight_decay': 0.01960659897740812, 'batch_size': 32} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 06:51:30,288] Trial 41 finished with value: 0.5619844745831449 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10294198601110448, 'ffn_dropout': 0.2458924807981811, 'lr': 0.001109737756472616, 'weight_decay': 0.00020239751843869719, 'batch_size': 128}. Best is trial 23 with value: 0.5673234518633549. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.561984 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10294198601110448, 'ffn_dropout': 0.2458924807981811, 'lr': 0.001109737756472616, 'weight_decay': 0.00020239751843869719, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 06:51:38,572] Trial 42 pruned. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.513583 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.11501509157355441, 'ffn_dropout': 0.2504593212337229, 'lr': 0.001813503963596022, 'weight_decay': 0.00022864187333567125, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 06:53:11,818] Trial 43 pruned. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.527875 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.1002316940932777, 'ffn_dropout': 0.26888678752254985, 'lr': 0.0009423185812287568, 'weight_decay': 0.00013362019746969138, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 06:53:30,067] Trial 44 pruned. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12424423164453778, 'ffn_dropout': 0.24081777935534168, 'lr': 0.0011909318296277926, 'weight_decay': 0.00036957735464548204, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 06:55:44,698] Trial 45 finished with value: 0.5613916785166351 and parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.11778256138489303, 'ffn_dropout': 0.21929231439566954, 'lr': 0.0004046090471254043, 'weight_decay': 0.0001045893534529528, 'batch_size': 128}. Best is trial 23 with value: 0.5673234518633549. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.561392 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.11778256138489303, 'ffn_dropout': 0.21929231439566954, 'lr': 0.0004046090471254043, 'weight_decay': 0.0001045893534529528, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 06:56:50,501] Trial 46 finished with value: 0.5570930924541627 and parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1126643681921102, 'ffn_dropout': 0.19236077231692622, 'lr': 0.000333665436367717, 'weight_decay': 0.00010369802758258233, 'batch_size': 128}. Best is trial 23 with value: 0.5673234518633549. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.557093 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1126643681921102, 'ffn_dropout': 0.19236077231692622, 'lr': 0.000333665436367717, 'weight_decay': 0.00010369802758258233, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 06:56:58,380] Trial 47 pruned. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.519749 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.14035167262715945, 'ffn_dropout': 0.21498112030197747, 'lr': 0.0004090238326969228, 'weight_decay': 0.00018354642275337444, 'batch_size': 256} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 06:57:09,511] Trial 48 pruned. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.532614 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.12391607429425383, 'ffn_dropout': 0.22450926692685833, 'lr': 0.0006455838651087578, 'weight_decay': 0.00013571893237180336, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 06:57:40,646] Trial 49 pruned. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.442817 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.11290011137875997, 'ffn_dropout': 0.2097453842744962, 'lr': 0.0011233968244386344, 'weight_decay': 0.0002544969262327021, 'batch_size': 64} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 06:57:55,423] Trial 50 pruned. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.520477 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.142906500679646, 'ffn_dropout': 0.25962043143167723, 'lr': 0.002183547662375953, 'weight_decay': 0.0004369344408503457, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 06:58:05,128] Trial 51 pruned. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.468116 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10941723089816566, 'ffn_dropout': 0.24517957080429398, 'lr': 0.0013777718725485999, 'weight_decay': 0.00010061611254539375, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 06:59:40,653] Trial 52 finished with value: 0.5585078073512814 and parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.13045934347609722, 'ffn_dropout': 0.2315861707316811, 'lr': 0.0004690003389278206, 'weight_decay': 0.00019041178321122618, 'batch_size': 128}. Best is trial 23 with value: 0.5673234518633549. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.558508 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.13045934347609722, 'ffn_dropout': 0.2315861707316811, 'lr': 0.0004690003389278206, 'weight_decay': 0.00019041178321122618, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 06:59:56,052] Trial 53 pruned. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.528841 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.10151940972000272, 'ffn_dropout': 0.2093731690104555, 'lr': 0.0007482267767925803, 'weight_decay': 0.00014282175256641536, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 07:00:05,442] Trial 54 pruned. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.490291 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.15920175376645507, 'ffn_dropout': 0.23970302614788955, 'lr': 0.0005965359702291647, 'weight_decay': 0.00022319891258199475, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 07:00:42,487] Trial 55 pruned. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.12342946785675463, 'ffn_dropout': 0.2223798276194096, 'lr': 0.0011547914666763786, 'weight_decay': 0.00030095731984255145, 'batch_size': 32} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 07:01:01,784] Trial 56 pruned. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.531111 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.1380425448327971, 'ffn_dropout': 0.24721408407777326, 'lr': 0.0003887558998240844, 'weight_decay': 0.00012737418257108757, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 07:01:15,598] Trial 57 pruned. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.129326 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.1124055161669908, 'ffn_dropout': 0.2626201951575484, 'lr': 0.0021039911887976498, 'weight_decay': 0.0001778007443822745, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 07:01:26,935] Trial 58 pruned. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.510558 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.14896949629794498, 'ffn_dropout': 0.19907115067168207, 'lr': 0.0009390725760416146, 'weight_decay': 0.0006775809251056785, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 07:01:40,363] Trial 59 pruned. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.499544 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.21106746040791097, 'ffn_dropout': 0.25537877962857963, 'lr': 0.0002968361599703228, 'weight_decay': 0.0001191149461477361, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 07:01:52,142] Trial 60 pruned. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.444165 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22947695568272905, 'ffn_dropout': 0.18596861561182923, 'lr': 0.0015021769597192136, 'weight_decay': 0.00020551666524536174, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 07:02:03,994] Trial 61 pruned. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.503686 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10581112020050276, 'ffn_dropout': 0.23544967980553988, 'lr': 0.0011822546682288425, 'weight_decay': 0.0002701763285693385, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 07:02:20,258] Trial 62 pruned. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.528102 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10003678990488277, 'ffn_dropout': 0.22168615525681906, 'lr': 0.0008199880254154385, 'weight_decay': 0.0001736291340956286, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 07:02:37,551] Trial 63 pruned. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.539276 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12714415472900936, 'ffn_dropout': 0.2734734822203269, 'lr': 0.0005592318159644944, 'weight_decay': 0.00012224158543320225, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 07:02:50,783] Trial 64 pruned. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.021465 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.11771186933477777, 'ffn_dropout': 0.24358235066778725, 'lr': 0.002837980857792554, 'weight_decay': 0.0008603752320224208, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 07:07:39,122] Trial 65 finished with value: 0.5589917958792664 and parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.13245987614386515, 'ffn_dropout': 0.2541668796146638, 'lr': 0.0009530955649906689, 'weight_decay': 0.00035386203058233574, 'batch_size': 32}. Best is trial 23 with value: 0.5673234518633549. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.558992 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.13245987614386515, 'ffn_dropout': 0.2541668796146638, 'lr': 0.0009530955649906689, 'weight_decay': 0.00035386203058233574, 'batch_size': 32} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 07:07:51,284] Trial 66 pruned. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.426819 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.10893112993751106, 'ffn_dropout': 0.20928653988071094, 'lr': 0.001726600418875313, 'weight_decay': 0.0002386527753523931, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 07:07:58,402] Trial 67 pruned. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.501848 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.13689322039567017, 'ffn_dropout': 0.22623479425468065, 'lr': 0.0006649976311164956, 'weight_decay': 0.00014824757684682056, 'batch_size': 256} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 07:09:18,200] Trial 68 finished with value: 0.5630920965979487 and parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.15272816134906017, 'ffn_dropout': 0.2370638563231482, 'lr': 0.0013238396248552967, 'weight_decay': 0.00010137364531438386, 'batch_size': 128}. Best is trial 23 with value: 0.5673234518633549. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.563092 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.15272816134906017, 'ffn_dropout': 0.2370638563231482, 'lr': 0.0013238396248552967, 'weight_decay': 0.00010137364531438386, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 07:09:29,227] Trial 69 pruned. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.522354 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.1559264821506815, 'ffn_dropout': 0.28261431223984257, 'lr': 0.0013659953512738827, 'weight_decay': 0.00010781552968504348, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 07:11:40,839] Trial 70 finished with value: 0.5546036714652783 and parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.25848758596151444, 'ffn_dropout': 0.23826408852600423, 'lr': 0.0004965327260409777, 'weight_decay': 0.0001651211795438362, 'batch_size': 64}. Best is trial 23 with value: 0.5673234518633549. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.554604 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.25848758596151444, 'ffn_dropout': 0.23826408852600423, 'lr': 0.0004965327260409777, 'weight_decay': 0.0001651211795438362, 'batch_size': 64} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 07:11:51,344] Trial 71 pruned. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.527411 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.11828007405586916, 'ffn_dropout': 0.2623476950165934, 'lr': 0.0010505687073851795, 'weight_decay': 0.00010128511141521309, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 07:12:17,564] Trial 72 pruned. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.544813 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12541009733103747, 'ffn_dropout': 0.25049082803338685, 'lr': 0.000870242479759837, 'weight_decay': 0.00019319977641739255, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 07:12:26,333] Trial 73 pruned. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.506779 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10953656224799999, 'ffn_dropout': 0.233354403161391, 'lr': 0.0013592407478757967, 'weight_decay': 0.00012561228668832278, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 07:12:41,916] Trial 74 pruned. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.547903 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.14178137858571038, 'ffn_dropout': 0.21999116487829629, 'lr': 0.0006437128648160788, 'weight_decay': 0.0002213536640900457, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 07:12:52,410] Trial 75 pruned. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.498590 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.12218601701293104, 'ffn_dropout': 0.26989958842536865, 'lr': 0.0019840013376080773, 'weight_decay': 0.00016595213528509972, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 07:13:05,362] Trial 76 pruned. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.536199 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10669035086761205, 'ffn_dropout': 0.24558832502567074, 'lr': 0.0007931159492287499, 'weight_decay': 0.0004807442069029227, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 07:14:23,672] Trial 77 finished with value: 0.5602677172261242 and parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.1345979958777974, 'ffn_dropout': 0.225552601916621, 'lr': 0.0004318955742744389, 'weight_decay': 0.0003035565288221005, 'batch_size': 128}. Best is trial 23 with value: 0.5673234518633549. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.560268 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.1345979958777974, 'ffn_dropout': 0.225552601916621, 'lr': 0.0004318955742744389, 'weight_decay': 0.0003035565288221005, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 07:14:30,703] Trial 78 pruned. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.489829 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.14812033586276363, 'ffn_dropout': 0.20478778727992406, 'lr': 0.0011635303663200484, 'weight_decay': 0.0001430355467026487, 'batch_size': 256} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 07:14:39,991] Trial 79 pruned. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.450980 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.11720846951128194, 'ffn_dropout': 0.213793301026177, 'lr': 0.002388519605266936, 'weight_decay': 0.00011842927282511962, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 07:15:19,071] Trial 80 pruned. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1300993408742097, 'ffn_dropout': 0.23703139794448186, 'lr': 0.003395741664525577, 'weight_decay': 0.0028281194106626983, 'batch_size': 32} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 07:15:33,989] Trial 81 pruned. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.534298 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10015065093858434, 'ffn_dropout': 0.25401460847135365, 'lr': 0.0016817060019209064, 'weight_decay': 0.0001512737795756964, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 07:17:01,635] Trial 82 finished with value: 0.557451049057104 and parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.11558986547088425, 'ffn_dropout': 0.2295377483714132, 'lr': 0.0015084798019324957, 'weight_decay': 0.00010122423589856241, 'batch_size': 128}. Best is trial 23 with value: 0.5673234518633549. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.557451 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.11558986547088425, 'ffn_dropout': 0.2295377483714132, 'lr': 0.0015084798019324957, 'weight_decay': 0.00010122423589856241, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 07:17:13,234] Trial 83 pruned. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.475339 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.1077347541902555, 'ffn_dropout': 0.24346040000355837, 'lr': 0.0010120425446530868, 'weight_decay': 0.00020533229648775765, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 07:17:24,690] Trial 84 pruned. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.483297 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12321121442849256, 'ffn_dropout': 0.26570602378341474, 'lr': 0.000691813142629914, 'weight_decay': 0.00012739060865399188, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 07:17:46,292] Trial 85 pruned. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.478136 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.14034600638018035, 'ffn_dropout': 0.25611570245356735, 'lr': 0.0013040107601561303, 'weight_decay': 0.000164234255806877, 'batch_size': 64} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 07:17:59,295] Trial 86 pruned. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12776636724510745, 'ffn_dropout': 0.21460684921266734, 'lr': 0.0019157195953662526, 'weight_decay': 0.00023208818121793167, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 07:18:14,278] Trial 87 pruned. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.547682 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.11335811829188672, 'ffn_dropout': 0.27635358714632513, 'lr': 0.0008677533148935669, 'weight_decay': 0.00012350092021729412, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 07:18:26,203] Trial 88 pruned. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.518460 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.16871047544982468, 'ffn_dropout': 0.2388100971514077, 'lr': 0.0005242274420110453, 'weight_decay': 0.00018809619941529134, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 07:20:18,602] Trial 89 finished with value: 0.5609178763332597 and parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.15095024657967324, 'ffn_dropout': 0.25183108574848023, 'lr': 0.0010812305522258832, 'weight_decay': 0.0002673523262933242, 'batch_size': 128}. Best is trial 23 with value: 0.5673234518633549. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.560918 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.15095024657967324, 'ffn_dropout': 0.25183108574848023, 'lr': 0.0010812305522258832, 'weight_decay': 0.0002673523262933242, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 16.154696132596683, 1: 2.297838899803536, 2: 0.3995354239256678} (클래스별 샘플 수: {0: 362, 1: 2545, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 19.04885993485342, 1: 2.213474640423921, 2: 0.40068516615279204} (클래스별 샘플 수: {0: 307, 1: 2642, 2: 14595}) -[I 2025-12-25 07:22:10,601] Trial 90 finished with value: 0.558089095584786 and parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.15499310208384037, 'ffn_dropout': 0.25906732619028044, 'lr': 0.0007499848196698733, 'weight_decay': 0.00026029226063242414, 'batch_size': 128}. Best is trial 23 with value: 0.5673234518633549. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.558089 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.15499310208384037, 'ffn_dropout': 0.25906732619028044, 'lr': 0.0007499848196698733, 'weight_decay': 0.00026029226063242414, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 07:22:26,538] Trial 91 pruned. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.502479 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.1465665384952893, 'ffn_dropout': 0.24988385009388395, 'lr': 0.0010784811432363486, 'weight_decay': 0.0001414319092803071, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 07:22:46,611] Trial 92 pruned. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.550133 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13322203554273399, 'ffn_dropout': 0.2312655914423539, 'lr': 0.0012537833023604336, 'weight_decay': 0.00011585187515792863, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 07:22:58,413] Trial 93 pruned. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.512834 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10579157944200678, 'ffn_dropout': 0.24474105302260635, 'lr': 0.0015146555160636527, 'weight_decay': 0.00015482765291912118, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 07:23:12,807] Trial 94 pruned. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.519523 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.11879484759434887, 'ffn_dropout': 0.2707928587500692, 'lr': 0.0005822613158079102, 'weight_decay': 0.0001993489636222018, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 07:23:23,308] Trial 95 pruned. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.545793 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.16143115699626526, 'ffn_dropout': 0.2256022089771042, 'lr': 0.0009662977616486305, 'weight_decay': 0.00028171907157805386, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 07:23:31,858] Trial 96 pruned. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.487982 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.15188729798183037, 'ffn_dropout': 0.26264454521101416, 'lr': 0.0017707658850600145, 'weight_decay': 0.0001737744083580078, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 07:23:39,198] Trial 97 pruned. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.522466 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1274005919243627, 'ffn_dropout': 0.25062578638302235, 'lr': 0.00036716551853883825, 'weight_decay': 0.0003358189414410445, 'batch_size': 128} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 07:23:46,036] Trial 98 pruned. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.509833 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.11152821978881004, 'ffn_dropout': 0.23909790437136705, 'lr': 0.0007962193809000453, 'weight_decay': 0.00010061915238722948, 'batch_size': 256} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 15.826558265582657, 1: 2.248748556026184, 2: 0.4012642572488663} (클래스별 샘플 수: {0: 369, 1: 2597, 2: 14554}) -[I 2025-12-25 07:24:16,168] Trial 99 pruned. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.451117 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.13893357896656316, 'ffn_dropout': 0.21967225610942365, 'lr': 0.0010979331658424985, 'weight_decay': 0.0001397695837883291, 'batch_size': 32} - Best Value (CSI): 0.567323 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.5673 -Best Hyperparameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12006219567079585, 'ffn_dropout': 0.19152888035195653, 'lr': 0.0011919865831209798, 'weight_decay': 0.00010616617862067153, 'batch_size': 128} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.5024 - - 최종 CSI: 0.4511 - - 최고 CSI: 0.5673 - - 최저 CSI: 0.0000 - - 평균 CSI: 0.4514 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/ft_transformer_pure_incheon_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 31, Best CSI: 0.5529 - Fold 1 학습 완료 (검증 CSI: 0.5529) -Fold 2 학습 중... - Early stopping at epoch 39, Best CSI: 0.5763 - Fold 2 학습 완료 (검증 CSI: 0.5763) -Fold 3 학습 중... - Early stopping at epoch 57, Best CSI: 0.5337 - Fold 3 학습 완료 (검증 CSI: 0.5337) - -모든 모델 저장 완료: ../save_model/ft_transformer_optima/ft_transformer_pure_incheon.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/ft_transformer_optima/scaler/ft_transformer_pure_incheon_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: - - . - - . - - / - - s - - a - - v - - e - - _ - - m - - o - - d - - e - - l - - / - - f - - t - - _ - - t - - r - - a - - n - - s - - f - - o - - r - - m - - e - - r - - _ - - o - - p - - t - - i - - m - - a - - / - - f - - t - - _ - - t - - r - - a - - n - - s - - f - - o - - r - - m - - e - - r - - _ - - p - - u - - r - - e - - _ - - i - - n - - c - - h - - e - - o - - n - - . - - p - - k - - l - -✓ 완료: ft_transformer_pure/ft_transforemer_pure_incheon.py (소요 시간: 4632초) - ----------------------------------------- -실행 중: ft_transformer_pure/ft_transforemer_pure_seoul.py -시작 시간: 2025-12-25 07:25:54 ----------------------------------------- -[I 2025-12-25 07:25:55,483] A new study created in memory with name: no-name-ae23788f-af81-465a-97aa-bb3287cd4008 - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 07:28:26,019] Trial 0 finished with value: 0.5516272189922957 and parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.24598045981097041, 'ffn_dropout': 0.1492675958727639, 'lr': 6.505783120864953e-05, 'weight_decay': 0.04165805124014258, 'batch_size': 64}. Best is trial 0 with value: 0.5516272189922957. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.551627 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.24598045981097041, 'ffn_dropout': 0.1492675958727639, 'lr': 6.505783120864953e-05, 'weight_decay': 0.04165805124014258, 'batch_size': 64} - Best Value (CSI): 0.551627 - Best Trial: 0 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.24598045981097041, 'ffn_dropout': 0.1492675958727639, 'lr': 6.505783120864953e-05, 'weight_decay': 0.04165805124014258, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 07:33:01,928] Trial 1 finished with value: 0.5381974059111133 and parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3957624914419582, 'ffn_dropout': 0.28221873024846195, 'lr': 5.922024977291002e-05, 'weight_decay': 0.01834449314154107, 'batch_size': 32}. Best is trial 0 with value: 0.5516272189922957. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.538197 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3957624914419582, 'ffn_dropout': 0.28221873024846195, 'lr': 5.922024977291002e-05, 'weight_decay': 0.01834449314154107, 'batch_size': 32} - Best Value (CSI): 0.551627 - Best Trial: 0 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.24598045981097041, 'ffn_dropout': 0.1492675958727639, 'lr': 6.505783120864953e-05, 'weight_decay': 0.04165805124014258, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 07:34:27,239] Trial 2 finished with value: 0.34316179183287976 and parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.1849419874986023, 'ffn_dropout': 0.3194382563399701, 'lr': 1.3215155944918477e-05, 'weight_decay': 0.00010723029366949362, 'batch_size': 256}. Best is trial 0 with value: 0.5516272189922957. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.343162 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.1849419874986023, 'ffn_dropout': 0.3194382563399701, 'lr': 1.3215155944918477e-05, 'weight_decay': 0.00010723029366949362, 'batch_size': 256} - Best Value (CSI): 0.551627 - Best Trial: 0 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.24598045981097041, 'ffn_dropout': 0.1492675958727639, 'lr': 6.505783120864953e-05, 'weight_decay': 0.04165805124014258, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 07:40:26,567] Trial 3 finished with value: 0.502765263560935 and parameters: {'d_token': 224, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.3734167968154649, 'ffn_dropout': 0.2820248473948035, 'lr': 1.117632574228902e-05, 'weight_decay': 0.044130376903043556, 'batch_size': 32}. Best is trial 0 with value: 0.5516272189922957. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.502765 - Parameters: {'d_token': 224, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.3734167968154649, 'ffn_dropout': 0.2820248473948035, 'lr': 1.117632574228902e-05, 'weight_decay': 0.044130376903043556, 'batch_size': 32} - Best Value (CSI): 0.551627 - Best Trial: 0 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.24598045981097041, 'ffn_dropout': 0.1492675958727639, 'lr': 6.505783120864953e-05, 'weight_decay': 0.04165805124014258, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 07:43:17,622] Trial 4 finished with value: 0.5249086792788855 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.122488946224889, 'ffn_dropout': 0.12644996179894155, 'lr': 0.0010718671209128574, 'weight_decay': 0.0014851947005563343, 'batch_size': 64}. Best is trial 0 with value: 0.5516272189922957. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.524909 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.122488946224889, 'ffn_dropout': 0.12644996179894155, 'lr': 0.0010718671209128574, 'weight_decay': 0.0014851947005563343, 'batch_size': 64} - Best Value (CSI): 0.551627 - Best Trial: 0 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.24598045981097041, 'ffn_dropout': 0.1492675958727639, 'lr': 6.505783120864953e-05, 'weight_decay': 0.04165805124014258, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 07:46:35,629] Trial 5 finished with value: 0.5321412931059356 and parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.32084512543935795, 'ffn_dropout': 0.24110226508088783, 'lr': 0.000587923764519226, 'weight_decay': 0.00017014671016480896, 'batch_size': 32}. Best is trial 0 with value: 0.5516272189922957. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.532141 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.32084512543935795, 'ffn_dropout': 0.24110226508088783, 'lr': 0.000587923764519226, 'weight_decay': 0.00017014671016480896, 'batch_size': 32} - Best Value (CSI): 0.551627 - Best Trial: 0 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.24598045981097041, 'ffn_dropout': 0.1492675958727639, 'lr': 6.505783120864953e-05, 'weight_decay': 0.04165805124014258, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 07:46:40,824] Trial 6 pruned. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.298845 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.14386947983650183, 'ffn_dropout': 0.332291102133211, 'lr': 7.671551506136383e-05, 'weight_decay': 0.00031258635385618503, 'batch_size': 256} - Best Value (CSI): 0.551627 - Best Trial: 0 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.24598045981097041, 'ffn_dropout': 0.1492675958727639, 'lr': 6.505783120864953e-05, 'weight_decay': 0.04165805124014258, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 07:47:01,861] Trial 7 pruned. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.420724 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3714757570198084, 'ffn_dropout': 0.3161536172905419, 'lr': 0.00010129660602362034, 'weight_decay': 0.0013472002169098482, 'batch_size': 128} - Best Value (CSI): 0.551627 - Best Trial: 0 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.24598045981097041, 'ffn_dropout': 0.1492675958727639, 'lr': 6.505783120864953e-05, 'weight_decay': 0.04165805124014258, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 07:47:52,778] Trial 8 pruned. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.396172 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.31049221863361653, 'ffn_dropout': 0.30441785533549093, 'lr': 8.210429436419445e-05, 'weight_decay': 0.0018896836870957452, 'batch_size': 32} - Best Value (CSI): 0.551627 - Best Trial: 0 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.24598045981097041, 'ffn_dropout': 0.1492675958727639, 'lr': 6.505783120864953e-05, 'weight_decay': 0.04165805124014258, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) -[I 2025-12-25 07:49:42,183] Trial 9 pruned. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.552115 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.34316616117018295, 'ffn_dropout': 0.23488563022890852, 'lr': 0.00010812279211311514, 'weight_decay': 0.006591201554469069, 'batch_size': 32} - Best Value (CSI): 0.551627 - Best Trial: 0 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.24598045981097041, 'ffn_dropout': 0.1492675958727639, 'lr': 6.505783120864953e-05, 'weight_decay': 0.04165805124014258, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 07:50:07,448] Trial 10 pruned. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 256, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.25313204325871247, 'ffn_dropout': 0.11242173336007309, 'lr': 0.005479340095904968, 'weight_decay': 0.09001629340633736, 'batch_size': 64} - Best Value (CSI): 0.551627 - Best Trial: 0 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.24598045981097041, 'ffn_dropout': 0.1492675958727639, 'lr': 6.505783120864953e-05, 'weight_decay': 0.04165805124014258, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 07:50:46,125] Trial 11 pruned. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.415990 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.39810129115854076, 'ffn_dropout': 0.38167657547950534, 'lr': 3.644060632316875e-05, 'weight_decay': 0.02118723961381504, 'batch_size': 64} - Best Value (CSI): 0.551627 - Best Trial: 0 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.24598045981097041, 'ffn_dropout': 0.1492675958727639, 'lr': 6.505783120864953e-05, 'weight_decay': 0.04165805124014258, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 07:51:04,416] Trial 12 pruned. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.420716 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.26455943682334065, 'ffn_dropout': 0.1813215409629474, 'lr': 0.0002512652761174567, 'weight_decay': 0.01652236140471896, 'batch_size': 128} - Best Value (CSI): 0.551627 - Best Trial: 0 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.24598045981097041, 'ffn_dropout': 0.1492675958727639, 'lr': 6.505783120864953e-05, 'weight_decay': 0.04165805124014258, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) -[I 2025-12-25 07:52:46,106] Trial 13 pruned. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.559690 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.21083940534141485, 'ffn_dropout': 0.17742765350306205, 'lr': 2.7230039730583293e-05, 'weight_decay': 0.08917891408168774, 'batch_size': 64} - Best Value (CSI): 0.551627 - Best Trial: 0 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.24598045981097041, 'ffn_dropout': 0.1492675958727639, 'lr': 6.505783120864953e-05, 'weight_decay': 0.04165805124014258, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 07:58:41,428] Trial 14 finished with value: 0.5315997607666519 and parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2787525644055048, 'ffn_dropout': 0.2030400087597299, 'lr': 0.00023280027847102073, 'weight_decay': 0.014229632703614848, 'batch_size': 32}. Best is trial 0 with value: 0.5516272189922957. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.531600 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2787525644055048, 'ffn_dropout': 0.2030400087597299, 'lr': 0.00023280027847102073, 'weight_decay': 0.014229632703614848, 'batch_size': 32} - Best Value (CSI): 0.551627 - Best Trial: 0 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.24598045981097041, 'ffn_dropout': 0.1492675958727639, 'lr': 6.505783120864953e-05, 'weight_decay': 0.04165805124014258, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 07:59:16,728] Trial 15 pruned. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.390097 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.29703098872550243, 'ffn_dropout': 0.14600639818942096, 'lr': 2.8638212554517335e-05, 'weight_decay': 0.03351305719392332, 'batch_size': 64} - Best Value (CSI): 0.551627 - Best Trial: 0 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.24598045981097041, 'ffn_dropout': 0.1492675958727639, 'lr': 6.505783120864953e-05, 'weight_decay': 0.04165805124014258, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 07:59:23,078] Trial 16 pruned. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.324988 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.23687131287685745, 'ffn_dropout': 0.10280282461178619, 'lr': 4.609241367366993e-05, 'weight_decay': 0.0056972532623146225, 'batch_size': 256} - Best Value (CSI): 0.551627 - Best Trial: 0 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.24598045981097041, 'ffn_dropout': 0.1492675958727639, 'lr': 6.505783120864953e-05, 'weight_decay': 0.04165805124014258, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 07:59:37,361] Trial 17 pruned. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.398175 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.33417592642771893, 'ffn_dropout': 0.2659476425754799, 'lr': 0.00019986222076242768, 'weight_decay': 0.009291689478051977, 'batch_size': 128} - Best Value (CSI): 0.551627 - Best Trial: 0 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.24598045981097041, 'ffn_dropout': 0.1492675958727639, 'lr': 6.505783120864953e-05, 'weight_decay': 0.04165805124014258, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 07:59:55,298] Trial 18 pruned. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.329510 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.21268367465668145, 'ffn_dropout': 0.2255176361708237, 'lr': 2.2193384046683638e-05, 'weight_decay': 0.038034618169927314, 'batch_size': 64} - Best Value (CSI): 0.551627 - Best Trial: 0 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.24598045981097041, 'ffn_dropout': 0.1492675958727639, 'lr': 6.505783120864953e-05, 'weight_decay': 0.04165805124014258, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 08:04:55,355] Trial 19 finished with value: 0.5554215697637764 and parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2868389431100919, 'ffn_dropout': 0.16640752856148106, 'lr': 5.463974806450829e-05, 'weight_decay': 0.004850813772365092, 'batch_size': 32}. Best is trial 19 with value: 0.5554215697637764. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.555422 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2868389431100919, 'ffn_dropout': 0.16640752856148106, 'lr': 5.463974806450829e-05, 'weight_decay': 0.004850813772365092, 'batch_size': 32} - Best Value (CSI): 0.555422 - Best Trial: 19 - Best Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2868389431100919, 'ffn_dropout': 0.16640752856148106, 'lr': 5.463974806450829e-05, 'weight_decay': 0.004850813772365092, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) -[I 2025-12-25 08:07:28,171] Trial 20 pruned. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.493623 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.2810839842475639, 'ffn_dropout': 0.1534448693886259, 'lr': 0.00015780932911467425, 'weight_decay': 0.0032131756015100392, 'batch_size': 32} - Best Value (CSI): 0.555422 - Best Trial: 19 - Best Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2868389431100919, 'ffn_dropout': 0.16640752856148106, 'lr': 5.463974806450829e-05, 'weight_decay': 0.004850813772365092, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) -[I 2025-12-25 08:09:50,910] Trial 21 pruned. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.557430 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.29717698961380573, 'ffn_dropout': 0.20976130652579494, 'lr': 5.343681295037588e-05, 'weight_decay': 0.010231218793211124, 'batch_size': 32} - Best Value (CSI): 0.555422 - Best Trial: 19 - Best Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2868389431100919, 'ffn_dropout': 0.16640752856148106, 'lr': 5.463974806450829e-05, 'weight_decay': 0.004850813772365092, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 08:13:35,326] Trial 22 finished with value: 0.5417138999802594 and parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.34863429382910055, 'ffn_dropout': 0.16194611936613346, 'lr': 5.73158749607141e-05, 'weight_decay': 0.025239319775156963, 'batch_size': 32}. Best is trial 19 with value: 0.5554215697637764. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.541714 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.34863429382910055, 'ffn_dropout': 0.16194611936613346, 'lr': 5.73158749607141e-05, 'weight_decay': 0.025239319775156963, 'batch_size': 32} - Best Value (CSI): 0.555422 - Best Trial: 19 - Best Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2868389431100919, 'ffn_dropout': 0.16640752856148106, 'lr': 5.463974806450829e-05, 'weight_decay': 0.004850813772365092, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 08:14:27,741] Trial 23 pruned. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.405533 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.34722808720913334, 'ffn_dropout': 0.14650268513655668, 'lr': 2.0993536358958997e-05, 'weight_decay': 0.04967521473537206, 'batch_size': 32} - Best Value (CSI): 0.555422 - Best Trial: 19 - Best Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2868389431100919, 'ffn_dropout': 0.16640752856148106, 'lr': 5.463974806450829e-05, 'weight_decay': 0.004850813772365092, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 08:18:44,093] Trial 24 finished with value: 0.5457417451729959 and parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.31249426454931456, 'ffn_dropout': 0.18325267410505997, 'lr': 0.000127339516024954, 'weight_decay': 0.021974288000954616, 'batch_size': 32}. Best is trial 19 with value: 0.5554215697637764. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.545742 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.31249426454931456, 'ffn_dropout': 0.18325267410505997, 'lr': 0.000127339516024954, 'weight_decay': 0.021974288000954616, 'batch_size': 32} - Best Value (CSI): 0.555422 - Best Trial: 19 - Best Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2868389431100919, 'ffn_dropout': 0.16640752856148106, 'lr': 5.463974806450829e-05, 'weight_decay': 0.004850813772365092, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 08:19:25,905] Trial 25 pruned. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.431646 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.26887880403103126, 'ffn_dropout': 0.1897655577332956, 'lr': 0.00013869876237473664, 'weight_decay': 0.0675509547913591, 'batch_size': 64} - Best Value (CSI): 0.555422 - Best Trial: 19 - Best Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2868389431100919, 'ffn_dropout': 0.16640752856148106, 'lr': 5.463974806450829e-05, 'weight_decay': 0.004850813772365092, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 08:19:44,823] Trial 26 pruned. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.414887 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.24056004590267777, 'ffn_dropout': 0.12609703046482773, 'lr': 0.00036972322554796184, 'weight_decay': 0.025446072008396967, 'batch_size': 128} - Best Value (CSI): 0.555422 - Best Trial: 19 - Best Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2868389431100919, 'ffn_dropout': 0.16640752856148106, 'lr': 5.463974806450829e-05, 'weight_decay': 0.004850813772365092, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 08:19:52,559] Trial 27 pruned. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.346694 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.3046215289366382, 'ffn_dropout': 0.170926726735502, 'lr': 0.00012092362879186356, 'weight_decay': 0.05425113041079499, 'batch_size': 256} - Best Value (CSI): 0.555422 - Best Trial: 19 - Best Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2868389431100919, 'ffn_dropout': 0.16640752856148106, 'lr': 5.463974806450829e-05, 'weight_decay': 0.004850813772365092, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 08:23:33,644] Trial 28 finished with value: 0.562070126103511 and parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32}. Best is trial 28 with value: 0.562070126103511. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.562070 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 08:25:59,934] Trial 29 finished with value: 0.5463403272253701 and parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2879669548127678, 'ffn_dropout': 0.21762177868970356, 'lr': 5.178662913743865e-05, 'weight_decay': 0.013703768925630307, 'batch_size': 32}. Best is trial 28 with value: 0.562070126103511. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.546340 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2879669548127678, 'ffn_dropout': 0.21762177868970356, 'lr': 5.178662913743865e-05, 'weight_decay': 0.013703768925630307, 'batch_size': 32} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 08:26:24,943] Trial 30 pruned. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.442472 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2584861855253809, 'ffn_dropout': 0.19799860769861008, 'lr': 3.859663593043522e-05, 'weight_decay': 0.004485926336279485, 'batch_size': 64} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) -[I 2025-12-25 08:27:56,476] Trial 31 pruned. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.541916 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.28361289211352503, 'ffn_dropout': 0.22041062051725724, 'lr': 6.550896699132325e-05, 'weight_decay': 0.00971814817100261, 'batch_size': 32} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 08:28:28,648] Trial 32 pruned. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.395713 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2871642182505098, 'ffn_dropout': 0.24832958834537353, 'lr': 1.819072946665581e-05, 'weight_decay': 0.013688473557228187, 'batch_size': 32} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 08:29:13,734] Trial 33 pruned. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.418075 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2413919761563776, 'ffn_dropout': 0.2105842385439346, 'lr': 1.437893826267893e-05, 'weight_decay': 0.03579089733944812, 'batch_size': 32} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 08:29:42,120] Trial 34 pruned. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.337775 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2711329661366219, 'ffn_dropout': 0.16718280567799854, 'lr': 1.062530947582775e-05, 'weight_decay': 0.013983875486636491, 'batch_size': 32} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) -[I 2025-12-25 08:31:10,388] Trial 35 pruned. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.548054 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.32445044927554334, 'ffn_dropout': 0.1950885405558097, 'lr': 3.3602628164525815e-05, 'weight_decay': 0.008191417158953591, 'batch_size': 32} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 08:31:19,826] Trial 36 pruned. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.414695 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2936207285205797, 'ffn_dropout': 0.13472844581929178, 'lr': 7.387583928198726e-05, 'weight_decay': 0.00517446125094821, 'batch_size': 256} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 08:34:07,446] Trial 37 finished with value: 0.5310525741462949 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.22093087860252783, 'ffn_dropout': 0.22414605069547192, 'lr': 4.425122651216155e-05, 'weight_decay': 0.030510542717127487, 'batch_size': 32}. Best is trial 28 with value: 0.562070126103511. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.531053 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.22093087860252783, 'ffn_dropout': 0.22414605069547192, 'lr': 4.425122651216155e-05, 'weight_decay': 0.030510542717127487, 'batch_size': 32} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) -[I 2025-12-25 08:35:37,320] Trial 38 pruned. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.560153 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2552677442034818, 'ffn_dropout': 0.15112507585529883, 'lr': 9.460362683254514e-05, 'weight_decay': 0.019125368589434925, 'batch_size': 32} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 08:37:44,272] Trial 39 finished with value: 0.5403674251668541 and parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.17877448631586923, 'ffn_dropout': 0.23720195556969415, 'lr': 6.355505571845566e-05, 'weight_decay': 0.0036785956316733545, 'batch_size': 64}. Best is trial 28 with value: 0.562070126103511. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.540367 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.17877448631586923, 'ffn_dropout': 0.23720195556969415, 'lr': 6.355505571845566e-05, 'weight_decay': 0.0036785956316733545, 'batch_size': 64} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 08:37:51,548] Trial 40 pruned. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.380144 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3178951311574407, 'ffn_dropout': 0.25771632176856274, 'lr': 8.646315065741757e-05, 'weight_decay': 0.0071552695227808565, 'batch_size': 128} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 08:42:18,116] Trial 41 finished with value: 0.5459289508978732 and parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.30768231877857705, 'ffn_dropout': 0.1822640968989523, 'lr': 0.0001411897255038765, 'weight_decay': 0.020814956110416935, 'batch_size': 32}. Best is trial 28 with value: 0.562070126103511. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.545929 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.30768231877857705, 'ffn_dropout': 0.1822640968989523, 'lr': 0.0001411897255038765, 'weight_decay': 0.020814956110416935, 'batch_size': 32} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) -[I 2025-12-25 08:44:13,772] Trial 42 pruned. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.566718 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.30122257987107753, 'ffn_dropout': 0.1666829430030687, 'lr': 5.353834645428403e-05, 'weight_decay': 0.01106491982443498, 'batch_size': 32} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 08:47:59,580] Trial 43 finished with value: 0.5457199576979873 and parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2738154541992785, 'ffn_dropout': 0.2016834142621864, 'lr': 0.00016374315358315842, 'weight_decay': 0.019272054116882546, 'batch_size': 32}. Best is trial 28 with value: 0.562070126103511. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.545720 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2738154541992785, 'ffn_dropout': 0.2016834142621864, 'lr': 0.00016374315358315842, 'weight_decay': 0.019272054116882546, 'batch_size': 32} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 08:49:31,455] Trial 44 pruned. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.419580 - Parameters: {'d_token': 256, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.32702457837667914, 'ffn_dropout': 0.18150316802767166, 'lr': 8.913288902920807e-05, 'weight_decay': 0.0026147556268247105, 'batch_size': 32} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) -[I 2025-12-25 08:50:57,611] Trial 45 pruned. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.543171 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3126437535403685, 'ffn_dropout': 0.19331056088949622, 'lr': 3.532887605984638e-05, 'weight_decay': 0.006576006315518689, 'batch_size': 32} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 08:51:08,716] Trial 46 pruned. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.393939 - Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.2873341218636772, 'ffn_dropout': 0.2124951160717216, 'lr': 0.00010164502781121964, 'weight_decay': 0.012519604837412867, 'batch_size': 256} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 08:51:42,892] Trial 47 pruned. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.411305 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.26787658142993614, 'ffn_dropout': 0.17629034671019322, 'lr': 6.995684127860934e-05, 'weight_decay': 0.017251388465541355, 'batch_size': 64} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 08:52:41,946] Trial 48 pruned. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.420620 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.25323615500713, 'ffn_dropout': 0.23100211798919867, 'lr': 2.6863589461420407e-05, 'weight_decay': 0.027511360374086132, 'batch_size': 32} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 08:53:51,434] Trial 49 pruned. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.404527 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3033265739243797, 'ffn_dropout': 0.1395342023884493, 'lr': 4.5581824251467965e-05, 'weight_decay': 0.047873432962633564, 'batch_size': 32} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 08:57:17,907] Trial 50 finished with value: 0.5457473549045301 and parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.29001734438705484, 'ffn_dropout': 0.1638789901645844, 'lr': 0.00011555556645607427, 'weight_decay': 0.0073815725730472, 'batch_size': 64}. Best is trial 28 with value: 0.562070126103511. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.545747 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.29001734438705484, 'ffn_dropout': 0.1638789901645844, 'lr': 0.00011555556645607427, 'weight_decay': 0.0073815725730472, 'batch_size': 64} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) -[I 2025-12-25 08:58:28,962] Trial 51 pruned. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.561390 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.28108494847493726, 'ffn_dropout': 0.15716615709747975, 'lr': 0.0001200240870038988, 'weight_decay': 0.008147463880996415, 'batch_size': 64} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 09:00:42,550] Trial 52 finished with value: 0.5414908259876977 and parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.29023794888645094, 'ffn_dropout': 0.16220045629486163, 'lr': 0.0001728106052313947, 'weight_decay': 0.015031125056450116, 'batch_size': 64}. Best is trial 28 with value: 0.562070126103511. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.541491 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.29023794888645094, 'ffn_dropout': 0.16220045629486163, 'lr': 0.0001728106052313947, 'weight_decay': 0.015031125056450116, 'batch_size': 64} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 09:02:51,162] Trial 53 finished with value: 0.5384322342255672 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.26375224988611623, 'ffn_dropout': 0.12580375477043804, 'lr': 0.00027375979568912434, 'weight_decay': 0.005887964021874846, 'batch_size': 64}. Best is trial 28 with value: 0.562070126103511. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.538432 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.26375224988611623, 'ffn_dropout': 0.12580375477043804, 'lr': 0.00027375979568912434, 'weight_decay': 0.005887964021874846, 'batch_size': 64} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 09:05:10,157] Trial 54 finished with value: 0.5465328682478096 and parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3065860861042893, 'ffn_dropout': 0.17523841633063436, 'lr': 8.352361967773e-05, 'weight_decay': 0.011019702919082075, 'batch_size': 64}. Best is trial 28 with value: 0.562070126103511. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.546533 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3065860861042893, 'ffn_dropout': 0.17523841633063436, 'lr': 8.352361967773e-05, 'weight_decay': 0.011019702919082075, 'batch_size': 64} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 09:05:33,890] Trial 55 pruned. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.429242 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3353827789267406, 'ffn_dropout': 0.18706485633757103, 'lr': 8.044064082499987e-05, 'weight_decay': 0.02169917608135279, 'batch_size': 128} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) -[I 2025-12-25 09:06:33,594] Trial 56 pruned. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.587375 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3087278604421053, 'ffn_dropout': 0.1786594042459489, 'lr': 5.612837829758283e-05, 'weight_decay': 0.01055731836486332, 'batch_size': 64} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) -[I 2025-12-25 09:09:00,742] Trial 57 pruned. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.589078 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2749790332941584, 'ffn_dropout': 0.2068959384018273, 'lr': 0.00019516863957490694, 'weight_decay': 0.03322828679381044, 'batch_size': 32} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 09:09:19,320] Trial 58 pruned. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.409091 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.318178257455011, 'ffn_dropout': 0.19195595190603393, 'lr': 4.186498175408503e-05, 'weight_decay': 0.017944769603722103, 'batch_size': 64} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 09:09:27,509] Trial 59 pruned. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.339143 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3579873790798576, 'ffn_dropout': 0.17204756365626866, 'lr': 7.243239006818476e-05, 'weight_decay': 0.012394190321638066, 'batch_size': 256} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) -[I 2025-12-25 09:12:20,391] Trial 60 pruned. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.585062 - Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.32769684530937443, 'ffn_dropout': 0.1519019206527023, 'lr': 0.00014167937452403645, 'weight_decay': 0.022893263619975755, 'batch_size': 32} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 09:12:44,204] Trial 61 pruned. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.443564 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.29664161102225756, 'ffn_dropout': 0.15996563936188798, 'lr': 0.00010487961324456186, 'weight_decay': 0.0097137437289535, 'batch_size': 64} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 09:13:00,699] Trial 62 pruned. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.396572 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3083426827205797, 'ffn_dropout': 0.18481500655742436, 'lr': 5.0347052380055105e-05, 'weight_decay': 0.004670181832000532, 'batch_size': 64} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 09:15:51,114] Trial 63 finished with value: 0.5525839754505822 and parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.29257810592451183, 'ffn_dropout': 0.21781445223448181, 'lr': 0.00011240275451906387, 'weight_decay': 0.008348943910945933, 'batch_size': 64}. Best is trial 28 with value: 0.562070126103511. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.552584 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.29257810592451183, 'ffn_dropout': 0.21781445223448181, 'lr': 0.00011240275451906387, 'weight_decay': 0.008348943910945933, 'batch_size': 64} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) -[I 2025-12-25 09:16:45,981] Trial 64 pruned. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.568536 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2780175813566006, 'ffn_dropout': 0.20461871535367468, 'lr': 6.348820485685483e-05, 'weight_decay': 0.012278106567620252, 'batch_size': 64} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 09:17:15,546] Trial 65 pruned. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.440667 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2982298404640549, 'ffn_dropout': 0.24223793467797433, 'lr': 8.266097119008794e-05, 'weight_decay': 0.008376276046408462, 'batch_size': 64} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 09:17:51,193] Trial 66 pruned. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.368162 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.25933535407371394, 'ffn_dropout': 0.21210724014933782, 'lr': 0.0001961788061488939, 'weight_decay': 0.016595401608750178, 'batch_size': 32} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 09:18:01,859] Trial 67 pruned. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.361702 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2798575118956407, 'ffn_dropout': 0.21843966391837544, 'lr': 3.064561554736292e-05, 'weight_decay': 0.0055172211175228605, 'batch_size': 128} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) -[I 2025-12-25 09:20:10,901] Trial 68 pruned. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.609334 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3192774441115201, 'ffn_dropout': 0.22954957502594683, 'lr': 0.00010263702781212295, 'weight_decay': 0.024282355729070244, 'batch_size': 32} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 09:22:20,036] Trial 69 finished with value: 0.5423219814241064 and parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.24972957462776307, 'ffn_dropout': 0.19857874156431607, 'lr': 0.00014023546913538497, 'weight_decay': 0.029019896008141404, 'batch_size': 64}. Best is trial 28 with value: 0.562070126103511. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.542322 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.24972957462776307, 'ffn_dropout': 0.19857874156431607, 'lr': 0.00014023546913538497, 'weight_decay': 0.029019896008141404, 'batch_size': 64} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) -[I 2025-12-25 09:24:31,737] Trial 70 pruned. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.569678 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.28939564909339976, 'ffn_dropout': 0.17417145581986787, 'lr': 5.014224268809361e-05, 'weight_decay': 0.03934849584042267, 'batch_size': 32} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) -[I 2025-12-25 09:25:23,566] Trial 71 pruned. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.599669 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2952197899960165, 'ffn_dropout': 0.16448188388852159, 'lr': 0.00011897101915145409, 'weight_decay': 0.0071697501748524545, 'batch_size': 64} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 09:25:39,199] Trial 72 pruned. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.386637 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3067623077313092, 'ffn_dropout': 0.18819860572380528, 'lr': 7.710303844627952e-05, 'weight_decay': 0.008726664048252506, 'batch_size': 64} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) -[I 2025-12-25 09:26:33,815] Trial 73 pruned. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.553543 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.267020865980079, 'ffn_dropout': 0.14377754245093252, 'lr': 0.00011474163485954852, 'weight_decay': 0.014960127021872986, 'batch_size': 64} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 09:26:46,700] Trial 74 pruned. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.397017 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2863419566956, 'ffn_dropout': 0.15653030198481113, 'lr': 5.871599163474262e-05, 'weight_decay': 0.004171806506342129, 'batch_size': 64} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 09:27:14,645] Trial 75 pruned. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.427051 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.27434514616094235, 'ffn_dropout': 0.17089464346427125, 'lr': 4.070450043993896e-05, 'weight_decay': 0.006944990963760583, 'batch_size': 64} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) -[I 2025-12-25 09:28:45,756] Trial 76 pruned. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.597613 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.30263236766050194, 'ffn_dropout': 0.21885315964356694, 'lr': 0.00015280401873982486, 'weight_decay': 0.01181418393502355, 'batch_size': 32} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 09:28:59,367] Trial 77 pruned. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.374212 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.2927680244734795, 'ffn_dropout': 0.20011253854652816, 'lr': 6.667804804102877e-05, 'weight_decay': 0.010050095698690508, 'batch_size': 256} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 09:29:20,964] Trial 78 pruned. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.409257 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.31697349876545156, 'ffn_dropout': 0.1867725147723599, 'lr': 9.373396928459183e-05, 'weight_decay': 0.005966206498782802, 'batch_size': 64} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 09:30:15,541] Trial 79 pruned. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.389850 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.28212812007453275, 'ffn_dropout': 0.14930755981156033, 'lr': 3.5214561420353395e-05, 'weight_decay': 0.01374149828238767, 'batch_size': 32} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 09:31:17,719] Trial 80 pruned. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.422333 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.31169614993397304, 'ffn_dropout': 0.13474806266116046, 'lr': 9.449054657037952e-05, 'weight_decay': 0.018197035063025124, 'batch_size': 32} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 09:36:11,107] Trial 81 finished with value: 0.5522114948820387 and parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.29908797322246794, 'ffn_dropout': 0.1750651361903481, 'lr': 0.00011522069731884435, 'weight_decay': 0.02130553248327465, 'batch_size': 32}. Best is trial 28 with value: 0.562070126103511. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.552211 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.29908797322246794, 'ffn_dropout': 0.1750651361903481, 'lr': 0.00011522069731884435, 'weight_decay': 0.02130553248327465, 'batch_size': 32} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) -[I 2025-12-25 09:38:32,664] Trial 82 pruned. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.598657 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.30169231186784123, 'ffn_dropout': 0.17518513646031003, 'lr': 0.00013600338957476705, 'weight_decay': 0.021251778403280113, 'batch_size': 32} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) -[I 2025-12-25 09:40:48,014] Trial 83 pruned. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.544624 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.28809104910473904, 'ffn_dropout': 0.18138491585091573, 'lr': 8.081857523924903e-05, 'weight_decay': 0.04121820371882086, 'batch_size': 32} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) -[I 2025-12-25 09:42:54,385] Trial 84 pruned. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.557122 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2703448934802698, 'ffn_dropout': 0.19434938189993547, 'lr': 6.20057494755154e-05, 'weight_decay': 0.015895025988485915, 'batch_size': 32} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 09:43:31,924] Trial 85 pruned. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.403114 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2618991965462718, 'ffn_dropout': 0.16730191734911898, 'lr': 0.00023547578617873633, 'weight_decay': 0.027873201171358497, 'batch_size': 32} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 09:43:45,513] Trial 86 pruned. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.418919 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.29590564046485685, 'ffn_dropout': 0.1587776859622761, 'lr': 0.0001141224114723154, 'weight_decay': 0.010520114849056367, 'batch_size': 128} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 09:44:24,444] Trial 87 pruned. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.402636 - Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3248897780536072, 'ffn_dropout': 0.1980916602107739, 'lr': 0.00017125614956711298, 'weight_decay': 0.008306181672228827, 'batch_size': 64} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) -[I 2025-12-25 09:46:17,746] Trial 88 pruned. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.542289 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.283763375023306, 'ffn_dropout': 0.17977488185772986, 'lr': 4.913836140741647e-05, 'weight_decay': 0.056103692142684486, 'batch_size': 32} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) -[I 2025-12-25 09:47:00,107] Trial 89 pruned. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.399884 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3101021405101785, 'ffn_dropout': 0.16655329902535482, 'lr': 7.142288837572873e-05, 'weight_decay': 0.013186826745742977, 'batch_size': 32} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) -[I 2025-12-25 09:48:02,639] Trial 90 pruned. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.587186 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.27582009754489833, 'ffn_dropout': 0.21200150728018638, 'lr': 9.111706541410853e-05, 'weight_decay': 0.020304620839548083, 'batch_size': 64} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) -[I 2025-12-25 09:50:10,054] Trial 91 pruned. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.560000 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.31658545634117, 'ffn_dropout': 0.20594646623117188, 'lr': 0.00011696339394878027, 'weight_decay': 0.03162125058731505, 'batch_size': 32} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 09:54:12,704] Trial 92 finished with value: 0.5513517872478811 and parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.30215352866745376, 'ffn_dropout': 0.1901725577197075, 'lr': 0.00013173589045107465, 'weight_decay': 0.015576128345423467, 'batch_size': 32}. Best is trial 28 with value: 0.562070126103511. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.551352 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.30215352866745376, 'ffn_dropout': 0.1901725577197075, 'lr': 0.00013173589045107465, 'weight_decay': 0.015576128345423467, 'batch_size': 32} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) -[I 2025-12-25 09:56:25,272] Trial 93 pruned. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.600813 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.30351941440897473, 'ffn_dropout': 0.19379599622535823, 'lr': 0.00013504335762524244, 'weight_decay': 0.011699870691978292, 'batch_size': 32} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) -[I 2025-12-25 09:58:48,506] Trial 94 pruned. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.578447 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.29439639906735154, 'ffn_dropout': 0.18777596563005042, 'lr': 5.559371089065815e-05, 'weight_decay': 0.014261180909866462, 'batch_size': 32} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 365.5, 1: 3.533534743202417, 2: 0.36842436842436843} (클래스별 샘플 수: {0: 16, 1: 1655, 2: 15873}) -[I 2025-12-25 10:03:08,046] Trial 95 finished with value: 0.5460386186858687 and parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.28893137693203524, 'ffn_dropout': 0.17572057601386684, 'lr': 9.788407295637717e-05, 'weight_decay': 0.025017601247231357, 'batch_size': 32}. Best is trial 28 with value: 0.562070126103511. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.546039 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.28893137693203524, 'ffn_dropout': 0.17572057601386684, 'lr': 9.788407295637717e-05, 'weight_decay': 0.025017601247231357, 'batch_size': 32} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) -[I 2025-12-25 10:05:10,155] Trial 96 pruned. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.556420 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.33481975496414573, 'ffn_dropout': 0.1778070779808575, 'lr': 7.891067472230128e-05, 'weight_decay': 0.026300142169420882, 'batch_size': 32} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) -[I 2025-12-25 10:07:14,087] Trial 97 pruned. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.557918 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.3043230672650425, 'ffn_dropout': 0.20149721039392232, 'lr': 9.686721971856521e-05, 'weight_decay': 0.017334106962579036, 'batch_size': 32} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) -[I 2025-12-25 10:09:22,054] Trial 98 pruned. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.554589 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2836297353896279, 'ffn_dropout': 0.1717945027353816, 'lr': 4.284637312921357e-05, 'weight_decay': 0.021821556229264457, 'batch_size': 32} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 176.96969696969697, 1: 3.2247377139701823, 2: 0.3725440163306966} (클래스별 샘플 수: {0: 33, 1: 1811, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 201.6551724137931, 1: 3.4562647754137115, 2: 0.3695885735953991} (클래스별 샘플 수: {0: 29, 1: 1692, 2: 15823}) -[I 2025-12-25 10:11:28,768] Trial 99 pruned. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.564177 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2705004268782494, 'ffn_dropout': 0.15423311162846828, 'lr': 0.0001751653878099956, 'weight_decay': 0.01599843705081302, 'batch_size': 32} - Best Value (CSI): 0.562070 - Best Trial: 28 - Best Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.5621 -Best Hyperparameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2855445640312001, 'ffn_dropout': 0.20563167448836292, 'lr': 7.430025637172839e-05, 'weight_decay': 0.012136192435211931, 'batch_size': 32} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.5516 - - 최종 CSI: 0.5642 - - 최고 CSI: 0.6093 - - 최저 CSI: 0.0000 - - 평균 CSI: 0.4795 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/ft_transformer_pure_seoul_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 21, Best CSI: 0.4613 - Fold 1 학습 완료 (검증 CSI: 0.4613) -Fold 2 학습 중... - Early stopping at epoch 69, Best CSI: 0.6205 - Fold 2 학습 완료 (검증 CSI: 0.6205) -Fold 3 학습 중... - Early stopping at epoch 32, Best CSI: 0.5634 - Fold 3 학습 완료 (검증 CSI: 0.5634) - -모든 모델 저장 완료: ../save_model/ft_transformer_optima/ft_transformer_pure_seoul.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/ft_transformer_optima/scaler/ft_transformer_pure_seoul_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: - - . - - . - - / - - s - - a - - v - - e - - _ - - m - - o - - d - - e - - l - - / - - f - - t - - _ - - t - - r - - a - - n - - s - - f - - o - - r - - m - - e - - r - - _ - - o - - p - - t - - i - - m - - a - - / - - f - - t - - _ - - t - - r - - a - - n - - s - - f - - o - - r - - m - - e - - r - - _ - - p - - u - - r - - e - - _ - - s - - e - - o - - u - - l - - . - - p - - k - - l - -✓ 완료: ft_transformer_pure/ft_transforemer_pure_seoul.py (소요 시간: 10188초) - -========================================== -FT-Transformer Pure 파일 실행 완료 -종료 시간: 2025-12-25 10:15:42 -총 소요 시간: 13시간 9분 51초 -성공: 6개 -실패: 0개 -========================================== diff --git a/Analysis_code/5.optima/run_bash/ft_transformer/ft_transformer_smote.log b/Analysis_code/5.optima/run_bash/ft_transformer/ft_transformer_smote.log deleted file mode 100644 index d8174e0bc82044475524764541c8365ebdc6a4e3..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/run_bash/ft_transformer/ft_transformer_smote.log +++ /dev/null @@ -1,7967 +0,0 @@ -nohup: ignoring input -/bin/bash: /opt/conda/lib/libtinfo.so.6: no version information available (required by /bin/bash) -========================================== -FT-Transformer SMOTE 파일 실행 시작 -시작 시간: 2025-12-24 21:05:54 -GPU: 0번 (CUDA_VISIBLE_DEVICES=0) -========================================== - ----------------------------------------- -실행 중: ft_transformer_smote/ft_transformer_smote_busan.py -시작 시간: 2025-12-24 21:05:54 ----------------------------------------- -[I 2025-12-24 21:05:55,889] A new study created in memory with name: no-name-47815f99-cf7c-435c-bccc-b9cfbfadae6a - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-24 21:12:28,543] Trial 0 finished with value: 0.41965141552801977 and parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.1574935976731961, 'ffn_dropout': 0.30988558670860916, 'lr': 0.0009464150023590392, 'weight_decay': 0.0025483001332046312, 'batch_size': 32}. Best is trial 0 with value: 0.41965141552801977. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.419651 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.1574935976731961, 'ffn_dropout': 0.30988558670860916, 'lr': 0.0009464150023590392, 'weight_decay': 0.0025483001332046312, 'batch_size': 32} - Best Value (CSI): 0.419651 - Best Trial: 0 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.1574935976731961, 'ffn_dropout': 0.30988558670860916, 'lr': 0.0009464150023590392, 'weight_decay': 0.0025483001332046312, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-24 21:15:25,215] Trial 1 finished with value: 0.4334669922507663 and parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.20913135186001872, 'ffn_dropout': 0.19083318435575872, 'lr': 0.001389560850445599, 'weight_decay': 0.005112284813526378, 'batch_size': 256}. Best is trial 1 with value: 0.4334669922507663. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.433467 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.20913135186001872, 'ffn_dropout': 0.19083318435575872, 'lr': 0.001389560850445599, 'weight_decay': 0.005112284813526378, 'batch_size': 256} - Best Value (CSI): 0.433467 - Best Trial: 1 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.20913135186001872, 'ffn_dropout': 0.19083318435575872, 'lr': 0.001389560850445599, 'weight_decay': 0.005112284813526378, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-24 21:16:47,955] Trial 2 finished with value: 0.32463801945895776 and parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3236019678279256, 'ffn_dropout': 0.16654956503815277, 'lr': 0.003736625649918855, 'weight_decay': 0.0006263372812843186, 'batch_size': 256}. Best is trial 1 with value: 0.4334669922507663. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.324638 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3236019678279256, 'ffn_dropout': 0.16654956503815277, 'lr': 0.003736625649918855, 'weight_decay': 0.0006263372812843186, 'batch_size': 256} - Best Value (CSI): 0.433467 - Best Trial: 1 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.20913135186001872, 'ffn_dropout': 0.19083318435575872, 'lr': 0.001389560850445599, 'weight_decay': 0.005112284813526378, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-24 21:20:58,831] Trial 3 finished with value: 0.39680243410364485 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2695097297697054, 'ffn_dropout': 0.2928213639887195, 'lr': 2.440676516352321e-05, 'weight_decay': 0.0016235810946773038, 'batch_size': 64}. Best is trial 1 with value: 0.4334669922507663. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.396802 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2695097297697054, 'ffn_dropout': 0.2928213639887195, 'lr': 2.440676516352321e-05, 'weight_decay': 0.0016235810946773038, 'batch_size': 64} - Best Value (CSI): 0.433467 - Best Trial: 1 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.20913135186001872, 'ffn_dropout': 0.19083318435575872, 'lr': 0.001389560850445599, 'weight_decay': 0.005112284813526378, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-24 21:22:46,047] Trial 4 finished with value: 0.40399158382571887 and parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.1598591149682682, 'ffn_dropout': 0.22447400715104449, 'lr': 0.00035943399423804084, 'weight_decay': 0.09174534108052207, 'batch_size': 256}. Best is trial 1 with value: 0.4334669922507663. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.403992 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.1598591149682682, 'ffn_dropout': 0.22447400715104449, 'lr': 0.00035943399423804084, 'weight_decay': 0.09174534108052207, 'batch_size': 256} - Best Value (CSI): 0.433467 - Best Trial: 1 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.20913135186001872, 'ffn_dropout': 0.19083318435575872, 'lr': 0.001389560850445599, 'weight_decay': 0.005112284813526378, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-24 21:24:29,964] Trial 5 finished with value: 0.4375110175056123 and parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.36388758910043406, 'ffn_dropout': 0.29740853665511835, 'lr': 0.0024044174573707097, 'weight_decay': 0.000343846266426076, 'batch_size': 128}. Best is trial 5 with value: 0.4375110175056123. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.437511 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.36388758910043406, 'ffn_dropout': 0.29740853665511835, 'lr': 0.0024044174573707097, 'weight_decay': 0.000343846266426076, 'batch_size': 128} - Best Value (CSI): 0.437511 - Best Trial: 5 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.36388758910043406, 'ffn_dropout': 0.29740853665511835, 'lr': 0.0024044174573707097, 'weight_decay': 0.000343846266426076, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-24 21:24:52,617] Trial 6 pruned. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.427095 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2655596423760539, 'ffn_dropout': 0.22190839625702635, 'lr': 2.0013738329828316e-05, 'weight_decay': 0.03413801401669146, 'batch_size': 128} - Best Value (CSI): 0.437511 - Best Trial: 5 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.36388758910043406, 'ffn_dropout': 0.29740853665511835, 'lr': 0.0024044174573707097, 'weight_decay': 0.000343846266426076, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-24 21:25:06,730] Trial 7 pruned. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.055556 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2194144511212589, 'ffn_dropout': 0.38382670675094377, 'lr': 0.0031539957812792307, 'weight_decay': 0.00014795822138527736, 'batch_size': 128} - Best Value (CSI): 0.437511 - Best Trial: 5 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.36388758910043406, 'ffn_dropout': 0.29740853665511835, 'lr': 0.0024044174573707097, 'weight_decay': 0.000343846266426076, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-24 21:28:57,175] Trial 8 finished with value: 0.4166224751181035 and parameters: {'d_token': 224, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.2332383594859541, 'ffn_dropout': 0.36305168512300656, 'lr': 0.00013001003991295996, 'weight_decay': 0.0027087254518589994, 'batch_size': 128}. Best is trial 5 with value: 0.4375110175056123. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.416622 - Parameters: {'d_token': 224, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.2332383594859541, 'ffn_dropout': 0.36305168512300656, 'lr': 0.00013001003991295996, 'weight_decay': 0.0027087254518589994, 'batch_size': 128} - Best Value (CSI): 0.437511 - Best Trial: 5 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.36388758910043406, 'ffn_dropout': 0.29740853665511835, 'lr': 0.0024044174573707097, 'weight_decay': 0.000343846266426076, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-24 21:29:35,198] Trial 9 pruned. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.404588 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.10751956210401374, 'ffn_dropout': 0.16464681918192303, 'lr': 0.00012662986306850234, 'weight_decay': 0.02342516728093419, 'batch_size': 32} - Best Value (CSI): 0.437511 - Best Trial: 5 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.36388758910043406, 'ffn_dropout': 0.29740853665511835, 'lr': 0.0024044174573707097, 'weight_decay': 0.000343846266426076, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-24 21:30:09,945] Trial 10 pruned. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.004668 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3898439442423115, 'ffn_dropout': 0.10681319536078082, 'lr': 0.008658219863750703, 'weight_decay': 0.00010555729964301237, 'batch_size': 64} - Best Value (CSI): 0.437511 - Best Trial: 5 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.36388758910043406, 'ffn_dropout': 0.29740853665511835, 'lr': 0.0024044174573707097, 'weight_decay': 0.000343846266426076, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-24 21:30:36,905] Trial 11 pruned. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.414716 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.3638651295874337, 'ffn_dropout': 0.2642494382623264, 'lr': 0.0011905783073190076, 'weight_decay': 0.008088603232781398, 'batch_size': 256} - Best Value (CSI): 0.437511 - Best Trial: 5 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.36388758910043406, 'ffn_dropout': 0.29740853665511835, 'lr': 0.0024044174573707097, 'weight_decay': 0.000343846266426076, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-24 21:32:45,785] Trial 12 finished with value: 0.42300968712454384 and parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.33704343113081175, 'ffn_dropout': 0.3235601855526829, 'lr': 0.0011604191302588547, 'weight_decay': 0.0006686151814379874, 'batch_size': 128}. Best is trial 5 with value: 0.4375110175056123. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.423010 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.33704343113081175, 'ffn_dropout': 0.3235601855526829, 'lr': 0.0011604191302588547, 'weight_decay': 0.0006686151814379874, 'batch_size': 128} - Best Value (CSI): 0.437511 - Best Trial: 5 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.36388758910043406, 'ffn_dropout': 0.29740853665511835, 'lr': 0.0024044174573707097, 'weight_decay': 0.000343846266426076, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-24 21:33:05,197] Trial 13 pruned. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.004668 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.30623679320906483, 'ffn_dropout': 0.25280745574750896, 'lr': 0.009708106028279226, 'weight_decay': 0.007280780572685686, 'batch_size': 256} - Best Value (CSI): 0.437511 - Best Trial: 5 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.36388758910043406, 'ffn_dropout': 0.29740853665511835, 'lr': 0.0024044174573707097, 'weight_decay': 0.000343846266426076, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-24 21:34:49,662] Trial 14 finished with value: 0.423669310426247 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.38776500456448787, 'ffn_dropout': 0.34521481112445573, 'lr': 0.0029765086830707706, 'weight_decay': 0.00045247618273238293, 'batch_size': 128}. Best is trial 5 with value: 0.4375110175056123. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.423669 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.38776500456448787, 'ffn_dropout': 0.34521481112445573, 'lr': 0.0029765086830707706, 'weight_decay': 0.00045247618273238293, 'batch_size': 128} - Best Value (CSI): 0.437511 - Best Trial: 5 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.36388758910043406, 'ffn_dropout': 0.29740853665511835, 'lr': 0.0024044174573707097, 'weight_decay': 0.000343846266426076, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-24 21:38:51,619] Trial 15 finished with value: 0.4365318008837689 and parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.2999068452257059, 'ffn_dropout': 0.2656001055016814, 'lr': 0.0007119719336366016, 'weight_decay': 0.006173782177895953, 'batch_size': 256}. Best is trial 5 with value: 0.4375110175056123. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.436532 - Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.2999068452257059, 'ffn_dropout': 0.2656001055016814, 'lr': 0.0007119719336366016, 'weight_decay': 0.006173782177895953, 'batch_size': 256} - Best Value (CSI): 0.437511 - Best Trial: 5 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.36388758910043406, 'ffn_dropout': 0.29740853665511835, 'lr': 0.0024044174573707097, 'weight_decay': 0.000343846266426076, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-24 21:45:03,484] Trial 16 finished with value: 0.43280990739996156 and parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2971442062381562, 'ffn_dropout': 0.29015538747493885, 'lr': 0.0003538573033897117, 'weight_decay': 0.0011816252898125496, 'batch_size': 32}. Best is trial 5 with value: 0.4375110175056123. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.432810 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2971442062381562, 'ffn_dropout': 0.29015538747493885, 'lr': 0.0003538573033897117, 'weight_decay': 0.0011816252898125496, 'batch_size': 32} - Best Value (CSI): 0.437511 - Best Trial: 5 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.36388758910043406, 'ffn_dropout': 0.29740853665511835, 'lr': 0.0024044174573707097, 'weight_decay': 0.000343846266426076, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-24 21:48:11,069] Trial 17 finished with value: 0.4372625602497062 and parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.32878153873614646, 'ffn_dropout': 0.3281289651580391, 'lr': 0.0005719163604844605, 'weight_decay': 0.0002543813823444051, 'batch_size': 64}. Best is trial 5 with value: 0.4375110175056123. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.437263 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.32878153873614646, 'ffn_dropout': 0.3281289651580391, 'lr': 0.0005719163604844605, 'weight_decay': 0.0002543813823444051, 'batch_size': 64} - Best Value (CSI): 0.437511 - Best Trial: 5 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.36388758910043406, 'ffn_dropout': 0.29740853665511835, 'lr': 0.0024044174573707097, 'weight_decay': 0.000343846266426076, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-24 21:48:46,653] Trial 18 pruned. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.418902 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.34980121968769395, 'ffn_dropout': 0.3987179566593859, 'lr': 0.00016241238377965098, 'weight_decay': 0.00024399990341743757, 'batch_size': 64} - Best Value (CSI): 0.437511 - Best Trial: 5 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.36388758910043406, 'ffn_dropout': 0.29740853665511835, 'lr': 0.0024044174573707097, 'weight_decay': 0.000343846266426076, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-24 21:51:11,629] Trial 19 finished with value: 0.4359863113211031 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3644873901170365, 'ffn_dropout': 0.3336321391123297, 'lr': 0.0005355930716015892, 'weight_decay': 0.0003022826262774228, 'batch_size': 64}. Best is trial 5 with value: 0.4375110175056123. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.435986 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3644873901170365, 'ffn_dropout': 0.3336321391123297, 'lr': 0.0005355930716015892, 'weight_decay': 0.0003022826262774228, 'batch_size': 64} - Best Value (CSI): 0.437511 - Best Trial: 5 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.36388758910043406, 'ffn_dropout': 0.29740853665511835, 'lr': 0.0024044174573707097, 'weight_decay': 0.000343846266426076, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-24 21:51:42,808] Trial 20 pruned. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.050238 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3294070952189383, 'ffn_dropout': 0.3584180402593875, 'lr': 0.002201007483093833, 'weight_decay': 0.00023566347793866209, 'batch_size': 64} - Best Value (CSI): 0.437511 - Best Trial: 5 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.36388758910043406, 'ffn_dropout': 0.29740853665511835, 'lr': 0.0024044174573707097, 'weight_decay': 0.000343846266426076, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-24 21:53:13,410] Trial 21 finished with value: 0.41660778074477284 and parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2996503080720502, 'ffn_dropout': 0.2850671156681769, 'lr': 0.000613877242535718, 'weight_decay': 0.0009973432087874302, 'batch_size': 256}. Best is trial 5 with value: 0.4375110175056123. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.416608 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2996503080720502, 'ffn_dropout': 0.2850671156681769, 'lr': 0.000613877242535718, 'weight_decay': 0.0009973432087874302, 'batch_size': 256} - Best Value (CSI): 0.437511 - Best Trial: 5 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.36388758910043406, 'ffn_dropout': 0.29740853665511835, 'lr': 0.0024044174573707097, 'weight_decay': 0.000343846266426076, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-24 21:54:50,973] Trial 22 finished with value: 0.410518360427276 and parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3608237164642354, 'ffn_dropout': 0.3195409223897255, 'lr': 0.0007151084409601565, 'weight_decay': 0.0004212352907288091, 'batch_size': 128}. Best is trial 5 with value: 0.4375110175056123. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.410518 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3608237164642354, 'ffn_dropout': 0.3195409223897255, 'lr': 0.0007151084409601565, 'weight_decay': 0.0004212352907288091, 'batch_size': 128} - Best Value (CSI): 0.437511 - Best Trial: 5 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.36388758910043406, 'ffn_dropout': 0.29740853665511835, 'lr': 0.0024044174573707097, 'weight_decay': 0.000343846266426076, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-24 21:55:21,870] Trial 23 pruned. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.004668 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2867797909315473, 'ffn_dropout': 0.2752686726720989, 'lr': 0.0017117696447767838, 'weight_decay': 0.0001333568973646567, 'batch_size': 64} - Best Value (CSI): 0.437511 - Best Trial: 5 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.36388758910043406, 'ffn_dropout': 0.29740853665511835, 'lr': 0.0024044174573707097, 'weight_decay': 0.000343846266426076, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-24 21:58:28,381] Trial 24 finished with value: 0.4301591461595642 and parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.32598949654607123, 'ffn_dropout': 0.2949630817646046, 'lr': 0.00023496751147774778, 'weight_decay': 0.0015427648762640848, 'batch_size': 64}. Best is trial 5 with value: 0.4375110175056123. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.430159 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.32598949654607123, 'ffn_dropout': 0.2949630817646046, 'lr': 0.00023496751147774778, 'weight_decay': 0.0015427648762640848, 'batch_size': 64} - Best Value (CSI): 0.437511 - Best Trial: 5 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.36388758910043406, 'ffn_dropout': 0.29740853665511835, 'lr': 0.0024044174573707097, 'weight_decay': 0.000343846266426076, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-24 21:58:48,514] Trial 25 pruned. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.004668 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39733584541613337, 'ffn_dropout': 0.3104955960832677, 'lr': 0.004490491441231848, 'weight_decay': 0.000741514778599734, 'batch_size': 128} - Best Value (CSI): 0.437511 - Best Trial: 5 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.36388758910043406, 'ffn_dropout': 0.29740853665511835, 'lr': 0.0024044174573707097, 'weight_decay': 0.000343846266426076, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-24 22:00:37,601] Trial 26 finished with value: 0.2722354443181987 and parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.3125321665444423, 'ffn_dropout': 0.2651471331189512, 'lr': 0.0018756512814265501, 'weight_decay': 0.00017414858345101038, 'batch_size': 256}. Best is trial 5 with value: 0.4375110175056123. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.272235 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.3125321665444423, 'ffn_dropout': 0.2651471331189512, 'lr': 0.0018756512814265501, 'weight_decay': 0.00017414858345101038, 'batch_size': 256} - Best Value (CSI): 0.437511 - Best Trial: 5 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.36388758910043406, 'ffn_dropout': 0.29740853665511835, 'lr': 0.0024044174573707097, 'weight_decay': 0.000343846266426076, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-24 22:08:08,269] Trial 27 finished with value: 0.43790937194515145 and parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.34401571296485917, 'ffn_dropout': 0.3388500820159284, 'lr': 0.0007783286317934511, 'weight_decay': 0.0003221318744740996, 'batch_size': 32}. Best is trial 27 with value: 0.43790937194515145. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.437909 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.34401571296485917, 'ffn_dropout': 0.3388500820159284, 'lr': 0.0007783286317934511, 'weight_decay': 0.0003221318744740996, 'batch_size': 32} - Best Value (CSI): 0.437909 - Best Trial: 27 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.34401571296485917, 'ffn_dropout': 0.3388500820159284, 'lr': 0.0007783286317934511, 'weight_decay': 0.0003221318744740996, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-24 22:13:45,165] Trial 28 finished with value: 0.4459102004022069 and parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3510971813482271, 'ffn_dropout': 0.3408188888127756, 'lr': 0.0004510576399065289, 'weight_decay': 0.0003549366009774532, 'batch_size': 32}. Best is trial 28 with value: 0.4459102004022069. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.445910 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3510971813482271, 'ffn_dropout': 0.3408188888127756, 'lr': 0.0004510576399065289, 'weight_decay': 0.0003549366009774532, 'batch_size': 32} - Best Value (CSI): 0.445910 - Best Trial: 28 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3510971813482271, 'ffn_dropout': 0.3408188888127756, 'lr': 0.0004510576399065289, 'weight_decay': 0.0003549366009774532, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-24 22:18:39,059] Trial 29 finished with value: 0.43084113253128925 and parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3800431597607441, 'ffn_dropout': 0.3471051880561999, 'lr': 0.0010434808124028848, 'weight_decay': 0.00042210998090241327, 'batch_size': 32}. Best is trial 28 with value: 0.4459102004022069. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.430841 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3800431597607441, 'ffn_dropout': 0.3471051880561999, 'lr': 0.0010434808124028848, 'weight_decay': 0.00042210998090241327, 'batch_size': 32} - Best Value (CSI): 0.445910 - Best Trial: 28 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3510971813482271, 'ffn_dropout': 0.3408188888127756, 'lr': 0.0004510576399065289, 'weight_decay': 0.0003549366009774532, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-24 22:19:28,177] Trial 30 pruned. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.004668 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.35210601115778195, 'ffn_dropout': 0.30374027686689364, 'lr': 0.005141179188304294, 'weight_decay': 0.00012057549926705647, 'batch_size': 32} - Best Value (CSI): 0.445910 - Best Trial: 28 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3510971813482271, 'ffn_dropout': 0.3408188888127756, 'lr': 0.0004510576399065289, 'weight_decay': 0.0003549366009774532, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-24 22:27:26,753] Trial 31 finished with value: 0.4207704266088823 and parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3402271885386149, 'ffn_dropout': 0.3291554132416151, 'lr': 0.0008719726767718228, 'weight_decay': 0.0002764905639208041, 'batch_size': 32}. Best is trial 28 with value: 0.4459102004022069. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.420770 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3402271885386149, 'ffn_dropout': 0.3291554132416151, 'lr': 0.0008719726767718228, 'weight_decay': 0.0002764905639208041, 'batch_size': 32} - Best Value (CSI): 0.445910 - Best Trial: 28 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3510971813482271, 'ffn_dropout': 0.3408188888127756, 'lr': 0.0004510576399065289, 'weight_decay': 0.0003549366009774532, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-24 22:31:32,856] Trial 32 finished with value: 0.4355171145967385 and parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3499588016115413, 'ffn_dropout': 0.3153384457826252, 'lr': 0.0004821970149214626, 'weight_decay': 0.0001973829181104033, 'batch_size': 32}. Best is trial 28 with value: 0.4459102004022069. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.435517 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3499588016115413, 'ffn_dropout': 0.3153384457826252, 'lr': 0.0004821970149214626, 'weight_decay': 0.0001973829181104033, 'batch_size': 32} - Best Value (CSI): 0.445910 - Best Trial: 28 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3510971813482271, 'ffn_dropout': 0.3408188888127756, 'lr': 0.0004510576399065289, 'weight_decay': 0.0003549366009774532, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-24 22:32:19,802] Trial 33 pruned. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.283617 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3700858359524777, 'ffn_dropout': 0.36670124248533253, 'lr': 0.0013832951659969199, 'weight_decay': 0.0003303861364929431, 'batch_size': 32} - Best Value (CSI): 0.445910 - Best Trial: 28 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3510971813482271, 'ffn_dropout': 0.3408188888127756, 'lr': 0.0004510576399065289, 'weight_decay': 0.0003549366009774532, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-24 22:36:09,828] Trial 34 finished with value: 0.4463630039318461 and parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3987215090426597, 'ffn_dropout': 0.336566517106967, 'lr': 0.0008572049638578863, 'weight_decay': 0.0005589082638801729, 'batch_size': 32}. Best is trial 34 with value: 0.4463630039318461. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.446363 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3987215090426597, 'ffn_dropout': 0.336566517106967, 'lr': 0.0008572049638578863, 'weight_decay': 0.0005589082638801729, 'batch_size': 32} - Best Value (CSI): 0.446363 - Best Trial: 34 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3987215090426597, 'ffn_dropout': 0.336566517106967, 'lr': 0.0008572049638578863, 'weight_decay': 0.0005589082638801729, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-24 22:42:35,255] Trial 35 finished with value: 0.4392975901752612 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3991229252546097, 'ffn_dropout': 0.34166060026816564, 'lr': 0.002043281809261203, 'weight_decay': 0.0005694828170719871, 'batch_size': 32}. Best is trial 34 with value: 0.4463630039318461. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.439298 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3991229252546097, 'ffn_dropout': 0.34166060026816564, 'lr': 0.002043281809261203, 'weight_decay': 0.0005694828170719871, 'batch_size': 32} - Best Value (CSI): 0.446363 - Best Trial: 34 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3987215090426597, 'ffn_dropout': 0.336566517106967, 'lr': 0.0008572049638578863, 'weight_decay': 0.0005589082638801729, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-24 22:48:30,974] Trial 36 finished with value: 0.4324567645689313 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3996134636792994, 'ffn_dropout': 0.3749623569062994, 'lr': 0.001284119548876431, 'weight_decay': 0.0006929232625133617, 'batch_size': 32}. Best is trial 34 with value: 0.4463630039318461. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.432457 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3996134636792994, 'ffn_dropout': 0.3749623569062994, 'lr': 0.001284119548876431, 'weight_decay': 0.0006929232625133617, 'batch_size': 32} - Best Value (CSI): 0.446363 - Best Trial: 34 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3987215090426597, 'ffn_dropout': 0.336566517106967, 'lr': 0.0008572049638578863, 'weight_decay': 0.0005589082638801729, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-24 22:52:02,290] Trial 37 finished with value: 0.43425429630786416 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3809257667210215, 'ffn_dropout': 0.3450200811081154, 'lr': 0.0008954511118199262, 'weight_decay': 0.0008826837576775063, 'batch_size': 32}. Best is trial 34 with value: 0.4463630039318461. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.434254 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3809257667210215, 'ffn_dropout': 0.3450200811081154, 'lr': 0.0008954511118199262, 'weight_decay': 0.0008826837576775063, 'batch_size': 32} - Best Value (CSI): 0.446363 - Best Trial: 34 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3987215090426597, 'ffn_dropout': 0.336566517106967, 'lr': 0.0008572049638578863, 'weight_decay': 0.0005589082638801729, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-24 22:56:12,998] Trial 38 finished with value: 0.42355923241246457 and parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3782840056891267, 'ffn_dropout': 0.38015128076210386, 'lr': 0.0002618202409430784, 'weight_decay': 0.0005419490720556146, 'batch_size': 32}. Best is trial 34 with value: 0.4463630039318461. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.423559 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3782840056891267, 'ffn_dropout': 0.38015128076210386, 'lr': 0.0002618202409430784, 'weight_decay': 0.0005419490720556146, 'batch_size': 32} - Best Value (CSI): 0.446363 - Best Trial: 34 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3987215090426597, 'ffn_dropout': 0.336566517106967, 'lr': 0.0008572049638578863, 'weight_decay': 0.0005589082638801729, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-24 23:00:51,298] Trial 39 finished with value: 0.4293577858951964 and parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.37617196257945157, 'ffn_dropout': 0.34911502328672944, 'lr': 0.0017822104239784387, 'weight_decay': 0.0015491367978491912, 'batch_size': 32}. Best is trial 34 with value: 0.4463630039318461. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.429358 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.37617196257945157, 'ffn_dropout': 0.34911502328672944, 'lr': 0.0017822104239784387, 'weight_decay': 0.0015491367978491912, 'batch_size': 32} - Best Value (CSI): 0.446363 - Best Trial: 34 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3987215090426597, 'ffn_dropout': 0.336566517106967, 'lr': 0.0008572049638578863, 'weight_decay': 0.0005589082638801729, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-24 23:07:40,465] Trial 40 finished with value: 0.43040988464990776 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.3979081549487835, 'ffn_dropout': 0.30772561574665236, 'lr': 0.0003699016051387335, 'weight_decay': 0.0005347442517567145, 'batch_size': 32}. Best is trial 34 with value: 0.4463630039318461. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.430410 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.3979081549487835, 'ffn_dropout': 0.30772561574665236, 'lr': 0.0003699016051387335, 'weight_decay': 0.0005347442517567145, 'batch_size': 32} - Best Value (CSI): 0.446363 - Best Trial: 34 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3987215090426597, 'ffn_dropout': 0.336566517106967, 'lr': 0.0008572049638578863, 'weight_decay': 0.0005589082638801729, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-24 23:08:18,299] Trial 41 pruned. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.151296 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3690296331054903, 'ffn_dropout': 0.3362332391781359, 'lr': 0.002556340832413569, 'weight_decay': 0.0003678077827591992, 'batch_size': 32} - Best Value (CSI): 0.446363 - Best Trial: 34 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3987215090426597, 'ffn_dropout': 0.336566517106967, 'lr': 0.0008572049638578863, 'weight_decay': 0.0005589082638801729, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-24 23:08:56,867] Trial 42 pruned. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.034725 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.34542573806708565, 'ffn_dropout': 0.36791580387941364, 'lr': 0.0031290058861051726, 'weight_decay': 0.00019119292670322397, 'batch_size': 32} - Best Value (CSI): 0.446363 - Best Trial: 34 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3987215090426597, 'ffn_dropout': 0.336566517106967, 'lr': 0.0008572049638578863, 'weight_decay': 0.0005589082638801729, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-24 23:09:36,361] Trial 43 pruned. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.419817 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.35568098341239796, 'ffn_dropout': 0.3556063054110026, 'lr': 0.0018070892474032457, 'weight_decay': 0.0005476438985192454, 'batch_size': 32} - Best Value (CSI): 0.446363 - Best Trial: 34 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3987215090426597, 'ffn_dropout': 0.336566517106967, 'lr': 0.0008572049638578863, 'weight_decay': 0.0005589082638801729, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-24 23:11:01,869] Trial 44 finished with value: 0.44111954815903504 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3834549301338547, 'ffn_dropout': 0.3365599356377051, 'lr': 0.0008983437647027366, 'weight_decay': 0.000347998835242264, 'batch_size': 128}. Best is trial 34 with value: 0.4463630039318461. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.441120 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3834549301338547, 'ffn_dropout': 0.3365599356377051, 'lr': 0.0008983437647027366, 'weight_decay': 0.000347998835242264, 'batch_size': 128} - Best Value (CSI): 0.446363 - Best Trial: 34 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3987215090426597, 'ffn_dropout': 0.336566517106967, 'lr': 0.0008572049638578863, 'weight_decay': 0.0005589082638801729, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-24 23:14:38,493] Trial 45 finished with value: 0.44472954017480887 and parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.37965005910168254, 'ffn_dropout': 0.38882701329268754, 'lr': 0.0008562616919280586, 'weight_decay': 0.00016801314800781678, 'batch_size': 32}. Best is trial 34 with value: 0.4463630039318461. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.444730 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.37965005910168254, 'ffn_dropout': 0.38882701329268754, 'lr': 0.0008562616919280586, 'weight_decay': 0.00016801314800781678, 'batch_size': 32} - Best Value (CSI): 0.446363 - Best Trial: 34 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3987215090426597, 'ffn_dropout': 0.336566517106967, 'lr': 0.0008572049638578863, 'weight_decay': 0.0005589082638801729, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-24 23:14:49,482] Trial 46 pruned. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.421176 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.38705454482221274, 'ffn_dropout': 0.3929136716183279, 'lr': 0.0010480836216839933, 'weight_decay': 0.0001597332891299988, 'batch_size': 128} - Best Value (CSI): 0.446363 - Best Trial: 34 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3987215090426597, 'ffn_dropout': 0.336566517106967, 'lr': 0.0008572049638578863, 'weight_decay': 0.0005589082638801729, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-24 23:21:37,954] Trial 47 finished with value: 0.4417178940552165 and parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3877763157368248, 'ffn_dropout': 0.37386553403101047, 'lr': 0.0004439310744126959, 'weight_decay': 0.00010075731886403501, 'batch_size': 32}. Best is trial 34 with value: 0.4463630039318461. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.441718 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3877763157368248, 'ffn_dropout': 0.37386553403101047, 'lr': 0.0004439310744126959, 'weight_decay': 0.00010075731886403501, 'batch_size': 32} - Best Value (CSI): 0.446363 - Best Trial: 34 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3987215090426597, 'ffn_dropout': 0.336566517106967, 'lr': 0.0008572049638578863, 'weight_decay': 0.0005589082638801729, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-24 23:21:49,994] Trial 48 pruned. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.377698 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.37434098264801074, 'ffn_dropout': 0.38506015513481084, 'lr': 0.0003961252295306341, 'weight_decay': 0.00010040717349969793, 'batch_size': 128} - Best Value (CSI): 0.446363 - Best Trial: 34 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3987215090426597, 'ffn_dropout': 0.336566517106967, 'lr': 0.0008572049638578863, 'weight_decay': 0.0005589082638801729, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-24 23:26:37,929] Trial 49 finished with value: 0.4374699560152692 and parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.38209034821616505, 'ffn_dropout': 0.3710426456174736, 'lr': 0.00048307709673726544, 'weight_decay': 0.00012957978594674337, 'batch_size': 32}. Best is trial 34 with value: 0.4463630039318461. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.437470 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.38209034821616505, 'ffn_dropout': 0.3710426456174736, 'lr': 0.00048307709673726544, 'weight_decay': 0.00012957978594674337, 'batch_size': 32} - Best Value (CSI): 0.446363 - Best Trial: 34 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3987215090426597, 'ffn_dropout': 0.336566517106967, 'lr': 0.0008572049638578863, 'weight_decay': 0.0005589082638801729, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-24 23:26:51,101] Trial 50 pruned. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.406889 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.35891486123916533, 'ffn_dropout': 0.3858056714637104, 'lr': 0.0002633439939888438, 'weight_decay': 0.00018526132778799977, 'batch_size': 128} - Best Value (CSI): 0.446363 - Best Trial: 34 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3987215090426597, 'ffn_dropout': 0.336566517106967, 'lr': 0.0008572049638578863, 'weight_decay': 0.0005589082638801729, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-24 23:30:58,213] Trial 51 finished with value: 0.4470813836364582 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39802492085352037, 'ffn_dropout': 0.36050837574968037, 'lr': 0.0007457095006929073, 'weight_decay': 0.00015274852257799338, 'batch_size': 32}. Best is trial 51 with value: 0.4470813836364582. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.447081 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39802492085352037, 'ffn_dropout': 0.36050837574968037, 'lr': 0.0007457095006929073, 'weight_decay': 0.00015274852257799338, 'batch_size': 32} - Best Value (CSI): 0.447081 - Best Trial: 51 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39802492085352037, 'ffn_dropout': 0.36050837574968037, 'lr': 0.0007457095006929073, 'weight_decay': 0.00015274852257799338, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-24 23:35:14,700] Trial 52 finished with value: 0.4524714686603366 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.452471 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-24 23:39:59,451] Trial 53 finished with value: 0.43754904898926544 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39236434626913347, 'ffn_dropout': 0.3981778752838289, 'lr': 0.0006429176365114437, 'weight_decay': 0.0001069906651384945, 'batch_size': 32}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.437549 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39236434626913347, 'ffn_dropout': 0.3981778752838289, 'lr': 0.0006429176365114437, 'weight_decay': 0.0001069906651384945, 'batch_size': 32} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-24 23:44:14,236] Trial 54 finished with value: 0.42834110304718415 and parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3680804908089453, 'ffn_dropout': 0.3575549793890863, 'lr': 0.00040557616771507555, 'weight_decay': 0.00015475304765726872, 'batch_size': 32}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.428341 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3680804908089453, 'ffn_dropout': 0.3575549793890863, 'lr': 0.00040557616771507555, 'weight_decay': 0.00015475304765726872, 'batch_size': 32} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-24 23:49:49,344] Trial 55 finished with value: 0.43885857354898933 and parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3898348881259034, 'ffn_dropout': 0.3792779781922507, 'lr': 0.0005387624717992186, 'weight_decay': 0.00023593327315027827, 'batch_size': 32}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.438859 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3898348881259034, 'ffn_dropout': 0.3792779781922507, 'lr': 0.0005387624717992186, 'weight_decay': 0.00023593327315027827, 'batch_size': 32} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-24 23:53:18,926] Trial 56 finished with value: 0.4304403523930242 and parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3627327867744227, 'ffn_dropout': 0.36337311479779966, 'lr': 0.0006612147176581125, 'weight_decay': 0.0001415127593021277, 'batch_size': 32}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.430440 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3627327867744227, 'ffn_dropout': 0.36337311479779966, 'lr': 0.0006612147176581125, 'weight_decay': 0.0001415127593021277, 'batch_size': 32} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-24 23:57:12,451] Trial 57 finished with value: 0.43340193826456225 and parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3880356023357459, 'ffn_dropout': 0.35515172460070743, 'lr': 0.0012946521919838818, 'weight_decay': 0.00022928222948790844, 'batch_size': 32}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.433402 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3880356023357459, 'ffn_dropout': 0.35515172460070743, 'lr': 0.0012946521919838818, 'weight_decay': 0.00022928222948790844, 'batch_size': 32} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 00:02:46,847] Trial 58 finished with value: 0.440228455477268 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.33522901837496155, 'ffn_dropout': 0.37319305006606285, 'lr': 0.000304907622995195, 'weight_decay': 0.00012439582990311432, 'batch_size': 32}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.440228 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.33522901837496155, 'ffn_dropout': 0.37319305006606285, 'lr': 0.000304907622995195, 'weight_decay': 0.00012439582990311432, 'batch_size': 32} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 00:10:14,065] Trial 59 finished with value: 0.42505075039160617 and parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3749503051501799, 'ffn_dropout': 0.3244125818471737, 'lr': 0.00019780841935826746, 'weight_decay': 0.00019233497657578932, 'batch_size': 32}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.425051 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3749503051501799, 'ffn_dropout': 0.3244125818471737, 'lr': 0.00019780841935826746, 'weight_decay': 0.00019233497657578932, 'batch_size': 32} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 00:16:06,197] Trial 60 finished with value: 0.4307908163359146 and parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3559488733948905, 'ffn_dropout': 0.3861395738251825, 'lr': 0.000751168863602969, 'weight_decay': 0.00010773594118176444, 'batch_size': 32}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.430791 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3559488733948905, 'ffn_dropout': 0.3861395738251825, 'lr': 0.000751168863602969, 'weight_decay': 0.00010773594118176444, 'batch_size': 32} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 00:17:43,341] Trial 61 finished with value: 0.4290478870517596 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3877448319352789, 'ffn_dropout': 0.3346908705360814, 'lr': 0.0009442974322951213, 'weight_decay': 0.00031849566634718524, 'batch_size': 128}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.429048 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3877448319352789, 'ffn_dropout': 0.3346908705360814, 'lr': 0.0009442974322951213, 'weight_decay': 0.00031849566634718524, 'batch_size': 128} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-25 00:17:51,419] Trial 62 pruned. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.404255 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.38258347660620834, 'ffn_dropout': 0.3530598990297043, 'lr': 0.0004458728754533901, 'weight_decay': 0.00015289244631086648, 'batch_size': 256} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 00:22:54,968] Trial 63 finished with value: 0.43719945440904634 and parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.36834347380393107, 'ffn_dropout': 0.3630749134498788, 'lr': 0.0005949406350637634, 'weight_decay': 0.0004055462380454483, 'batch_size': 32}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.437199 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.36834347380393107, 'ffn_dropout': 0.3630749134498788, 'lr': 0.0005949406350637634, 'weight_decay': 0.0004055462380454483, 'batch_size': 32} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 00:26:33,109] Trial 64 finished with value: 0.42894352570735217 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39843045883125217, 'ffn_dropout': 0.3921934301797705, 'lr': 0.0008690301169089306, 'weight_decay': 0.0002674577079669126, 'batch_size': 32}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.428944 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39843045883125217, 'ffn_dropout': 0.3921934301797705, 'lr': 0.0008690301169089306, 'weight_decay': 0.0002674577079669126, 'batch_size': 32} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 00:27:54,291] Trial 65 finished with value: 0.4396614718917194 and parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.38998613771234125, 'ffn_dropout': 0.31990452440327, 'lr': 0.0015022244413207802, 'weight_decay': 0.0002236400224585015, 'batch_size': 128}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.439661 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.38998613771234125, 'ffn_dropout': 0.31990452440327, 'lr': 0.0015022244413207802, 'weight_decay': 0.0002236400224585015, 'batch_size': 128} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 00:33:07,113] Trial 66 finished with value: 0.4385736528144148 and parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3751956684199736, 'ffn_dropout': 0.3734565488947016, 'lr': 0.0003421432913318969, 'weight_decay': 0.00028726406341612616, 'batch_size': 32}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.438574 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3751956684199736, 'ffn_dropout': 0.3734565488947016, 'lr': 0.0003421432913318969, 'weight_decay': 0.00028726406341612616, 'batch_size': 32} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 00:34:24,884] Trial 67 finished with value: 0.42405126237063273 and parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.36155797124154165, 'ffn_dropout': 0.3428262528232195, 'lr': 0.001117845388669062, 'weight_decay': 0.00016189751698972752, 'batch_size': 256}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.424051 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.36155797124154165, 'ffn_dropout': 0.3428262528232195, 'lr': 0.001117845388669062, 'weight_decay': 0.00016189751698972752, 'batch_size': 256} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 00:39:01,279] Trial 68 finished with value: 0.4267084321409 and parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.34818254044557617, 'ffn_dropout': 0.3262210667809475, 'lr': 0.0007541450719359268, 'weight_decay': 0.0003794875498721067, 'batch_size': 32}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.426708 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.34818254044557617, 'ffn_dropout': 0.3262210667809475, 'lr': 0.0007541450719359268, 'weight_decay': 0.0003794875498721067, 'batch_size': 32} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 00:41:36,267] Trial 69 finished with value: 0.42265196869423755 and parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.382482793072264, 'ffn_dropout': 0.35735286884564027, 'lr': 0.0005245089406667109, 'weight_decay': 0.00012766736664694816, 'batch_size': 64}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.422652 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.382482793072264, 'ffn_dropout': 0.35735286884564027, 'lr': 0.0005245089406667109, 'weight_decay': 0.00012766736664694816, 'batch_size': 64} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 00:43:07,970] Trial 70 finished with value: 0.4267836244659659 and parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3992872204077113, 'ffn_dropout': 0.39973807165970543, 'lr': 0.0010759585033466622, 'weight_decay': 0.00020855677625551477, 'batch_size': 128}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.426784 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3992872204077113, 'ffn_dropout': 0.39973807165970543, 'lr': 0.0010759585033466622, 'weight_decay': 0.00020855677625551477, 'batch_size': 128} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 00:47:32,209] Trial 71 finished with value: 0.42919655192587597 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3199639342053662, 'ffn_dropout': 0.36475910895175373, 'lr': 0.00030343293316050185, 'weight_decay': 0.00010042096031798556, 'batch_size': 32}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.429197 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3199639342053662, 'ffn_dropout': 0.36475910895175373, 'lr': 0.00030343293316050185, 'weight_decay': 0.00010042096031798556, 'batch_size': 32} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 00:54:58,078] Trial 72 finished with value: 0.4301108661398494 and parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3355558625936439, 'ffn_dropout': 0.3753786516318626, 'lr': 0.0005839901064248956, 'weight_decay': 0.00013225780170645593, 'batch_size': 32}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.430111 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3355558625936439, 'ffn_dropout': 0.3753786516318626, 'lr': 0.0005839901064248956, 'weight_decay': 0.00013225780170645593, 'batch_size': 32} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 00:58:12,253] Trial 73 finished with value: 0.44631962551718174 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3364660958704192, 'ffn_dropout': 0.37233671385764067, 'lr': 0.0004342982639757243, 'weight_decay': 0.00015735128581742888, 'batch_size': 32}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.446320 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3364660958704192, 'ffn_dropout': 0.37233671385764067, 'lr': 0.0004342982639757243, 'weight_decay': 0.00015735128581742888, 'batch_size': 32} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 01:02:10,240] Trial 74 finished with value: 0.4260671456095319 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3706617504922054, 'ffn_dropout': 0.3485745035186264, 'lr': 0.0004583578021752384, 'weight_decay': 0.0001779733668309905, 'batch_size': 32}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.426067 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3706617504922054, 'ffn_dropout': 0.3485745035186264, 'lr': 0.0004583578021752384, 'weight_decay': 0.0001779733668309905, 'batch_size': 32} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 01:09:12,707] Trial 75 finished with value: 0.44081472064658134 and parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3533468804519124, 'ffn_dropout': 0.33567880862057065, 'lr': 0.0008377203285850037, 'weight_decay': 0.00028371766732843444, 'batch_size': 32}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.440815 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3533468804519124, 'ffn_dropout': 0.33567880862057065, 'lr': 0.0008377203285850037, 'weight_decay': 0.00028371766732843444, 'batch_size': 32} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 01:13:36,104] Trial 76 finished with value: 0.4165250582836412 and parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3922676680384752, 'ffn_dropout': 0.3819052769153386, 'lr': 0.0006820577877752963, 'weight_decay': 0.00021059194246007988, 'batch_size': 32}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.416525 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3922676680384752, 'ffn_dropout': 0.3819052769153386, 'lr': 0.0006820577877752963, 'weight_decay': 0.00021059194246007988, 'batch_size': 32} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 01:19:16,014] Trial 77 finished with value: 0.4287628550785925 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.36126872047838093, 'ffn_dropout': 0.3468273875688979, 'lr': 0.00038983404399227806, 'weight_decay': 0.0004850247309998202, 'batch_size': 32}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.428763 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.36126872047838093, 'ffn_dropout': 0.3468273875688979, 'lr': 0.00038983404399227806, 'weight_decay': 0.0004850247309998202, 'batch_size': 32} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 01:24:02,870] Trial 78 finished with value: 0.43032044254311047 and parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3822058294366925, 'ffn_dropout': 0.367009674921376, 'lr': 0.001427288928756966, 'weight_decay': 0.0001632956107522345, 'batch_size': 32}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.430320 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3822058294366925, 'ffn_dropout': 0.367009674921376, 'lr': 0.001427288928756966, 'weight_decay': 0.0001632956107522345, 'batch_size': 32} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-25 01:24:55,602] Trial 79 pruned. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.415940 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3700178755950696, 'ffn_dropout': 0.312542406077148, 'lr': 0.0010067278801691975, 'weight_decay': 0.00033412920115836916, 'batch_size': 32} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 01:27:54,068] Trial 80 finished with value: 0.43193302554285745 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.34211128211283887, 'ffn_dropout': 0.3029611374377256, 'lr': 0.0005111900710460897, 'weight_decay': 0.0002445264880002216, 'batch_size': 64}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.431933 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.34211128211283887, 'ffn_dropout': 0.3029611374377256, 'lr': 0.0005111900710460897, 'weight_decay': 0.0002445264880002216, 'batch_size': 64} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 01:33:24,190] Trial 81 finished with value: 0.446262458083924 and parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3572327822731239, 'ffn_dropout': 0.33310410180915645, 'lr': 0.0008386265194139737, 'weight_decay': 0.00027723940843503106, 'batch_size': 32}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.446262 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3572327822731239, 'ffn_dropout': 0.33310410180915645, 'lr': 0.0008386265194139737, 'weight_decay': 0.00027723940843503106, 'batch_size': 32} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 01:37:41,089] Trial 82 finished with value: 0.4388017394577212 and parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3767882192057152, 'ffn_dropout': 0.33222775702979673, 'lr': 0.0008300829167825953, 'weight_decay': 0.00040697573899379244, 'batch_size': 32}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.438802 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3767882192057152, 'ffn_dropout': 0.33222775702979673, 'lr': 0.0008300829167825953, 'weight_decay': 0.00040697573899379244, 'batch_size': 32} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 01:41:40,906] Trial 83 finished with value: 0.43482664525216624 and parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3925959954448734, 'ffn_dropout': 0.3406428028500527, 'lr': 0.0006468561401931767, 'weight_decay': 0.0002837773827255065, 'batch_size': 32}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.434827 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3925959954448734, 'ffn_dropout': 0.3406428028500527, 'lr': 0.0006468561401931767, 'weight_decay': 0.0002837773827255065, 'batch_size': 32} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) -[I 2025-12-25 01:42:38,546] Trial 84 pruned. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.415465 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.3645364711987154, 'ffn_dropout': 0.35490889896736644, 'lr': 0.0007542691885826817, 'weight_decay': 0.00014230870706725057, 'batch_size': 32} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 01:43:53,790] Trial 85 finished with value: 0.4355990722434991 and parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.35107244022359924, 'ffn_dropout': 0.31789415577476565, 'lr': 0.0011471425278474358, 'weight_decay': 0.0006498664288365438, 'batch_size': 128}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.435599 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.35107244022359924, 'ffn_dropout': 0.31789415577476565, 'lr': 0.0011471425278474358, 'weight_decay': 0.0006498664288365438, 'batch_size': 128} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 01:48:41,803] Trial 86 finished with value: 0.4335830263692664 and parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.38411449397164366, 'ffn_dropout': 0.3286950780698764, 'lr': 0.0005603156455331876, 'weight_decay': 0.0004632017052970361, 'batch_size': 32}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.433583 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.38411449397164366, 'ffn_dropout': 0.3286950780698764, 'lr': 0.0005603156455331876, 'weight_decay': 0.0004632017052970361, 'batch_size': 32} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 01:49:32,600] Trial 87 finished with value: 0.39531210099894903 and parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39275696948874683, 'ffn_dropout': 0.36020853567289096, 'lr': 0.00043108408976983055, 'weight_decay': 0.00019204063826109958, 'batch_size': 256}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.395312 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39275696948874683, 'ffn_dropout': 0.36020853567289096, 'lr': 0.00043108408976983055, 'weight_decay': 0.00019204063826109958, 'batch_size': 256} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 01:59:52,038] Trial 88 finished with value: 0.4394986935674306 and parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.37799759891384477, 'ffn_dropout': 0.3502811321606756, 'lr': 0.0009429925335529256, 'weight_decay': 0.0003523551911354679, 'batch_size': 32}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.439499 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.37799759891384477, 'ffn_dropout': 0.3502811321606756, 'lr': 0.0009429925335529256, 'weight_decay': 0.0003523551911354679, 'batch_size': 32} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 02:04:00,021] Trial 89 finished with value: 0.4306130158301151 and parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3705325610746285, 'ffn_dropout': 0.36803538140974196, 'lr': 0.0015121083690838595, 'weight_decay': 0.00011475474838184393, 'batch_size': 32}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.430613 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3705325610746285, 'ffn_dropout': 0.36803538140974196, 'lr': 0.0015121083690838595, 'weight_decay': 0.00011475474838184393, 'batch_size': 32} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 02:09:31,723] Trial 90 finished with value: 0.43618579699871374 and parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.35724878574310176, 'ffn_dropout': 0.37953460706960507, 'lr': 0.0003488531163924191, 'weight_decay': 0.00017186060067949215, 'batch_size': 32}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.436186 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.35724878574310176, 'ffn_dropout': 0.37953460706960507, 'lr': 0.0003488531163924191, 'weight_decay': 0.00017186060067949215, 'batch_size': 32} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 02:12:45,955] Trial 91 finished with value: 0.43486180206245173 and parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.35451256767510825, 'ffn_dropout': 0.33764367062974227, 'lr': 0.0007746486343784267, 'weight_decay': 0.0002509501228082196, 'batch_size': 32}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.434862 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.35451256767510825, 'ffn_dropout': 0.33764367062974227, 'lr': 0.0007746486343784267, 'weight_decay': 0.0002509501228082196, 'batch_size': 32} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 02:17:31,234] Trial 92 finished with value: 0.43295322317056545 and parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.34401605552553316, 'ffn_dropout': 0.33107880281058955, 'lr': 0.0008894306510504784, 'weight_decay': 0.0002762042621261719, 'batch_size': 32}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.432953 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.34401605552553316, 'ffn_dropout': 0.33107880281058955, 'lr': 0.0008894306510504784, 'weight_decay': 0.0002762042621261719, 'batch_size': 32} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 02:22:33,903] Trial 93 finished with value: 0.4331601255852222 and parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.32814689951074305, 'ffn_dropout': 0.3448050408690674, 'lr': 0.0012095312281879631, 'weight_decay': 0.0002138566067464312, 'batch_size': 32}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.433160 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.32814689951074305, 'ffn_dropout': 0.3448050408690674, 'lr': 0.0012095312281879631, 'weight_decay': 0.0002138566067464312, 'batch_size': 32} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 02:26:22,665] Trial 94 finished with value: 0.42803304866761466 and parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.38557146325237407, 'ffn_dropout': 0.38998743389958107, 'lr': 0.0006244383653863572, 'weight_decay': 0.0003077647157624163, 'batch_size': 32}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.428033 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.38557146325237407, 'ffn_dropout': 0.38998743389958107, 'lr': 0.0006244383653863572, 'weight_decay': 0.0003077647157624163, 'batch_size': 32} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 02:30:45,396] Trial 95 finished with value: 0.44634441792462404 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3623541531367033, 'ffn_dropout': 0.3623825849364181, 'lr': 0.0004833980589009521, 'weight_decay': 0.00013917892497235964, 'batch_size': 32}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.446344 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3623541531367033, 'ffn_dropout': 0.3623825849364181, 'lr': 0.0004833980589009521, 'weight_decay': 0.00013917892497235964, 'batch_size': 32} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 02:32:25,309] Trial 96 finished with value: 0.4099479937938628 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3646543239219856, 'ffn_dropout': 0.36147404951680756, 'lr': 0.0004888612651132257, 'weight_decay': 0.00015243389148785055, 'batch_size': 128}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.409948 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3646543239219856, 'ffn_dropout': 0.36147404951680756, 'lr': 0.0004888612651132257, 'weight_decay': 0.00015243389148785055, 'batch_size': 128} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 02:35:31,013] Trial 97 finished with value: 0.43205084088421675 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.37472331976689366, 'ffn_dropout': 0.37873219896893184, 'lr': 0.0006755619559884673, 'weight_decay': 0.0001350922422535954, 'batch_size': 32}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.432051 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.37472331976689366, 'ffn_dropout': 0.37873219896893184, 'lr': 0.0006755619559884673, 'weight_decay': 0.0001350922422535954, 'batch_size': 32} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 02:40:10,545] Trial 98 finished with value: 0.4257135157049438 and parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39304237579389734, 'ffn_dropout': 0.35258984485978945, 'lr': 0.0003921972403898015, 'weight_decay': 0.00011114115329892082, 'batch_size': 32}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.425714 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39304237579389734, 'ffn_dropout': 0.35258984485978945, 'lr': 0.0003921972403898015, 'weight_decay': 0.00011114115329892082, 'batch_size': 32} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3134117647058823, 1: 1.3134117647058823, 2: 0.6769342711617754} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 1.3120392156862746, 1: 1.3120392156862746, 2: 0.677665026027425} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 1.3113333333333332, 1: 1.3113333333333332, 2: 0.6780420544639779} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16439}) -[I 2025-12-25 02:43:34,019] Trial 99 finished with value: 0.4315499725816589 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3997372444985806, 'ffn_dropout': 0.36984318582343284, 'lr': 0.0005401130027958582, 'weight_decay': 0.00012340281324564283, 'batch_size': 32}. Best is trial 52 with value: 0.4524714686603366. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.431550 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3997372444985806, 'ffn_dropout': 0.36984318582343284, 'lr': 0.0005401130027958582, 'weight_decay': 0.00012340281324564283, 'batch_size': 32} - Best Value (CSI): 0.452471 - Best Trial: 52 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.4525 -Best Hyperparameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.39058519125437824, 'ffn_dropout': 0.35781462874340314, 'lr': 0.0006705029713893173, 'weight_decay': 0.0001426209011329072, 'batch_size': 32} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.4197 - - 최종 CSI: 0.4315 - - 최고 CSI: 0.4525 - - 최저 CSI: 0.0047 - - 평균 CSI: 0.3893 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/ft_transformer_smote_busan_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 19, Best CSI: 0.4447 - Fold 1 학습 완료 (검증 CSI: 0.4447) -Fold 2 학습 중... - Early stopping at epoch 28, Best CSI: 0.4485 - Fold 2 학습 완료 (검증 CSI: 0.4485) -Fold 3 학습 중... - Early stopping at epoch 22, Best CSI: 0.4237 - Fold 3 학습 완료 (검증 CSI: 0.4237) - -모든 모델 저장 완료: ../save_model/ft_transformer_optima/ft_transformer_smote_busan.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/ft_transformer_optima/scaler/ft_transformer_smote_busan_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: ../save_model/ft_transformer_optima/ft_transformer_smote_busan.pkl - -✓ 완료: ft_transformer_smote/ft_transformer_smote_busan.py (소요 시간: 20477초) - ----------------------------------------- -실행 중: ft_transformer_smote/ft_transformer_smote_daegu.py -시작 시간: 2025-12-25 02:47:11 ----------------------------------------- -[I 2025-12-25 02:47:12,966] A new study created in memory with name: no-name-697d59a3-2643-4866-a067-fdbcb247ebdd - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 02:49:06,449] Trial 0 finished with value: 0.2812067766028447 and parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1879831726709214, 'ffn_dropout': 0.2860744078624963, 'lr': 1.9254223590463017e-05, 'weight_decay': 0.01569864682368352, 'batch_size': 128}. Best is trial 0 with value: 0.2812067766028447. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.281207 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1879831726709214, 'ffn_dropout': 0.2860744078624963, 'lr': 1.9254223590463017e-05, 'weight_decay': 0.01569864682368352, 'batch_size': 128} - Best Value (CSI): 0.281207 - Best Trial: 0 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1879831726709214, 'ffn_dropout': 0.2860744078624963, 'lr': 1.9254223590463017e-05, 'weight_decay': 0.01569864682368352, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 02:52:54,308] Trial 1 finished with value: 0.37702086444160926 and parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.14076657318485314, 'ffn_dropout': 0.13510676381958134, 'lr': 0.000270809492698125, 'weight_decay': 0.003265134345064216, 'batch_size': 64}. Best is trial 1 with value: 0.37702086444160926. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.377021 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.14076657318485314, 'ffn_dropout': 0.13510676381958134, 'lr': 0.000270809492698125, 'weight_decay': 0.003265134345064216, 'batch_size': 64} - Best Value (CSI): 0.377021 - Best Trial: 1 - Best Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.14076657318485314, 'ffn_dropout': 0.13510676381958134, 'lr': 0.000270809492698125, 'weight_decay': 0.003265134345064216, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 02:55:22,833] Trial 2 finished with value: 0.37989919111373327 and parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2868181616319193, 'ffn_dropout': 0.123738325647433, 'lr': 0.003843972582259738, 'weight_decay': 0.0001982128926958435, 'batch_size': 64}. Best is trial 2 with value: 0.37989919111373327. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.379899 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2868181616319193, 'ffn_dropout': 0.123738325647433, 'lr': 0.003843972582259738, 'weight_decay': 0.0001982128926958435, 'batch_size': 64} - Best Value (CSI): 0.379899 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2868181616319193, 'ffn_dropout': 0.123738325647433, 'lr': 0.003843972582259738, 'weight_decay': 0.0001982128926958435, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 02:59:50,043] Trial 3 finished with value: 0.3790986173258594 and parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.250398893314667, 'ffn_dropout': 0.31690218823362654, 'lr': 9.648754323271959e-05, 'weight_decay': 0.0005395269712289563, 'batch_size': 64}. Best is trial 2 with value: 0.37989919111373327. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.379099 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.250398893314667, 'ffn_dropout': 0.31690218823362654, 'lr': 9.648754323271959e-05, 'weight_decay': 0.0005395269712289563, 'batch_size': 64} - Best Value (CSI): 0.379899 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2868181616319193, 'ffn_dropout': 0.123738325647433, 'lr': 0.003843972582259738, 'weight_decay': 0.0001982128926958435, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 03:01:03,376] Trial 4 finished with value: 0.30959689562299336 and parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.20239440461256902, 'ffn_dropout': 0.27943333000267306, 'lr': 0.00010840211704830602, 'weight_decay': 0.005437777021607537, 'batch_size': 256}. Best is trial 2 with value: 0.37989919111373327. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.309597 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.20239440461256902, 'ffn_dropout': 0.27943333000267306, 'lr': 0.00010840211704830602, 'weight_decay': 0.005437777021607537, 'batch_size': 256} - Best Value (CSI): 0.379899 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2868181616319193, 'ffn_dropout': 0.123738325647433, 'lr': 0.003843972582259738, 'weight_decay': 0.0001982128926958435, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 03:02:47,849] Trial 5 pruned. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.297762 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.20618571621254383, 'ffn_dropout': 0.29618959005199696, 'lr': 0.0005383543565944512, 'weight_decay': 0.004147158084699937, 'batch_size': 32} - Best Value (CSI): 0.379899 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2868181616319193, 'ffn_dropout': 0.123738325647433, 'lr': 0.003843972582259738, 'weight_decay': 0.0001982128926958435, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 03:04:02,756] Trial 6 pruned. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.001594 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.35559546485150273, 'ffn_dropout': 0.24452976580267327, 'lr': 0.00399899905674066, 'weight_decay': 0.0002831509213860315, 'batch_size': 32} - Best Value (CSI): 0.379899 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2868181616319193, 'ffn_dropout': 0.123738325647433, 'lr': 0.003843972582259738, 'weight_decay': 0.0001982128926958435, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 03:05:22,619] Trial 7 pruned. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.318584 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.20557472266618607, 'ffn_dropout': 0.22724238428304752, 'lr': 0.0006107876761251589, 'weight_decay': 0.0006202092925555244, 'batch_size': 64} - Best Value (CSI): 0.379899 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2868181616319193, 'ffn_dropout': 0.123738325647433, 'lr': 0.003843972582259738, 'weight_decay': 0.0001982128926958435, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 03:11:39,085] Trial 8 finished with value: 0.3853624237748203 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.11961651106610285, 'ffn_dropout': 0.3167728848293262, 'lr': 0.00014464164267284058, 'weight_decay': 0.006051933062323265, 'batch_size': 32}. Best is trial 8 with value: 0.3853624237748203. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.385362 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.11961651106610285, 'ffn_dropout': 0.3167728848293262, 'lr': 0.00014464164267284058, 'weight_decay': 0.006051933062323265, 'batch_size': 32} - Best Value (CSI): 0.385362 - Best Trial: 8 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.11961651106610285, 'ffn_dropout': 0.3167728848293262, 'lr': 0.00014464164267284058, 'weight_decay': 0.006051933062323265, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 03:13:50,844] Trial 9 pruned. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.315425 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.143655116605296, 'ffn_dropout': 0.2604624212558915, 'lr': 8.78284036418241e-05, 'weight_decay': 0.011257047336784296, 'batch_size': 32} - Best Value (CSI): 0.385362 - Best Trial: 8 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.11961651106610285, 'ffn_dropout': 0.3167728848293262, 'lr': 0.00014464164267284058, 'weight_decay': 0.006051933062323265, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 03:14:27,773] Trial 10 pruned. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.258021 - Parameters: {'d_token': 256, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.10142120095070578, 'ffn_dropout': 0.386789925740145, 'lr': 1.3627413018965891e-05, 'weight_decay': 0.09350592471893021, 'batch_size': 256} - Best Value (CSI): 0.385362 - Best Trial: 8 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.11961651106610285, 'ffn_dropout': 0.3167728848293262, 'lr': 0.00014464164267284058, 'weight_decay': 0.006051933062323265, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 03:14:38,672] Trial 11 pruned. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.015824 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.28612155844570575, 'ffn_dropout': 0.11067192651134383, 'lr': 0.009591285518966958, 'weight_decay': 0.00012892966336286357, 'batch_size': 128} - Best Value (CSI): 0.385362 - Best Trial: 8 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.11961651106610285, 'ffn_dropout': 0.3167728848293262, 'lr': 0.00014464164267284058, 'weight_decay': 0.006051933062323265, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 03:17:59,037] Trial 12 finished with value: 0.38779208484622557 and parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3022782899185378, 'ffn_dropout': 0.16486562467289673, 'lr': 0.001714286873751556, 'weight_decay': 0.0011673512318092114, 'batch_size': 64}. Best is trial 12 with value: 0.38779208484622557. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.387792 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3022782899185378, 'ffn_dropout': 0.16486562467289673, 'lr': 0.001714286873751556, 'weight_decay': 0.0011673512318092114, 'batch_size': 64} - Best Value (CSI): 0.387792 - Best Trial: 12 - Best Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3022782899185378, 'ffn_dropout': 0.16486562467289673, 'lr': 0.001714286873751556, 'weight_decay': 0.0011673512318092114, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 03:23:39,655] Trial 13 finished with value: 0.3791441955050125 and parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.38667801313530215, 'ffn_dropout': 0.18899965844443198, 'lr': 0.0009723706713066178, 'weight_decay': 0.0013168731659000197, 'batch_size': 32}. Best is trial 12 with value: 0.38779208484622557. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.379144 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.38667801313530215, 'ffn_dropout': 0.18899965844443198, 'lr': 0.0009723706713066178, 'weight_decay': 0.0013168731659000197, 'batch_size': 32} - Best Value (CSI): 0.387792 - Best Trial: 12 - Best Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3022782899185378, 'ffn_dropout': 0.16486562467289673, 'lr': 0.001714286873751556, 'weight_decay': 0.0011673512318092114, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 03:24:14,001] Trial 14 pruned. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.001594 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3213782631761972, 'ffn_dropout': 0.17786403500836126, 'lr': 0.0016338945803592564, 'weight_decay': 0.0013273659076852098, 'batch_size': 64} - Best Value (CSI): 0.387792 - Best Trial: 12 - Best Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3022782899185378, 'ffn_dropout': 0.16486562467289673, 'lr': 0.001714286873751556, 'weight_decay': 0.0011673512318092114, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 03:25:50,722] Trial 15 pruned. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.307002 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2709599703680377, 'ffn_dropout': 0.3342502098121999, 'lr': 0.000330006801959337, 'weight_decay': 0.0014322398872397008, 'batch_size': 32} - Best Value (CSI): 0.387792 - Best Trial: 12 - Best Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3022782899185378, 'ffn_dropout': 0.16486562467289673, 'lr': 0.001714286873751556, 'weight_decay': 0.0011673512318092114, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 03:26:27,642] Trial 16 pruned. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.301613 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.32069275139897707, 'ffn_dropout': 0.20610022721203453, 'lr': 0.0015835049823439565, 'weight_decay': 0.009177823993563549, 'batch_size': 256} - Best Value (CSI): 0.387792 - Best Trial: 12 - Best Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3022782899185378, 'ffn_dropout': 0.16486562467289673, 'lr': 0.001714286873751556, 'weight_decay': 0.0011673512318092114, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 03:26:40,355] Trial 17 pruned. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.186730 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.23363970715470467, 'ffn_dropout': 0.1790029010744846, 'lr': 0.0002547145708382806, 'weight_decay': 0.0020636968866453802, 'batch_size': 128} - Best Value (CSI): 0.387792 - Best Trial: 12 - Best Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3022782899185378, 'ffn_dropout': 0.16486562467289673, 'lr': 0.001714286873751556, 'weight_decay': 0.0011673512318092114, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 03:28:01,381] Trial 18 pruned. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.240491 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2508720361796684, 'ffn_dropout': 0.3537434239536059, 'lr': 3.863320622710195e-05, 'weight_decay': 0.000516781530084733, 'batch_size': 32} - Best Value (CSI): 0.387792 - Best Trial: 12 - Best Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3022782899185378, 'ffn_dropout': 0.16486562467289673, 'lr': 0.001714286873751556, 'weight_decay': 0.0011673512318092114, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 03:29:06,353] Trial 19 pruned. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.287462 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.10274953142067977, 'ffn_dropout': 0.1441748120294991, 'lr': 0.00015036316608268052, 'weight_decay': 0.0189862088020303, 'batch_size': 64} - Best Value (CSI): 0.387792 - Best Trial: 12 - Best Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3022782899185378, 'ffn_dropout': 0.16486562467289673, 'lr': 0.001714286873751556, 'weight_decay': 0.0011673512318092114, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 03:29:31,191] Trial 20 pruned. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.222965 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.174731418405138, 'ffn_dropout': 0.221898737726037, 'lr': 5.744493731378139e-05, 'weight_decay': 0.002365042258330668, 'batch_size': 64} - Best Value (CSI): 0.387792 - Best Trial: 12 - Best Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3022782899185378, 'ffn_dropout': 0.16486562467289673, 'lr': 0.001714286873751556, 'weight_decay': 0.0011673512318092114, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 03:30:03,897] Trial 21 pruned. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.278992 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.29476701165062846, 'ffn_dropout': 0.1160265612140759, 'lr': 0.003040220519393638, 'weight_decay': 0.00023906500210906157, 'batch_size': 64} - Best Value (CSI): 0.387792 - Best Trial: 12 - Best Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3022782899185378, 'ffn_dropout': 0.16486562467289673, 'lr': 0.001714286873751556, 'weight_decay': 0.0011673512318092114, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 03:30:21,854] Trial 22 pruned. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.017632 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3026282027715034, 'ffn_dropout': 0.15258483239656603, 'lr': 0.008791382650413758, 'weight_decay': 0.00012511951638805607, 'batch_size': 64} - Best Value (CSI): 0.387792 - Best Trial: 12 - Best Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3022782899185378, 'ffn_dropout': 0.16486562467289673, 'lr': 0.001714286873751556, 'weight_decay': 0.0011673512318092114, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 03:30:47,966] Trial 23 pruned. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.001594 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2297598960535283, 'ffn_dropout': 0.10424510869646186, 'lr': 0.0044953162736430805, 'weight_decay': 0.0009282890194624731, 'batch_size': 64} - Best Value (CSI): 0.387792 - Best Trial: 12 - Best Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3022782899185378, 'ffn_dropout': 0.16486562467289673, 'lr': 0.001714286873751556, 'weight_decay': 0.0011673512318092114, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 03:31:29,256] Trial 24 pruned. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.289062 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2698916090217714, 'ffn_dropout': 0.1612768468066842, 'lr': 0.001685711760314237, 'weight_decay': 0.00023186856743877827, 'batch_size': 64} - Best Value (CSI): 0.387792 - Best Trial: 12 - Best Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3022782899185378, 'ffn_dropout': 0.16486562467289673, 'lr': 0.001714286873751556, 'weight_decay': 0.0011673512318092114, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 03:33:35,766] Trial 25 pruned. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.289600 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.3396227994644088, 'ffn_dropout': 0.1285840816947155, 'lr': 0.0009461724187748454, 'weight_decay': 0.00010472055537077704, 'batch_size': 32} - Best Value (CSI): 0.387792 - Best Trial: 12 - Best Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3022782899185378, 'ffn_dropout': 0.16486562467289673, 'lr': 0.001714286873751556, 'weight_decay': 0.0011673512318092114, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 03:33:55,846] Trial 26 pruned. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.288889 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.27642990217872654, 'ffn_dropout': 0.100239928582399, 'lr': 0.0029050101386477933, 'weight_decay': 0.0008092065283248381, 'batch_size': 256} - Best Value (CSI): 0.387792 - Best Trial: 12 - Best Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3022782899185378, 'ffn_dropout': 0.16486562467289673, 'lr': 0.001714286873751556, 'weight_decay': 0.0011673512318092114, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 03:34:08,038] Trial 27 pruned. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.005441 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3087913470846128, 'ffn_dropout': 0.15859861423186664, 'lr': 0.006917236285483397, 'weight_decay': 0.00040324644250083725, 'batch_size': 128} - Best Value (CSI): 0.387792 - Best Trial: 12 - Best Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3022782899185378, 'ffn_dropout': 0.16486562467289673, 'lr': 0.001714286873751556, 'weight_decay': 0.0011673512318092114, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 03:37:08,887] Trial 28 finished with value: 0.3812085296361016 and parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2612576392987448, 'ffn_dropout': 0.20323343231200774, 'lr': 0.0023047748733702237, 'weight_decay': 0.00033590648444216023, 'batch_size': 64}. Best is trial 12 with value: 0.38779208484622557. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.381209 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2612576392987448, 'ffn_dropout': 0.20323343231200774, 'lr': 0.0023047748733702237, 'weight_decay': 0.00033590648444216023, 'batch_size': 64} - Best Value (CSI): 0.387792 - Best Trial: 12 - Best Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3022782899185378, 'ffn_dropout': 0.16486562467289673, 'lr': 0.001714286873751556, 'weight_decay': 0.0011673512318092114, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 03:37:22,390] Trial 29 pruned. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.080792 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.22864103413022271, 'ffn_dropout': 0.1988523488313971, 'lr': 3.57922083392259e-05, 'weight_decay': 0.0003442807242219826, 'batch_size': 128} - Best Value (CSI): 0.387792 - Best Trial: 12 - Best Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3022782899185378, 'ffn_dropout': 0.16486562467289673, 'lr': 0.001714286873751556, 'weight_decay': 0.0011673512318092114, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 03:39:15,217] Trial 30 pruned. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.304700 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2553435076333425, 'ffn_dropout': 0.252279805370846, 'lr': 0.00016521791582858953, 'weight_decay': 0.0008405855221256496, 'batch_size': 32} - Best Value (CSI): 0.387792 - Best Trial: 12 - Best Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3022782899185378, 'ffn_dropout': 0.16486562467289673, 'lr': 0.001714286873751556, 'weight_decay': 0.0011673512318092114, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 03:39:40,850] Trial 31 pruned. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.003920 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2850427481228138, 'ffn_dropout': 0.16945568474325062, 'lr': 0.005463099497036865, 'weight_decay': 0.00017989983481850018, 'batch_size': 64} - Best Value (CSI): 0.387792 - Best Trial: 12 - Best Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3022782899185378, 'ffn_dropout': 0.16486562467289673, 'lr': 0.001714286873751556, 'weight_decay': 0.0011673512318092114, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 03:40:28,246] Trial 32 pruned. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.302876 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.26461508746978324, 'ffn_dropout': 0.14450546424193253, 'lr': 0.0024387523803484344, 'weight_decay': 0.0003627787223626409, 'batch_size': 64} - Best Value (CSI): 0.387792 - Best Trial: 12 - Best Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3022782899185378, 'ffn_dropout': 0.16486562467289673, 'lr': 0.001714286873751556, 'weight_decay': 0.0011673512318092114, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 03:41:07,988] Trial 33 pruned. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.001594 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.29154542024055324, 'ffn_dropout': 0.1255779795654879, 'lr': 0.005556203074498462, 'weight_decay': 0.00016252197222932447, 'batch_size': 64} - Best Value (CSI): 0.387792 - Best Trial: 12 - Best Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3022782899185378, 'ffn_dropout': 0.16486562467289673, 'lr': 0.001714286873751556, 'weight_decay': 0.0011673512318092114, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 03:44:10,618] Trial 34 finished with value: 0.39505004744774913 and parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24340203452901607, 'ffn_dropout': 0.13354137712882302, 'lr': 0.0022377110711388755, 'weight_decay': 0.00046867064985372874, 'batch_size': 64}. Best is trial 34 with value: 0.39505004744774913. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.395050 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24340203452901607, 'ffn_dropout': 0.13354137712882302, 'lr': 0.0022377110711388755, 'weight_decay': 0.00046867064985372874, 'batch_size': 64} - Best Value (CSI): 0.395050 - Best Trial: 34 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24340203452901607, 'ffn_dropout': 0.13354137712882302, 'lr': 0.0022377110711388755, 'weight_decay': 0.00046867064985372874, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 03:44:52,693] Trial 35 pruned. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.256868 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.18022263629103918, 'ffn_dropout': 0.13791348837672157, 'lr': 0.0020789264561401413, 'weight_decay': 0.00047083689828901503, 'batch_size': 64} - Best Value (CSI): 0.395050 - Best Trial: 34 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24340203452901607, 'ffn_dropout': 0.13354137712882302, 'lr': 0.0022377110711388755, 'weight_decay': 0.00046867064985372874, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 03:45:16,826] Trial 36 pruned. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.001617 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.15964500314651298, 'ffn_dropout': 0.20612374099955183, 'lr': 0.003347337969292242, 'weight_decay': 0.0007185566749494165, 'batch_size': 64} - Best Value (CSI): 0.395050 - Best Trial: 34 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24340203452901607, 'ffn_dropout': 0.13354137712882302, 'lr': 0.0022377110711388755, 'weight_decay': 0.00046867064985372874, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 03:46:07,217] Trial 37 pruned. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.305603 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.12388442338042327, 'ffn_dropout': 0.1857205022954614, 'lr': 0.0011843446559142614, 'weight_decay': 0.0003233328988403014, 'batch_size': 64} - Best Value (CSI): 0.395050 - Best Trial: 34 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24340203452901607, 'ffn_dropout': 0.13354137712882302, 'lr': 0.0022377110711388755, 'weight_decay': 0.00046867064985372874, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 03:46:24,575] Trial 38 pruned. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.265278 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2175669883474332, 'ffn_dropout': 0.16550074809654586, 'lr': 0.0007431545086022852, 'weight_decay': 0.0005419792616517631, 'batch_size': 256} - Best Value (CSI): 0.395050 - Best Trial: 34 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24340203452901607, 'ffn_dropout': 0.13354137712882302, 'lr': 0.0022377110711388755, 'weight_decay': 0.00046867064985372874, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 03:52:23,300] Trial 39 finished with value: 0.38514312369495407 and parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.1998989178679907, 'ffn_dropout': 0.2814513682173936, 'lr': 0.00036401523317541423, 'weight_decay': 0.004196418839635773, 'batch_size': 32}. Best is trial 34 with value: 0.39505004744774913. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.385143 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.1998989178679907, 'ffn_dropout': 0.2814513682173936, 'lr': 0.00036401523317541423, 'weight_decay': 0.004196418839635773, 'batch_size': 32} - Best Value (CSI): 0.395050 - Best Trial: 34 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24340203452901607, 'ffn_dropout': 0.13354137712882302, 'lr': 0.0022377110711388755, 'weight_decay': 0.00046867064985372874, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 03:58:33,717] Trial 40 finished with value: 0.38523361238305 and parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.19478641730771995, 'ffn_dropout': 0.2886101184760076, 'lr': 0.0004239627239655387, 'weight_decay': 0.00455783942537374, 'batch_size': 32}. Best is trial 34 with value: 0.39505004744774913. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.385234 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.19478641730771995, 'ffn_dropout': 0.2886101184760076, 'lr': 0.0004239627239655387, 'weight_decay': 0.00455783942537374, 'batch_size': 32} - Best Value (CSI): 0.395050 - Best Trial: 34 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24340203452901607, 'ffn_dropout': 0.13354137712882302, 'lr': 0.0022377110711388755, 'weight_decay': 0.00046867064985372874, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 04:00:17,235] Trial 41 pruned. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.278116 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.19524138635338936, 'ffn_dropout': 0.2818783140963953, 'lr': 0.00045674608897684164, 'weight_decay': 0.004116046317573246, 'batch_size': 32} - Best Value (CSI): 0.395050 - Best Trial: 34 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24340203452901607, 'ffn_dropout': 0.13354137712882302, 'lr': 0.0022377110711388755, 'weight_decay': 0.00046867064985372874, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 04:02:47,728] Trial 42 pruned. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.320856 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.18588384518312812, 'ffn_dropout': 0.2990433441365329, 'lr': 0.00040982073456723893, 'weight_decay': 0.0029775199923843063, 'batch_size': 32} - Best Value (CSI): 0.395050 - Best Trial: 34 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24340203452901607, 'ffn_dropout': 0.13354137712882302, 'lr': 0.0022377110711388755, 'weight_decay': 0.00046867064985372874, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 04:03:57,648] Trial 43 pruned. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.001594 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.20315458483035104, 'ffn_dropout': 0.26344662472398717, 'lr': 0.0006684573506004782, 'weight_decay': 0.0048854155676408976, 'batch_size': 32} - Best Value (CSI): 0.395050 - Best Trial: 34 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24340203452901607, 'ffn_dropout': 0.13354137712882302, 'lr': 0.0022377110711388755, 'weight_decay': 0.00046867064985372874, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 04:11:41,255] Trial 44 finished with value: 0.3784773132750196 and parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.23891534291242386, 'ffn_dropout': 0.2965023193976481, 'lr': 0.00022278269858875426, 'weight_decay': 0.005422816664087459, 'batch_size': 32}. Best is trial 34 with value: 0.39505004744774913. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.378477 - Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.23891534291242386, 'ffn_dropout': 0.2965023193976481, 'lr': 0.00022278269858875426, 'weight_decay': 0.005422816664087459, 'batch_size': 32} - Best Value (CSI): 0.395050 - Best Trial: 34 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24340203452901607, 'ffn_dropout': 0.13354137712882302, 'lr': 0.0022377110711388755, 'weight_decay': 0.00046867064985372874, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 04:14:01,740] Trial 45 pruned. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.294320 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.21844842536274345, 'ffn_dropout': 0.31624309398862216, 'lr': 0.00032549979137332937, 'weight_decay': 0.007463106490809942, 'batch_size': 32} - Best Value (CSI): 0.395050 - Best Trial: 34 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24340203452901607, 'ffn_dropout': 0.13354137712882302, 'lr': 0.0022377110711388755, 'weight_decay': 0.00046867064985372874, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 04:15:28,912] Trial 46 pruned. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.001594 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.17216878433488741, 'ffn_dropout': 0.2633546664367143, 'lr': 0.0005501064763861383, 'weight_decay': 0.0032444662345977988, 'batch_size': 32} - Best Value (CSI): 0.395050 - Best Trial: 34 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24340203452901607, 'ffn_dropout': 0.13354137712882302, 'lr': 0.0022377110711388755, 'weight_decay': 0.00046867064985372874, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 04:20:44,269] Trial 47 finished with value: 0.3525943421701017 and parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.1590383416323308, 'ffn_dropout': 0.24087732907427584, 'lr': 0.00040952538694169293, 'weight_decay': 0.001987044398650424, 'batch_size': 32}. Best is trial 34 with value: 0.39505004744774913. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.352594 - Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.1590383416323308, 'ffn_dropout': 0.24087732907427584, 'lr': 0.00040952538694169293, 'weight_decay': 0.001987044398650424, 'batch_size': 32} - Best Value (CSI): 0.395050 - Best Trial: 34 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24340203452901607, 'ffn_dropout': 0.13354137712882302, 'lr': 0.0022377110711388755, 'weight_decay': 0.00046867064985372874, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 04:21:53,906] Trial 48 pruned. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.001594 - Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.19664900528026683, 'ffn_dropout': 0.2884775114458888, 'lr': 0.0012037493345826837, 'weight_decay': 0.007235995354656053, 'batch_size': 32} - Best Value (CSI): 0.395050 - Best Trial: 34 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24340203452901607, 'ffn_dropout': 0.13354137712882302, 'lr': 0.0022377110711388755, 'weight_decay': 0.00046867064985372874, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 04:23:54,763] Trial 49 pruned. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.322993 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.14358403762421593, 'ffn_dropout': 0.2687315188513908, 'lr': 0.000216289333194313, 'weight_decay': 0.013683808505908005, 'batch_size': 32} - Best Value (CSI): 0.395050 - Best Trial: 34 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24340203452901607, 'ffn_dropout': 0.13354137712882302, 'lr': 0.0022377110711388755, 'weight_decay': 0.00046867064985372874, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 04:24:43,309] Trial 50 pruned. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.298429 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2509485470097197, 'ffn_dropout': 0.3076031922664093, 'lr': 0.000782889150219472, 'weight_decay': 0.001417964288812357, 'batch_size': 128} - Best Value (CSI): 0.395050 - Best Trial: 34 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24340203452901607, 'ffn_dropout': 0.13354137712882302, 'lr': 0.0022377110711388755, 'weight_decay': 0.00046867064985372874, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 04:25:13,210] Trial 51 pruned. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.006059 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.24065490904720305, 'ffn_dropout': 0.27755955320828696, 'lr': 0.002103517798027969, 'weight_decay': 0.0010570007223208763, 'batch_size': 64} - Best Value (CSI): 0.395050 - Best Trial: 34 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24340203452901607, 'ffn_dropout': 0.13354137712882302, 'lr': 0.0022377110711388755, 'weight_decay': 0.00046867064985372874, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 04:25:24,489] Trial 52 pruned. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.242767 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2166896438324357, 'ffn_dropout': 0.3309245069096152, 'lr': 0.00030128311159843303, 'weight_decay': 0.0006580428326011249, 'batch_size': 256} - Best Value (CSI): 0.395050 - Best Trial: 34 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24340203452901607, 'ffn_dropout': 0.13354137712882302, 'lr': 0.0022377110711388755, 'weight_decay': 0.00046867064985372874, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 04:25:52,225] Trial 53 pruned. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.001594 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2584903235895161, 'ffn_dropout': 0.23359906849651788, 'lr': 0.0013111209884364428, 'weight_decay': 0.004159836978184238, 'batch_size': 64} - Best Value (CSI): 0.395050 - Best Trial: 34 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24340203452901607, 'ffn_dropout': 0.13354137712882302, 'lr': 0.0022377110711388755, 'weight_decay': 0.00046867064985372874, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 04:26:38,496] Trial 54 pruned. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.001594 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2429029318331303, 'ffn_dropout': 0.2520403326024167, 'lr': 0.0038054080299961784, 'weight_decay': 0.0024623762877685473, 'batch_size': 32} - Best Value (CSI): 0.395050 - Best Trial: 34 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24340203452901607, 'ffn_dropout': 0.13354137712882302, 'lr': 0.0022377110711388755, 'weight_decay': 0.00046867064985372874, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 04:28:52,943] Trial 55 finished with value: 0.3623525229192282 and parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.21096429745513628, 'ffn_dropout': 0.22040451247101603, 'lr': 0.00011851983807545293, 'weight_decay': 0.001761561939776351, 'batch_size': 64}. Best is trial 34 with value: 0.39505004744774913. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.362353 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.21096429745513628, 'ffn_dropout': 0.22040451247101603, 'lr': 0.00011851983807545293, 'weight_decay': 0.001761561939776351, 'batch_size': 64} - Best Value (CSI): 0.395050 - Best Trial: 34 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24340203452901607, 'ffn_dropout': 0.13354137712882302, 'lr': 0.0022377110711388755, 'weight_decay': 0.00046867064985372874, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 04:30:24,747] Trial 56 pruned. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.299145 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1903842396454483, 'ffn_dropout': 0.2750995406532721, 'lr': 0.0008963884662593914, 'weight_decay': 0.0011324366473625003, 'batch_size': 32} - Best Value (CSI): 0.395050 - Best Trial: 34 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24340203452901607, 'ffn_dropout': 0.13354137712882302, 'lr': 0.0022377110711388755, 'weight_decay': 0.00046867064985372874, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 04:31:30,746] Trial 57 pruned. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.296236 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.27433128762520187, 'ffn_dropout': 0.14987774492373251, 'lr': 0.0005788485889725044, 'weight_decay': 0.0028367070199076085, 'batch_size': 64} - Best Value (CSI): 0.395050 - Best Trial: 34 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24340203452901607, 'ffn_dropout': 0.13354137712882302, 'lr': 0.0022377110711388755, 'weight_decay': 0.00046867064985372874, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 04:32:21,633] Trial 58 pruned. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.003283 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2277938694650306, 'ffn_dropout': 0.13482350470095136, 'lr': 0.0016073838243543298, 'weight_decay': 0.0005713198616016543, 'batch_size': 32} - Best Value (CSI): 0.395050 - Best Trial: 34 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24340203452901607, 'ffn_dropout': 0.13354137712882302, 'lr': 0.0022377110711388755, 'weight_decay': 0.00046867064985372874, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 04:33:27,551] Trial 59 pruned. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.308378 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.12097657349799473, 'ffn_dropout': 0.1152170187390747, 'lr': 0.001104624530890027, 'weight_decay': 0.000276794711378692, 'batch_size': 64} - Best Value (CSI): 0.395050 - Best Trial: 34 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24340203452901607, 'ffn_dropout': 0.13354137712882302, 'lr': 0.0022377110711388755, 'weight_decay': 0.00046867064985372874, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 04:35:19,153] Trial 60 finished with value: 0.36733248772078236 and parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.261770351310711, 'ffn_dropout': 0.2885360875483319, 'lr': 0.002070889843176905, 'weight_decay': 0.0018667347692247816, 'batch_size': 128}. Best is trial 34 with value: 0.39505004744774913. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.367332 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.261770351310711, 'ffn_dropout': 0.2885360875483319, 'lr': 0.002070889843176905, 'weight_decay': 0.0018667347692247816, 'batch_size': 128} - Best Value (CSI): 0.395050 - Best Trial: 34 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24340203452901607, 'ffn_dropout': 0.13354137712882302, 'lr': 0.0022377110711388755, 'weight_decay': 0.00046867064985372874, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 04:35:38,982] Trial 61 pruned. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.256275 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2843578099241539, 'ffn_dropout': 0.1269758191902234, 'lr': 0.00407806018994813, 'weight_decay': 0.00046020001703229617, 'batch_size': 64} - Best Value (CSI): 0.395050 - Best Trial: 34 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24340203452901607, 'ffn_dropout': 0.13354137712882302, 'lr': 0.0022377110711388755, 'weight_decay': 0.00046867064985372874, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 04:37:40,917] Trial 62 finished with value: 0.3965786227459637 and parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3052862966097679, 'ffn_dropout': 0.15467102369761743, 'lr': 0.0034927702704919835, 'weight_decay': 0.00021589622481913361, 'batch_size': 64}. Best is trial 62 with value: 0.3965786227459637. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.396579 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3052862966097679, 'ffn_dropout': 0.15467102369761743, 'lr': 0.0034927702704919835, 'weight_decay': 0.00021589622481913361, 'batch_size': 64} - Best Value (CSI): 0.396579 - Best Trial: 62 - Best Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3052862966097679, 'ffn_dropout': 0.15467102369761743, 'lr': 0.0034927702704919835, 'weight_decay': 0.00021589622481913361, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 04:38:13,870] Trial 63 pruned. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.271676 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3130804253398747, 'ffn_dropout': 0.17238112050843893, 'lr': 0.0031587120526263544, 'weight_decay': 0.0002375636630134161, 'batch_size': 64} - Best Value (CSI): 0.396579 - Best Trial: 62 - Best Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3052862966097679, 'ffn_dropout': 0.15467102369761743, 'lr': 0.0034927702704919835, 'weight_decay': 0.00021589622481913361, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 04:38:41,934] Trial 64 pruned. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.276596 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3000819558789799, 'ffn_dropout': 0.15381251128032616, 'lr': 0.0025869108636711684, 'weight_decay': 0.00017031630145488197, 'batch_size': 64} - Best Value (CSI): 0.396579 - Best Trial: 62 - Best Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3052862966097679, 'ffn_dropout': 0.15467102369761743, 'lr': 0.0034927702704919835, 'weight_decay': 0.00021589622481913361, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 04:41:25,321] Trial 65 finished with value: 0.3854612673290987 and parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24857102439984788, 'ffn_dropout': 0.18064151565210088, 'lr': 0.0014098895490284153, 'weight_decay': 0.000294620683275061, 'batch_size': 64}. Best is trial 62 with value: 0.3965786227459637. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.385461 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24857102439984788, 'ffn_dropout': 0.18064151565210088, 'lr': 0.0014098895490284153, 'weight_decay': 0.000294620683275061, 'batch_size': 64} - Best Value (CSI): 0.396579 - Best Trial: 62 - Best Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3052862966097679, 'ffn_dropout': 0.15467102369761743, 'lr': 0.0034927702704919835, 'weight_decay': 0.00021589622481913361, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 04:41:39,780] Trial 66 pruned. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.275915 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.20692676715165567, 'ffn_dropout': 0.1747113795867506, 'lr': 0.0013444606550259233, 'weight_decay': 0.0004134272260885048, 'batch_size': 256} - Best Value (CSI): 0.396579 - Best Trial: 62 - Best Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3052862966097679, 'ffn_dropout': 0.15467102369761743, 'lr': 0.0034927702704919835, 'weight_decay': 0.00021589622481913361, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 04:43:40,910] Trial 67 finished with value: 0.38686982916845 and parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.25033459400341257, 'ffn_dropout': 0.18310904785351584, 'lr': 0.0009110260599488356, 'weight_decay': 0.0002534912723578786, 'batch_size': 64}. Best is trial 62 with value: 0.3965786227459637. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.386870 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.25033459400341257, 'ffn_dropout': 0.18310904785351584, 'lr': 0.0009110260599488356, 'weight_decay': 0.0002534912723578786, 'batch_size': 64} - Best Value (CSI): 0.396579 - Best Trial: 62 - Best Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3052862966097679, 'ffn_dropout': 0.15467102369761743, 'lr': 0.0034927702704919835, 'weight_decay': 0.00021589622481913361, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 04:45:56,081] Trial 68 finished with value: 0.3777725767795596 and parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.25016927953806606, 'ffn_dropout': 0.18427180761100995, 'lr': 0.0017945277905589664, 'weight_decay': 0.0002016564047907231, 'batch_size': 64}. Best is trial 62 with value: 0.3965786227459637. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.377773 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.25016927953806606, 'ffn_dropout': 0.18427180761100995, 'lr': 0.0017945277905589664, 'weight_decay': 0.0002016564047907231, 'batch_size': 64} - Best Value (CSI): 0.396579 - Best Trial: 62 - Best Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3052862966097679, 'ffn_dropout': 0.15467102369761743, 'lr': 0.0034927702704919835, 'weight_decay': 0.00021589622481913361, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 04:48:11,642] Trial 69 finished with value: 0.37728739854498566 and parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.28574613385830966, 'ffn_dropout': 0.14120561281138785, 'lr': 0.0009378648581627557, 'weight_decay': 0.00029093072988542457, 'batch_size': 64}. Best is trial 62 with value: 0.3965786227459637. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.377287 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.28574613385830966, 'ffn_dropout': 0.14120561281138785, 'lr': 0.0009378648581627557, 'weight_decay': 0.00029093072988542457, 'batch_size': 64} - Best Value (CSI): 0.396579 - Best Trial: 62 - Best Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3052862966097679, 'ffn_dropout': 0.15467102369761743, 'lr': 0.0034927702704919835, 'weight_decay': 0.00021589622481913361, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 04:48:50,451] Trial 70 pruned. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.307282 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2703008153405818, 'ffn_dropout': 0.16276005007244657, 'lr': 0.001532368622764538, 'weight_decay': 0.0006841297125681985, 'batch_size': 64} - Best Value (CSI): 0.396579 - Best Trial: 62 - Best Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3052862966097679, 'ffn_dropout': 0.15467102369761743, 'lr': 0.0034927702704919835, 'weight_decay': 0.00021589622481913361, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 04:51:07,792] Trial 71 finished with value: 0.38791606194711004 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.22747081033229655, 'ffn_dropout': 0.15559721465419232, 'lr': 0.0010204255197691127, 'weight_decay': 0.00015018217309182812, 'batch_size': 64}. Best is trial 62 with value: 0.3965786227459637. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.387916 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.22747081033229655, 'ffn_dropout': 0.15559721465419232, 'lr': 0.0010204255197691127, 'weight_decay': 0.00015018217309182812, 'batch_size': 64} - Best Value (CSI): 0.396579 - Best Trial: 62 - Best Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3052862966097679, 'ffn_dropout': 0.15467102369761743, 'lr': 0.0034927702704919835, 'weight_decay': 0.00021589622481913361, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 04:51:54,669] Trial 72 pruned. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.306368 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.24359600304251913, 'ffn_dropout': 0.15588595599475277, 'lr': 0.0007571489320242547, 'weight_decay': 0.0002042729794921658, 'batch_size': 64} - Best Value (CSI): 0.396579 - Best Trial: 62 - Best Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3052862966097679, 'ffn_dropout': 0.15467102369761743, 'lr': 0.0034927702704919835, 'weight_decay': 0.00021589622481913361, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 04:53:59,522] Trial 73 finished with value: 0.38788136561448655 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.23264037016584585, 'ffn_dropout': 0.1664600247677824, 'lr': 0.0011128656802975106, 'weight_decay': 0.00014244501768653672, 'batch_size': 64}. Best is trial 62 with value: 0.3965786227459637. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.387881 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.23264037016584585, 'ffn_dropout': 0.1664600247677824, 'lr': 0.0011128656802975106, 'weight_decay': 0.00014244501768653672, 'batch_size': 64} - Best Value (CSI): 0.396579 - Best Trial: 62 - Best Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3052862966097679, 'ffn_dropout': 0.15467102369761743, 'lr': 0.0034927702704919835, 'weight_decay': 0.00021589622481913361, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 04:54:26,000] Trial 74 pruned. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.001594 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.232458715722362, 'ffn_dropout': 0.1640430999056214, 'lr': 0.002667738908202744, 'weight_decay': 0.0001436874152715882, 'batch_size': 64} - Best Value (CSI): 0.396579 - Best Trial: 62 - Best Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3052862966097679, 'ffn_dropout': 0.15467102369761743, 'lr': 0.0034927702704919835, 'weight_decay': 0.00021589622481913361, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 04:57:33,216] Trial 75 finished with value: 0.3931295800006289 and parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3308215078468919, 'ffn_dropout': 0.19189082422640127, 'lr': 0.0010545897770873741, 'weight_decay': 0.00011961655599343352, 'batch_size': 64}. Best is trial 62 with value: 0.3965786227459637. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.393130 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3308215078468919, 'ffn_dropout': 0.19189082422640127, 'lr': 0.0010545897770873741, 'weight_decay': 0.00011961655599343352, 'batch_size': 64} - Best Value (CSI): 0.396579 - Best Trial: 62 - Best Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3052862966097679, 'ffn_dropout': 0.15467102369761743, 'lr': 0.0034927702704919835, 'weight_decay': 0.00021589622481913361, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 04:58:20,304] Trial 76 pruned. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.294599 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3305379742618786, 'ffn_dropout': 0.1916417311632724, 'lr': 0.0010890392863801186, 'weight_decay': 0.00010765461316265984, 'batch_size': 64} - Best Value (CSI): 0.396579 - Best Trial: 62 - Best Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3052862966097679, 'ffn_dropout': 0.15467102369761743, 'lr': 0.0034927702704919835, 'weight_decay': 0.00021589622481913361, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 05:00:39,680] Trial 77 finished with value: 0.38281858244918476 and parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.34581019449736045, 'ffn_dropout': 0.17942012278665023, 'lr': 0.0014215149737039628, 'weight_decay': 0.00014179343534084966, 'batch_size': 64}. Best is trial 62 with value: 0.3965786227459637. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.382819 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.34581019449736045, 'ffn_dropout': 0.17942012278665023, 'lr': 0.0014215149737039628, 'weight_decay': 0.00014179343534084966, 'batch_size': 64} - Best Value (CSI): 0.396579 - Best Trial: 62 - Best Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3052862966097679, 'ffn_dropout': 0.15467102369761743, 'lr': 0.0034927702704919835, 'weight_decay': 0.00021589622481913361, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 05:01:05,741] Trial 78 pruned. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.001594 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.31692975448492794, 'ffn_dropout': 0.1691841004407642, 'lr': 0.0016726874241114664, 'weight_decay': 0.00016252463821710703, 'batch_size': 64} - Best Value (CSI): 0.396579 - Best Trial: 62 - Best Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3052862966097679, 'ffn_dropout': 0.15467102369761743, 'lr': 0.0034927702704919835, 'weight_decay': 0.00021589622481913361, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 05:01:31,855] Trial 79 pruned. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.001594 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3082448344201325, 'ffn_dropout': 0.1478384028584312, 'lr': 0.0019030469764353864, 'weight_decay': 0.00012192723787335833, 'batch_size': 64} - Best Value (CSI): 0.396579 - Best Trial: 62 - Best Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3052862966097679, 'ffn_dropout': 0.15467102369761743, 'lr': 0.0034927702704919835, 'weight_decay': 0.00021589622481913361, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 05:02:18,295] Trial 80 pruned. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.248670 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2763740512250765, 'ffn_dropout': 0.1563843276087364, 'lr': 0.002274788727028034, 'weight_decay': 0.0002736472108688998, 'batch_size': 64} - Best Value (CSI): 0.396579 - Best Trial: 62 - Best Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3052862966097679, 'ffn_dropout': 0.15467102369761743, 'lr': 0.0034927702704919835, 'weight_decay': 0.00021589622481913361, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 05:03:19,174] Trial 81 pruned. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.323308 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.29604146043065716, 'ffn_dropout': 0.1792996071995582, 'lr': 0.0009237513393314215, 'weight_decay': 0.0001000377774850905, 'batch_size': 64} - Best Value (CSI): 0.396579 - Best Trial: 62 - Best Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3052862966097679, 'ffn_dropout': 0.15467102369761743, 'lr': 0.0034927702704919835, 'weight_decay': 0.00021589622481913361, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 05:06:11,428] Trial 82 finished with value: 0.40272068323222654 and parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2530528162951749, 'ffn_dropout': 0.1899328578250674, 'lr': 0.0013866055842525612, 'weight_decay': 0.00020752948982868583, 'batch_size': 64}. Best is trial 82 with value: 0.40272068323222654. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.402721 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2530528162951749, 'ffn_dropout': 0.1899328578250674, 'lr': 0.0013866055842525612, 'weight_decay': 0.00020752948982868583, 'batch_size': 64} - Best Value (CSI): 0.402721 - Best Trial: 82 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2530528162951749, 'ffn_dropout': 0.1899328578250674, 'lr': 0.0013866055842525612, 'weight_decay': 0.00020752948982868583, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 05:06:53,262] Trial 83 pruned. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.331418 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2651497754752364, 'ffn_dropout': 0.19466367480402613, 'lr': 0.0013012371737321842, 'weight_decay': 0.00021221834916125947, 'batch_size': 64} - Best Value (CSI): 0.402721 - Best Trial: 82 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2530528162951749, 'ffn_dropout': 0.1899328578250674, 'lr': 0.0013866055842525612, 'weight_decay': 0.00020752948982868583, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 05:07:32,922] Trial 84 pruned. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.311337 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2557014314876149, 'ffn_dropout': 0.1885922167084537, 'lr': 0.0017383190417840071, 'weight_decay': 0.00019601252883544242, 'batch_size': 64} - Best Value (CSI): 0.402721 - Best Trial: 82 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2530528162951749, 'ffn_dropout': 0.1899328578250674, 'lr': 0.0013866055842525612, 'weight_decay': 0.00020752948982868583, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 1.3256078431372549, 1: 1.3256078431372549, 2: 0.6705746989624869} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 1.329921568627451, 1: 1.329921568627451, 2: 0.6683813240308244} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16913}) -[I 2025-12-25 05:09:39,259] Trial 85 pruned. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.365414 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24629162704468205, 'ffn_dropout': 0.16845240385314297, 'lr': 0.0010274431364122962, 'weight_decay': 0.000248943216370203, 'batch_size': 64} - Best Value (CSI): 0.402721 - Best Trial: 82 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2530528162951749, 'ffn_dropout': 0.1899328578250674, 'lr': 0.0013866055842525612, 'weight_decay': 0.00020752948982868583, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 05:10:15,357] Trial 86 pruned. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.305085 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.22630828317519425, 'ffn_dropout': 0.14466085324215008, 'lr': 0.0006847925861119112, 'weight_decay': 0.0001466885203456596, 'batch_size': 64} - Best Value (CSI): 0.402721 - Best Trial: 82 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2530528162951749, 'ffn_dropout': 0.1899328578250674, 'lr': 0.0013866055842525612, 'weight_decay': 0.00020752948982868583, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 05:10:58,860] Trial 87 pruned. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.307692 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.25275605599055273, 'ffn_dropout': 0.1343972202505709, 'lr': 0.0014155241217180877, 'weight_decay': 0.00018218362943862458, 'batch_size': 64} - Best Value (CSI): 0.402721 - Best Trial: 82 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2530528162951749, 'ffn_dropout': 0.1899328578250674, 'lr': 0.0013866055842525612, 'weight_decay': 0.00020752948982868583, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 05:12:00,519] Trial 88 pruned. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.290323 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24024477951523718, 'ffn_dropout': 0.1587186302413476, 'lr': 0.0008415880003707745, 'weight_decay': 0.00032352143082226795, 'batch_size': 64} - Best Value (CSI): 0.402721 - Best Trial: 82 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2530528162951749, 'ffn_dropout': 0.1899328578250674, 'lr': 0.0013866055842525612, 'weight_decay': 0.00020752948982868583, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 05:13:12,343] Trial 89 pruned. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.300687 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.235485171286379, 'ffn_dropout': 0.18206801537501122, 'lr': 0.001120478933988194, 'weight_decay': 0.00012370576026725155, 'batch_size': 64} - Best Value (CSI): 0.402721 - Best Trial: 82 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2530528162951749, 'ffn_dropout': 0.1899328578250674, 'lr': 0.0013866055842525612, 'weight_decay': 0.00020752948982868583, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 05:13:40,371] Trial 90 pruned. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.001594 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2789629198009878, 'ffn_dropout': 0.1733291176347897, 'lr': 0.0025896078700494074, 'weight_decay': 0.0002406524018092201, 'batch_size': 64} - Best Value (CSI): 0.402721 - Best Trial: 82 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2530528162951749, 'ffn_dropout': 0.1899328578250674, 'lr': 0.0013866055842525612, 'weight_decay': 0.00020752948982868583, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 05:14:14,952] Trial 91 pruned. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.001594 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.32495215395258636, 'ffn_dropout': 0.20507796265210632, 'lr': 0.0021524054547993284, 'weight_decay': 0.00038679597160989025, 'batch_size': 64} - Best Value (CSI): 0.402721 - Best Trial: 82 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2530528162951749, 'ffn_dropout': 0.1899328578250674, 'lr': 0.0013866055842525612, 'weight_decay': 0.00020752948982868583, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 05:14:49,523] Trial 92 pruned. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.331532 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.22072572080887523, 'ffn_dropout': 0.19831514867565855, 'lr': 0.0012261650277785292, 'weight_decay': 0.0001464608413231596, 'batch_size': 128} - Best Value (CSI): 0.402721 - Best Trial: 82 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2530528162951749, 'ffn_dropout': 0.1899328578250674, 'lr': 0.0013866055842525612, 'weight_decay': 0.00020752948982868583, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 05:15:44,271] Trial 93 pruned. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.300163 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2366667016027234, 'ffn_dropout': 0.15178146718500238, 'lr': 0.0005158107788918303, 'weight_decay': 0.00017525698171098758, 'batch_size': 64} - Best Value (CSI): 0.402721 - Best Trial: 82 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2530528162951749, 'ffn_dropout': 0.1899328578250674, 'lr': 0.0013866055842525612, 'weight_decay': 0.00020752948982868583, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 05:16:18,834] Trial 94 pruned. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.001594 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2910311156506059, 'ffn_dropout': 0.16453213446778495, 'lr': 0.001828894513024565, 'weight_decay': 0.00022117006518336895, 'batch_size': 64} - Best Value (CSI): 0.402721 - Best Trial: 82 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2530528162951749, 'ffn_dropout': 0.1899328578250674, 'lr': 0.0013866055842525612, 'weight_decay': 0.00020752948982868583, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 05:16:32,662] Trial 95 pruned. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.195946 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2652687062658311, 'ffn_dropout': 0.17548690521241875, 'lr': 0.0008107518345106616, 'weight_decay': 0.00029175850536014564, 'batch_size': 256} - Best Value (CSI): 0.402721 - Best Trial: 82 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2530528162951749, 'ffn_dropout': 0.1899328578250674, 'lr': 0.0013866055842525612, 'weight_decay': 0.00020752948982868583, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 05:17:27,308] Trial 96 pruned. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.300000 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2243611234333362, 'ffn_dropout': 0.21146930330935843, 'lr': 0.0010280794138031106, 'weight_decay': 0.00011914760951793655, 'batch_size': 64} - Best Value (CSI): 0.402721 - Best Trial: 82 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2530528162951749, 'ffn_dropout': 0.1899328578250674, 'lr': 0.0013866055842525612, 'weight_decay': 0.00020752948982868583, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 05:18:09,707] Trial 97 pruned. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.302170 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2119125201627533, 'ffn_dropout': 0.18698281310694495, 'lr': 0.0006191384021948767, 'weight_decay': 0.000493922995649859, 'batch_size': 64} - Best Value (CSI): 0.402721 - Best Trial: 82 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2530528162951749, 'ffn_dropout': 0.1899328578250674, 'lr': 0.0013866055842525612, 'weight_decay': 0.00020752948982868583, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 05:18:44,199] Trial 98 pruned. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.147335 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2480563359486886, 'ffn_dropout': 0.19304338516553096, 'lr': 0.003308037477561071, 'weight_decay': 0.00038521313865806845, 'batch_size': 64} - Best Value (CSI): 0.402721 - Best Trial: 82 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2530528162951749, 'ffn_dropout': 0.1899328578250674, 'lr': 0.0013866055842525612, 'weight_decay': 0.00020752948982868583, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3169411764705883, 1: 1.3169411764705883, 2: 0.6750693523097334} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16582}) -[I 2025-12-25 05:19:43,028] Trial 99 pruned. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.323792 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.25649324712960875, 'ffn_dropout': 0.1388735364922094, 'lr': 0.0015866250450879385, 'weight_decay': 0.0001618910164727616, 'batch_size': 64} - Best Value (CSI): 0.402721 - Best Trial: 82 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2530528162951749, 'ffn_dropout': 0.1899328578250674, 'lr': 0.0013866055842525612, 'weight_decay': 0.00020752948982868583, 'batch_size': 64} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.4027 -Best Hyperparameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2530528162951749, 'ffn_dropout': 0.1899328578250674, 'lr': 0.0013866055842525612, 'weight_decay': 0.00020752948982868583, 'batch_size': 64} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.2812 - - 최종 CSI: 0.3238 - - 최고 CSI: 0.4027 - - 최저 CSI: 0.0016 - - 평균 CSI: 0.2458 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/ft_transformer_smote_daegu_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 48, Best CSI: 0.3359 - Fold 1 학습 완료 (검증 CSI: 0.3359) -Fold 2 학습 중... - Early stopping at epoch 27, Best CSI: 0.4263 - Fold 2 학습 완료 (검증 CSI: 0.4263) -Fold 3 학습 중... - Early stopping at epoch 25, Best CSI: 0.4090 - Fold 3 학습 완료 (검증 CSI: 0.4090) - -모든 모델 저장 완료: ../save_model/ft_transformer_optima/ft_transformer_smote_daegu.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/ft_transformer_optima/scaler/ft_transformer_smote_daegu_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: ../save_model/ft_transformer_optima/ft_transformer_smote_daegu.pkl - -✓ 완료: ft_transformer_smote/ft_transformer_smote_daegu.py (소요 시간: 9367초) - ----------------------------------------- -실행 중: ft_transformer_smote/ft_transformer_smote_daejeon.py -시작 시간: 2025-12-25 05:23:18 ----------------------------------------- -[I 2025-12-25 05:23:20,047] A new study created in memory with name: no-name-2eafe00f-22f7-4457-a4bc-5608dbaaf5b8 - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.3215416666666666, 1: 1.3215416666666666, 2: 0.6726686602617123} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.3243333333333334, 1: 1.3243333333333334, 2: 0.6712282480148674} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15784}) -[I 2025-12-25 05:26:35,096] Trial 0 finished with value: 0.435194083401059 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.35630491265424435, 'ffn_dropout': 0.30318468546180316, 'lr': 4.741701472353272e-05, 'weight_decay': 0.0004128250492459912, 'batch_size': 64}. Best is trial 0 with value: 0.435194083401059. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.435194 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.35630491265424435, 'ffn_dropout': 0.30318468546180316, 'lr': 4.741701472353272e-05, 'weight_decay': 0.0004128250492459912, 'batch_size': 64} - Best Value (CSI): 0.435194 - Best Trial: 0 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.35630491265424435, 'ffn_dropout': 0.30318468546180316, 'lr': 4.741701472353272e-05, 'weight_decay': 0.0004128250492459912, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.3215416666666666, 1: 1.3215416666666666, 2: 0.6726686602617123} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.3243333333333334, 1: 1.3243333333333334, 2: 0.6712282480148674} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15784}) -[I 2025-12-25 05:30:15,731] Trial 1 finished with value: 0.10114217631060095 and parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.17777624723763696, 'ffn_dropout': 0.2722715902408209, 'lr': 0.0029203401969831134, 'weight_decay': 0.013194604673933295, 'batch_size': 32}. Best is trial 0 with value: 0.435194083401059. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.101142 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.17777624723763696, 'ffn_dropout': 0.2722715902408209, 'lr': 0.0029203401969831134, 'weight_decay': 0.013194604673933295, 'batch_size': 32} - Best Value (CSI): 0.435194 - Best Trial: 0 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.35630491265424435, 'ffn_dropout': 0.30318468546180316, 'lr': 4.741701472353272e-05, 'weight_decay': 0.0004128250492459912, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.3215416666666666, 1: 1.3215416666666666, 2: 0.6726686602617123} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.3243333333333334, 1: 1.3243333333333334, 2: 0.6712282480148674} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15784}) -[I 2025-12-25 05:32:58,118] Trial 2 finished with value: 0.482035457043179 and parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64}. Best is trial 2 with value: 0.482035457043179. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.482035 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.3215416666666666, 1: 1.3215416666666666, 2: 0.6726686602617123} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.3243333333333334, 1: 1.3243333333333334, 2: 0.6712282480148674} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15784}) -[I 2025-12-25 05:36:17,520] Trial 3 finished with value: 0.41946575380769774 and parameters: {'d_token': 224, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.24230466569763393, 'ffn_dropout': 0.29258204773770935, 'lr': 2.501591289252331e-05, 'weight_decay': 0.010699423627311641, 'batch_size': 256}. Best is trial 2 with value: 0.482035457043179. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.419466 - Parameters: {'d_token': 224, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.24230466569763393, 'ffn_dropout': 0.29258204773770935, 'lr': 2.501591289252331e-05, 'weight_decay': 0.010699423627311641, 'batch_size': 256} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.3215416666666666, 1: 1.3215416666666666, 2: 0.6726686602617123} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.3243333333333334, 1: 1.3243333333333334, 2: 0.6712282480148674} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15784}) -[I 2025-12-25 05:39:11,712] Trial 4 finished with value: 0.179696132253106 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3588179865786624, 'ffn_dropout': 0.17594203278394177, 'lr': 0.002098570861068094, 'weight_decay': 0.02244462393201445, 'batch_size': 32}. Best is trial 2 with value: 0.482035457043179. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.179696 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3588179865786624, 'ffn_dropout': 0.17594203278394177, 'lr': 0.002098570861068094, 'weight_decay': 0.02244462393201445, 'batch_size': 32} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 05:39:21,137] Trial 5 pruned. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.226107 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.19599258873671155, 'ffn_dropout': 0.3385294580346525, 'lr': 3.642408033542372e-05, 'weight_decay': 0.00027209518632823396, 'batch_size': 256} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 05:40:09,451] Trial 6 pruned. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.392444 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.33150134429608746, 'ffn_dropout': 0.16731576029206097, 'lr': 0.000537046432493899, 'weight_decay': 0.006505884125126589, 'batch_size': 128} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 05:40:41,003] Trial 7 pruned. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.273997 - Parameters: {'d_token': 256, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3461896949499914, 'ffn_dropout': 0.38598605859514323, 'lr': 1.870134521346119e-05, 'weight_decay': 0.0026023527152729754, 'batch_size': 256} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 05:40:53,546] Trial 8 pruned. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.228582 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2638747134302847, 'ffn_dropout': 0.21023322334932779, 'lr': 1.820368142532858e-05, 'weight_decay': 0.002351928990425821, 'batch_size': 256} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 05:41:21,144] Trial 9 pruned. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.256772 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.33935298622594395, 'ffn_dropout': 0.21088283954952491, 'lr': 3.2544199990811325e-05, 'weight_decay': 0.0015862717787733394, 'batch_size': 64} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 05:41:45,120] Trial 10 pruned. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.12109055482993017, 'ffn_dropout': 0.1109052624435885, 'lr': 0.006096506639993064, 'weight_decay': 0.0001296273011270279, 'batch_size': 64} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 05:42:25,077] Trial 11 pruned. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.389918 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3904377654618627, 'ffn_dropout': 0.3012297799293693, 'lr': 0.00020654209021246333, 'weight_decay': 0.0004200190135031989, 'batch_size': 64} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 05:43:09,826] Trial 12 pruned. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.333717 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.39710965030289147, 'ffn_dropout': 0.2410277636918873, 'lr': 0.00012856866590593653, 'weight_decay': 0.000110546156911118, 'batch_size': 64} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 05:43:57,810] Trial 13 pruned. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.381203 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.30270339276876407, 'ffn_dropout': 0.10572392995404509, 'lr': 0.0006145550288664171, 'weight_decay': 0.0007410279153205748, 'batch_size': 64} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 05:44:12,634] Trial 14 pruned. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.295279 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38818244359717646, 'ffn_dropout': 0.3328322741600634, 'lr': 5.738842849277875e-05, 'weight_decay': 0.0007065029288120263, 'batch_size': 128} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 05:44:37,688] Trial 15 pruned. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.300931 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.30325538459019874, 'ffn_dropout': 0.24937187468831662, 'lr': 1.0268376890038298e-05, 'weight_decay': 0.00023761547791210352, 'batch_size': 64} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 05:45:23,481] Trial 16 pruned. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.341733 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.37070665048103224, 'ffn_dropout': 0.1497568962244653, 'lr': 7.536908368341014e-05, 'weight_decay': 0.00010442036180904675, 'batch_size': 64} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 05:46:31,291] Trial 17 pruned. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.390093 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3156443589102168, 'ffn_dropout': 0.2143996111617863, 'lr': 0.00030868778702509243, 'weight_decay': 0.04916784753801883, 'batch_size': 64} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 05:46:52,718] Trial 18 pruned. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.389058 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3726731722039025, 'ffn_dropout': 0.14340880064598888, 'lr': 0.0007718348961869099, 'weight_decay': 0.0011363675459477552, 'batch_size': 128} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.3215416666666666, 1: 1.3215416666666666, 2: 0.6726686602617123} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.3243333333333334, 1: 1.3243333333333334, 2: 0.6712282480148674} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15784}) -[I 2025-12-25 05:51:40,266] Trial 19 finished with value: 0.45796371146362064 and parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.39619063072335076, 'ffn_dropout': 0.18710073970945706, 'lr': 0.00010024889239283773, 'weight_decay': 0.0003002198494392534, 'batch_size': 32}. Best is trial 2 with value: 0.482035457043179. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.457964 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.39619063072335076, 'ffn_dropout': 0.18710073970945706, 'lr': 0.00010024889239283773, 'weight_decay': 0.0003002198494392534, 'batch_size': 32} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 05:53:34,224] Trial 20 pruned. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.360208 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3962778382759863, 'ffn_dropout': 0.185053617338563, 'lr': 0.00010353006315128545, 'weight_decay': 0.00020510606938246382, 'batch_size': 32} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 05:54:54,833] Trial 21 pruned. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.358100 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.36779423404459893, 'ffn_dropout': 0.13171093761975644, 'lr': 0.00018051187360066615, 'weight_decay': 0.00041078887466432733, 'batch_size': 32} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 05:56:17,844] Trial 22 pruned. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.358834 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3504420488620527, 'ffn_dropout': 0.19409262698707652, 'lr': 6.974141371411731e-05, 'weight_decay': 0.00043738877832807596, 'batch_size': 32} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 05:57:34,728] Trial 23 pruned. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.349235 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3982791007228654, 'ffn_dropout': 0.15222250826852096, 'lr': 5.075360982861611e-05, 'weight_decay': 0.0001988841113945303, 'batch_size': 32} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 05:58:27,665] Trial 24 pruned. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.365541 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.36575919432501147, 'ffn_dropout': 0.24517497266634225, 'lr': 0.00011268869007155552, 'weight_decay': 0.0008516135503928507, 'batch_size': 64} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 05:59:10,361] Trial 25 pruned. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.385821 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.32754091767890925, 'ffn_dropout': 0.12762044202122977, 'lr': 0.00033354254201223185, 'weight_decay': 0.00016832445102931898, 'batch_size': 64} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 05:59:53,043] Trial 26 pruned. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.315444 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3728040928857398, 'ffn_dropout': 0.1699592828596161, 'lr': 4.484804886226935e-05, 'weight_decay': 0.0003746292221895203, 'batch_size': 32} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:00:15,846] Trial 27 pruned. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.380623 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3464976601033162, 'ffn_dropout': 0.22058426110744436, 'lr': 0.001031709624054449, 'weight_decay': 0.00010417808062079, 'batch_size': 128} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:00:52,144] Trial 28 pruned. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.364838 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3179918502174328, 'ffn_dropout': 0.1974046312448996, 'lr': 0.00018360559009522736, 'weight_decay': 0.00028767938955750685, 'batch_size': 64} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:01:49,854] Trial 29 pruned. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.003188 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.291156019100097, 'ffn_dropout': 0.27371289522629305, 'lr': 0.0012937114895499235, 'weight_decay': 0.0005188686934419268, 'batch_size': 32} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:02:39,824] Trial 30 pruned. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.003188 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.38055137387311483, 'ffn_dropout': 0.2299084697994096, 'lr': 0.0034308827100690297, 'weight_decay': 0.0013199068451902822, 'batch_size': 32} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:03:21,829] Trial 31 pruned. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.315578 - Parameters: {'d_token': 224, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.2404232293928068, 'ffn_dropout': 0.2760687163406419, 'lr': 3.1196356955139245e-05, 'weight_decay': 0.006652453598869895, 'batch_size': 256} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:03:56,119] Trial 32 pruned. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.279945 - Parameters: {'d_token': 256, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.36043843312657653, 'ffn_dropout': 0.2604427135843803, 'lr': 8.251273145950291e-05, 'weight_decay': 0.00015463793358723655, 'batch_size': 256} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:04:16,031] Trial 33 pruned. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.261406 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.22444268798775252, 'ffn_dropout': 0.2977594413870529, 'lr': 2.8024361496239e-05, 'weight_decay': 0.000283276707532014, 'batch_size': 256} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:04:29,363] Trial 34 pruned. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.264561 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2716840391924549, 'ffn_dropout': 0.1748271177717835, 'lr': 4.6202537873762256e-05, 'weight_decay': 0.016244963854803025, 'batch_size': 256} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:04:57,410] Trial 35 pruned. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.307391 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3410318869631717, 'ffn_dropout': 0.1648668214874827, 'lr': 2.2389559544948873e-05, 'weight_decay': 0.0051306782135012545, 'batch_size': 256} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:05:15,236] Trial 36 pruned. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.246954 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.3836509541444429, 'ffn_dropout': 0.1940246541476147, 'lr': 1.479679200223157e-05, 'weight_decay': 0.00015972205524177833, 'batch_size': 256} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:06:08,630] Trial 37 pruned. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.335905 - Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.35546278460219005, 'ffn_dropout': 0.3252805067879826, 'lr': 3.827979498147093e-05, 'weight_decay': 0.0002507757613509754, 'batch_size': 64} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:06:47,738] Trial 38 pruned. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.314314 - Parameters: {'d_token': 224, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.33144423277206303, 'ffn_dropout': 0.3571965552025107, 'lr': 2.186781577494653e-05, 'weight_decay': 0.0020510366346726556, 'batch_size': 128} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:07:47,028] Trial 39 pruned. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.349873 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.21081199178897642, 'ffn_dropout': 0.29580355398987723, 'lr': 6.228199246406535e-05, 'weight_decay': 0.0032689837620931603, 'batch_size': 32} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:08:03,369] Trial 40 pruned. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.221717 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1814818199564683, 'ffn_dropout': 0.26196974913466736, 'lr': 3.21542547123497e-05, 'weight_decay': 0.0005881198691017782, 'batch_size': 256} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:08:54,345] Trial 41 pruned. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.003188 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3548922591236492, 'ffn_dropout': 0.17968661333570538, 'lr': 0.0031455813024586785, 'weight_decay': 0.014405721366653823, 'batch_size': 32} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 1.3215416666666666, 1: 1.3215416666666666, 2: 0.6726686602617123} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 1.3243333333333334, 1: 1.3243333333333334, 2: 0.6712282480148674} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15784}) -[I 2025-12-25 06:16:57,697] Trial 42 finished with value: 0.47049460961250594 and parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3992877307097387, 'ffn_dropout': 0.21057498553460652, 'lr': 0.001530448267390241, 'weight_decay': 0.020277332563201727, 'batch_size': 32}. Best is trial 2 with value: 0.482035457043179. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.470495 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3992877307097387, 'ffn_dropout': 0.21057498553460652, 'lr': 0.001530448267390241, 'weight_decay': 0.020277332563201727, 'batch_size': 32} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:18:35,700] Trial 43 pruned. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.321945 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.3849523777606599, 'ffn_dropout': 0.23358166556471682, 'lr': 0.0015842827767408928, 'weight_decay': 0.0295153186884493, 'batch_size': 32} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:19:38,798] Trial 44 pruned. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.366236 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3832232435446611, 'ffn_dropout': 0.20426783141303423, 'lr': 0.0022965945746403252, 'weight_decay': 0.009500694176380126, 'batch_size': 64} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:21:40,855] Trial 45 pruned. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.372188 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.39907283026984053, 'ffn_dropout': 0.2262318705255812, 'lr': 0.00045868819983105856, 'weight_decay': 0.026137087511014363, 'batch_size': 32} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:22:38,854] Trial 46 pruned. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.371544 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.37503075797823837, 'ffn_dropout': 0.16123646497200633, 'lr': 0.0007253389171436486, 'weight_decay': 0.00012935355124640442, 'batch_size': 64} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:23:08,499] Trial 47 pruned. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.003188 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39909245464269066, 'ffn_dropout': 0.20955977238404055, 'lr': 0.005369240429555812, 'weight_decay': 0.00031484196332935943, 'batch_size': 64} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:25:26,181] Trial 48 pruned. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.344615 - Parameters: {'d_token': 224, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.3844019908871621, 'ffn_dropout': 0.186716668054185, 'lr': 9.425575289216899e-05, 'weight_decay': 0.01039424978312511, 'batch_size': 32} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:25:53,504] Trial 49 pruned. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.373316 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3584179207735206, 'ffn_dropout': 0.21665597232291198, 'lr': 0.0010449100243591978, 'weight_decay': 0.07016947368489082, 'batch_size': 128} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:26:46,432] Trial 50 pruned. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.374116 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.34145519296643384, 'ffn_dropout': 0.28474995806155456, 'lr': 0.0001387940464044104, 'weight_decay': 0.0002082794975108132, 'batch_size': 64} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:27:37,680] Trial 51 pruned. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.058632 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3647187615141512, 'ffn_dropout': 0.3144725894228163, 'lr': 0.001968999187803701, 'weight_decay': 0.019770983747416437, 'batch_size': 32} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:28:42,420] Trial 52 pruned. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.305595 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.39035927160407313, 'ffn_dropout': 0.18043136273214297, 'lr': 0.0016781059649267184, 'weight_decay': 0.02820193131985511, 'batch_size': 32} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:29:39,930] Trial 53 pruned. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.003188 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3754660512950028, 'ffn_dropout': 0.20305879834456092, 'lr': 0.0024669036510468973, 'weight_decay': 0.0369057207717192, 'batch_size': 32} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:30:56,778] Trial 54 pruned. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.345848 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3998268335740356, 'ffn_dropout': 0.16503259759109884, 'lr': 5.9052458359203345e-05, 'weight_decay': 0.020879292427025152, 'batch_size': 32} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:31:32,772] Trial 55 pruned. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.350687 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3667255202799211, 'ffn_dropout': 0.1544998463868853, 'lr': 0.004155322045208773, 'weight_decay': 0.0009499637193641076, 'batch_size': 64} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:32:25,946] Trial 56 pruned. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.003188 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.35210973957711367, 'ffn_dropout': 0.13605438466877512, 'lr': 0.007166090784521867, 'weight_decay': 0.0006067127479049742, 'batch_size': 32} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:32:44,083] Trial 57 pruned. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.374420 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.39104296240740777, 'ffn_dropout': 0.18739449400881097, 'lr': 0.0011818927736617604, 'weight_decay': 0.0001032566294656706, 'batch_size': 256} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:33:36,603] Trial 58 pruned. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.351182 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3761994974169578, 'ffn_dropout': 0.23489766692918246, 'lr': 0.0005166108151504077, 'weight_decay': 0.000348760785847715, 'batch_size': 64} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:35:04,357] Trial 59 pruned. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.395885 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.33547909427432954, 'ffn_dropout': 0.12067942711820132, 'lr': 0.0009149539386328306, 'weight_decay': 0.00045740265900319775, 'batch_size': 32} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:35:20,416] Trial 60 pruned. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.313121 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.34637604114532383, 'ffn_dropout': 0.14747905026352412, 'lr': 7.791266368091504e-05, 'weight_decay': 0.0007308148705734484, 'batch_size': 128} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:36:22,737] Trial 61 pruned. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.003188 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.3192261855857527, 'ffn_dropout': 0.2518149082061173, 'lr': 0.0027336267959246026, 'weight_decay': 0.00023476576338720908, 'batch_size': 32} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:37:25,243] Trial 62 pruned. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.003188 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.16708471693445678, 'ffn_dropout': 0.17343633670698932, 'lr': 0.001427896849429843, 'weight_decay': 0.013826276157900413, 'batch_size': 32} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:38:23,859] Trial 63 pruned. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.003188 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.3692157924157389, 'ffn_dropout': 0.28614815607640187, 'lr': 0.0018089618037505596, 'weight_decay': 0.0001335635429572805, 'batch_size': 32} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:39:29,428] Trial 64 pruned. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.003188 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.2956431875720221, 'ffn_dropout': 0.3085364817014323, 'lr': 0.004040845811919421, 'weight_decay': 0.00018474115356024296, 'batch_size': 32} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:39:59,883] Trial 65 pruned. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.003188 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.25442306752412547, 'ffn_dropout': 0.2183908372914257, 'lr': 0.009651486111800084, 'weight_decay': 0.0004104491759737441, 'batch_size': 64} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:40:35,624] Trial 66 pruned. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.360208 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.38894613115075083, 'ffn_dropout': 0.14232224706649113, 'lr': 0.002016098594785894, 'weight_decay': 0.011218626247333127, 'batch_size': 256} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:42:01,752] Trial 67 pruned. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.381579 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3096997748747929, 'ffn_dropout': 0.15796575147791214, 'lr': 0.0014866457584689588, 'weight_decay': 0.0076616604444691965, 'batch_size': 32} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:42:45,159] Trial 68 pruned. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.315730 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.27668852753526785, 'ffn_dropout': 0.19420931684213166, 'lr': 3.71576425546584e-05, 'weight_decay': 0.004574004892039827, 'batch_size': 64} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:43:17,317] Trial 69 pruned. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.349558 - Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3623706579212562, 'ffn_dropout': 0.16721175084350676, 'lr': 0.0012084136989055096, 'weight_decay': 0.0014928160881165623, 'batch_size': 256} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:44:14,427] Trial 70 pruned. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.003188 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.325306215753842, 'ffn_dropout': 0.2689178110606701, 'lr': 0.002821893911622381, 'weight_decay': 0.00028836441161129333, 'batch_size': 32} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:44:52,183] Trial 71 pruned. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.370000 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3355550411442044, 'ffn_dropout': 0.1059503864317626, 'lr': 0.000728437677488462, 'weight_decay': 0.0004712735199084819, 'batch_size': 64} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:45:29,519] Trial 72 pruned. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.348036 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.38113538193064356, 'ffn_dropout': 0.1190601422458849, 'lr': 0.0021226541343342424, 'weight_decay': 0.00021404629397469562, 'batch_size': 64} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:46:10,384] Trial 73 pruned. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.361663 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.35192736894174165, 'ffn_dropout': 0.11166348187751633, 'lr': 0.00024421730469178187, 'weight_decay': 0.0003202450833667886, 'batch_size': 64} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:46:55,233] Trial 74 pruned. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.376183 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.39131010475971717, 'ffn_dropout': 0.13374387720921155, 'lr': 0.0008603507356502913, 'weight_decay': 0.0002444774569510799, 'batch_size': 64} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:47:12,850] Trial 75 pruned. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.340843 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.30172568324985893, 'ffn_dropout': 0.14853451278897264, 'lr': 4.2823826501414976e-05, 'weight_decay': 0.0005416327466483893, 'batch_size': 128} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:47:59,041] Trial 76 pruned. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.360025 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.32364997585962163, 'ffn_dropout': 0.10188361667133514, 'lr': 5.343373930211499e-05, 'weight_decay': 0.0010804889986723585, 'batch_size': 64} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:49:18,014] Trial 77 pruned. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.381882 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3737015586731457, 'ffn_dropout': 0.18511627905659322, 'lr': 0.0013421867530335476, 'weight_decay': 0.0007328668518360746, 'batch_size': 32} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:49:58,211] Trial 78 pruned. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.368988 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2868480960750851, 'ffn_dropout': 0.1719391994598928, 'lr': 2.874646970032627e-05, 'weight_decay': 0.00036112945400203715, 'batch_size': 256} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:51:03,591] Trial 79 pruned. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.392882 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.3096204961230813, 'ffn_dropout': 0.2067534581050884, 'lr': 0.0005881024452613355, 'weight_decay': 0.00015975541942196423, 'batch_size': 64} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:52:32,128] Trial 80 pruned. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.391598 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3448730826063865, 'ffn_dropout': 0.13990993087639628, 'lr': 0.001759476437896277, 'weight_decay': 0.01961419588656968, 'batch_size': 32} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:53:23,257] Trial 81 pruned. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.383505 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.36046392344927874, 'ffn_dropout': 0.15473224656527096, 'lr': 0.0006020622066714857, 'weight_decay': 0.013010607662362197, 'batch_size': 128} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:54:08,645] Trial 82 pruned. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.380145 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.33622769930564644, 'ffn_dropout': 0.15843886849119132, 'lr': 0.0003590854910328803, 'weight_decay': 0.016170008786231035, 'batch_size': 128} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:54:57,984] Trial 83 pruned. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.003188 - Parameters: {'d_token': 224, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3306915913446745, 'ffn_dropout': 0.1784345745753021, 'lr': 0.0009815544592581649, 'weight_decay': 0.008754995470375374, 'batch_size': 128} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:55:35,592] Trial 84 pruned. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.37809642232487806, 'ffn_dropout': 0.12774763123957789, 'lr': 0.0011460892958535182, 'weight_decay': 0.011786863298840319, 'batch_size': 128} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:57:15,660] Trial 85 pruned. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.390469 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.36687134932861054, 'ffn_dropout': 0.1983567931205194, 'lr': 0.00042394843555603845, 'weight_decay': 0.006718201631664788, 'batch_size': 32} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:57:52,453] Trial 86 pruned. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.361533 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39087833058217086, 'ffn_dropout': 0.18899192245136262, 'lr': 0.0007410712838945122, 'weight_decay': 0.00940426195474712, 'batch_size': 256} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:58:46,772] Trial 87 pruned. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.361582 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.35603112766267664, 'ffn_dropout': 0.16574730002477756, 'lr': 1.525126738497364e-05, 'weight_decay': 0.00012988808252722522, 'batch_size': 64} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:59:37,721] Trial 88 pruned. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.193446 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.347897299677989, 'ffn_dropout': 0.21158340923661137, 'lr': 0.0016012851730263856, 'weight_decay': 0.00027321493249328683, 'batch_size': 32} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 06:59:55,408] Trial 89 pruned. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.282792 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3950103732186416, 'ffn_dropout': 0.17704193350798816, 'lr': 6.404967809548521e-05, 'weight_decay': 0.00038262578221755363, 'batch_size': 128} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 07:00:28,920] Trial 90 pruned. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.301310 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.3805838182533225, 'ffn_dropout': 0.14646582274447714, 'lr': 2.492674540520319e-05, 'weight_decay': 0.012218872430036052, 'batch_size': 64} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 07:01:40,335] Trial 91 pruned. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.376404 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3408903778762287, 'ffn_dropout': 0.22567196894429373, 'lr': 0.00013560820123629218, 'weight_decay': 0.0006108646350502622, 'batch_size': 64} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 07:02:47,215] Trial 92 pruned. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.376597 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.32818565902774877, 'ffn_dropout': 0.20045487494704317, 'lr': 0.0002763550288905753, 'weight_decay': 0.00018762300399772315, 'batch_size': 64} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 07:03:51,825] Trial 93 pruned. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.383346 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.37117875149380725, 'ffn_dropout': 0.19158902704545194, 'lr': 0.0001648060581211439, 'weight_decay': 0.03776638143162874, 'batch_size': 64} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 07:04:55,209] Trial 94 pruned. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.003188 - Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3844723207601901, 'ffn_dropout': 0.18391702733905102, 'lr': 0.0008731766096177255, 'weight_decay': 0.015224377178318765, 'batch_size': 32} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 07:05:33,145] Trial 95 pruned. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.318625 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3103933910003279, 'ffn_dropout': 0.19709824689998762, 'lr': 8.720160011305069e-05, 'weight_decay': 0.018309787281725467, 'batch_size': 64} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 07:05:49,209] Trial 96 pruned. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.307774 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.39954598522817275, 'ffn_dropout': 0.17168406080786575, 'lr': 0.0003661898056523877, 'weight_decay': 0.013271341304475062, 'batch_size': 256} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 07:08:12,263] Trial 97 pruned. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.380373 - Parameters: {'d_token': 224, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3190022624358252, 'ffn_dropout': 0.21484799904590776, 'lr': 7.005864563818163e-05, 'weight_decay': 0.010284972134559905, 'batch_size': 32} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 07:08:47,301] Trial 98 pruned. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.366644 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.36034658048375157, 'ffn_dropout': 0.2053466969646277, 'lr': 0.000654410953267678, 'weight_decay': 0.001992845915312216, 'batch_size': 64} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3100416666666668, 1: 1.3100416666666668, 2: 0.6787341061675626} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15441}) -[I 2025-12-25 07:10:26,024] Trial 99 pruned. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.374815 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.22723764472934604, 'ffn_dropout': 0.16334830807925632, 'lr': 0.000495818487090032, 'weight_decay': 0.025043786250964914, 'batch_size': 32} - Best Value (CSI): 0.482035 - Best Trial: 2 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.4820 -Best Hyperparameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3951058265943127, 'ffn_dropout': 0.15816355519966163, 'lr': 0.0011481409855838528, 'weight_decay': 0.00011134016766733501, 'batch_size': 64} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.4352 - - 최종 CSI: 0.3748 - - 최고 CSI: 0.4820 - - 최저 CSI: 0.0000 - - 평균 CSI: 0.2858 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/ft_transformer_smote_daejeon_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 38, Best CSI: 0.4083 - Fold 1 학습 완료 (검증 CSI: 0.4083) -Fold 2 학습 중... - Early stopping at epoch 19, Best CSI: 0.5045 - Fold 2 학습 완료 (검증 CSI: 0.5045) -Fold 3 학습 중... - Early stopping at epoch 30, Best CSI: 0.5143 - Fold 3 학습 완료 (검증 CSI: 0.5143) - -모든 모델 저장 완료: ../save_model/ft_transformer_optima/ft_transformer_smote_daejeon.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/ft_transformer_optima/scaler/ft_transformer_smote_daejeon_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: ../save_model/ft_transformer_optima/ft_transformer_smote_daejeon.pkl - -✓ 완료: ft_transformer_smote/ft_transformer_smote_daejeon.py (소요 시간: 6604초) - ----------------------------------------- -실행 중: ft_transformer_smote/ft_transformer_smote_gwangju.py -시작 시간: 2025-12-25 07:13:22 ----------------------------------------- -[I 2025-12-25 07:13:23,613] A new study created in memory with name: no-name-5349d2b6-e800-4dfc-9fbe-12bd1bc937df - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 07:16:44,543] Trial 0 finished with value: 0.4720379044756742 and parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.20204180094743923, 'ffn_dropout': 0.3073161090438865, 'lr': 0.0005024966682405841, 'weight_decay': 0.000989264866109286, 'batch_size': 64}. Best is trial 0 with value: 0.4720379044756742. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.472038 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.20204180094743923, 'ffn_dropout': 0.3073161090438865, 'lr': 0.0005024966682405841, 'weight_decay': 0.000989264866109286, 'batch_size': 64} - Best Value (CSI): 0.472038 - Best Trial: 0 - Best Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.20204180094743923, 'ffn_dropout': 0.3073161090438865, 'lr': 0.0005024966682405841, 'weight_decay': 0.000989264866109286, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 07:20:05,570] Trial 1 finished with value: 0.4705839531329334 and parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.2083667092536843, 'ffn_dropout': 0.2744598584859157, 'lr': 0.0005927780357092684, 'weight_decay': 0.014632416816661825, 'batch_size': 128}. Best is trial 0 with value: 0.4720379044756742. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.470584 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.2083667092536843, 'ffn_dropout': 0.2744598584859157, 'lr': 0.0005927780357092684, 'weight_decay': 0.014632416816661825, 'batch_size': 128} - Best Value (CSI): 0.472038 - Best Trial: 0 - Best Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.20204180094743923, 'ffn_dropout': 0.3073161090438865, 'lr': 0.0005024966682405841, 'weight_decay': 0.000989264866109286, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 07:23:05,002] Trial 2 finished with value: 0.42232184595273004 and parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2841328433383815, 'ffn_dropout': 0.1795677450326215, 'lr': 1.903749576214546e-05, 'weight_decay': 0.0019845340633137896, 'batch_size': 128}. Best is trial 0 with value: 0.4720379044756742. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.422322 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2841328433383815, 'ffn_dropout': 0.1795677450326215, 'lr': 1.903749576214546e-05, 'weight_decay': 0.0019845340633137896, 'batch_size': 128} - Best Value (CSI): 0.472038 - Best Trial: 0 - Best Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.20204180094743923, 'ffn_dropout': 0.3073161090438865, 'lr': 0.0005024966682405841, 'weight_decay': 0.000989264866109286, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 07:28:43,262] Trial 3 finished with value: 0.4741962384900029 and parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.362678844726258, 'ffn_dropout': 0.16635293152622824, 'lr': 0.000390125889967722, 'weight_decay': 0.006710255477547039, 'batch_size': 32}. Best is trial 3 with value: 0.4741962384900029. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.474196 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.362678844726258, 'ffn_dropout': 0.16635293152622824, 'lr': 0.000390125889967722, 'weight_decay': 0.006710255477547039, 'batch_size': 32} - Best Value (CSI): 0.474196 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.362678844726258, 'ffn_dropout': 0.16635293152622824, 'lr': 0.000390125889967722, 'weight_decay': 0.006710255477547039, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 07:30:05,505] Trial 4 finished with value: 0.09167591968793302 and parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.16706765101805265, 'ffn_dropout': 0.2710303189936548, 'lr': 0.008225551320386045, 'weight_decay': 0.00103097881257981, 'batch_size': 256}. Best is trial 3 with value: 0.4741962384900029. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.091676 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.16706765101805265, 'ffn_dropout': 0.2710303189936548, 'lr': 0.008225551320386045, 'weight_decay': 0.00103097881257981, 'batch_size': 256} - Best Value (CSI): 0.474196 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.362678844726258, 'ffn_dropout': 0.16635293152622824, 'lr': 0.000390125889967722, 'weight_decay': 0.006710255477547039, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 07:30:20,524] Trial 5 pruned. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.331300 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.31271122487459135, 'ffn_dropout': 0.3063844970519128, 'lr': 7.134307139020366e-05, 'weight_decay': 0.001496486958251086, 'batch_size': 256} - Best Value (CSI): 0.474196 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.362678844726258, 'ffn_dropout': 0.16635293152622824, 'lr': 0.000390125889967722, 'weight_decay': 0.006710255477547039, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 07:30:39,789] Trial 6 pruned. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.073201 - Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.31538515577389015, 'ffn_dropout': 0.2874494661457717, 'lr': 0.0067553955792339715, 'weight_decay': 0.01648451400834992, 'batch_size': 256} - Best Value (CSI): 0.474196 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.362678844726258, 'ffn_dropout': 0.16635293152622824, 'lr': 0.000390125889967722, 'weight_decay': 0.006710255477547039, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 07:35:05,802] Trial 7 finished with value: 0.45715506699902786 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19489612347554697, 'ffn_dropout': 0.27471179173444293, 'lr': 0.00020006433814541208, 'weight_decay': 0.0007949635679956494, 'batch_size': 64}. Best is trial 3 with value: 0.4741962384900029. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.457155 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19489612347554697, 'ffn_dropout': 0.27471179173444293, 'lr': 0.00020006433814541208, 'weight_decay': 0.0007949635679956494, 'batch_size': 64} - Best Value (CSI): 0.474196 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.362678844726258, 'ffn_dropout': 0.16635293152622824, 'lr': 0.000390125889967722, 'weight_decay': 0.006710255477547039, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 07:36:43,489] Trial 8 finished with value: 0.2876524298073911 and parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.20374264869932915, 'ffn_dropout': 0.28788110799680894, 'lr': 0.0025910502335220863, 'weight_decay': 0.0003917948823094255, 'batch_size': 256}. Best is trial 3 with value: 0.4741962384900029. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.287652 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.20374264869932915, 'ffn_dropout': 0.28788110799680894, 'lr': 0.0025910502335220863, 'weight_decay': 0.0003917948823094255, 'batch_size': 256} - Best Value (CSI): 0.474196 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.362678844726258, 'ffn_dropout': 0.16635293152622824, 'lr': 0.000390125889967722, 'weight_decay': 0.006710255477547039, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 07:37:54,354] Trial 9 pruned. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.003985 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3963361584101709, 'ffn_dropout': 0.22745698894940455, 'lr': 0.00212288609626765, 'weight_decay': 0.00011607988220984215, 'batch_size': 32} - Best Value (CSI): 0.474196 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.362678844726258, 'ffn_dropout': 0.16635293152622824, 'lr': 0.000390125889967722, 'weight_decay': 0.006710255477547039, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 07:38:33,213] Trial 10 pruned. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.365079 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.10399142241164921, 'ffn_dropout': 0.10335971486429973, 'lr': 7.38016313598997e-05, 'weight_decay': 0.07230209748539067, 'batch_size': 32} - Best Value (CSI): 0.474196 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.362678844726258, 'ffn_dropout': 0.16635293152622824, 'lr': 0.000390125889967722, 'weight_decay': 0.006710255477547039, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 07:41:54,243] Trial 11 finished with value: 0.4674103046460849 and parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.39060177323497614, 'ffn_dropout': 0.3648553313590831, 'lr': 0.0005458589656315063, 'weight_decay': 0.00486527812066804, 'batch_size': 64}. Best is trial 3 with value: 0.4741962384900029. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.467410 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.39060177323497614, 'ffn_dropout': 0.3648553313590831, 'lr': 0.0005458589656315063, 'weight_decay': 0.00486527812066804, 'batch_size': 64} - Best Value (CSI): 0.474196 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.362678844726258, 'ffn_dropout': 0.16635293152622824, 'lr': 0.000390125889967722, 'weight_decay': 0.006710255477547039, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 07:44:07,381] Trial 12 finished with value: 0.467176511103991 and parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2560672688564572, 'ffn_dropout': 0.197451817128118, 'lr': 0.0002701425252678861, 'weight_decay': 0.0036959343395224042, 'batch_size': 64}. Best is trial 3 with value: 0.4741962384900029. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.467177 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2560672688564572, 'ffn_dropout': 0.197451817128118, 'lr': 0.0002701425252678861, 'weight_decay': 0.0036959343395224042, 'batch_size': 64} - Best Value (CSI): 0.474196 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.362678844726258, 'ffn_dropout': 0.16635293152622824, 'lr': 0.000390125889967722, 'weight_decay': 0.006710255477547039, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 07:44:48,751] Trial 13 pruned. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.412318 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3420597134501866, 'ffn_dropout': 0.3535814163694028, 'lr': 0.0010559182681130475, 'weight_decay': 0.0066958710799923694, 'batch_size': 32} - Best Value (CSI): 0.474196 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.362678844726258, 'ffn_dropout': 0.16635293152622824, 'lr': 0.000390125889967722, 'weight_decay': 0.006710255477547039, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 07:45:59,019] Trial 14 pruned. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.422360 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2512379966625318, 'ffn_dropout': 0.1496893730248987, 'lr': 0.00019598652034468706, 'weight_decay': 0.0004140194498585335, 'batch_size': 64} - Best Value (CSI): 0.474196 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.362678844726258, 'ffn_dropout': 0.16635293152622824, 'lr': 0.000390125889967722, 'weight_decay': 0.006710255477547039, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 07:46:48,063] Trial 15 pruned. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.030747 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.35275269625307676, 'ffn_dropout': 0.32605324400674884, 'lr': 0.0010549431116902018, 'weight_decay': 0.002778746637652542, 'batch_size': 32} - Best Value (CSI): 0.474196 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.362678844726258, 'ffn_dropout': 0.16635293152622824, 'lr': 0.000390125889967722, 'weight_decay': 0.006710255477547039, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 07:48:09,740] Trial 16 pruned. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.432203 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.2821037686506863, 'ffn_dropout': 0.3974394873166107, 'lr': 0.00013359016368262052, 'weight_decay': 0.00783926035751152, 'batch_size': 64} - Best Value (CSI): 0.474196 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.362678844726258, 'ffn_dropout': 0.16635293152622824, 'lr': 0.000390125889967722, 'weight_decay': 0.006710255477547039, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 07:49:22,811] Trial 17 pruned. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.367694 - Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.2320225831519145, 'ffn_dropout': 0.242980702327867, 'lr': 0.0003018306608974723, 'weight_decay': 0.002089753189763317, 'batch_size': 32} - Best Value (CSI): 0.474196 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.362678844726258, 'ffn_dropout': 0.16635293152622824, 'lr': 0.000390125889967722, 'weight_decay': 0.006710255477547039, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 07:49:37,439] Trial 18 pruned. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.375994 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.16115813619018382, 'ffn_dropout': 0.22712174825902054, 'lr': 0.00044717001262476494, 'weight_decay': 0.03254284599428779, 'batch_size': 128} - Best Value (CSI): 0.474196 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.362678844726258, 'ffn_dropout': 0.16635293152622824, 'lr': 0.000390125889967722, 'weight_decay': 0.006710255477547039, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 07:50:08,157] Trial 19 pruned. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.370273 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.36016078978870275, 'ffn_dropout': 0.14593893399890512, 'lr': 1.1479295502115612e-05, 'weight_decay': 0.008179087189183025, 'batch_size': 64} - Best Value (CSI): 0.474196 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.362678844726258, 'ffn_dropout': 0.16635293152622824, 'lr': 0.000390125889967722, 'weight_decay': 0.006710255477547039, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 07:51:08,891] Trial 20 pruned. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.383209 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2833297237664411, 'ffn_dropout': 0.21168560160828515, 'lr': 0.0010092554267859717, 'weight_decay': 0.003255463180548007, 'batch_size': 32} - Best Value (CSI): 0.474196 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.362678844726258, 'ffn_dropout': 0.16635293152622824, 'lr': 0.000390125889967722, 'weight_decay': 0.006710255477547039, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 07:51:30,390] Trial 21 pruned. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.399502 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.2156817864410657, 'ffn_dropout': 0.24945179380696025, 'lr': 0.0006121077742300931, 'weight_decay': 0.010331016107316477, 'batch_size': 128} - Best Value (CSI): 0.474196 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.362678844726258, 'ffn_dropout': 0.16635293152622824, 'lr': 0.000390125889967722, 'weight_decay': 0.006710255477547039, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 07:51:51,982] Trial 22 pruned. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.385714 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.22815625277594867, 'ffn_dropout': 0.3179992267013516, 'lr': 0.000467242446905391, 'weight_decay': 0.017319010211914187, 'batch_size': 128} - Best Value (CSI): 0.474196 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.362678844726258, 'ffn_dropout': 0.16635293152622824, 'lr': 0.000390125889967722, 'weight_decay': 0.006710255477547039, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 07:52:10,212] Trial 23 pruned. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.321016 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.17380698991496613, 'ffn_dropout': 0.26648372616411564, 'lr': 0.00011956399263883416, 'weight_decay': 0.02730721670470813, 'batch_size': 128} - Best Value (CSI): 0.474196 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.362678844726258, 'ffn_dropout': 0.16635293152622824, 'lr': 0.000390125889967722, 'weight_decay': 0.006710255477547039, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 07:52:33,391] Trial 24 pruned. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.392954 - Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.24313756274960596, 'ffn_dropout': 0.2553734948181849, 'lr': 0.0007268649219073515, 'weight_decay': 0.00457767780447946, 'batch_size': 128} - Best Value (CSI): 0.474196 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.362678844726258, 'ffn_dropout': 0.16635293152622824, 'lr': 0.000390125889967722, 'weight_decay': 0.006710255477547039, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 07:52:52,784] Trial 25 pruned. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.394531 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.20567698991096273, 'ffn_dropout': 0.287165870989031, 'lr': 0.00033359612387219345, 'weight_decay': 0.012470086675965981, 'batch_size': 128} - Best Value (CSI): 0.474196 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.362678844726258, 'ffn_dropout': 0.16635293152622824, 'lr': 0.000390125889967722, 'weight_decay': 0.006710255477547039, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 07:53:28,018] Trial 26 pruned. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.352507 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.25670861814473506, 'ffn_dropout': 0.23491628384421928, 'lr': 0.0015770516122500429, 'weight_decay': 0.00596414247999668, 'batch_size': 64} - Best Value (CSI): 0.474196 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.362678844726258, 'ffn_dropout': 0.16635293152622824, 'lr': 0.000390125889967722, 'weight_decay': 0.006710255477547039, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 07:54:22,447] Trial 27 pruned. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.004554 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.38105392284643225, 'ffn_dropout': 0.30855561747259685, 'lr': 0.003953526909486609, 'weight_decay': 0.02965986552323307, 'batch_size': 32} - Best Value (CSI): 0.474196 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.362678844726258, 'ffn_dropout': 0.16635293152622824, 'lr': 0.000390125889967722, 'weight_decay': 0.006710255477547039, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 07:54:56,601] Trial 28 pruned. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.406167 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.1864319830001009, 'ffn_dropout': 0.25540913942286314, 'lr': 0.000815693405473862, 'weight_decay': 0.0036929848669349026, 'batch_size': 64} - Best Value (CSI): 0.474196 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.362678844726258, 'ffn_dropout': 0.16635293152622824, 'lr': 0.000390125889967722, 'weight_decay': 0.006710255477547039, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 07:55:15,402] Trial 29 pruned. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.406908 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3102569198316723, 'ffn_dropout': 0.2002687884849375, 'lr': 0.0015843822714020235, 'weight_decay': 0.0019340690991311565, 'batch_size': 128} - Best Value (CSI): 0.474196 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.362678844726258, 'ffn_dropout': 0.16635293152622824, 'lr': 0.000390125889967722, 'weight_decay': 0.006710255477547039, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 08:04:21,154] Trial 30 finished with value: 0.47233101581587933 and parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.14415165648476053, 'ffn_dropout': 0.17912124888067452, 'lr': 4.438241357658025e-05, 'weight_decay': 0.010383044036211425, 'batch_size': 32}. Best is trial 3 with value: 0.4741962384900029. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.472331 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.14415165648476053, 'ffn_dropout': 0.17912124888067452, 'lr': 4.438241357658025e-05, 'weight_decay': 0.010383044036211425, 'batch_size': 32} - Best Value (CSI): 0.474196 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.362678844726258, 'ffn_dropout': 0.16635293152622824, 'lr': 0.000390125889967722, 'weight_decay': 0.006710255477547039, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 08:05:28,516] Trial 31 pruned. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.380293 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1506901478817769, 'ffn_dropout': 0.17305868592264959, 'lr': 3.795483739521149e-05, 'weight_decay': 0.010660862051272044, 'batch_size': 32} - Best Value (CSI): 0.474196 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.362678844726258, 'ffn_dropout': 0.16635293152622824, 'lr': 0.000390125889967722, 'weight_decay': 0.006710255477547039, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 08:13:49,141] Trial 32 finished with value: 0.4741922828834186 and parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.13770834153987738, 'ffn_dropout': 0.17707113415276612, 'lr': 0.00041783771623119957, 'weight_decay': 0.00591066785953918, 'batch_size': 32}. Best is trial 3 with value: 0.4741962384900029. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.474192 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.13770834153987738, 'ffn_dropout': 0.17707113415276612, 'lr': 0.00041783771623119957, 'weight_decay': 0.00591066785953918, 'batch_size': 32} - Best Value (CSI): 0.474196 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.362678844726258, 'ffn_dropout': 0.16635293152622824, 'lr': 0.000390125889967722, 'weight_decay': 0.006710255477547039, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 08:16:34,370] Trial 33 pruned. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.414313 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.14088374043893348, 'ffn_dropout': 0.17987664454419122, 'lr': 0.0004504888858218718, 'weight_decay': 0.007770885902545867, 'batch_size': 32} - Best Value (CSI): 0.474196 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.362678844726258, 'ffn_dropout': 0.16635293152622824, 'lr': 0.000390125889967722, 'weight_decay': 0.006710255477547039, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 08:17:33,296] Trial 34 pruned. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.403226 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.12581685586538152, 'ffn_dropout': 0.15440568785243164, 'lr': 3.0469176490338206e-05, 'weight_decay': 0.005064481959360235, 'batch_size': 32} - Best Value (CSI): 0.474196 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.362678844726258, 'ffn_dropout': 0.16635293152622824, 'lr': 0.000390125889967722, 'weight_decay': 0.006710255477547039, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 08:20:30,415] Trial 35 pruned. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.423963 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1807923638239496, 'ffn_dropout': 0.21596423415828062, 'lr': 0.0002247554176488156, 'weight_decay': 0.0028536234189931392, 'batch_size': 32} - Best Value (CSI): 0.474196 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.362678844726258, 'ffn_dropout': 0.16635293152622824, 'lr': 0.000390125889967722, 'weight_decay': 0.006710255477547039, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 08:21:37,040] Trial 36 pruned. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.324916 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.16182739561352028, 'ffn_dropout': 0.12615926364507254, 'lr': 0.00033540906130910216, 'weight_decay': 0.0012346253178126948, 'batch_size': 32} - Best Value (CSI): 0.474196 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.362678844726258, 'ffn_dropout': 0.16635293152622824, 'lr': 0.000390125889967722, 'weight_decay': 0.006710255477547039, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 08:21:51,230] Trial 37 pruned. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.333128 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.13186156331180623, 'ffn_dropout': 0.18048625482968195, 'lr': 0.00014884285841544232, 'weight_decay': 0.01809399633389842, 'batch_size': 256} - Best Value (CSI): 0.474196 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.362678844726258, 'ffn_dropout': 0.16635293152622824, 'lr': 0.000390125889967722, 'weight_decay': 0.006710255477547039, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 08:22:53,466] Trial 38 pruned. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.409212 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.19301744959967568, 'ffn_dropout': 0.16320027235828408, 'lr': 9.51965011703439e-05, 'weight_decay': 0.0016665544022868206, 'batch_size': 32} - Best Value (CSI): 0.474196 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.362678844726258, 'ffn_dropout': 0.16635293152622824, 'lr': 0.000390125889967722, 'weight_decay': 0.006710255477547039, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 08:23:04,071] Trial 39 pruned. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.221868 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.11507699129683853, 'ffn_dropout': 0.19076285082893188, 'lr': 5.714953390990964e-05, 'weight_decay': 0.0022802547657260774, 'batch_size': 256} - Best Value (CSI): 0.474196 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.362678844726258, 'ffn_dropout': 0.16635293152622824, 'lr': 0.000390125889967722, 'weight_decay': 0.006710255477547039, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 08:31:16,081] Trial 40 finished with value: 0.46870915794904944 and parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.15353824229180524, 'ffn_dropout': 0.13546402616129943, 'lr': 0.0001953106142043923, 'weight_decay': 0.0010469169126827223, 'batch_size': 32}. Best is trial 3 with value: 0.4741962384900029. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.468709 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.15353824229180524, 'ffn_dropout': 0.13546402616129943, 'lr': 0.0001953106142043923, 'weight_decay': 0.0010469169126827223, 'batch_size': 32} - Best Value (CSI): 0.474196 - Best Trial: 3 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.362678844726258, 'ffn_dropout': 0.16635293152622824, 'lr': 0.000390125889967722, 'weight_decay': 0.006710255477547039, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 08:38:35,078] Trial 41 finished with value: 0.47489630797501753 and parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.17275240623937005, 'ffn_dropout': 0.16805135550235922, 'lr': 0.00035176834779108887, 'weight_decay': 0.0117090891310112, 'batch_size': 32}. Best is trial 41 with value: 0.47489630797501753. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.474896 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.17275240623937005, 'ffn_dropout': 0.16805135550235922, 'lr': 0.00035176834779108887, 'weight_decay': 0.0117090891310112, 'batch_size': 32} - Best Value (CSI): 0.474896 - Best Trial: 41 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.17275240623937005, 'ffn_dropout': 0.16805135550235922, 'lr': 0.00035176834779108887, 'weight_decay': 0.0117090891310112, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 08:46:42,272] Trial 42 finished with value: 0.46792737162304726 and parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.174774710862942, 'ffn_dropout': 0.1794951177939058, 'lr': 0.0006009514069944774, 'weight_decay': 0.005982689875678239, 'batch_size': 32}. Best is trial 41 with value: 0.47489630797501753. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.467927 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.174774710862942, 'ffn_dropout': 0.1794951177939058, 'lr': 0.0006009514069944774, 'weight_decay': 0.005982689875678239, 'batch_size': 32} - Best Value (CSI): 0.474896 - Best Trial: 41 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.17275240623937005, 'ffn_dropout': 0.16805135550235922, 'lr': 0.00035176834779108887, 'weight_decay': 0.0117090891310112, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) -[I 2025-12-25 08:51:45,786] Trial 43 pruned. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.473597 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.13641113462579152, 'ffn_dropout': 0.1678934924209093, 'lr': 0.0002883390384109889, 'weight_decay': 0.004416854823620532, 'batch_size': 32} - Best Value (CSI): 0.474896 - Best Trial: 41 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.17275240623937005, 'ffn_dropout': 0.16805135550235922, 'lr': 0.00035176834779108887, 'weight_decay': 0.0117090891310112, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 08:52:37,201] Trial 44 pruned. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.402830 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.14645807556484142, 'ffn_dropout': 0.16152494238879414, 'lr': 0.00041592317390234793, 'weight_decay': 0.013408559981047714, 'batch_size': 32} - Best Value (CSI): 0.474896 - Best Trial: 41 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.17275240623937005, 'ffn_dropout': 0.16805135550235922, 'lr': 0.00035176834779108887, 'weight_decay': 0.0117090891310112, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 09:00:29,792] Trial 45 pruned. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.465353 - Parameters: {'d_token': 224, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.16640470708190203, 'ffn_dropout': 0.1929582985658304, 'lr': 0.00016219445706574633, 'weight_decay': 0.009513317680773918, 'batch_size': 32} - Best Value (CSI): 0.474896 - Best Trial: 41 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.17275240623937005, 'ffn_dropout': 0.16805135550235922, 'lr': 0.00035176834779108887, 'weight_decay': 0.0117090891310112, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 09:00:53,597] Trial 46 pruned. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.410236 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.19727650841022645, 'ffn_dropout': 0.11816209361333756, 'lr': 0.0002589341882173789, 'weight_decay': 0.006315101420884494, 'batch_size': 64} - Best Value (CSI): 0.474896 - Best Trial: 41 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.17275240623937005, 'ffn_dropout': 0.16805135550235922, 'lr': 0.00035176834779108887, 'weight_decay': 0.0117090891310112, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 09:01:05,725] Trial 47 pruned. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.306762 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.10122165181163222, 'ffn_dropout': 0.13911023154261565, 'lr': 0.00035723858771938153, 'weight_decay': 0.0035498453659353934, 'batch_size': 256} - Best Value (CSI): 0.474896 - Best Trial: 41 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.17275240623937005, 'ffn_dropout': 0.16805135550235922, 'lr': 0.00035176834779108887, 'weight_decay': 0.0117090891310112, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) -[I 2025-12-25 09:06:08,396] Trial 48 pruned. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.453364 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.12288786482645203, 'ffn_dropout': 0.15010889413188538, 'lr': 0.00021648099485005597, 'weight_decay': 0.014316252515237845, 'batch_size': 32} - Best Value (CSI): 0.474896 - Best Trial: 41 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.17275240623937005, 'ffn_dropout': 0.16805135550235922, 'lr': 0.00035176834779108887, 'weight_decay': 0.0117090891310112, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 09:11:27,530] Trial 49 finished with value: 0.4706072358288978 and parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.18384403362157248, 'ffn_dropout': 0.20505849351424932, 'lr': 0.0005648941973819628, 'weight_decay': 0.00068204207942196, 'batch_size': 32}. Best is trial 41 with value: 0.47489630797501753. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.470607 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.18384403362157248, 'ffn_dropout': 0.20505849351424932, 'lr': 0.0005648941973819628, 'weight_decay': 0.00068204207942196, 'batch_size': 32} - Best Value (CSI): 0.474896 - Best Trial: 41 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.17275240623937005, 'ffn_dropout': 0.16805135550235922, 'lr': 0.00035176834779108887, 'weight_decay': 0.0117090891310112, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 09:11:49,088] Trial 50 pruned. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.406926 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.15884596421917077, 'ffn_dropout': 0.22440713286696817, 'lr': 0.00011898283718150083, 'weight_decay': 0.008346177808329334, 'batch_size': 64} - Best Value (CSI): 0.474896 - Best Trial: 41 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.17275240623937005, 'ffn_dropout': 0.16805135550235922, 'lr': 0.00035176834779108887, 'weight_decay': 0.0117090891310112, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 09:16:42,465] Trial 51 finished with value: 0.46508084270435623 and parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.1838972626442682, 'ffn_dropout': 0.20688847662621346, 'lr': 0.0005270640240030382, 'weight_decay': 0.0008497010011042979, 'batch_size': 32}. Best is trial 41 with value: 0.47489630797501753. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.465081 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.1838972626442682, 'ffn_dropout': 0.20688847662621346, 'lr': 0.0005270640240030382, 'weight_decay': 0.0008497010011042979, 'batch_size': 32} - Best Value (CSI): 0.474896 - Best Trial: 41 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.17275240623937005, 'ffn_dropout': 0.16805135550235922, 'lr': 0.00035176834779108887, 'weight_decay': 0.0117090891310112, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 09:21:20,787] Trial 52 finished with value: 0.4767043189003746 and parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21325799602620366, 'ffn_dropout': 0.18692403687389716, 'lr': 0.0007382412792826251, 'weight_decay': 0.0005280963619347703, 'batch_size': 32}. Best is trial 52 with value: 0.4767043189003746. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.476704 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21325799602620366, 'ffn_dropout': 0.18692403687389716, 'lr': 0.0007382412792826251, 'weight_decay': 0.0005280963619347703, 'batch_size': 32} - Best Value (CSI): 0.476704 - Best Trial: 52 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21325799602620366, 'ffn_dropout': 0.18692403687389716, 'lr': 0.0007382412792826251, 'weight_decay': 0.0005280963619347703, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 09:22:19,828] Trial 53 pruned. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.003985 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.21170205045078502, 'ffn_dropout': 0.18595134937078941, 'lr': 0.000826669402573001, 'weight_decay': 0.0003022622590249711, 'batch_size': 32} - Best Value (CSI): 0.476704 - Best Trial: 52 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21325799602620366, 'ffn_dropout': 0.18692403687389716, 'lr': 0.0007382412792826251, 'weight_decay': 0.0005280963619347703, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 09:26:51,578] Trial 54 finished with value: 0.47587124323030877 and parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.16826593888757221, 'ffn_dropout': 0.16997226751068456, 'lr': 0.00040909314782382953, 'weight_decay': 0.021242317687803235, 'batch_size': 32}. Best is trial 52 with value: 0.4767043189003746. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.475871 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.16826593888757221, 'ffn_dropout': 0.16997226751068456, 'lr': 0.00040909314782382953, 'weight_decay': 0.021242317687803235, 'batch_size': 32} - Best Value (CSI): 0.476704 - Best Trial: 52 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21325799602620366, 'ffn_dropout': 0.18692403687389716, 'lr': 0.0007382412792826251, 'weight_decay': 0.0005280963619347703, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 09:28:15,558] Trial 55 pruned. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.434077 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.14316059993498464, 'ffn_dropout': 0.16824513375756542, 'lr': 0.00041208899599562545, 'weight_decay': 0.018048190249985295, 'batch_size': 32} - Best Value (CSI): 0.476704 - Best Trial: 52 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21325799602620366, 'ffn_dropout': 0.18692403687389716, 'lr': 0.0007382412792826251, 'weight_decay': 0.0005280963619347703, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 09:29:31,220] Trial 56 pruned. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.411163 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.17229635803634932, 'ffn_dropout': 0.19591713946707037, 'lr': 0.00030494786948894256, 'weight_decay': 0.023613525136676135, 'batch_size': 32} - Best Value (CSI): 0.476704 - Best Trial: 52 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21325799602620366, 'ffn_dropout': 0.18692403687389716, 'lr': 0.0007382412792826251, 'weight_decay': 0.0005280963619347703, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 09:33:57,254] Trial 57 finished with value: 0.470141197160931 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.11257897803928164, 'ffn_dropout': 0.1570752629649038, 'lr': 0.0001770406001148639, 'weight_decay': 0.01141473490834107, 'batch_size': 32}. Best is trial 52 with value: 0.4767043189003746. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.470141 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.11257897803928164, 'ffn_dropout': 0.1570752629649038, 'lr': 0.0001770406001148639, 'weight_decay': 0.01141473490834107, 'batch_size': 32} - Best Value (CSI): 0.476704 - Best Trial: 52 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21325799602620366, 'ffn_dropout': 0.18692403687389716, 'lr': 0.0007382412792826251, 'weight_decay': 0.0005280963619347703, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 09:35:37,058] Trial 58 pruned. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.423077 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.15624015939439462, 'ffn_dropout': 0.17544501888650318, 'lr': 0.0002456573667898298, 'weight_decay': 0.043116257665743264, 'batch_size': 32} - Best Value (CSI): 0.476704 - Best Trial: 52 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21325799602620366, 'ffn_dropout': 0.18692403687389716, 'lr': 0.0007382412792826251, 'weight_decay': 0.0005280963619347703, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 09:40:40,078] Trial 59 finished with value: 0.46848127532810535 and parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1997271824365651, 'ffn_dropout': 0.18930430580960822, 'lr': 0.0006506626669223021, 'weight_decay': 0.009472619018495413, 'batch_size': 32}. Best is trial 52 with value: 0.4767043189003746. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.468481 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1997271824365651, 'ffn_dropout': 0.18930430580960822, 'lr': 0.0006506626669223021, 'weight_decay': 0.009472619018495413, 'batch_size': 32} - Best Value (CSI): 0.476704 - Best Trial: 52 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21325799602620366, 'ffn_dropout': 0.18692403687389716, 'lr': 0.0007382412792826251, 'weight_decay': 0.0005280963619347703, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 09:45:14,397] Trial 60 finished with value: 0.467114254462897 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.16909501846756528, 'ffn_dropout': 0.16110502783403383, 'lr': 0.00038088414746942145, 'weight_decay': 0.020599690508678204, 'batch_size': 32}. Best is trial 52 with value: 0.4767043189003746. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.467114 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.16909501846756528, 'ffn_dropout': 0.16110502783403383, 'lr': 0.00038088414746942145, 'weight_decay': 0.020599690508678204, 'batch_size': 32} - Best Value (CSI): 0.476704 - Best Trial: 52 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21325799602620366, 'ffn_dropout': 0.18692403687389716, 'lr': 0.0007382412792826251, 'weight_decay': 0.0005280963619347703, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 09:48:42,961] Trial 61 finished with value: 0.47215756606491704 and parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.21672617794474255, 'ffn_dropout': 0.17618999740360458, 'lr': 0.0007811337382526331, 'weight_decay': 0.015370058485009247, 'batch_size': 64}. Best is trial 52 with value: 0.4767043189003746. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.472158 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.21672617794474255, 'ffn_dropout': 0.17618999740360458, 'lr': 0.0007811337382526331, 'weight_decay': 0.015370058485009247, 'batch_size': 64} - Best Value (CSI): 0.476704 - Best Trial: 52 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21325799602620366, 'ffn_dropout': 0.18692403687389716, 'lr': 0.0007382412792826251, 'weight_decay': 0.0005280963619347703, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 09:49:36,186] Trial 62 pruned. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.418834 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2289197384011037, 'ffn_dropout': 0.1711279909281566, 'lr': 0.0008513161142791167, 'weight_decay': 0.01352353785740787, 'batch_size': 64} - Best Value (CSI): 0.476704 - Best Trial: 52 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21325799602620366, 'ffn_dropout': 0.18692403687389716, 'lr': 0.0007382412792826251, 'weight_decay': 0.0005280963619347703, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 09:55:58,290] Trial 63 finished with value: 0.47216236834477926 and parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.21760852676668482, 'ffn_dropout': 0.1482198690506053, 'lr': 0.0005073266345707749, 'weight_decay': 0.015837147872110113, 'batch_size': 32}. Best is trial 52 with value: 0.4767043189003746. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.472162 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.21760852676668482, 'ffn_dropout': 0.1482198690506053, 'lr': 0.0005073266345707749, 'weight_decay': 0.015837147872110113, 'batch_size': 32} - Best Value (CSI): 0.476704 - Best Trial: 52 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21325799602620366, 'ffn_dropout': 0.18692403687389716, 'lr': 0.0007382412792826251, 'weight_decay': 0.0005280963619347703, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 10:02:03,164] Trial 64 finished with value: 0.4670365087085717 and parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.19343614180402866, 'ffn_dropout': 0.15330528031360416, 'lr': 0.0005034875126247166, 'weight_decay': 0.0063917444994517295, 'batch_size': 32}. Best is trial 52 with value: 0.4767043189003746. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.467037 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.19343614180402866, 'ffn_dropout': 0.15330528031360416, 'lr': 0.0005034875126247166, 'weight_decay': 0.0063917444994517295, 'batch_size': 32} - Best Value (CSI): 0.476704 - Best Trial: 52 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21325799602620366, 'ffn_dropout': 0.18692403687389716, 'lr': 0.0007382412792826251, 'weight_decay': 0.0005280963619347703, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 10:03:14,929] Trial 65 pruned. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.407306 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.1490279273768902, 'ffn_dropout': 0.14157200461447975, 'lr': 0.00026872678942493775, 'weight_decay': 0.01210373759152832, 'batch_size': 32} - Best Value (CSI): 0.476704 - Best Trial: 52 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21325799602620366, 'ffn_dropout': 0.18692403687389716, 'lr': 0.0007382412792826251, 'weight_decay': 0.0005280963619347703, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 10:04:50,245] Trial 66 pruned. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.390950 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.264951671947516, 'ffn_dropout': 0.14852930995657432, 'lr': 0.0011556695863045225, 'weight_decay': 0.007804141700166611, 'batch_size': 32} - Best Value (CSI): 0.476704 - Best Trial: 52 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21325799602620366, 'ffn_dropout': 0.18692403687389716, 'lr': 0.0007382412792826251, 'weight_decay': 0.0005280963619347703, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 10:06:13,427] Trial 67 pruned. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.414085 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.22222082115633013, 'ffn_dropout': 0.1312929144660041, 'lr': 0.0003866415396820585, 'weight_decay': 0.022999624411080596, 'batch_size': 32} - Best Value (CSI): 0.476704 - Best Trial: 52 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21325799602620366, 'ffn_dropout': 0.18692403687389716, 'lr': 0.0007382412792826251, 'weight_decay': 0.0005280963619347703, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 10:09:58,403] Trial 68 pruned. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.474565 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.21022961672982488, 'ffn_dropout': 0.18551139523151255, 'lr': 0.0006436728891131892, 'weight_decay': 0.009751694485365605, 'batch_size': 32} - Best Value (CSI): 0.476704 - Best Trial: 52 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21325799602620366, 'ffn_dropout': 0.18692403687389716, 'lr': 0.0007382412792826251, 'weight_decay': 0.0005280963619347703, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 10:10:41,655] Trial 69 pruned. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.407227 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.20243002873168053, 'ffn_dropout': 0.19786967487262686, 'lr': 0.0004969315502556393, 'weight_decay': 0.0050337576115472155, 'batch_size': 32} - Best Value (CSI): 0.476704 - Best Trial: 52 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21325799602620366, 'ffn_dropout': 0.18692403687389716, 'lr': 0.0007382412792826251, 'weight_decay': 0.0005280963619347703, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 10:10:52,345] Trial 70 pruned. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.286640 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.24094136223497442, 'ffn_dropout': 0.16223295250560046, 'lr': 0.00020944044294536862, 'weight_decay': 0.0359085340371786, 'batch_size': 256} - Best Value (CSI): 0.476704 - Best Trial: 52 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21325799602620366, 'ffn_dropout': 0.18692403687389716, 'lr': 0.0007382412792826251, 'weight_decay': 0.0005280963619347703, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 10:11:46,654] Trial 71 pruned. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.398018 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.21940016394243123, 'ffn_dropout': 0.17392413208731855, 'lr': 0.000844171034064192, 'weight_decay': 0.016287426331592032, 'batch_size': 64} - Best Value (CSI): 0.476704 - Best Trial: 52 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21325799602620366, 'ffn_dropout': 0.18692403687389716, 'lr': 0.0007382412792826251, 'weight_decay': 0.0005280963619347703, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 10:16:42,195] Trial 72 finished with value: 0.47480951392142706 and parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.21051196322340707, 'ffn_dropout': 0.1451107773424894, 'lr': 0.0004377921353752095, 'weight_decay': 0.01459326427302212, 'batch_size': 32}. Best is trial 52 with value: 0.4767043189003746. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.474810 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.21051196322340707, 'ffn_dropout': 0.1451107773424894, 'lr': 0.0004377921353752095, 'weight_decay': 0.01459326427302212, 'batch_size': 32} - Best Value (CSI): 0.476704 - Best Trial: 52 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21325799602620366, 'ffn_dropout': 0.18692403687389716, 'lr': 0.0007382412792826251, 'weight_decay': 0.0005280963619347703, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 10:21:46,143] Trial 73 finished with value: 0.46827818872682964 and parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.20859338734884372, 'ffn_dropout': 0.14365997966058183, 'lr': 0.0003402250519658842, 'weight_decay': 0.010800545269864657, 'batch_size': 32}. Best is trial 52 with value: 0.4767043189003746. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.468278 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.20859338734884372, 'ffn_dropout': 0.14365997966058183, 'lr': 0.0003402250519658842, 'weight_decay': 0.010800545269864657, 'batch_size': 32} - Best Value (CSI): 0.476704 - Best Trial: 52 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21325799602620366, 'ffn_dropout': 0.18692403687389716, 'lr': 0.0007382412792826251, 'weight_decay': 0.0005280963619347703, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 10:23:20,594] Trial 74 pruned. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.398693 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.17593404486177558, 'ffn_dropout': 0.15669870373430925, 'lr': 0.00044810492499149025, 'weight_decay': 0.007208946764916029, 'batch_size': 32} - Best Value (CSI): 0.476704 - Best Trial: 52 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21325799602620366, 'ffn_dropout': 0.18692403687389716, 'lr': 0.0007382412792826251, 'weight_decay': 0.0005280963619347703, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 10:28:28,825] Trial 75 finished with value: 0.4755241106853168 and parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.1923612880286984, 'ffn_dropout': 0.12300837171626129, 'lr': 0.0003040983701920279, 'weight_decay': 0.018851813827069453, 'batch_size': 32}. Best is trial 52 with value: 0.4767043189003746. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.475524 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.1923612880286984, 'ffn_dropout': 0.12300837171626129, 'lr': 0.0003040983701920279, 'weight_decay': 0.018851813827069453, 'batch_size': 32} - Best Value (CSI): 0.476704 - Best Trial: 52 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21325799602620366, 'ffn_dropout': 0.18692403687389716, 'lr': 0.0007382412792826251, 'weight_decay': 0.0005280963619347703, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 10:34:10,893] Trial 76 finished with value: 0.47408744605395864 and parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.19107471790904815, 'ffn_dropout': 0.11352957097513591, 'lr': 0.00028263708478297786, 'weight_decay': 0.019593569330121637, 'batch_size': 32}. Best is trial 52 with value: 0.4767043189003746. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.474087 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.19107471790904815, 'ffn_dropout': 0.11352957097513591, 'lr': 0.00028263708478297786, 'weight_decay': 0.019593569330121637, 'batch_size': 32} - Best Value (CSI): 0.476704 - Best Trial: 52 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21325799602620366, 'ffn_dropout': 0.18692403687389716, 'lr': 0.0007382412792826251, 'weight_decay': 0.0005280963619347703, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 10:38:58,842] Trial 77 finished with value: 0.48424711598330084 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19167241349972552, 'ffn_dropout': 0.10372384139481815, 'lr': 0.0003028578585093515, 'weight_decay': 0.021302792376896054, 'batch_size': 32}. Best is trial 77 with value: 0.48424711598330084. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.484247 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19167241349972552, 'ffn_dropout': 0.10372384139481815, 'lr': 0.0003028578585093515, 'weight_decay': 0.021302792376896054, 'batch_size': 32} - Best Value (CSI): 0.484247 - Best Trial: 77 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19167241349972552, 'ffn_dropout': 0.10372384139481815, 'lr': 0.0003028578585093515, 'weight_decay': 0.021302792376896054, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 10:40:41,185] Trial 78 pruned. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.402015 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.18776908347305754, 'ffn_dropout': 0.10569273168699556, 'lr': 0.0003176482264087263, 'weight_decay': 0.02718758232469967, 'batch_size': 32} - Best Value (CSI): 0.484247 - Best Trial: 77 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19167241349972552, 'ffn_dropout': 0.10372384139481815, 'lr': 0.0003028578585093515, 'weight_decay': 0.021302792376896054, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 10:40:57,102] Trial 79 pruned. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.370020 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2034385157216474, 'ffn_dropout': 0.12649229504665455, 'lr': 0.00025115658291628864, 'weight_decay': 0.023089493511241073, 'batch_size': 128} - Best Value (CSI): 0.484247 - Best Trial: 77 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19167241349972552, 'ffn_dropout': 0.10372384139481815, 'lr': 0.0003028578585093515, 'weight_decay': 0.021302792376896054, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) -[I 2025-12-25 10:44:13,775] Trial 80 pruned. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.448390 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.16225353436613235, 'ffn_dropout': 0.13536801343459398, 'lr': 0.0004012908310444893, 'weight_decay': 0.012626445356471653, 'batch_size': 32} - Best Value (CSI): 0.484247 - Best Trial: 77 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19167241349972552, 'ffn_dropout': 0.10372384139481815, 'lr': 0.0003028578585093515, 'weight_decay': 0.021302792376896054, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 10:50:31,225] Trial 81 finished with value: 0.4696611250421601 and parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.19180948867785538, 'ffn_dropout': 0.11368850932107591, 'lr': 0.0002993578369308809, 'weight_decay': 0.01792718639888758, 'batch_size': 32}. Best is trial 77 with value: 0.48424711598330084. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.469661 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.19180948867785538, 'ffn_dropout': 0.11368850932107591, 'lr': 0.0002993578369308809, 'weight_decay': 0.01792718639888758, 'batch_size': 32} - Best Value (CSI): 0.484247 - Best Trial: 77 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19167241349972552, 'ffn_dropout': 0.10372384139481815, 'lr': 0.0003028578585093515, 'weight_decay': 0.021302792376896054, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) -[I 2025-12-25 10:54:42,780] Trial 82 pruned. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.467401 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.1809485470976483, 'ffn_dropout': 0.10249254161934479, 'lr': 0.00022107718262492018, 'weight_decay': 0.020088343505239862, 'batch_size': 32} - Best Value (CSI): 0.484247 - Best Trial: 77 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19167241349972552, 'ffn_dropout': 0.10372384139481815, 'lr': 0.0003028578585093515, 'weight_decay': 0.021302792376896054, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 10:56:58,251] Trial 83 pruned. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.412613 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.19081110679119254, 'ffn_dropout': 0.12315706252613781, 'lr': 0.00035421426160260676, 'weight_decay': 0.03649246787563337, 'batch_size': 32} - Best Value (CSI): 0.484247 - Best Trial: 77 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19167241349972552, 'ffn_dropout': 0.10372384139481815, 'lr': 0.0003028578585093515, 'weight_decay': 0.021302792376896054, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 11:05:18,951] Trial 84 finished with value: 0.47443205661249777 and parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.1986786604478145, 'ffn_dropout': 0.11592933504275221, 'lr': 0.0006651440078053198, 'weight_decay': 0.014416131405320028, 'batch_size': 32}. Best is trial 77 with value: 0.48424711598330084. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.474432 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.1986786604478145, 'ffn_dropout': 0.11592933504275221, 'lr': 0.0006651440078053198, 'weight_decay': 0.014416131405320028, 'batch_size': 32} - Best Value (CSI): 0.484247 - Best Trial: 77 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19167241349972552, 'ffn_dropout': 0.10372384139481815, 'lr': 0.0003028578585093515, 'weight_decay': 0.021302792376896054, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 11:06:17,244] Trial 85 pruned. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.407882 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19940983281010446, 'ffn_dropout': 0.1359556127792862, 'lr': 0.0006764498715365083, 'weight_decay': 0.00889456675938438, 'batch_size': 32} - Best Value (CSI): 0.484247 - Best Trial: 77 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19167241349972552, 'ffn_dropout': 0.10372384139481815, 'lr': 0.0003028578585093515, 'weight_decay': 0.021302792376896054, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) -[I 2025-12-25 11:11:44,400] Trial 86 pruned. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.439406 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.17721354181082535, 'ffn_dropout': 0.12031437749584363, 'lr': 0.0005809995517192802, 'weight_decay': 0.013936574546455947, 'batch_size': 32} - Best Value (CSI): 0.484247 - Best Trial: 77 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19167241349972552, 'ffn_dropout': 0.10372384139481815, 'lr': 0.0003028578585093515, 'weight_decay': 0.021302792376896054, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 11:12:01,198] Trial 87 pruned. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.344327 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.22562192884621202, 'ffn_dropout': 0.12826809775720618, 'lr': 0.000718623253348669, 'weight_decay': 0.011562817003861118, 'batch_size': 256} - Best Value (CSI): 0.484247 - Best Trial: 77 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19167241349972552, 'ffn_dropout': 0.10372384139481815, 'lr': 0.0003028578585093515, 'weight_decay': 0.021302792376896054, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 11:14:10,907] Trial 88 pruned. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.398382 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.20982054838799044, 'ffn_dropout': 0.10847548596318767, 'lr': 0.000469609555784295, 'weight_decay': 0.007136145290084126, 'batch_size': 32} - Best Value (CSI): 0.484247 - Best Trial: 77 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19167241349972552, 'ffn_dropout': 0.10372384139481815, 'lr': 0.0003028578585093515, 'weight_decay': 0.021302792376896054, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 11:15:39,138] Trial 89 pruned. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.400366 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.16761758942573363, 'ffn_dropout': 0.1428703944081191, 'lr': 0.0005707263523059709, 'weight_decay': 0.005678884872657404, 'batch_size': 32} - Best Value (CSI): 0.484247 - Best Trial: 77 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19167241349972552, 'ffn_dropout': 0.10372384139481815, 'lr': 0.0003028578585093515, 'weight_decay': 0.021302792376896054, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 11:17:50,466] Trial 90 pruned. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.412402 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.18425764912876466, 'ffn_dropout': 0.11930863166878838, 'lr': 0.0004150328634845637, 'weight_decay': 0.0041874734907828256, 'batch_size': 32} - Best Value (CSI): 0.484247 - Best Trial: 77 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19167241349972552, 'ffn_dropout': 0.10372384139481815, 'lr': 0.0003028578585093515, 'weight_decay': 0.021302792376896054, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 11:26:00,595] Trial 91 finished with value: 0.46749239582246105 and parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.19940890445496326, 'ffn_dropout': 0.10036115168921073, 'lr': 0.0002986310136067908, 'weight_decay': 0.015985139790496167, 'batch_size': 32}. Best is trial 77 with value: 0.48424711598330084. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.467492 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.19940890445496326, 'ffn_dropout': 0.10036115168921073, 'lr': 0.0002986310136067908, 'weight_decay': 0.015985139790496167, 'batch_size': 32} - Best Value (CSI): 0.484247 - Best Trial: 77 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19167241349972552, 'ffn_dropout': 0.10372384139481815, 'lr': 0.0003028578585093515, 'weight_decay': 0.021302792376896054, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 11:28:13,282] Trial 92 pruned. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.410394 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.23453409652183138, 'ffn_dropout': 0.116477104822192, 'lr': 0.00025678842146691994, 'weight_decay': 0.01953158683838399, 'batch_size': 32} - Best Value (CSI): 0.484247 - Best Trial: 77 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19167241349972552, 'ffn_dropout': 0.10372384139481815, 'lr': 0.0003028578585093515, 'weight_decay': 0.021302792376896054, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 11:30:26,671] Trial 93 pruned. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.443309 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.19005011249425105, 'ffn_dropout': 0.11340889945795947, 'lr': 0.00018384728170315657, 'weight_decay': 0.008586111283148509, 'batch_size': 32} - Best Value (CSI): 0.484247 - Best Trial: 77 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19167241349972552, 'ffn_dropout': 0.10372384139481815, 'lr': 0.0003028578585093515, 'weight_decay': 0.021302792376896054, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) -[I 2025-12-25 11:35:16,523] Trial 94 pruned. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.461011 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.15508224428095263, 'ffn_dropout': 0.13215937397791927, 'lr': 0.0003692000229834178, 'weight_decay': 0.01417897752926101, 'batch_size': 32} - Best Value (CSI): 0.484247 - Best Trial: 77 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19167241349972552, 'ffn_dropout': 0.10372384139481815, 'lr': 0.0003028578585093515, 'weight_decay': 0.021302792376896054, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 11:37:35,530] Trial 95 pruned. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.407008 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.17695238863133247, 'ffn_dropout': 0.11194555321594793, 'lr': 0.00046918684129386944, 'weight_decay': 0.023702106986033818, 'batch_size': 32} - Best Value (CSI): 0.484247 - Best Trial: 77 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19167241349972552, 'ffn_dropout': 0.10372384139481815, 'lr': 0.0003028578585093515, 'weight_decay': 0.021302792376896054, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 11:38:12,470] Trial 96 pruned. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.399676 - Parameters: {'d_token': 256, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.2056455273627931, 'ffn_dropout': 0.10830628174827617, 'lr': 0.0003417369418361361, 'weight_decay': 0.010376213709983964, 'batch_size': 128} - Best Value (CSI): 0.484247 - Best Trial: 77 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19167241349972552, 'ffn_dropout': 0.10372384139481815, 'lr': 0.0003028578585093515, 'weight_decay': 0.021302792376896054, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 11:39:10,811] Trial 97 pruned. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.397579 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.16849895405128704, 'ffn_dropout': 0.12698737769200627, 'lr': 0.00028164747844708506, 'weight_decay': 0.026332905679638096, 'batch_size': 32} - Best Value (CSI): 0.484247 - Best Trial: 77 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19167241349972552, 'ffn_dropout': 0.10372384139481815, 'lr': 0.0003028578585093515, 'weight_decay': 0.021302792376896054, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 1.3233333333333333, 1: 1.3233333333333333, 2: 0.6717428087986463} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 1.299764705882353, 1: 1.299764705882353, 2: 0.6843409316154608} (클래스별 샘플 수: {0: 8500, 1: 8500, 2: 16144}) -[I 2025-12-25 11:44:49,412] Trial 98 finished with value: 0.4654213457732255 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.21464572873892457, 'ffn_dropout': 0.15254758824869638, 'lr': 0.00023235151528820596, 'weight_decay': 0.019680100497598996, 'batch_size': 32}. Best is trial 77 with value: 0.48424711598330084. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.465421 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.21464572873892457, 'ffn_dropout': 0.15254758824869638, 'lr': 0.00023235151528820596, 'weight_decay': 0.019680100497598996, 'batch_size': 32} - Best Value (CSI): 0.484247 - Best Trial: 77 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19167241349972552, 'ffn_dropout': 0.10372384139481815, 'lr': 0.0003028578585093515, 'weight_decay': 0.021302792376896054, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3205, 1: 1.3205, 2: 0.6732092786133062} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15692}) -[I 2025-12-25 11:46:25,756] Trial 99 pruned. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.412636 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.19258008058013176, 'ffn_dropout': 0.13977188874034077, 'lr': 0.0006218161772693334, 'weight_decay': 0.012113758350049833, 'batch_size': 32} - Best Value (CSI): 0.484247 - Best Trial: 77 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19167241349972552, 'ffn_dropout': 0.10372384139481815, 'lr': 0.0003028578585093515, 'weight_decay': 0.021302792376896054, 'batch_size': 32} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.4842 -Best Hyperparameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19167241349972552, 'ffn_dropout': 0.10372384139481815, 'lr': 0.0003028578585093515, 'weight_decay': 0.021302792376896054, 'batch_size': 32} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.4720 - - 최종 CSI: 0.4126 - - 최고 CSI: 0.4842 - - 최저 CSI: 0.0040 - - 평균 CSI: 0.3969 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/ft_transformer_smote_gwangju_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 20, Best CSI: 0.4341 - Fold 1 학습 완료 (검증 CSI: 0.4341) -Fold 2 학습 중... - Early stopping at epoch 23, Best CSI: 0.4934 - Fold 2 학습 완료 (검증 CSI: 0.4934) -Fold 3 학습 중... - Early stopping at epoch 32, Best CSI: 0.4950 - Fold 3 학습 완료 (검증 CSI: 0.4950) - -모든 모델 저장 완료: ../save_model/ft_transformer_optima/ft_transformer_smote_gwangju.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/ft_transformer_optima/scaler/ft_transformer_smote_gwangju_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: ../save_model/ft_transformer_optima/ft_transformer_smote_gwangju.pkl - -✓ 완료: ft_transformer_smote/ft_transformer_smote_gwangju.py (소요 시간: 16771초) - ----------------------------------------- -실행 중: ft_transformer_smote/ft_transformer_smote_incheon.py -시작 시간: 2025-12-25 11:52:53 ----------------------------------------- -[I 2025-12-25 11:52:54,382] A new study created in memory with name: no-name-cb5c8bfa-43e3-46af-9b80-e0fd8e5b12d8 - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 11:57:43,096] Trial 0 finished with value: 0.5290135641452779 and parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.35241299216126, 'ffn_dropout': 0.10064334052685374, 'lr': 3.7468220904137635e-05, 'weight_decay': 0.025011323959777416, 'batch_size': 64}. Best is trial 0 with value: 0.5290135641452779. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.529014 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.35241299216126, 'ffn_dropout': 0.10064334052685374, 'lr': 3.7468220904137635e-05, 'weight_decay': 0.025011323959777416, 'batch_size': 64} - Best Value (CSI): 0.529014 - Best Trial: 0 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.35241299216126, 'ffn_dropout': 0.10064334052685374, 'lr': 3.7468220904137635e-05, 'weight_decay': 0.025011323959777416, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 12:05:26,036] Trial 1 finished with value: 0.5600702236157239 and parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.33101932441058307, 'ffn_dropout': 0.1869711092937486, 'lr': 0.00039510549155000066, 'weight_decay': 0.0003981847623162329, 'batch_size': 32}. Best is trial 1 with value: 0.5600702236157239. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.560070 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.33101932441058307, 'ffn_dropout': 0.1869711092937486, 'lr': 0.00039510549155000066, 'weight_decay': 0.0003981847623162329, 'batch_size': 32} - Best Value (CSI): 0.560070 - Best Trial: 1 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.33101932441058307, 'ffn_dropout': 0.1869711092937486, 'lr': 0.00039510549155000066, 'weight_decay': 0.0003981847623162329, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 12:11:35,040] Trial 2 finished with value: 0.5544745460046895 and parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1106274776801292, 'ffn_dropout': 0.33967281595489207, 'lr': 0.00027292830958530127, 'weight_decay': 0.059593685385707605, 'batch_size': 64}. Best is trial 1 with value: 0.5600702236157239. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.554475 - Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1106274776801292, 'ffn_dropout': 0.33967281595489207, 'lr': 0.00027292830958530127, 'weight_decay': 0.059593685385707605, 'batch_size': 64} - Best Value (CSI): 0.560070 - Best Trial: 1 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.33101932441058307, 'ffn_dropout': 0.1869711092937486, 'lr': 0.00039510549155000066, 'weight_decay': 0.0003981847623162329, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 12:17:40,164] Trial 3 finished with value: 0.5602589539896052 and parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.26479143883103207, 'ffn_dropout': 0.204776298692791, 'lr': 0.0001984180335264211, 'weight_decay': 0.00015250523037228518, 'batch_size': 32}. Best is trial 3 with value: 0.5602589539896052. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.560259 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.26479143883103207, 'ffn_dropout': 0.204776298692791, 'lr': 0.0001984180335264211, 'weight_decay': 0.00015250523037228518, 'batch_size': 32} - Best Value (CSI): 0.560259 - Best Trial: 3 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.26479143883103207, 'ffn_dropout': 0.204776298692791, 'lr': 0.0001984180335264211, 'weight_decay': 0.00015250523037228518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 12:19:12,903] Trial 4 finished with value: 0.4055188140210806 and parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1518640214965258, 'ffn_dropout': 0.26041961834996685, 'lr': 0.00011711607623822504, 'weight_decay': 0.011270438687092247, 'batch_size': 256}. Best is trial 3 with value: 0.5602589539896052. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.405519 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1518640214965258, 'ffn_dropout': 0.26041961834996685, 'lr': 0.00011711607623822504, 'weight_decay': 0.011270438687092247, 'batch_size': 256} - Best Value (CSI): 0.560259 - Best Trial: 3 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.26479143883103207, 'ffn_dropout': 0.204776298692791, 'lr': 0.0001984180335264211, 'weight_decay': 0.00015250523037228518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 12:20:04,889] Trial 5 pruned. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.475610 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.2844941412106118, 'ffn_dropout': 0.16265289992697096, 'lr': 1.873213436424764e-05, 'weight_decay': 0.00020809132273903782, 'batch_size': 64} - Best Value (CSI): 0.560259 - Best Trial: 3 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.26479143883103207, 'ffn_dropout': 0.204776298692791, 'lr': 0.0001984180335264211, 'weight_decay': 0.00015250523037228518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 12:25:21,322] Trial 6 finished with value: 0.5602051847200396 and parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.25437256535572816, 'ffn_dropout': 0.39566134640211525, 'lr': 0.0004970604231220774, 'weight_decay': 0.00044099003206331277, 'batch_size': 32}. Best is trial 3 with value: 0.5602589539896052. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.560205 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.25437256535572816, 'ffn_dropout': 0.39566134640211525, 'lr': 0.0004970604231220774, 'weight_decay': 0.00044099003206331277, 'batch_size': 32} - Best Value (CSI): 0.560259 - Best Trial: 3 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.26479143883103207, 'ffn_dropout': 0.204776298692791, 'lr': 0.0001984180335264211, 'weight_decay': 0.00015250523037228518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 12:25:49,133] Trial 7 pruned. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.508005 - Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.3222234362382693, 'ffn_dropout': 0.3828624786203374, 'lr': 3.429561287552719e-05, 'weight_decay': 0.015360563039303806, 'batch_size': 128} - Best Value (CSI): 0.560259 - Best Trial: 3 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.26479143883103207, 'ffn_dropout': 0.204776298692791, 'lr': 0.0001984180335264211, 'weight_decay': 0.00015250523037228518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 12:26:58,983] Trial 8 pruned. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.017077 - Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.1659907157885946, 'ffn_dropout': 0.24031970715043294, 'lr': 0.005566488246860429, 'weight_decay': 0.07603462944011716, 'batch_size': 32} - Best Value (CSI): 0.560259 - Best Trial: 3 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.26479143883103207, 'ffn_dropout': 0.204776298692791, 'lr': 0.0001984180335264211, 'weight_decay': 0.00015250523037228518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 12:27:38,572] Trial 9 pruned. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.324001 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.16216796303363837, 'ffn_dropout': 0.313880083861369, 'lr': 0.002099154316627524, 'weight_decay': 0.0055925748185883355, 'batch_size': 32} - Best Value (CSI): 0.560259 - Best Trial: 3 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.26479143883103207, 'ffn_dropout': 0.204776298692791, 'lr': 0.0001984180335264211, 'weight_decay': 0.00015250523037228518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 12:27:51,890] Trial 10 pruned. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.451440 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.38470484735032845, 'ffn_dropout': 0.24099124318371903, 'lr': 1.284353477693741e-05, 'weight_decay': 0.00010225657857021053, 'batch_size': 128} - Best Value (CSI): 0.560259 - Best Trial: 3 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.26479143883103207, 'ffn_dropout': 0.204776298692791, 'lr': 0.0001984180335264211, 'weight_decay': 0.00015250523037228518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 12:35:23,748] Trial 11 finished with value: 0.5576349002084688 and parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2430750095590928, 'ffn_dropout': 0.3945484452764427, 'lr': 0.0007429217112733956, 'weight_decay': 0.0007958348756277548, 'batch_size': 32}. Best is trial 3 with value: 0.5602589539896052. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.557635 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2430750095590928, 'ffn_dropout': 0.3945484452764427, 'lr': 0.0007429217112733956, 'weight_decay': 0.0007958348756277548, 'batch_size': 32} - Best Value (CSI): 0.560259 - Best Trial: 3 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.26479143883103207, 'ffn_dropout': 0.204776298692791, 'lr': 0.0001984180335264211, 'weight_decay': 0.00015250523037228518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 12:40:43,290] Trial 12 finished with value: 0.5502138583647628 and parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.25150701299946476, 'ffn_dropout': 0.3148413010949642, 'lr': 0.00013610048719266273, 'weight_decay': 0.0009742064848253665, 'batch_size': 32}. Best is trial 3 with value: 0.5602589539896052. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.550214 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.25150701299946476, 'ffn_dropout': 0.3148413010949642, 'lr': 0.00013610048719266273, 'weight_decay': 0.0009742064848253665, 'batch_size': 32} - Best Value (CSI): 0.560259 - Best Trial: 3 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.26479143883103207, 'ffn_dropout': 0.204776298692791, 'lr': 0.0001984180335264211, 'weight_decay': 0.00015250523037228518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 12:40:54,070] Trial 13 pruned. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.457543 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.22894109997296452, 'ffn_dropout': 0.39930508116941676, 'lr': 0.0012199138300010397, 'weight_decay': 0.001209405258539608, 'batch_size': 256} - Best Value (CSI): 0.560259 - Best Trial: 3 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.26479143883103207, 'ffn_dropout': 0.204776298692791, 'lr': 0.0001984180335264211, 'weight_decay': 0.00015250523037228518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 12:45:49,208] Trial 14 finished with value: 0.5518322538377599 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2858825942793524, 'ffn_dropout': 0.3457258989477239, 'lr': 0.00016756513132053067, 'weight_decay': 0.00010090051005844714, 'batch_size': 32}. Best is trial 3 with value: 0.5602589539896052. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.551832 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2858825942793524, 'ffn_dropout': 0.3457258989477239, 'lr': 0.00016756513132053067, 'weight_decay': 0.00010090051005844714, 'batch_size': 32} - Best Value (CSI): 0.560259 - Best Trial: 3 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.26479143883103207, 'ffn_dropout': 0.204776298692791, 'lr': 0.0001984180335264211, 'weight_decay': 0.00015250523037228518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 12:51:59,226] Trial 15 finished with value: 0.5566821651935685 and parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22183529169096108, 'ffn_dropout': 0.28304135442567163, 'lr': 0.000574420562043957, 'weight_decay': 0.00032913850704070985, 'batch_size': 32}. Best is trial 3 with value: 0.5602589539896052. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.556682 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22183529169096108, 'ffn_dropout': 0.28304135442567163, 'lr': 0.000574420562043957, 'weight_decay': 0.00032913850704070985, 'batch_size': 32} - Best Value (CSI): 0.560259 - Best Trial: 3 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.26479143883103207, 'ffn_dropout': 0.204776298692791, 'lr': 0.0001984180335264211, 'weight_decay': 0.00015250523037228518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 12:52:52,799] Trial 16 pruned. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.20456326141997463, 'ffn_dropout': 0.20139299976287517, 'lr': 0.0016106176442438713, 'weight_decay': 0.0021043452176577144, 'batch_size': 32} - Best Value (CSI): 0.560259 - Best Trial: 3 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.26479143883103207, 'ffn_dropout': 0.204776298692791, 'lr': 0.0001984180335264211, 'weight_decay': 0.00015250523037228518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 12:53:06,061] Trial 17 pruned. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.381530 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2733270898020459, 'ffn_dropout': 0.2802070074001712, 'lr': 8.820522586520798e-05, 'weight_decay': 0.0004543996354629352, 'batch_size': 256} - Best Value (CSI): 0.560259 - Best Trial: 3 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.26479143883103207, 'ffn_dropout': 0.204776298692791, 'lr': 0.0001984180335264211, 'weight_decay': 0.00015250523037228518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 12:53:28,313] Trial 18 pruned. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.524087 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.20196313741811167, 'ffn_dropout': 0.3634376777003573, 'lr': 0.000292114257882763, 'weight_decay': 0.00021850227823046273, 'batch_size': 128} - Best Value (CSI): 0.560259 - Best Trial: 3 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.26479143883103207, 'ffn_dropout': 0.204776298692791, 'lr': 0.0001984180335264211, 'weight_decay': 0.00015250523037228518, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 13:02:12,148] Trial 19 finished with value: 0.5644204174525339 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.30833195889165943, 'ffn_dropout': 0.3609460480143811, 'lr': 0.0008207310230466623, 'weight_decay': 0.0026850151897298475, 'batch_size': 32}. Best is trial 19 with value: 0.5644204174525339. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.564420 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.30833195889165943, 'ffn_dropout': 0.3609460480143811, 'lr': 0.0008207310230466623, 'weight_decay': 0.0026850151897298475, 'batch_size': 32} - Best Value (CSI): 0.564420 - Best Trial: 19 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.30833195889165943, 'ffn_dropout': 0.3609460480143811, 'lr': 0.0008207310230466623, 'weight_decay': 0.0026850151897298475, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 13:03:40,240] Trial 20 pruned. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.017077 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3001059297490968, 'ffn_dropout': 0.3239281901197215, 'lr': 0.008823089739492043, 'weight_decay': 0.004002080172140601, 'batch_size': 32} - Best Value (CSI): 0.564420 - Best Trial: 19 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.30833195889165943, 'ffn_dropout': 0.3609460480143811, 'lr': 0.0008207310230466623, 'weight_decay': 0.0026850151897298475, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 13:11:42,394] Trial 21 finished with value: 0.5563199450364734 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.26221030045102683, 'ffn_dropout': 0.37146308195833966, 'lr': 0.0007281495999689204, 'weight_decay': 0.0007199490889444567, 'batch_size': 32}. Best is trial 19 with value: 0.5644204174525339. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.556320 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.26221030045102683, 'ffn_dropout': 0.37146308195833966, 'lr': 0.0007281495999689204, 'weight_decay': 0.0007199490889444567, 'batch_size': 32} - Best Value (CSI): 0.564420 - Best Trial: 19 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.30833195889165943, 'ffn_dropout': 0.3609460480143811, 'lr': 0.0008207310230466623, 'weight_decay': 0.0026850151897298475, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 13:16:51,779] Trial 22 finished with value: 0.551226455126777 and parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.30630580718669626, 'ffn_dropout': 0.35901055134797577, 'lr': 0.00023132303424030544, 'weight_decay': 0.001958361228478509, 'batch_size': 32}. Best is trial 19 with value: 0.5644204174525339. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.551226 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.30630580718669626, 'ffn_dropout': 0.35901055134797577, 'lr': 0.00023132303424030544, 'weight_decay': 0.001958361228478509, 'batch_size': 32} - Best Value (CSI): 0.564420 - Best Trial: 19 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.30833195889165943, 'ffn_dropout': 0.3609460480143811, 'lr': 0.0008207310230466623, 'weight_decay': 0.0026850151897298475, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 13:21:35,865] Trial 23 finished with value: 0.552644045295305 and parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2719661514568396, 'ffn_dropout': 0.37232982626535005, 'lr': 0.0004799355599181699, 'weight_decay': 0.0017230013711211738, 'batch_size': 32}. Best is trial 19 with value: 0.5644204174525339. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.552644 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2719661514568396, 'ffn_dropout': 0.37232982626535005, 'lr': 0.0004799355599181699, 'weight_decay': 0.0017230013711211738, 'batch_size': 32} - Best Value (CSI): 0.564420 - Best Trial: 19 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.30833195889165943, 'ffn_dropout': 0.3609460480143811, 'lr': 0.0008207310230466623, 'weight_decay': 0.0026850151897298475, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 13:22:52,023] Trial 24 pruned. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.521585 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2466659861082474, 'ffn_dropout': 0.34433708216791237, 'lr': 0.001031109761704499, 'weight_decay': 0.0005674789716822204, 'batch_size': 32} - Best Value (CSI): 0.564420 - Best Trial: 19 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.30833195889165943, 'ffn_dropout': 0.3609460480143811, 'lr': 0.0008207310230466623, 'weight_decay': 0.0026850151897298475, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 13:24:17,828] Trial 25 pruned. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.30272146458275484, 'ffn_dropout': 0.3857698285495125, 'lr': 0.002533533914268958, 'weight_decay': 0.00022533325176231892, 'batch_size': 32} - Best Value (CSI): 0.564420 - Best Trial: 19 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.30833195889165943, 'ffn_dropout': 0.3609460480143811, 'lr': 0.0008207310230466623, 'weight_decay': 0.0026850151897298475, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 13:28:48,949] Trial 26 finished with value: 0.5468510370898504 and parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3345414860186212, 'ffn_dropout': 0.395039898135807, 'lr': 0.00037822865787097486, 'weight_decay': 0.001113996039192389, 'batch_size': 64}. Best is trial 19 with value: 0.5644204174525339. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.546851 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3345414860186212, 'ffn_dropout': 0.395039898135807, 'lr': 0.00037822865787097486, 'weight_decay': 0.001113996039192389, 'batch_size': 64} - Best Value (CSI): 0.564420 - Best Trial: 19 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.30833195889165943, 'ffn_dropout': 0.3609460480143811, 'lr': 0.0008207310230466623, 'weight_decay': 0.0026850151897298475, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 13:29:18,833] Trial 27 pruned. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.516563 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2576515410171349, 'ffn_dropout': 0.35993424768783316, 'lr': 0.0007525084106910842, 'weight_decay': 0.0032915997662603578, 'batch_size': 128} - Best Value (CSI): 0.564420 - Best Trial: 19 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.30833195889165943, 'ffn_dropout': 0.3609460480143811, 'lr': 0.0008207310230466623, 'weight_decay': 0.0026850151897298475, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 13:29:30,332] Trial 28 pruned. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.389287 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.28562292262454997, 'ffn_dropout': 0.2925591964338915, 'lr': 7.334630365796853e-05, 'weight_decay': 0.0006062687831285982, 'batch_size': 256} - Best Value (CSI): 0.564420 - Best Trial: 19 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.30833195889165943, 'ffn_dropout': 0.3609460480143811, 'lr': 0.0008207310230466623, 'weight_decay': 0.0026850151897298475, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 13:30:11,224] Trial 29 pruned. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.477332 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.35054071662623165, 'ffn_dropout': 0.15454589776632924, 'lr': 0.0002084639299169338, 'weight_decay': 0.0057563803910018205, 'batch_size': 64} - Best Value (CSI): 0.564420 - Best Trial: 19 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.30833195889165943, 'ffn_dropout': 0.3609460480143811, 'lr': 0.0008207310230466623, 'weight_decay': 0.0026850151897298475, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 13:38:06,350] Trial 30 finished with value: 0.5674050423289939 and parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32}. Best is trial 30 with value: 0.5674050423289939. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.567405 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 13:44:35,073] Trial 31 finished with value: 0.5594214775248312 and parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3757209783601495, 'ffn_dropout': 0.14051508053271658, 'lr': 0.00038277646091875985, 'weight_decay': 0.0003387322668299275, 'batch_size': 32}. Best is trial 30 with value: 0.5674050423289939. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.559421 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3757209783601495, 'ffn_dropout': 0.14051508053271658, 'lr': 0.00038277646091875985, 'weight_decay': 0.0003387322668299275, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 13:52:41,358] Trial 32 finished with value: 0.566603336103756 and parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.36978506400939287, 'ffn_dropout': 0.20862049762767415, 'lr': 0.00048604332766457074, 'weight_decay': 0.00030420784277443875, 'batch_size': 32}. Best is trial 30 with value: 0.5674050423289939. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.566603 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.36978506400939287, 'ffn_dropout': 0.20862049762767415, 'lr': 0.00048604332766457074, 'weight_decay': 0.00030420784277443875, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 14:02:50,307] Trial 33 finished with value: 0.5555361553063559 and parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.39571224629611645, 'ffn_dropout': 0.1058387035560121, 'lr': 0.0003174267661519808, 'weight_decay': 0.0001659992631018192, 'batch_size': 32}. Best is trial 30 with value: 0.5674050423289939. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.555536 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.39571224629611645, 'ffn_dropout': 0.1058387035560121, 'lr': 0.0003174267661519808, 'weight_decay': 0.0001659992631018192, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 14:09:44,068] Trial 34 finished with value: 0.562692376038707 and parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3573556143383073, 'ffn_dropout': 0.19451866662642678, 'lr': 0.00018463306055615977, 'weight_decay': 0.0003174647747309408, 'batch_size': 32}. Best is trial 30 with value: 0.5674050423289939. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.562692 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3573556143383073, 'ffn_dropout': 0.19451866662642678, 'lr': 0.00018463306055615977, 'weight_decay': 0.0003174647747309408, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 14:17:42,248] Trial 35 finished with value: 0.5608330842485907 and parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3621629184492448, 'ffn_dropout': 0.21574504640640194, 'lr': 0.0002758936750916371, 'weight_decay': 0.00030889919236565185, 'batch_size': 32}. Best is trial 30 with value: 0.5674050423289939. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.560833 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3621629184492448, 'ffn_dropout': 0.21574504640640194, 'lr': 0.0002758936750916371, 'weight_decay': 0.00030889919236565185, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 14:21:57,109] Trial 36 finished with value: 0.5501454790785925 and parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3535552704951006, 'ffn_dropout': 0.1787906019758095, 'lr': 0.00016558469720193654, 'weight_decay': 0.0005441317423712665, 'batch_size': 64}. Best is trial 30 with value: 0.5674050423289939. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.550145 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3535552704951006, 'ffn_dropout': 0.1787906019758095, 'lr': 0.00016558469720193654, 'weight_decay': 0.0005441317423712665, 'batch_size': 64} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 14:29:41,839] Trial 37 finished with value: 0.5505506314381915 and parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3373362988978907, 'ffn_dropout': 0.22382914340055377, 'lr': 9.525864476217094e-05, 'weight_decay': 0.0003377980179299555, 'batch_size': 32}. Best is trial 30 with value: 0.5674050423289939. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.550551 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3373362988978907, 'ffn_dropout': 0.22382914340055377, 'lr': 9.525864476217094e-05, 'weight_decay': 0.0003377980179299555, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 14:37:34,031] Trial 38 finished with value: 0.5599911552790139 and parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.36895676765118507, 'ffn_dropout': 0.18345307876372632, 'lr': 0.000448426902509758, 'weight_decay': 0.03285126912161758, 'batch_size': 32}. Best is trial 30 with value: 0.5674050423289939. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.559991 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.36895676765118507, 'ffn_dropout': 0.18345307876372632, 'lr': 0.000448426902509758, 'weight_decay': 0.03285126912161758, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 14:37:45,356] Trial 39 pruned. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.369642 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3910543268253468, 'ffn_dropout': 0.25986015549333963, 'lr': 5.999048630008976e-05, 'weight_decay': 0.0007834742008388651, 'batch_size': 256} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 14:46:26,603] Trial 40 finished with value: 0.558362638277366 and parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.37383785700087396, 'ffn_dropout': 0.1989924039624996, 'lr': 0.00015091919593274934, 'weight_decay': 0.0001479213932290807, 'batch_size': 32}. Best is trial 30 with value: 0.5674050423289939. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.558363 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.37383785700087396, 'ffn_dropout': 0.1989924039624996, 'lr': 0.00015091919593274934, 'weight_decay': 0.0001479213932290807, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 14:53:35,216] Trial 41 finished with value: 0.563987440967996 and parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3546815707003426, 'ffn_dropout': 0.22185219347792834, 'lr': 0.0002742474103762457, 'weight_decay': 0.00028307631188384584, 'batch_size': 32}. Best is trial 30 with value: 0.5674050423289939. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.563987 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3546815707003426, 'ffn_dropout': 0.22185219347792834, 'lr': 0.0002742474103762457, 'weight_decay': 0.00028307631188384584, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 15:00:43,925] Trial 42 finished with value: 0.5606726472675968 and parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3424397614264985, 'ffn_dropout': 0.22552327477273837, 'lr': 0.000251594348545129, 'weight_decay': 0.0002339571216205119, 'batch_size': 32}. Best is trial 30 with value: 0.5674050423289939. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.560673 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3424397614264985, 'ffn_dropout': 0.22552327477273837, 'lr': 0.000251594348545129, 'weight_decay': 0.0002339571216205119, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 15:09:43,657] Trial 43 finished with value: 0.5631679641434025 and parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.32671087666215964, 'ffn_dropout': 0.24213357930050095, 'lr': 0.00020880225165183163, 'weight_decay': 0.00043193069337521913, 'batch_size': 32}. Best is trial 30 with value: 0.5674050423289939. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.563168 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.32671087666215964, 'ffn_dropout': 0.24213357930050095, 'lr': 0.00020880225165183163, 'weight_decay': 0.00043193069337521913, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 15:18:35,165] Trial 44 finished with value: 0.5643052020710759 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.32559868815405996, 'ffn_dropout': 0.24632699966782662, 'lr': 0.00036482273320846757, 'weight_decay': 0.0004604652969911148, 'batch_size': 32}. Best is trial 30 with value: 0.5674050423289939. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.564305 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.32559868815405996, 'ffn_dropout': 0.24632699966782662, 'lr': 0.00036482273320846757, 'weight_decay': 0.0004604652969911148, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 15:19:01,880] Trial 45 pruned. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.513081 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3199512001496372, 'ffn_dropout': 0.2536103898764961, 'lr': 0.000579051007254152, 'weight_decay': 0.0004854077379315191, 'batch_size': 128} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 15:31:40,825] Trial 46 finished with value: 0.556269090526079 and parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3795646126158546, 'ffn_dropout': 0.2171327055372871, 'lr': 0.00036394191472246434, 'weight_decay': 0.00014383574651275895, 'batch_size': 32}. Best is trial 30 with value: 0.5674050423289939. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.556269 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3795646126158546, 'ffn_dropout': 0.2171327055372871, 'lr': 0.00036394191472246434, 'weight_decay': 0.00014383574651275895, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 15:32:16,735] Trial 47 pruned. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.533333 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.34603801005935186, 'ffn_dropout': 0.2673443985972562, 'lr': 0.0009466040100440813, 'weight_decay': 0.0009066314439130622, 'batch_size': 64} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 15:33:19,598] Trial 48 pruned. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.502114 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3621848724916188, 'ffn_dropout': 0.23329129908859764, 'lr': 0.0005527812848733499, 'weight_decay': 0.0006575824032379648, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 15:34:32,832] Trial 49 pruned. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.539202 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.39657056635455257, 'ffn_dropout': 0.2106977947755285, 'lr': 0.00011425257655144456, 'weight_decay': 0.001360719741513329, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 15:35:40,266] Trial 50 pruned. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.531266 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3200979626765687, 'ffn_dropout': 0.24815303275910922, 'lr': 0.00035516721197788965, 'weight_decay': 0.0002673309442325525, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 15:44:27,527] Trial 51 finished with value: 0.5642803152794164 and parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3244808718893917, 'ffn_dropout': 0.23861428642053498, 'lr': 0.00024328965852287463, 'weight_decay': 0.00044988271199003846, 'batch_size': 32}. Best is trial 30 with value: 0.5674050423289939. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.564280 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3244808718893917, 'ffn_dropout': 0.23861428642053498, 'lr': 0.00024328965852287463, 'weight_decay': 0.00044988271199003846, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 15:51:42,611] Trial 52 finished with value: 0.5628170365931069 and parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3405675493448915, 'ffn_dropout': 0.23613482121858698, 'lr': 0.0002500199038825381, 'weight_decay': 0.0004205366023432731, 'batch_size': 32}. Best is trial 30 with value: 0.5674050423289939. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.562817 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3405675493448915, 'ffn_dropout': 0.23613482121858698, 'lr': 0.0002500199038825381, 'weight_decay': 0.0004205366023432731, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 16:00:52,822] Trial 53 finished with value: 0.5600607043024524 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3658949052055436, 'ffn_dropout': 0.2670863024720903, 'lr': 0.0004759320927009431, 'weight_decay': 0.00018503021243501815, 'batch_size': 32}. Best is trial 30 with value: 0.5674050423289939. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.560061 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3658949052055436, 'ffn_dropout': 0.2670863024720903, 'lr': 0.0004759320927009431, 'weight_decay': 0.00018503021243501815, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 16:08:35,814] Trial 54 finished with value: 0.5625459239634191 and parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.38379167712939116, 'ffn_dropout': 0.22995740937104606, 'lr': 0.0002884887038540088, 'weight_decay': 0.00041523635102405746, 'batch_size': 32}. Best is trial 30 with value: 0.5674050423289939. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.562546 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.38379167712939116, 'ffn_dropout': 0.22995740937104606, 'lr': 0.0002884887038540088, 'weight_decay': 0.00041523635102405746, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 16:08:49,115] Trial 55 pruned. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.496231 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3280560510991852, 'ffn_dropout': 0.20629469920702775, 'lr': 0.0006432370763180428, 'weight_decay': 0.0002539212579278552, 'batch_size': 256} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 16:09:14,048] Trial 56 pruned. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.516226 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.35125439478551274, 'ffn_dropout': 0.24865053789620528, 'lr': 0.00045912651176886814, 'weight_decay': 0.0007986774585721864, 'batch_size': 128} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 16:10:36,854] Trial 57 pruned. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.542182 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.31113550385415717, 'ffn_dropout': 0.29610124701004514, 'lr': 0.0001412840565843215, 'weight_decay': 0.0005318916311435066, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 16:11:46,659] Trial 58 pruned. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.527242 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.33418367833234836, 'ffn_dropout': 0.22215378599686825, 'lr': 0.0008816979559073934, 'weight_decay': 0.00013100863055965416, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 16:20:11,886] Trial 59 pruned. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.505707 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2947906257002787, 'ffn_dropout': 0.2727770108832929, 'lr': 0.0006412795025297683, 'weight_decay': 0.00021784585279470547, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 16:21:32,182] Trial 60 pruned. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3164542371529918, 'ffn_dropout': 0.24264627649344742, 'lr': 0.0013170968027558035, 'weight_decay': 0.00017991829519570918, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 16:31:47,031] Trial 61 finished with value: 0.5585264947651907 and parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3299791747422941, 'ffn_dropout': 0.25402235555769426, 'lr': 0.00020136858757464955, 'weight_decay': 0.00039807871877394895, 'batch_size': 32}. Best is trial 30 with value: 0.5674050423289939. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.558526 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3299791747422941, 'ffn_dropout': 0.25402235555769426, 'lr': 0.00020136858757464955, 'weight_decay': 0.00039807871877394895, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 16:41:19,826] Trial 62 finished with value: 0.5661290832313414 and parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.32554849951216197, 'ffn_dropout': 0.2429753423465282, 'lr': 0.0001976601543024105, 'weight_decay': 0.0006364254105893218, 'batch_size': 32}. Best is trial 30 with value: 0.5674050423289939. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.566129 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.32554849951216197, 'ffn_dropout': 0.2429753423465282, 'lr': 0.0001976601543024105, 'weight_decay': 0.0006364254105893218, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 16:42:26,766] Trial 63 pruned. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.523429 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3085095123640569, 'ffn_dropout': 0.23122291949261123, 'lr': 0.0002966630044132319, 'weight_decay': 0.0010522416050398008, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 16:51:22,559] Trial 64 finished with value: 0.5529709663241914 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3706081443177138, 'ffn_dropout': 0.2140474112647905, 'lr': 0.00039988584543343756, 'weight_decay': 0.0006515335833099849, 'batch_size': 32}. Best is trial 30 with value: 0.5674050423289939. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.552971 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3706081443177138, 'ffn_dropout': 0.2140474112647905, 'lr': 0.00039988584543343756, 'weight_decay': 0.0006515335833099849, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 16:59:57,883] Trial 65 pruned. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.527458 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.347145023715236, 'ffn_dropout': 0.25889994676044165, 'lr': 0.00024610903062881426, 'weight_decay': 0.0002882769362740267, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 17:11:05,257] Trial 66 finished with value: 0.5598204204475736 and parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3570837015358921, 'ffn_dropout': 0.19082714442687154, 'lr': 0.00017336880061988685, 'weight_decay': 0.0003774537629414265, 'batch_size': 32}. Best is trial 30 with value: 0.5674050423289939. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.559820 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3570837015358921, 'ffn_dropout': 0.19082714442687154, 'lr': 0.00017336880061988685, 'weight_decay': 0.0003774537629414265, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 17:17:15,803] Trial 67 finished with value: 0.5644949456493431 and parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.31751410833931226, 'ffn_dropout': 0.20240068168799835, 'lr': 0.0003275684579605444, 'weight_decay': 0.0005526570088024464, 'batch_size': 64}. Best is trial 30 with value: 0.5674050423289939. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.564495 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.31751410833931226, 'ffn_dropout': 0.20240068168799835, 'lr': 0.0003275684579605444, 'weight_decay': 0.0005526570088024464, 'batch_size': 64} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 17:17:55,581] Trial 68 pruned. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.521377 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3161673054356169, 'ffn_dropout': 0.20653602821189404, 'lr': 0.0005130117460785746, 'weight_decay': 0.0013092377059704956, 'batch_size': 64} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 17:18:29,489] Trial 69 pruned. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.524185 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3266080065399589, 'ffn_dropout': 0.1769395160201564, 'lr': 0.0007728317612906528, 'weight_decay': 0.0005318419548309079, 'batch_size': 64} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 17:19:06,304] Trial 70 pruned. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.536765 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2948529163259237, 'ffn_dropout': 0.23833580603292043, 'lr': 0.0003438411043093907, 'weight_decay': 0.0006752161402584663, 'batch_size': 64} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 17:19:43,176] Trial 71 pruned. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.539665 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3360421720923612, 'ffn_dropout': 0.22252374437209096, 'lr': 0.000314845033932528, 'weight_decay': 0.00030108685325666183, 'batch_size': 64} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 17:19:55,156] Trial 72 pruned. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.478625 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.34399243862716616, 'ffn_dropout': 0.19904304530338812, 'lr': 0.00023024631228989772, 'weight_decay': 0.0004711327393002076, 'batch_size': 256} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 17:20:14,970] Trial 73 pruned. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.507111 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3116479422181419, 'ffn_dropout': 0.2459231755638775, 'lr': 0.00040853721319629807, 'weight_decay': 0.0009316303492716685, 'batch_size': 128} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 17:30:44,669] Trial 74 finished with value: 0.5652006036703885 and parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.35763533445543894, 'ffn_dropout': 0.23161164516338711, 'lr': 0.00020465388726916779, 'weight_decay': 0.0003423360293297405, 'batch_size': 32}. Best is trial 30 with value: 0.5674050423289939. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.565201 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.35763533445543894, 'ffn_dropout': 0.23161164516338711, 'lr': 0.00020465388726916779, 'weight_decay': 0.0003423360293297405, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 17:31:51,483] Trial 75 pruned. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.534756 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38747517218721694, 'ffn_dropout': 0.23302544052571197, 'lr': 0.00018929496962671747, 'weight_decay': 0.0003818624945572018, 'batch_size': 64} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 17:32:56,310] Trial 76 pruned. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.535050 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.30145461860316847, 'ffn_dropout': 0.21113416423528023, 'lr': 0.00012823926283651456, 'weight_decay': 0.0006052598838434196, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 17:40:24,580] Trial 77 finished with value: 0.5575035380233367 and parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3786917685194243, 'ffn_dropout': 0.2521502050234237, 'lr': 0.00014587545184136568, 'weight_decay': 0.0008125924274305289, 'batch_size': 32}. Best is trial 30 with value: 0.5674050423289939. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.557504 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3786917685194243, 'ffn_dropout': 0.2521502050234237, 'lr': 0.00014587545184136568, 'weight_decay': 0.0008125924274305289, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 17:41:31,078] Trial 78 pruned. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.538251 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3620517059987306, 'ffn_dropout': 0.28223413499562866, 'lr': 0.0004113629336124001, 'weight_decay': 0.000234633059784876, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 17:44:11,296] Trial 79 pruned. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.530312 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3362812592350845, 'ffn_dropout': 0.1878533770819069, 'lr': 0.00020744348198387848, 'weight_decay': 0.0003537807645318261, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 17:44:42,273] Trial 80 pruned. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.530955 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3240097676470653, 'ffn_dropout': 0.23884319722804678, 'lr': 0.00033725322895608974, 'weight_decay': 0.0005077914369808697, 'batch_size': 64} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 17:54:19,562] Trial 81 finished with value: 0.5619965753706834 and parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.35697243757182073, 'ffn_dropout': 0.22095096121680724, 'lr': 0.0002307971326262494, 'weight_decay': 0.00028207228908645125, 'batch_size': 32}. Best is trial 30 with value: 0.5674050423289939. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.561997 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.35697243757182073, 'ffn_dropout': 0.22095096121680724, 'lr': 0.0002307971326262494, 'weight_decay': 0.00028207228908645125, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 17:55:32,695] Trial 82 pruned. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.540107 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.34836943438501483, 'ffn_dropout': 0.2045635899913562, 'lr': 0.000280099764641132, 'weight_decay': 0.00020604597149227657, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 17:56:46,245] Trial 83 pruned. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.536145 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.365400281041358, 'ffn_dropout': 0.22602945234155472, 'lr': 0.0001689391329359149, 'weight_decay': 0.0003378377079914079, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 18:05:11,437] Trial 84 finished with value: 0.5613987516497861 and parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.34205660394318593, 'ffn_dropout': 0.21869071039588409, 'lr': 0.0005283731813540785, 'weight_decay': 0.00045957798950018217, 'batch_size': 32}. Best is trial 30 with value: 0.5674050423289939. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.561399 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.34205660394318593, 'ffn_dropout': 0.21869071039588409, 'lr': 0.0005283731813540785, 'weight_decay': 0.00045957798950018217, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 18:06:37,020] Trial 85 pruned. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.539978 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.37285392806271395, 'ffn_dropout': 0.22868398128387246, 'lr': 0.0002685402535155513, 'weight_decay': 0.00026630715233407534, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 18:15:28,649] Trial 86 finished with value: 0.5646619766490142 and parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.33168195072092793, 'ffn_dropout': 0.24205233579297242, 'lr': 0.0003313737620774728, 'weight_decay': 0.00036269017078117407, 'batch_size': 32}. Best is trial 30 with value: 0.5674050423289939. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.564662 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.33168195072092793, 'ffn_dropout': 0.24205233579297242, 'lr': 0.0003313737620774728, 'weight_decay': 0.00036269017078117407, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 18:15:37,988] Trial 87 pruned. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.453095 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.33157240620352796, 'ffn_dropout': 0.2423061334990648, 'lr': 0.0004422495324936617, 'weight_decay': 0.0006494477592519485, 'batch_size': 256} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 18:15:51,975] Trial 88 pruned. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.512658 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.323261254375982, 'ffn_dropout': 0.26769016403497853, 'lr': 0.00033204447974512354, 'weight_decay': 0.0005672360091194626, 'batch_size': 128} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 18:16:50,735] Trial 89 pruned. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.523703 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.31760090403969976, 'ffn_dropout': 0.25668645068052154, 'lr': 0.000641453296369461, 'weight_decay': 0.0003789597611529661, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 18:17:40,608] Trial 90 pruned. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.527660 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3391995717623639, 'ffn_dropout': 0.25034177368355454, 'lr': 0.00022315865570545474, 'weight_decay': 0.0007452806759972192, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 18:24:36,749] Trial 91 pruned. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.514877 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.3522270455310675, 'ffn_dropout': 0.23592958394974028, 'lr': 0.0003142048850216142, 'weight_decay': 0.000457025097744545, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 18:31:29,596] Trial 92 finished with value: 0.5625301022558141 and parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3316778846124803, 'ffn_dropout': 0.2167509831934703, 'lr': 0.00025252017880273515, 'weight_decay': 0.00029690462852767106, 'batch_size': 32}. Best is trial 30 with value: 0.5674050423289939. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.562530 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3316778846124803, 'ffn_dropout': 0.2167509831934703, 'lr': 0.00025252017880273515, 'weight_decay': 0.00029690462852767106, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 18:39:15,155] Trial 93 pruned. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.515712 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.35700542273779784, 'ffn_dropout': 0.2285144608615685, 'lr': 0.00041009333545977237, 'weight_decay': 0.00023785043517588253, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) -[I 2025-12-25 18:43:36,536] Trial 94 pruned. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.555556 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3459338394968773, 'ffn_dropout': 0.1968426831799045, 'lr': 0.00016825231175600458, 'weight_decay': 0.00033881607417409653, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 18:50:41,970] Trial 95 finished with value: 0.567399549943466 and parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3049224290468632, 'ffn_dropout': 0.262458911386045, 'lr': 0.0004705378123090436, 'weight_decay': 0.0002011568536459783, 'batch_size': 32}. Best is trial 30 with value: 0.5674050423289939. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.567400 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3049224290468632, 'ffn_dropout': 0.262458911386045, 'lr': 0.0004705378123090436, 'weight_decay': 0.0002011568536459783, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 1.3172, 1: 1.3172, 2: 0.6749333879893421} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 1.3153333333333332, 1: 1.3153333333333332, 2: 0.6759164097293594} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14595}) -[I 2025-12-25 18:56:43,950] Trial 96 finished with value: 0.561816564837237 and parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.30896276854711474, 'ffn_dropout': 0.2630071033281542, 'lr': 0.00048624747270327744, 'weight_decay': 0.00020972461119679467, 'batch_size': 32}. Best is trial 30 with value: 0.5674050423289939. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.561817 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.30896276854711474, 'ffn_dropout': 0.2630071033281542, 'lr': 0.00048624747270327744, 'weight_decay': 0.00020972461119679467, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 18:57:40,140] Trial 97 pruned. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.537549 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.29492872114426294, 'ffn_dropout': 0.14031063910948866, 'lr': 0.0005902338352850365, 'weight_decay': 0.0004111862436463382, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 18:58:34,222] Trial 98 pruned. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.536913 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28072763298617825, 'ffn_dropout': 0.3336802876880405, 'lr': 0.00076676123816529, 'weight_decay': 0.00016953305738751375, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.313511111111111, 1: 1.313511111111111, 2: 0.6768814987861298} (클래스별 샘플 수: {0: 7500, 1: 7500, 2: 14554}) -[I 2025-12-25 18:59:31,145] Trial 99 pruned. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.546421 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3236561361103351, 'ffn_dropout': 0.3031467734958405, 'lr': 0.00039230307339006967, 'weight_decay': 0.0005623894036993773, 'batch_size': 32} - Best Value (CSI): 0.567405 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.5674 -Best Hyperparameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3637871224837107, 'ffn_dropout': 0.11479322703553738, 'lr': 0.0003009840584939789, 'weight_decay': 0.0003336039035587163, 'batch_size': 32} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.5290 - - 최종 CSI: 0.5464 - - 최고 CSI: 0.5674 - - 최저 CSI: 0.0000 - - 평균 CSI: 0.5042 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/ft_transformer_smote_incheon_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 25, Best CSI: 0.5545 - Fold 1 학습 완료 (검증 CSI: 0.5545) -Fold 2 학습 중... - Early stopping at epoch 22, Best CSI: 0.6011 - Fold 2 학습 완료 (검증 CSI: 0.6011) -Fold 3 학습 중... - Early stopping at epoch 20, Best CSI: 0.5260 - Fold 3 학습 완료 (검증 CSI: 0.5260) - -모든 모델 저장 완료: ../save_model/ft_transformer_optima/ft_transformer_smote_incheon.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/ft_transformer_optima/scaler/ft_transformer_smote_incheon_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: ../save_model/ft_transformer_optima/ft_transformer_smote_incheon.pkl - -✓ 완료: ft_transformer_smote/ft_transformer_smote_incheon.py (소요 시간: 25906초) - ----------------------------------------- -실행 중: ft_transformer_smote/ft_transformer_smote_seoul.py -시작 시간: 2025-12-25 19:04:39 ----------------------------------------- -[I 2025-12-25 19:04:40,322] A new study created in memory with name: no-name-7b6c1c0c-7f07-4abd-8acf-3eaf3c02983f - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 19:07:47,794] Trial 0 finished with value: 0.4938262435375931 and parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.17877587888051422, 'ffn_dropout': 0.25816851791180656, 'lr': 0.00013524525410014886, 'weight_decay': 0.000247082500026181, 'batch_size': 128}. Best is trial 0 with value: 0.4938262435375931. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.493826 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.17877587888051422, 'ffn_dropout': 0.25816851791180656, 'lr': 0.00013524525410014886, 'weight_decay': 0.000247082500026181, 'batch_size': 128} - Best Value (CSI): 0.493826 - Best Trial: 0 - Best Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.17877587888051422, 'ffn_dropout': 0.25816851791180656, 'lr': 0.00013524525410014886, 'weight_decay': 0.000247082500026181, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 19:13:48,805] Trial 1 finished with value: 0.5334517409672329 and parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.38636882799915206, 'ffn_dropout': 0.18085902479509552, 'lr': 9.024334489666502e-05, 'weight_decay': 0.000652210057637454, 'batch_size': 64}. Best is trial 1 with value: 0.5334517409672329. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.533452 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.38636882799915206, 'ffn_dropout': 0.18085902479509552, 'lr': 9.024334489666502e-05, 'weight_decay': 0.000652210057637454, 'batch_size': 64} - Best Value (CSI): 0.533452 - Best Trial: 1 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.38636882799915206, 'ffn_dropout': 0.18085902479509552, 'lr': 9.024334489666502e-05, 'weight_decay': 0.000652210057637454, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 19:17:03,923] Trial 2 finished with value: 0.5458125039748464 and parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.1587538990323335, 'ffn_dropout': 0.2904165146005051, 'lr': 0.00018365747922966267, 'weight_decay': 0.08900255730292767, 'batch_size': 64}. Best is trial 2 with value: 0.5458125039748464. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.545813 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.1587538990323335, 'ffn_dropout': 0.2904165146005051, 'lr': 0.00018365747922966267, 'weight_decay': 0.08900255730292767, 'batch_size': 64} - Best Value (CSI): 0.545813 - Best Trial: 2 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.1587538990323335, 'ffn_dropout': 0.2904165146005051, 'lr': 0.00018365747922966267, 'weight_decay': 0.08900255730292767, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 19:25:04,291] Trial 3 finished with value: 0.5466284706855625 and parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2535804581397322, 'ffn_dropout': 0.38751684839588385, 'lr': 0.00042041686603716034, 'weight_decay': 0.001336629427296846, 'batch_size': 32}. Best is trial 3 with value: 0.5466284706855625. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.546628 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2535804581397322, 'ffn_dropout': 0.38751684839588385, 'lr': 0.00042041686603716034, 'weight_decay': 0.001336629427296846, 'batch_size': 32} - Best Value (CSI): 0.546628 - Best Trial: 3 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2535804581397322, 'ffn_dropout': 0.38751684839588385, 'lr': 0.00042041686603716034, 'weight_decay': 0.001336629427296846, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 19:28:21,226] Trial 4 finished with value: 0.4870939358844726 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.15939959485476937, 'ffn_dropout': 0.203050088780319, 'lr': 7.605432624495413e-05, 'weight_decay': 0.02114229127092804, 'batch_size': 128}. Best is trial 3 with value: 0.5466284706855625. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.487094 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.15939959485476937, 'ffn_dropout': 0.203050088780319, 'lr': 7.605432624495413e-05, 'weight_decay': 0.02114229127092804, 'batch_size': 128} - Best Value (CSI): 0.546628 - Best Trial: 3 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2535804581397322, 'ffn_dropout': 0.38751684839588385, 'lr': 0.00042041686603716034, 'weight_decay': 0.001336629427296846, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 19:29:00,669] Trial 5 pruned. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.000683 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.262498055493321, 'ffn_dropout': 0.1268891467327522, 'lr': 0.001222995804781187, 'weight_decay': 0.004985200375250647, 'batch_size': 64} - Best Value (CSI): 0.546628 - Best Trial: 3 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2535804581397322, 'ffn_dropout': 0.38751684839588385, 'lr': 0.00042041686603716034, 'weight_decay': 0.001336629427296846, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 19:29:17,201] Trial 6 pruned. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.309722 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.31360651123852146, 'ffn_dropout': 0.1406902470759515, 'lr': 2.031552446004212e-05, 'weight_decay': 0.0011992935202302245, 'batch_size': 128} - Best Value (CSI): 0.546628 - Best Trial: 3 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2535804581397322, 'ffn_dropout': 0.38751684839588385, 'lr': 0.00042041686603716034, 'weight_decay': 0.001336629427296846, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 19:29:45,485] Trial 7 pruned. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.032541 - Parameters: {'d_token': 224, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.23404914807934393, 'ffn_dropout': 0.13211437991876396, 'lr': 0.0015971818363471882, 'weight_decay': 0.06034816396335996, 'batch_size': 128} - Best Value (CSI): 0.546628 - Best Trial: 3 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2535804581397322, 'ffn_dropout': 0.38751684839588385, 'lr': 0.00042041686603716034, 'weight_decay': 0.001336629427296846, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 19:38:13,012] Trial 8 finished with value: 0.5520605008418618 and parameters: {'d_token': 256, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.29828015124936436, 'ffn_dropout': 0.1615812663662866, 'lr': 0.00016062851372004058, 'weight_decay': 0.004155620940999291, 'batch_size': 32}. Best is trial 8 with value: 0.5520605008418618. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.552061 - Parameters: {'d_token': 256, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.29828015124936436, 'ffn_dropout': 0.1615812663662866, 'lr': 0.00016062851372004058, 'weight_decay': 0.004155620940999291, 'batch_size': 32} - Best Value (CSI): 0.552061 - Best Trial: 8 - Best Parameters: {'d_token': 256, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.29828015124936436, 'ffn_dropout': 0.1615812663662866, 'lr': 0.00016062851372004058, 'weight_decay': 0.004155620940999291, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 19:38:26,693] Trial 9 pruned. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.391198 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.22765643731941584, 'ffn_dropout': 0.3690250354489788, 'lr': 0.00033555491864971154, 'weight_decay': 0.06628616563114029, 'batch_size': 128} - Best Value (CSI): 0.552061 - Best Trial: 8 - Best Parameters: {'d_token': 256, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.29828015124936436, 'ffn_dropout': 0.1615812663662866, 'lr': 0.00016062851372004058, 'weight_decay': 0.004155620940999291, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 19:39:55,053] Trial 10 pruned. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.000683 - Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.12024134460854768, 'ffn_dropout': 0.10266841542391442, 'lr': 0.006982061895271842, 'weight_decay': 0.004822198063230748, 'batch_size': 32} - Best Value (CSI): 0.552061 - Best Trial: 8 - Best Parameters: {'d_token': 256, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.29828015124936436, 'ffn_dropout': 0.1615812663662866, 'lr': 0.00016062851372004058, 'weight_decay': 0.004155620940999291, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 19:47:10,509] Trial 11 finished with value: 0.5578292783958204 and parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2941938157012187, 'ffn_dropout': 0.36773295501771575, 'lr': 0.0005697089836996394, 'weight_decay': 0.0019057445511098665, 'batch_size': 32}. Best is trial 11 with value: 0.5578292783958204. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.557829 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2941938157012187, 'ffn_dropout': 0.36773295501771575, 'lr': 0.0005697089836996394, 'weight_decay': 0.0019057445511098665, 'batch_size': 32} - Best Value (CSI): 0.557829 - Best Trial: 11 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2941938157012187, 'ffn_dropout': 0.36773295501771575, 'lr': 0.0005697089836996394, 'weight_decay': 0.0019057445511098665, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 19:50:22,509] Trial 12 pruned. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.425654 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.31116992471832144, 'ffn_dropout': 0.31739936341585406, 'lr': 3.1044287702737566e-05, 'weight_decay': 0.007721485317587983, 'batch_size': 32} - Best Value (CSI): 0.557829 - Best Trial: 11 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2941938157012187, 'ffn_dropout': 0.36773295501771575, 'lr': 0.0005697089836996394, 'weight_decay': 0.0019057445511098665, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 19:50:54,888] Trial 13 pruned. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.410714 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3178344933477064, 'ffn_dropout': 0.20990090127857483, 'lr': 0.0006153736612946382, 'weight_decay': 0.002137043115536503, 'batch_size': 256} - Best Value (CSI): 0.557829 - Best Trial: 11 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2941938157012187, 'ffn_dropout': 0.36773295501771575, 'lr': 0.0005697089836996394, 'weight_decay': 0.0019057445511098665, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 19:52:15,517] Trial 14 pruned. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.383484 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.37407718474989915, 'ffn_dropout': 0.32749870977431106, 'lr': 1.1396160360865782e-05, 'weight_decay': 0.012312475883367872, 'batch_size': 32} - Best Value (CSI): 0.557829 - Best Trial: 11 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2941938157012187, 'ffn_dropout': 0.36773295501771575, 'lr': 0.0005697089836996394, 'weight_decay': 0.0019057445511098665, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 19:53:45,577] Trial 15 pruned. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.404919 - Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.28950542083211667, 'ffn_dropout': 0.2383486643665559, 'lr': 4.644565767203515e-05, 'weight_decay': 0.0034145033007323463, 'batch_size': 32} - Best Value (CSI): 0.557829 - Best Trial: 11 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2941938157012187, 'ffn_dropout': 0.36773295501771575, 'lr': 0.0005697089836996394, 'weight_decay': 0.0019057445511098665, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 19:54:06,748] Trial 16 pruned. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.400738 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3604632485086947, 'ffn_dropout': 0.39723730302900606, 'lr': 0.00018422805038315588, 'weight_decay': 0.00011345073719032854, 'batch_size': 256} - Best Value (CSI): 0.557829 - Best Trial: 11 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2941938157012187, 'ffn_dropout': 0.36773295501771575, 'lr': 0.0005697089836996394, 'weight_decay': 0.0019057445511098665, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 19:55:33,341] Trial 17 pruned. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.000368 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.341304612288705, 'ffn_dropout': 0.35709624930828915, 'lr': 0.000833954206267635, 'weight_decay': 0.0006363398003855473, 'batch_size': 32} - Best Value (CSI): 0.557829 - Best Trial: 11 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2941938157012187, 'ffn_dropout': 0.36773295501771575, 'lr': 0.0005697089836996394, 'weight_decay': 0.0019057445511098665, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 20:00:39,536] Trial 18 finished with value: 0.5559576299465977 and parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.28535402731157145, 'ffn_dropout': 0.27419232643813984, 'lr': 0.00028408291083977357, 'weight_decay': 0.0028877204175900384, 'batch_size': 32}. Best is trial 11 with value: 0.5578292783958204. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.555958 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.28535402731157145, 'ffn_dropout': 0.27419232643813984, 'lr': 0.00028408291083977357, 'weight_decay': 0.0028877204175900384, 'batch_size': 32} - Best Value (CSI): 0.557829 - Best Trial: 11 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2941938157012187, 'ffn_dropout': 0.36773295501771575, 'lr': 0.0005697089836996394, 'weight_decay': 0.0019057445511098665, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 20:01:17,538] Trial 19 pruned. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.114776 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.34124673680762085, 'ffn_dropout': 0.28326270713550894, 'lr': 0.002492136015271463, 'weight_decay': 0.0017882738162503095, 'batch_size': 32} - Best Value (CSI): 0.557829 - Best Trial: 11 - Best Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2941938157012187, 'ffn_dropout': 0.36773295501771575, 'lr': 0.0005697089836996394, 'weight_decay': 0.0019057445511098665, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 20:05:51,496] Trial 20 finished with value: 0.5599809245798847 and parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.39733800524948154, 'ffn_dropout': 0.3456021599313298, 'lr': 0.0005197977356768663, 'weight_decay': 0.012755783722561802, 'batch_size': 32}. Best is trial 20 with value: 0.5599809245798847. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.559981 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.39733800524948154, 'ffn_dropout': 0.3456021599313298, 'lr': 0.0005197977356768663, 'weight_decay': 0.012755783722561802, 'batch_size': 32} - Best Value (CSI): 0.559981 - Best Trial: 20 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.39733800524948154, 'ffn_dropout': 0.3456021599313298, 'lr': 0.0005197977356768663, 'weight_decay': 0.012755783722561802, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 20:09:42,340] Trial 21 finished with value: 0.5469949923023917 and parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3779328300507695, 'ffn_dropout': 0.34379482204582573, 'lr': 0.00041523837539485757, 'weight_decay': 0.014842552481655419, 'batch_size': 32}. Best is trial 20 with value: 0.5599809245798847. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.546995 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3779328300507695, 'ffn_dropout': 0.34379482204582573, 'lr': 0.00041523837539485757, 'weight_decay': 0.014842552481655419, 'batch_size': 32} - Best Value (CSI): 0.559981 - Best Trial: 20 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.39733800524948154, 'ffn_dropout': 0.3456021599313298, 'lr': 0.0005197977356768663, 'weight_decay': 0.012755783722561802, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 20:14:35,815] Trial 22 finished with value: 0.5633420079946059 and parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.39130884741380056, 'ffn_dropout': 0.31747304984650526, 'lr': 0.0006307339704492065, 'weight_decay': 0.029346384417081962, 'batch_size': 32}. Best is trial 22 with value: 0.5633420079946059. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.563342 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.39130884741380056, 'ffn_dropout': 0.31747304984650526, 'lr': 0.0006307339704492065, 'weight_decay': 0.029346384417081962, 'batch_size': 32} - Best Value (CSI): 0.563342 - Best Trial: 22 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.39130884741380056, 'ffn_dropout': 0.31747304984650526, 'lr': 0.0006307339704492065, 'weight_decay': 0.029346384417081962, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 20:14:49,339] Trial 23 pruned. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.386310 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3957397916283861, 'ffn_dropout': 0.31632777870510437, 'lr': 0.0006669706504333678, 'weight_decay': 0.03335292708832044, 'batch_size': 256} - Best Value (CSI): 0.563342 - Best Trial: 22 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.39130884741380056, 'ffn_dropout': 0.31747304984650526, 'lr': 0.0006307339704492065, 'weight_decay': 0.029346384417081962, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 20:15:39,869] Trial 24 pruned. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.410579 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.35714104155378446, 'ffn_dropout': 0.37079507967854647, 'lr': 0.0018517855077351795, 'weight_decay': 0.031637738635873484, 'batch_size': 32} - Best Value (CSI): 0.563342 - Best Trial: 22 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.39130884741380056, 'ffn_dropout': 0.31747304984650526, 'lr': 0.0006307339704492065, 'weight_decay': 0.029346384417081962, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 20:25:15,503] Trial 25 finished with value: 0.5550903654901403 and parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.39942489442906143, 'ffn_dropout': 0.3404917526953313, 'lr': 0.0010769319867698513, 'weight_decay': 0.011690555123057335, 'batch_size': 32}. Best is trial 22 with value: 0.5633420079946059. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.555090 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.39942489442906143, 'ffn_dropout': 0.3404917526953313, 'lr': 0.0010769319867698513, 'weight_decay': 0.011690555123057335, 'batch_size': 32} - Best Value (CSI): 0.563342 - Best Trial: 22 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.39130884741380056, 'ffn_dropout': 0.31747304984650526, 'lr': 0.0006307339704492065, 'weight_decay': 0.029346384417081962, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 20:29:54,479] Trial 26 finished with value: 0.55939181263975 and parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3411040979072826, 'ffn_dropout': 0.311035543851922, 'lr': 0.0005896875676686477, 'weight_decay': 0.008178262611152964, 'batch_size': 32}. Best is trial 22 with value: 0.5633420079946059. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.559392 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3411040979072826, 'ffn_dropout': 0.311035543851922, 'lr': 0.0005896875676686477, 'weight_decay': 0.008178262611152964, 'batch_size': 32} - Best Value (CSI): 0.563342 - Best Trial: 22 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.39130884741380056, 'ffn_dropout': 0.31747304984650526, 'lr': 0.0006307339704492065, 'weight_decay': 0.029346384417081962, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 20:33:50,512] Trial 27 finished with value: 0.5504349933152191 and parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.39883351702844466, 'ffn_dropout': 0.3003911590355156, 'lr': 0.00028910644866873944, 'weight_decay': 0.008674763492451389, 'batch_size': 32}. Best is trial 22 with value: 0.5633420079946059. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.550435 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.39883351702844466, 'ffn_dropout': 0.3003911590355156, 'lr': 0.00028910644866873944, 'weight_decay': 0.008674763492451389, 'batch_size': 32} - Best Value (CSI): 0.563342 - Best Trial: 22 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.39130884741380056, 'ffn_dropout': 0.31747304984650526, 'lr': 0.0006307339704492065, 'weight_decay': 0.029346384417081962, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 20:36:21,390] Trial 28 finished with value: 0.5617702504367125 and parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3603219989247117, 'ffn_dropout': 0.3070740159727858, 'lr': 0.001147442549345772, 'weight_decay': 0.02153662133095635, 'batch_size': 64}. Best is trial 22 with value: 0.5633420079946059. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.561770 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3603219989247117, 'ffn_dropout': 0.3070740159727858, 'lr': 0.001147442549345772, 'weight_decay': 0.02153662133095635, 'batch_size': 64} - Best Value (CSI): 0.563342 - Best Trial: 22 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.39130884741380056, 'ffn_dropout': 0.31747304984650526, 'lr': 0.0006307339704492065, 'weight_decay': 0.029346384417081962, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 20:37:11,579] Trial 29 pruned. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.404421 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3662330169848604, 'ffn_dropout': 0.25999209531996054, 'lr': 0.0029250720613883483, 'weight_decay': 0.02361092421963226, 'batch_size': 64} - Best Value (CSI): 0.563342 - Best Trial: 22 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.39130884741380056, 'ffn_dropout': 0.31747304984650526, 'lr': 0.0006307339704492065, 'weight_decay': 0.029346384417081962, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 20:41:13,641] Trial 30 finished with value: 0.5739423798669575 and parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64}. Best is trial 30 with value: 0.5739423798669575. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.573942 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} - Best Value (CSI): 0.573942 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 20:42:18,059] Trial 31 pruned. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.436872 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3807953366579965, 'ffn_dropout': 0.3008574669872796, 'lr': 0.0010160619594718244, 'weight_decay': 0.04025909225038649, 'batch_size': 64} - Best Value (CSI): 0.573942 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 20:44:59,167] Trial 32 finished with value: 0.5618651622550636 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3795712151186757, 'ffn_dropout': 0.33217869025520586, 'lr': 0.0014229096680863002, 'weight_decay': 0.019542774890304003, 'batch_size': 64}. Best is trial 30 with value: 0.5739423798669575. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.561865 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3795712151186757, 'ffn_dropout': 0.33217869025520586, 'lr': 0.0014229096680863002, 'weight_decay': 0.019542774890304003, 'batch_size': 64} - Best Value (CSI): 0.573942 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 20:45:37,878] Trial 33 pruned. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.000683 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.35241173755029787, 'ffn_dropout': 0.3313686956858255, 'lr': 0.003361011632909906, 'weight_decay': 0.05373029045269388, 'batch_size': 64} - Best Value (CSI): 0.573942 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 20:50:03,065] Trial 34 finished with value: 0.5655181937406549 and parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3784401077937454, 'ffn_dropout': 0.28918021102980446, 'lr': 0.0017761212737014292, 'weight_decay': 0.022494434992569402, 'batch_size': 64}. Best is trial 30 with value: 0.5739423798669575. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.565518 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3784401077937454, 'ffn_dropout': 0.28918021102980446, 'lr': 0.0017761212737014292, 'weight_decay': 0.022494434992569402, 'batch_size': 64} - Best Value (CSI): 0.573942 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 20:50:53,597] Trial 35 pruned. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.418049 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38035456691282044, 'ffn_dropout': 0.2834701479495254, 'lr': 0.0019484666245800318, 'weight_decay': 0.08536436271893352, 'batch_size': 64} - Best Value (CSI): 0.573942 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 20:51:26,112] Trial 36 pruned. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.000683 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.37379356704923183, 'ffn_dropout': 0.2663007491816, 'lr': 0.004631635199035477, 'weight_decay': 0.09939003399688277, 'batch_size': 64} - Best Value (CSI): 0.573942 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 20:52:17,610] Trial 37 pruned. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.423899 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3358011605492438, 'ffn_dropout': 0.2963393646635246, 'lr': 0.0015371744859914594, 'weight_decay': 0.04212961482789545, 'batch_size': 64} - Best Value (CSI): 0.573942 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 20:53:47,335] Trial 38 pruned. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.425016 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.382997367539803, 'ffn_dropout': 0.245232254370993, 'lr': 0.0008922586476283271, 'weight_decay': 0.026196118872176506, 'batch_size': 64} - Best Value (CSI): 0.573942 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 20:56:17,866] Trial 39 pruned. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.564516 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3316417065930028, 'ffn_dropout': 0.2836670232286214, 'lr': 0.0014672149515341092, 'weight_decay': 0.01679567471713732, 'batch_size': 64} - Best Value (CSI): 0.573942 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 20:57:00,385] Trial 40 pruned. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.439860 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.36357255020557244, 'ffn_dropout': 0.32883820088416715, 'lr': 0.002134183616985511, 'weight_decay': 0.04332567059798113, 'batch_size': 64} - Best Value (CSI): 0.573942 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 20:58:34,364] Trial 41 finished with value: 0.5491478271415667 and parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.35876914791226844, 'ffn_dropout': 0.30793630053418053, 'lr': 0.0013509663384419625, 'weight_decay': 0.02044411099592554, 'batch_size': 64}. Best is trial 30 with value: 0.5739423798669575. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.549148 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.35876914791226844, 'ffn_dropout': 0.30793630053418053, 'lr': 0.0013509663384419625, 'weight_decay': 0.02044411099592554, 'batch_size': 64} - Best Value (CSI): 0.573942 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 20:59:10,950] Trial 42 pruned. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.408374 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3875825095683591, 'ffn_dropout': 0.294353465450384, 'lr': 0.0008751682569871705, 'weight_decay': 0.0247182553603873, 'batch_size': 64} - Best Value (CSI): 0.573942 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 20:59:51,194] Trial 43 pruned. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.419002 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.35419582407430966, 'ffn_dropout': 0.31968769225963617, 'lr': 0.0013903669067727087, 'weight_decay': 0.017577671620451166, 'batch_size': 64} - Best Value (CSI): 0.573942 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 21:00:02,886] Trial 44 pruned. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.419536 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3704721780843632, 'ffn_dropout': 0.30744347023590446, 'lr': 0.003082452093230661, 'weight_decay': 0.06486041198727516, 'batch_size': 128} - Best Value (CSI): 0.573942 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 21:00:49,905] Trial 45 pruned. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.420447 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3834418233071221, 'ffn_dropout': 0.27733559881672915, 'lr': 0.001124694051144312, 'weight_decay': 0.03426761351175438, 'batch_size': 64} - Best Value (CSI): 0.573942 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 21:01:41,349] Trial 46 pruned. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.430225 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.3258115245749298, 'ffn_dropout': 0.2951572468132474, 'lr': 0.0019387029087251449, 'weight_decay': 0.05288197809421397, 'batch_size': 64} - Best Value (CSI): 0.573942 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 21:03:48,231] Trial 47 finished with value: 0.5410692749755706 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3504195800312222, 'ffn_dropout': 0.32527961828877716, 'lr': 0.000796585984433297, 'weight_decay': 0.025957611499380303, 'batch_size': 64}. Best is trial 30 with value: 0.5739423798669575. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.541069 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3504195800312222, 'ffn_dropout': 0.32527961828877716, 'lr': 0.000796585984433297, 'weight_decay': 0.025957611499380303, 'batch_size': 64} - Best Value (CSI): 0.573942 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 21:04:02,215] Trial 48 pruned. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.231242 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.369074683718013, 'ffn_dropout': 0.26812377653928404, 'lr': 0.004275900330718431, 'weight_decay': 0.019566827768521807, 'batch_size': 128} - Best Value (CSI): 0.573942 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 21:04:13,681] Trial 49 pruned. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.393647 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3885117876636148, 'ffn_dropout': 0.3352230174160327, 'lr': 0.0004294465780109999, 'weight_decay': 0.006388699820100441, 'batch_size': 256} - Best Value (CSI): 0.573942 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 21:05:25,813] Trial 50 pruned. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.413793 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.31736360489497384, 'ffn_dropout': 0.35303618272460857, 'lr': 0.0007740167856545144, 'weight_decay': 0.010110776428871121, 'batch_size': 64} - Best Value (CSI): 0.573942 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 21:06:16,566] Trial 51 pruned. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.446682 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.395950660694602, 'ffn_dropout': 0.3189649390773042, 'lr': 0.001177566240481648, 'weight_decay': 0.01324506264326737, 'batch_size': 64} - Best Value (CSI): 0.573942 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 21:07:04,192] Trial 52 pruned. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.422251 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.38844284320069034, 'ffn_dropout': 0.34502670840653643, 'lr': 0.0005157095053941474, 'weight_decay': 0.016343983249055213, 'batch_size': 64} - Best Value (CSI): 0.573942 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 21:07:31,907] Trial 53 pruned. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.391226 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.39947863322369054, 'ffn_dropout': 0.35406762659448393, 'lr': 0.000718756721326717, 'weight_decay': 0.01162435729199829, 'batch_size': 128} - Best Value (CSI): 0.573942 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 21:07:42,919] Trial 54 pruned. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.358849 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3695801375224326, 'ffn_dropout': 0.30998095451090996, 'lr': 0.0005063445099882185, 'weight_decay': 0.02918110238099175, 'batch_size': 256} - Best Value (CSI): 0.573942 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) -[I 2025-12-25 21:11:11,194] Trial 55 pruned. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.599469 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3490298737939594, 'ffn_dropout': 0.33255119904366465, 'lr': 0.0010667989277785895, 'weight_decay': 0.01893896510278957, 'batch_size': 32} - Best Value (CSI): 0.573942 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 21:11:54,393] Trial 56 pruned. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.413815 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.37557123205809045, 'ffn_dropout': 0.28672399896244044, 'lr': 0.0003634711928204699, 'weight_decay': 0.03777674258929632, 'batch_size': 64} - Best Value (CSI): 0.573942 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 21:13:02,618] Trial 57 pruned. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.397428 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3627313732525173, 'ffn_dropout': 0.36909467727156414, 'lr': 0.000640128266456393, 'weight_decay': 0.01490957664012032, 'batch_size': 32} - Best Value (CSI): 0.573942 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 21:17:18,616] Trial 58 finished with value: 0.5511796622846928 and parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38964197351487956, 'ffn_dropout': 0.3409667148688909, 'lr': 0.0016419398503787022, 'weight_decay': 0.023309905237820377, 'batch_size': 32}. Best is trial 30 with value: 0.5739423798669575. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.551180 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38964197351487956, 'ffn_dropout': 0.3409667148688909, 'lr': 0.0016419398503787022, 'weight_decay': 0.023309905237820377, 'batch_size': 32} - Best Value (CSI): 0.573942 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 21:17:53,538] Trial 59 pruned. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.438783 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.35032840066018256, 'ffn_dropout': 0.31829784814184925, 'lr': 0.00023739997889007713, 'weight_decay': 0.010554268173336765, 'batch_size': 64} - Best Value (CSI): 0.573942 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 21:18:08,642] Trial 60 pruned. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.389649 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.39999843716481176, 'ffn_dropout': 0.38295990649014866, 'lr': 0.002421069392654888, 'weight_decay': 0.052802037227199776, 'batch_size': 256} - Best Value (CSI): 0.573942 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 21:24:40,828] Trial 61 finished with value: 0.5602019085442339 and parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.37654335691627466, 'ffn_dropout': 0.3102323471459902, 'lr': 0.0005754783713231304, 'weight_decay': 0.006638880733046025, 'batch_size': 32}. Best is trial 30 with value: 0.5739423798669575. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.560202 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.37654335691627466, 'ffn_dropout': 0.3102323471459902, 'lr': 0.0005754783713231304, 'weight_decay': 0.006638880733046025, 'batch_size': 32} - Best Value (CSI): 0.573942 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 21:26:29,696] Trial 62 pruned. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.434753 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3773865501948357, 'ffn_dropout': 0.3040078477870456, 'lr': 0.00046089664767572504, 'weight_decay': 0.006234310058972083, 'batch_size': 32} - Best Value (CSI): 0.573942 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 21:31:04,410] Trial 63 pruned. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.559061 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.36422260626178843, 'ffn_dropout': 0.32455065181670145, 'lr': 0.0005968915440851955, 'weight_decay': 0.014024791992890034, 'batch_size': 32} - Best Value (CSI): 0.573942 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 21:34:48,410] Trial 64 finished with value: 0.5665880163727613 and parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3890792732898677, 'ffn_dropout': 0.29268256927689495, 'lr': 0.0007189259567489787, 'weight_decay': 0.03136458170589396, 'batch_size': 32}. Best is trial 30 with value: 0.5739423798669575. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.566588 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3890792732898677, 'ffn_dropout': 0.29268256927689495, 'lr': 0.0007189259567489787, 'weight_decay': 0.03136458170589396, 'batch_size': 32} - Best Value (CSI): 0.573942 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 21:38:51,737] Trial 65 finished with value: 0.5706486791923684 and parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.38737025053500174, 'ffn_dropout': 0.2885530256036787, 'lr': 0.0009615470402995749, 'weight_decay': 0.0298947595557374, 'batch_size': 32}. Best is trial 30 with value: 0.5739423798669575. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.570649 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.38737025053500174, 'ffn_dropout': 0.2885530256036787, 'lr': 0.0009615470402995749, 'weight_decay': 0.0298947595557374, 'batch_size': 32} - Best Value (CSI): 0.573942 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 21:42:55,975] Trial 66 finished with value: 0.5615172280155561 and parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3880516617886017, 'ffn_dropout': 0.29071859501263, 'lr': 0.0009684755365473027, 'weight_decay': 0.029378966445853867, 'batch_size': 32}. Best is trial 30 with value: 0.5739423798669575. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.561517 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3880516617886017, 'ffn_dropout': 0.29071859501263, 'lr': 0.0009684755365473027, 'weight_decay': 0.029378966445853867, 'batch_size': 32} - Best Value (CSI): 0.573942 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 21:46:58,418] Trial 67 finished with value: 0.5629685429875654 and parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.34425218202151553, 'ffn_dropout': 0.2769073742107657, 'lr': 0.0012387424376063703, 'weight_decay': 0.07546857055825353, 'batch_size': 32}. Best is trial 30 with value: 0.5739423798669575. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.562969 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.34425218202151553, 'ffn_dropout': 0.2769073742107657, 'lr': 0.0012387424376063703, 'weight_decay': 0.07546857055825353, 'batch_size': 32} - Best Value (CSI): 0.573942 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 21:51:06,738] Trial 68 finished with value: 0.5692813708774116 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3406548464622327, 'ffn_dropout': 0.25644132572381045, 'lr': 0.0016262866532545932, 'weight_decay': 0.07725577996196337, 'batch_size': 32}. Best is trial 30 with value: 0.5739423798669575. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.569281 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3406548464622327, 'ffn_dropout': 0.25644132572381045, 'lr': 0.0016262866532545932, 'weight_decay': 0.07725577996196337, 'batch_size': 32} - Best Value (CSI): 0.573942 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 21:58:59,748] Trial 69 finished with value: 0.5628392979329541 and parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.33767114719270636, 'ffn_dropout': 0.2563228033177759, 'lr': 0.0017363667797323876, 'weight_decay': 0.07371002706547067, 'batch_size': 32}. Best is trial 30 with value: 0.5739423798669575. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.562839 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.33767114719270636, 'ffn_dropout': 0.2563228033177759, 'lr': 0.0017363667797323876, 'weight_decay': 0.07371002706547067, 'batch_size': 32} - Best Value (CSI): 0.573942 - Best Trial: 30 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.38148005983524574, 'ffn_dropout': 0.3010843219695151, 'lr': 0.0010835171323778457, 'weight_decay': 0.04092948451329147, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 22:09:00,517] Trial 70 finished with value: 0.5788930444782093 and parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3074211243640513, 'ffn_dropout': 0.27614330827417055, 'lr': 0.0008013502604362781, 'weight_decay': 0.07731586815781724, 'batch_size': 32}. Best is trial 70 with value: 0.5788930444782093. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.578893 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3074211243640513, 'ffn_dropout': 0.27614330827417055, 'lr': 0.0008013502604362781, 'weight_decay': 0.07731586815781724, 'batch_size': 32} - Best Value (CSI): 0.578893 - Best Trial: 70 - Best Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3074211243640513, 'ffn_dropout': 0.27614330827417055, 'lr': 0.0008013502604362781, 'weight_decay': 0.07731586815781724, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) -[I 2025-12-25 22:13:10,261] Trial 71 pruned. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.595218 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.30008365770585377, 'ffn_dropout': 0.27491644995920816, 'lr': 0.000723688838853777, 'weight_decay': 0.08323835540876641, 'batch_size': 32} - Best Value (CSI): 0.578893 - Best Trial: 70 - Best Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3074211243640513, 'ffn_dropout': 0.27614330827417055, 'lr': 0.0008013502604362781, 'weight_decay': 0.07731586815781724, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 22:15:28,179] Trial 72 pruned. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.410857 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34253885679161217, 'ffn_dropout': 0.26632190993694255, 'lr': 0.0012053422335897349, 'weight_decay': 0.06931988179559491, 'batch_size': 32} - Best Value (CSI): 0.578893 - Best Trial: 70 - Best Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3074211243640513, 'ffn_dropout': 0.27614330827417055, 'lr': 0.0008013502604362781, 'weight_decay': 0.07731586815781724, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 22:23:14,343] Trial 73 finished with value: 0.5551125267882084 and parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.32248581721297853, 'ffn_dropout': 0.2785784584565224, 'lr': 0.0009249269917747778, 'weight_decay': 0.04427446957378213, 'batch_size': 32}. Best is trial 70 with value: 0.5788930444782093. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.555113 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.32248581721297853, 'ffn_dropout': 0.2785784584565224, 'lr': 0.0009249269917747778, 'weight_decay': 0.04427446957378213, 'batch_size': 32} - Best Value (CSI): 0.578893 - Best Trial: 70 - Best Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3074211243640513, 'ffn_dropout': 0.27614330827417055, 'lr': 0.0008013502604362781, 'weight_decay': 0.07731586815781724, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 22:32:24,659] Trial 74 finished with value: 0.5670259390135723 and parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.30996466621320123, 'ffn_dropout': 0.2517994263582584, 'lr': 0.0012537725979048621, 'weight_decay': 0.0996051466868357, 'batch_size': 32}. Best is trial 70 with value: 0.5788930444782093. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.567026 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.30996466621320123, 'ffn_dropout': 0.2517994263582584, 'lr': 0.0012537725979048621, 'weight_decay': 0.0996051466868357, 'batch_size': 32} - Best Value (CSI): 0.578893 - Best Trial: 70 - Best Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3074211243640513, 'ffn_dropout': 0.27614330827417055, 'lr': 0.0008013502604362781, 'weight_decay': 0.07731586815781724, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 22:39:12,999] Trial 75 finished with value: 0.5581589134457916 and parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.33100274641091665, 'ffn_dropout': 0.2370402114907833, 'lr': 0.0008142032158604621, 'weight_decay': 0.0917125256812803, 'batch_size': 32}. Best is trial 70 with value: 0.5788930444782093. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.558159 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.33100274641091665, 'ffn_dropout': 0.2370402114907833, 'lr': 0.0008142032158604621, 'weight_decay': 0.0917125256812803, 'batch_size': 32} - Best Value (CSI): 0.578893 - Best Trial: 70 - Best Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3074211243640513, 'ffn_dropout': 0.27614330827417055, 'lr': 0.0008013502604362781, 'weight_decay': 0.07731586815781724, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 22:40:18,580] Trial 76 pruned. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.001480 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.31352276934889156, 'ffn_dropout': 0.29051072975461034, 'lr': 0.001650775700828699, 'weight_decay': 0.05764269884567653, 'batch_size': 32} - Best Value (CSI): 0.578893 - Best Trial: 70 - Best Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3074211243640513, 'ffn_dropout': 0.27614330827417055, 'lr': 0.0008013502604362781, 'weight_decay': 0.07731586815781724, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 22:41:23,567] Trial 77 pruned. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.2824221278748904, 'ffn_dropout': 0.2545318467527504, 'lr': 0.0020954414274899497, 'weight_decay': 0.09733286345391665, 'batch_size': 32} - Best Value (CSI): 0.578893 - Best Trial: 70 - Best Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3074211243640513, 'ffn_dropout': 0.27614330827417055, 'lr': 0.0008013502604362781, 'weight_decay': 0.07731586815781724, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 22:43:11,854] Trial 78 pruned. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.398859 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3602818586257841, 'ffn_dropout': 0.29864795802031036, 'lr': 0.0009562108701837911, 'weight_decay': 0.059737355894209414, 'batch_size': 32} - Best Value (CSI): 0.578893 - Best Trial: 70 - Best Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3074211243640513, 'ffn_dropout': 0.27614330827417055, 'lr': 0.0008013502604362781, 'weight_decay': 0.07731586815781724, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 22:44:32,567] Trial 79 pruned. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.125343 - Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.30724566298703504, 'ffn_dropout': 0.2876518207185582, 'lr': 0.0006957193701722695, 'weight_decay': 0.03642485402655179, 'batch_size': 32} - Best Value (CSI): 0.578893 - Best Trial: 70 - Best Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3074211243640513, 'ffn_dropout': 0.27614330827417055, 'lr': 0.0008013502604362781, 'weight_decay': 0.07731586815781724, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 22:45:41,143] Trial 80 pruned. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.000683 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.37008560158513737, 'ffn_dropout': 0.26339907489289943, 'lr': 0.0013314078993539626, 'weight_decay': 0.045164283946253894, 'batch_size': 32} - Best Value (CSI): 0.578893 - Best Trial: 70 - Best Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3074211243640513, 'ffn_dropout': 0.27614330827417055, 'lr': 0.0008013502604362781, 'weight_decay': 0.07731586815781724, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 22:53:15,239] Trial 81 finished with value: 0.5651597176208346 and parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3480240975324377, 'ffn_dropout': 0.2715471757619841, 'lr': 0.001323723068581014, 'weight_decay': 0.0707799273774972, 'batch_size': 32}. Best is trial 70 with value: 0.5788930444782093. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.565160 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3480240975324377, 'ffn_dropout': 0.2715471757619841, 'lr': 0.001323723068581014, 'weight_decay': 0.0707799273774972, 'batch_size': 32} - Best Value (CSI): 0.578893 - Best Trial: 70 - Best Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3074211243640513, 'ffn_dropout': 0.27614330827417055, 'lr': 0.0008013502604362781, 'weight_decay': 0.07731586815781724, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 23:03:48,629] Trial 82 finished with value: 0.5628704264715482 and parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3573703706958984, 'ffn_dropout': 0.2504938218419798, 'lr': 0.001542618187645844, 'weight_decay': 0.07362777361146328, 'batch_size': 32}. Best is trial 70 with value: 0.5788930444782093. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.562870 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3573703706958984, 'ffn_dropout': 0.2504938218419798, 'lr': 0.001542618187645844, 'weight_decay': 0.07362777361146328, 'batch_size': 32} - Best Value (CSI): 0.578893 - Best Trial: 70 - Best Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3074211243640513, 'ffn_dropout': 0.27614330827417055, 'lr': 0.0008013502604362781, 'weight_decay': 0.07731586815781724, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 23:12:39,633] Trial 83 finished with value: 0.565812261770987 and parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3268795235299381, 'ffn_dropout': 0.2705959622998229, 'lr': 0.0010420768151247234, 'weight_decay': 0.04918193311558426, 'batch_size': 32}. Best is trial 70 with value: 0.5788930444782093. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.565812 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3268795235299381, 'ffn_dropout': 0.2705959622998229, 'lr': 0.0010420768151247234, 'weight_decay': 0.04918193311558426, 'batch_size': 32} - Best Value (CSI): 0.578893 - Best Trial: 70 - Best Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3074211243640513, 'ffn_dropout': 0.27614330827417055, 'lr': 0.0008013502604362781, 'weight_decay': 0.07731586815781724, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 23:14:01,430] Trial 84 pruned. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.428181 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3271590122321988, 'ffn_dropout': 0.2705307329833598, 'lr': 0.0022634644955080965, 'weight_decay': 0.048764632133182925, 'batch_size': 32} - Best Value (CSI): 0.578893 - Best Trial: 70 - Best Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3074211243640513, 'ffn_dropout': 0.27614330827417055, 'lr': 0.0008013502604362781, 'weight_decay': 0.07731586815781724, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) -[I 2025-12-25 23:17:52,081] Trial 85 pruned. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.583204 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.33014281590307154, 'ffn_dropout': 0.2599902383267461, 'lr': 0.0010102992357125479, 'weight_decay': 0.06143589759794122, 'batch_size': 32} - Best Value (CSI): 0.578893 - Best Trial: 70 - Best Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3074211243640513, 'ffn_dropout': 0.27614330827417055, 'lr': 0.0008013502604362781, 'weight_decay': 0.07731586815781724, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 23:19:33,360] Trial 86 pruned. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.419783 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3221892430452531, 'ffn_dropout': 0.28202546254283495, 'lr': 0.0018791466531770835, 'weight_decay': 0.0796201590672731, 'batch_size': 32} - Best Value (CSI): 0.578893 - Best Trial: 70 - Best Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3074211243640513, 'ffn_dropout': 0.27614330827417055, 'lr': 0.0008013502604362781, 'weight_decay': 0.07731586815781724, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 23:20:08,918] Trial 87 pruned. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.000683 - Parameters: {'d_token': 256, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.3355768427548912, 'ffn_dropout': 0.2739572592202757, 'lr': 0.0013587601011859163, 'weight_decay': 0.06292861151506204, 'batch_size': 128} - Best Value (CSI): 0.578893 - Best Trial: 70 - Best Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3074211243640513, 'ffn_dropout': 0.27614330827417055, 'lr': 0.0008013502604362781, 'weight_decay': 0.07731586815781724, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 23:21:09,545] Trial 88 pruned. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.000683 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.3449721072590436, 'ffn_dropout': 0.24506762797136117, 'lr': 0.0026752949720094572, 'weight_decay': 0.03492776211596092, 'batch_size': 32} - Best Value (CSI): 0.578893 - Best Trial: 70 - Best Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3074211243640513, 'ffn_dropout': 0.27614330827417055, 'lr': 0.0008013502604362781, 'weight_decay': 0.07731586815781724, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 23:28:41,662] Trial 89 finished with value: 0.5565324832208595 and parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.35430658446143476, 'ffn_dropout': 0.26881177234303066, 'lr': 0.0008413636189470239, 'weight_decay': 0.05061578234544091, 'batch_size': 32}. Best is trial 70 with value: 0.5788930444782093. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.556532 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.35430658446143476, 'ffn_dropout': 0.26881177234303066, 'lr': 0.0008413636189470239, 'weight_decay': 0.05061578234544091, 'batch_size': 32} - Best Value (CSI): 0.578893 - Best Trial: 70 - Best Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3074211243640513, 'ffn_dropout': 0.27614330827417055, 'lr': 0.0008013502604362781, 'weight_decay': 0.07731586815781724, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 23:36:40,182] Trial 90 finished with value: 0.5614517821634438 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.38258481486342033, 'ffn_dropout': 0.2998804506065136, 'lr': 0.0010949431786518207, 'weight_decay': 0.09851811155962549, 'batch_size': 32}. Best is trial 70 with value: 0.5788930444782093. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.561452 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.38258481486342033, 'ffn_dropout': 0.2998804506065136, 'lr': 0.0010949431786518207, 'weight_decay': 0.09851811155962549, 'batch_size': 32} - Best Value (CSI): 0.578893 - Best Trial: 70 - Best Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3074211243640513, 'ffn_dropout': 0.27614330827417055, 'lr': 0.0008013502604362781, 'weight_decay': 0.07731586815781724, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) -[I 2025-12-25 23:40:02,762] Trial 91 pruned. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.605410 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3932423152092808, 'ffn_dropout': 0.29301872108818416, 'lr': 0.0006998506199632206, 'weight_decay': 0.03970538329055356, 'batch_size': 32} - Best Value (CSI): 0.578893 - Best Trial: 70 - Best Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3074211243640513, 'ffn_dropout': 0.27614330827417055, 'lr': 0.0008013502604362781, 'weight_decay': 0.07731586815781724, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 23:47:21,754] Trial 92 finished with value: 0.5599567437283716 and parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.37251809274549397, 'ffn_dropout': 0.28150476079501385, 'lr': 0.0012287252121993462, 'weight_decay': 0.03022829917433228, 'batch_size': 32}. Best is trial 70 with value: 0.5788930444782093. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.559957 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.37251809274549397, 'ffn_dropout': 0.28150476079501385, 'lr': 0.0012287252121993462, 'weight_decay': 0.03022829917433228, 'batch_size': 32} - Best Value (CSI): 0.578893 - Best Trial: 70 - Best Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3074211243640513, 'ffn_dropout': 0.27614330827417055, 'lr': 0.0008013502604362781, 'weight_decay': 0.07731586815781724, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 23:48:24,023] Trial 93 pruned. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.000683 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.38377935609886926, 'ffn_dropout': 0.2879655871230607, 'lr': 0.0016194408896374286, 'weight_decay': 0.048061556827654915, 'batch_size': 32} - Best Value (CSI): 0.578893 - Best Trial: 70 - Best Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3074211243640513, 'ffn_dropout': 0.27614330827417055, 'lr': 0.0008013502604362781, 'weight_decay': 0.07731586815781724, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 23:48:34,937] Trial 94 pruned. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.395203 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.39240721936065365, 'ffn_dropout': 0.2632843898405157, 'lr': 0.0007847351498047383, 'weight_decay': 0.06391170731527436, 'batch_size': 256} - Best Value (CSI): 0.578893 - Best Trial: 70 - Best Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3074211243640513, 'ffn_dropout': 0.27614330827417055, 'lr': 0.0008013502604362781, 'weight_decay': 0.07731586815781724, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 23:49:21,095] Trial 95 pruned. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.062007 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3674599917982618, 'ffn_dropout': 0.30333793777215273, 'lr': 0.0010032512033497254, 'weight_decay': 0.08173363107303909, 'batch_size': 32} - Best Value (CSI): 0.578893 - Best Trial: 70 - Best Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3074211243640513, 'ffn_dropout': 0.27614330827417055, 'lr': 0.0008013502604362781, 'weight_decay': 0.07731586815781724, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) -[I 2025-12-25 23:53:17,024] Trial 96 pruned. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.601802 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3806036905422855, 'ffn_dropout': 0.31432255157989114, 'lr': 0.0006033798131889798, 'weight_decay': 0.041648225988786286, 'batch_size': 32} - Best Value (CSI): 0.578893 - Best Trial: 70 - Best Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3074211243640513, 'ffn_dropout': 0.27614330827417055, 'lr': 0.0008013502604362781, 'weight_decay': 0.07731586815781724, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) -[I 2025-12-25 23:53:41,012] Trial 97 pruned. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.411919 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.34952380464959953, 'ffn_dropout': 0.27217217230790786, 'lr': 0.0014220974799586887, 'weight_decay': 0.032451004333123, 'batch_size': 128} - Best Value (CSI): 0.578893 - Best Trial: 70 - Best Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3074211243640513, 'ffn_dropout': 0.27614330827417055, 'lr': 0.0008013502604362781, 'weight_decay': 0.07731586815781724, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-25 23:59:57,894] Trial 98 finished with value: 0.5566019310765739 and parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.39412281191838444, 'ffn_dropout': 0.2956749054464063, 'lr': 0.0008934989219919747, 'weight_decay': 0.054029038695790246, 'batch_size': 32}. Best is trial 70 with value: 0.5788930444782093. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.556602 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.39412281191838444, 'ffn_dropout': 0.2956749054464063, 'lr': 0.0008934989219919747, 'weight_decay': 0.054029038695790246, 'batch_size': 32} - Best Value (CSI): 0.578893 - Best Trial: 70 - Best Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3074211243640513, 'ffn_dropout': 0.27614330827417055, 'lr': 0.0008013502604362781, 'weight_decay': 0.07731586815781724, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 1.3198333333333334, 1: 1.3198333333333334, 2: 0.6735561792974398} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 1.3259583333333333, 1: 1.3259583333333333, 2: 0.6703954159556763} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 1.3280416666666666, 1: 1.3280416666666666, 2: 0.6693336693336693} (클래스별 샘플 수: {0: 8000, 1: 8000, 2: 15873}) -[I 2025-12-26 00:03:11,808] Trial 99 finished with value: 0.553663457901731 and parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.36414671164460966, 'ffn_dropout': 0.2813245471284871, 'lr': 0.0019368781689484509, 'weight_decay': 0.026749424188425228, 'batch_size': 32}. Best is trial 70 with value: 0.5788930444782093. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.553663 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.36414671164460966, 'ffn_dropout': 0.2813245471284871, 'lr': 0.0019368781689484509, 'weight_decay': 0.026749424188425228, 'batch_size': 32} - Best Value (CSI): 0.578893 - Best Trial: 70 - Best Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3074211243640513, 'ffn_dropout': 0.27614330827417055, 'lr': 0.0008013502604362781, 'weight_decay': 0.07731586815781724, 'batch_size': 32} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.5789 -Best Hyperparameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3074211243640513, 'ffn_dropout': 0.27614330827417055, 'lr': 0.0008013502604362781, 'weight_decay': 0.07731586815781724, 'batch_size': 32} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.4938 - - 최종 CSI: 0.5537 - - 최고 CSI: 0.6054 - - 최저 CSI: 0.0000 - - 평균 CSI: 0.4202 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/ft_transformer_smote_seoul_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 20, Best CSI: 0.4754 - Fold 1 학습 완료 (검증 CSI: 0.4754) -Fold 2 학습 중... - Early stopping at epoch 23, Best CSI: 0.6354 - Fold 2 학습 완료 (검증 CSI: 0.6354) -Fold 3 학습 중... - Early stopping at epoch 30, Best CSI: 0.5902 - Fold 3 학습 완료 (검증 CSI: 0.5902) - -모든 모델 저장 완료: ../save_model/ft_transformer_optima/ft_transformer_smote_seoul.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/ft_transformer_optima/scaler/ft_transformer_smote_seoul_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: ../save_model/ft_transformer_optima/ft_transformer_smote_seoul.pkl - -✓ 완료: ft_transformer_smote/ft_transformer_smote_seoul.py (소요 시간: 18329초) - -========================================== -FT-Transformer SMOTE 파일 실행 완료 -종료 시간: 2025-12-26 00:10:08 -총 소요 시간: 27시간 4분 14초 -성공: 6개 -실패: 0개 -========================================== diff --git a/Analysis_code/5.optima/run_bash/ft_transformer/ft_transformer_smotenc_ctgan20000.log b/Analysis_code/5.optima/run_bash/ft_transformer/ft_transformer_smotenc_ctgan20000.log deleted file mode 100644 index e98b40db1dd16fba699cd18e3a5c00b0f9e85ffe..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/run_bash/ft_transformer/ft_transformer_smotenc_ctgan20000.log +++ /dev/null @@ -1,7829 +0,0 @@ -nohup: ignoring input -/bin/bash: /opt/conda/lib/libtinfo.so.6: no version information available (required by /bin/bash) -========================================== -FT-Transformer SMOTENC CTGAN20000 파일 실행 시작 -시작 시간: 2025-12-25 10:38:16 -GPU: 0번 (CUDA_VISIBLE_DEVICES=0) -========================================== - ----------------------------------------- -실행 중: ft_transformer_smotenc_ctgan20000/ft_transformer_smotenc_ctgan20000_busan.py -시작 시간: 2025-12-25 10:38:16 ----------------------------------------- -[I 2025-12-25 10:38:17,224] A new study created in memory with name: no-name-2fef1dcd-e1c4-454b-ba29-9af2f12e8ff0 - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 10:45:27,018] Trial 0 finished with value: 0.34653609971275773 and parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.3191819416027283, 'ffn_dropout': 0.11837664159745498, 'lr': 4.8031238484876325e-05, 'weight_decay': 0.00017223807950133492, 'batch_size': 64}. Best is trial 0 with value: 0.34653609971275773. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.346536 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.3191819416027283, 'ffn_dropout': 0.11837664159745498, 'lr': 4.8031238484876325e-05, 'weight_decay': 0.00017223807950133492, 'batch_size': 64} - Best Value (CSI): 0.346536 - Best Trial: 0 - Best Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.3191819416027283, 'ffn_dropout': 0.11837664159745498, 'lr': 4.8031238484876325e-05, 'weight_decay': 0.00017223807950133492, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 10:48:12,137] Trial 1 finished with value: 0.14522147035380997 and parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3638819822996715, 'ffn_dropout': 0.22245185356504102, 'lr': 1.0187195009948774e-05, 'weight_decay': 0.0014007335114562208, 'batch_size': 256}. Best is trial 0 with value: 0.34653609971275773. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.145221 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3638819822996715, 'ffn_dropout': 0.22245185356504102, 'lr': 1.0187195009948774e-05, 'weight_decay': 0.0014007335114562208, 'batch_size': 256} - Best Value (CSI): 0.346536 - Best Trial: 0 - Best Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.3191819416027283, 'ffn_dropout': 0.11837664159745498, 'lr': 4.8031238484876325e-05, 'weight_decay': 0.00017223807950133492, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 10:50:16,208] Trial 2 finished with value: 0.26168385511642894 and parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.38913820974652547, 'ffn_dropout': 0.3898318082976693, 'lr': 5.4494237777809354e-05, 'weight_decay': 0.020325506457935245, 'batch_size': 256}. Best is trial 0 with value: 0.34653609971275773. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.261684 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.38913820974652547, 'ffn_dropout': 0.3898318082976693, 'lr': 5.4494237777809354e-05, 'weight_decay': 0.020325506457935245, 'batch_size': 256} - Best Value (CSI): 0.346536 - Best Trial: 0 - Best Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.3191819416027283, 'ffn_dropout': 0.11837664159745498, 'lr': 4.8031238484876325e-05, 'weight_decay': 0.00017223807950133492, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 10:54:51,934] Trial 3 finished with value: 0.44110809037062443 and parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.12075167071072943, 'ffn_dropout': 0.3490224616414502, 'lr': 0.001319965989646812, 'weight_decay': 0.0009097415920275851, 'batch_size': 64}. Best is trial 3 with value: 0.44110809037062443. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.441108 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.12075167071072943, 'ffn_dropout': 0.3490224616414502, 'lr': 0.001319965989646812, 'weight_decay': 0.0009097415920275851, 'batch_size': 64} - Best Value (CSI): 0.441108 - Best Trial: 3 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.12075167071072943, 'ffn_dropout': 0.3490224616414502, 'lr': 0.001319965989646812, 'weight_decay': 0.0009097415920275851, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 11:01:46,539] Trial 4 finished with value: 0.4199016993723717 and parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.19276121082866748, 'ffn_dropout': 0.24091996448447728, 'lr': 0.0002343986275540271, 'weight_decay': 0.003752694757196346, 'batch_size': 64}. Best is trial 3 with value: 0.44110809037062443. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.419902 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.19276121082866748, 'ffn_dropout': 0.24091996448447728, 'lr': 0.0002343986275540271, 'weight_decay': 0.003752694757196346, 'batch_size': 64} - Best Value (CSI): 0.441108 - Best Trial: 3 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.12075167071072943, 'ffn_dropout': 0.3490224616414502, 'lr': 0.001319965989646812, 'weight_decay': 0.0009097415920275851, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 11:04:07,517] Trial 5 finished with value: 0.4416230923959082 and parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3698929897285784, 'ffn_dropout': 0.13980663915386146, 'lr': 0.0014012472047719223, 'weight_decay': 0.0007896440966610926, 'batch_size': 256}. Best is trial 5 with value: 0.4416230923959082. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.441623 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3698929897285784, 'ffn_dropout': 0.13980663915386146, 'lr': 0.0014012472047719223, 'weight_decay': 0.0007896440966610926, 'batch_size': 256} - Best Value (CSI): 0.441623 - Best Trial: 5 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3698929897285784, 'ffn_dropout': 0.13980663915386146, 'lr': 0.0014012472047719223, 'weight_decay': 0.0007896440966610926, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 11:04:19,100] Trial 6 pruned. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.095640 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2944248346327449, 'ffn_dropout': 0.34521053920178524, 'lr': 5.6691388006350116e-05, 'weight_decay': 0.0032210019042800027, 'batch_size': 256} - Best Value (CSI): 0.441623 - Best Trial: 5 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3698929897285784, 'ffn_dropout': 0.13980663915386146, 'lr': 0.0014012472047719223, 'weight_decay': 0.0007896440966610926, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 11:04:56,979] Trial 7 pruned. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.021816 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3861664320090893, 'ffn_dropout': 0.11036500096476556, 'lr': 0.00621536949144761, 'weight_decay': 0.0007090933456994643, 'batch_size': 64} - Best Value (CSI): 0.441623 - Best Trial: 5 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3698929897285784, 'ffn_dropout': 0.13980663915386146, 'lr': 0.0014012472047719223, 'weight_decay': 0.0007896440966610926, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 11:05:31,077] Trial 8 pruned. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.197844 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.39582154030812045, 'ffn_dropout': 0.3262818723920545, 'lr': 4.006026392008907e-05, 'weight_decay': 0.0009558797678065192, 'batch_size': 256} - Best Value (CSI): 0.441623 - Best Trial: 5 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3698929897285784, 'ffn_dropout': 0.13980663915386146, 'lr': 0.0014012472047719223, 'weight_decay': 0.0007896440966610926, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 11:07:22,287] Trial 9 pruned. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.004668 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.17818246296749607, 'ffn_dropout': 0.2184297308783751, 'lr': 0.00903009147082888, 'weight_decay': 0.0010339336624258933, 'batch_size': 32} - Best Value (CSI): 0.441623 - Best Trial: 5 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3698929897285784, 'ffn_dropout': 0.13980663915386146, 'lr': 0.0014012472047719223, 'weight_decay': 0.0007896440966610926, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 11:12:04,244] Trial 10 finished with value: 0.4357512465375842 and parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2631232130359124, 'ffn_dropout': 0.1754167264101693, 'lr': 0.0009590341442389305, 'weight_decay': 0.0001097607107315249, 'batch_size': 128}. Best is trial 5 with value: 0.4416230923959082. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.435751 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2631232130359124, 'ffn_dropout': 0.1754167264101693, 'lr': 0.0009590341442389305, 'weight_decay': 0.0001097607107315249, 'batch_size': 128} - Best Value (CSI): 0.441623 - Best Trial: 5 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3698929897285784, 'ffn_dropout': 0.13980663915386146, 'lr': 0.0014012472047719223, 'weight_decay': 0.0007896440966610926, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 11:21:00,273] Trial 11 finished with value: 0.45512090988761494 and parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1366655411012947, 'ffn_dropout': 0.3017771627519923, 'lr': 0.001391698462510641, 'weight_decay': 0.00030625867776110804, 'batch_size': 32}. Best is trial 11 with value: 0.45512090988761494. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.455121 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1366655411012947, 'ffn_dropout': 0.3017771627519923, 'lr': 0.001391698462510641, 'weight_decay': 0.00030625867776110804, 'batch_size': 32} - Best Value (CSI): 0.455121 - Best Trial: 11 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1366655411012947, 'ffn_dropout': 0.3017771627519923, 'lr': 0.001391698462510641, 'weight_decay': 0.00030625867776110804, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 11:22:21,279] Trial 12 pruned. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.048743 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2253074546545586, 'ffn_dropout': 0.2822728881290043, 'lr': 0.0019307946161073038, 'weight_decay': 0.000249195875908889, 'batch_size': 32} - Best Value (CSI): 0.455121 - Best Trial: 11 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1366655411012947, 'ffn_dropout': 0.3017771627519923, 'lr': 0.001391698462510641, 'weight_decay': 0.00030625867776110804, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 11:30:08,315] Trial 13 finished with value: 0.44306829391425256 and parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11976964455483141, 'ffn_dropout': 0.29179886293505986, 'lr': 0.0005962781330656876, 'weight_decay': 0.000348821823835227, 'batch_size': 32}. Best is trial 11 with value: 0.45512090988761494. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.443068 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11976964455483141, 'ffn_dropout': 0.29179886293505986, 'lr': 0.0005962781330656876, 'weight_decay': 0.000348821823835227, 'batch_size': 32} - Best Value (CSI): 0.455121 - Best Trial: 11 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1366655411012947, 'ffn_dropout': 0.3017771627519923, 'lr': 0.001391698462510641, 'weight_decay': 0.00030625867776110804, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 11:47:23,489] Trial 14 finished with value: 0.4260741104009384 and parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.10687657698455881, 'ffn_dropout': 0.285518506066179, 'lr': 0.0003541159454050653, 'weight_decay': 0.00027651094993029273, 'batch_size': 32}. Best is trial 11 with value: 0.45512090988761494. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.426074 - Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.10687657698455881, 'ffn_dropout': 0.285518506066179, 'lr': 0.0003541159454050653, 'weight_decay': 0.00027651094993029273, 'batch_size': 32} - Best Value (CSI): 0.455121 - Best Trial: 11 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1366655411012947, 'ffn_dropout': 0.3017771627519923, 'lr': 0.001391698462510641, 'weight_decay': 0.00030625867776110804, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 11:48:47,853] Trial 15 pruned. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.004668 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13477271548048048, 'ffn_dropout': 0.3053287406310753, 'lr': 0.0038964666709539442, 'weight_decay': 0.0003371362850923006, 'batch_size': 32} - Best Value (CSI): 0.455121 - Best Trial: 11 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1366655411012947, 'ffn_dropout': 0.3017771627519923, 'lr': 0.001391698462510641, 'weight_decay': 0.00030625867776110804, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 12:01:04,928] Trial 16 finished with value: 0.4314638754221402 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.15253847611342802, 'ffn_dropout': 0.26551114044543866, 'lr': 0.00046763087116830754, 'weight_decay': 0.00011215562128124161, 'batch_size': 32}. Best is trial 11 with value: 0.45512090988761494. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.431464 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.15253847611342802, 'ffn_dropout': 0.26551114044543866, 'lr': 0.00046763087116830754, 'weight_decay': 0.00011215562128124161, 'batch_size': 32} - Best Value (CSI): 0.455121 - Best Trial: 11 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1366655411012947, 'ffn_dropout': 0.3017771627519923, 'lr': 0.001391698462510641, 'weight_decay': 0.00030625867776110804, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 12:01:35,939] Trial 17 pruned. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.021357 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.10813642957202581, 'ffn_dropout': 0.30791608046299745, 'lr': 0.003325935068555528, 'weight_decay': 0.0003851153223931616, 'batch_size': 128} - Best Value (CSI): 0.455121 - Best Trial: 11 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1366655411012947, 'ffn_dropout': 0.3017771627519923, 'lr': 0.001391698462510641, 'weight_decay': 0.00030625867776110804, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 12:03:17,978] Trial 18 pruned. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.260553 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1539397074042178, 'ffn_dropout': 0.25957613076998315, 'lr': 0.0007912782607302906, 'weight_decay': 0.09560444833822071, 'batch_size': 32} - Best Value (CSI): 0.455121 - Best Trial: 11 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1366655411012947, 'ffn_dropout': 0.3017771627519923, 'lr': 0.001391698462510641, 'weight_decay': 0.00030625867776110804, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 12:04:37,893] Trial 19 pruned. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.149817 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.10120118012366719, 'ffn_dropout': 0.38684970462683443, 'lr': 0.0030037756097401956, 'weight_decay': 0.00044648995109211387, 'batch_size': 32} - Best Value (CSI): 0.455121 - Best Trial: 11 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1366655411012947, 'ffn_dropout': 0.3017771627519923, 'lr': 0.001391698462510641, 'weight_decay': 0.00030625867776110804, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 12:06:43,259] Trial 20 pruned. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.364023 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1932224165939456, 'ffn_dropout': 0.35250051116508724, 'lr': 0.00018672352993339913, 'weight_decay': 0.0018497743263767763, 'batch_size': 32} - Best Value (CSI): 0.455121 - Best Trial: 11 - Best Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1366655411012947, 'ffn_dropout': 0.3017771627519923, 'lr': 0.001391698462510641, 'weight_decay': 0.00030625867776110804, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 12:09:13,628] Trial 21 finished with value: 0.4573290786148192 and parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.22601435178705062, 'ffn_dropout': 0.18810915653590365, 'lr': 0.0015810611024692123, 'weight_decay': 0.0005003482677601571, 'batch_size': 256}. Best is trial 21 with value: 0.4573290786148192. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.457329 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.22601435178705062, 'ffn_dropout': 0.18810915653590365, 'lr': 0.0015810611024692123, 'weight_decay': 0.0005003482677601571, 'batch_size': 256} - Best Value (CSI): 0.457329 - Best Trial: 21 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.22601435178705062, 'ffn_dropout': 0.18810915653590365, 'lr': 0.0015810611024692123, 'weight_decay': 0.0005003482677601571, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 12:10:25,306] Trial 22 pruned. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.362556 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.14201410608091833, 'ffn_dropout': 0.20207286702752467, 'lr': 0.0005754459733518823, 'weight_decay': 0.00019597166977063544, 'batch_size': 128} - Best Value (CSI): 0.457329 - Best Trial: 21 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.22601435178705062, 'ffn_dropout': 0.18810915653590365, 'lr': 0.0015810611024692123, 'weight_decay': 0.0005003482677601571, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 12:12:19,809] Trial 23 finished with value: 0.4601418991661907 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.22975736036712158, 'ffn_dropout': 0.24668962175256368, 'lr': 0.001991356894740147, 'weight_decay': 0.00043589104719548227, 'batch_size': 256}. Best is trial 23 with value: 0.4601418991661907. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.460142 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.22975736036712158, 'ffn_dropout': 0.24668962175256368, 'lr': 0.001991356894740147, 'weight_decay': 0.00043589104719548227, 'batch_size': 256} - Best Value (CSI): 0.460142 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.22975736036712158, 'ffn_dropout': 0.24668962175256368, 'lr': 0.001991356894740147, 'weight_decay': 0.00043589104719548227, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 12:13:31,926] Trial 24 finished with value: 0.43189809527831463 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.22903536587697548, 'ffn_dropout': 0.18251622241701987, 'lr': 0.001377405101923528, 'weight_decay': 0.00016769737643209377, 'batch_size': 256}. Best is trial 23 with value: 0.4601418991661907. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.431898 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.22903536587697548, 'ffn_dropout': 0.18251622241701987, 'lr': 0.001377405101923528, 'weight_decay': 0.00016769737643209377, 'batch_size': 256} - Best Value (CSI): 0.460142 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.22975736036712158, 'ffn_dropout': 0.24668962175256368, 'lr': 0.001991356894740147, 'weight_decay': 0.00043589104719548227, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 12:14:02,795] Trial 25 pruned. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.346549 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.24950673052246414, 'ffn_dropout': 0.24399378844850186, 'lr': 0.0024065252334759517, 'weight_decay': 0.0006103041826471478, 'batch_size': 256} - Best Value (CSI): 0.460142 - Best Trial: 23 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.22975736036712158, 'ffn_dropout': 0.24668962175256368, 'lr': 0.001991356894740147, 'weight_decay': 0.00043589104719548227, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 12:15:51,020] Trial 26 finished with value: 0.4767443843216419 and parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256}. Best is trial 26 with value: 0.4767443843216419. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.476744 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 12:16:16,222] Trial 27 pruned. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.389058 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.20510458182761265, 'ffn_dropout': 0.2641619064603114, 'lr': 0.0052707916618469075, 'weight_decay': 0.0020050110665772456, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 12:16:30,629] Trial 28 pruned. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.031918 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.16692908723021566, 'ffn_dropout': 0.21753755002024344, 'lr': 0.008849898455967753, 'weight_decay': 0.0005304127028983985, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 12:16:54,264] Trial 29 pruned. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.393124 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.21311349593431173, 'ffn_dropout': 0.15106879929394146, 'lr': 0.004553709007833873, 'weight_decay': 0.00016208992379898506, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 12:18:30,056] Trial 30 pruned. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.426997 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.18122861887091093, 'ffn_dropout': 0.19835754906728373, 'lr': 0.002222227018371496, 'weight_decay': 0.0004903407745676802, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 12:19:13,044] Trial 31 pruned. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.385174 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.16707289147953983, 'ffn_dropout': 0.24403597908599245, 'lr': 0.001957387065899047, 'weight_decay': 0.0002242138853413907, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 12:20:05,270] Trial 32 pruned. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.391952 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24923150989429632, 'ffn_dropout': 0.23453545840862375, 'lr': 0.003244395853248018, 'weight_decay': 0.0003533038975079406, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 12:20:33,218] Trial 33 pruned. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.348045 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.20414307979507088, 'ffn_dropout': 0.2558103687715998, 'lr': 0.0009578828545561773, 'weight_decay': 0.0014110856756452375, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 12:21:07,723] Trial 34 pruned. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.096196 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.22783194544703336, 'ffn_dropout': 0.27448298334881754, 'lr': 0.006227347698390083, 'weight_decay': 0.0005454258817693615, 'batch_size': 64} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 12:23:07,442] Trial 35 finished with value: 0.44928091200891856 and parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.13975699360191485, 'ffn_dropout': 0.22312419644815143, 'lr': 0.001661309009430179, 'weight_decay': 0.0002815515483685719, 'batch_size': 256}. Best is trial 26 with value: 0.4767443843216419. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.449281 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.13975699360191485, 'ffn_dropout': 0.22312419644815143, 'lr': 0.001661309009430179, 'weight_decay': 0.0002815515483685719, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 12:26:34,451] Trial 36 finished with value: 0.4559987678493925 and parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.18385108734731404, 'ffn_dropout': 0.2523527499762515, 'lr': 0.0028183059520031986, 'weight_decay': 0.0007311487426712292, 'batch_size': 128}. Best is trial 26 with value: 0.4767443843216419. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.455999 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.18385108734731404, 'ffn_dropout': 0.2523527499762515, 'lr': 0.0028183059520031986, 'weight_decay': 0.0007311487426712292, 'batch_size': 128} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 12:27:26,308] Trial 37 pruned. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.394118 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.19025170021789475, 'ffn_dropout': 0.25122699975507856, 'lr': 0.004530777317355316, 'weight_decay': 0.0010348597354733363, 'batch_size': 128} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 12:27:53,506] Trial 38 pruned. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.328704 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.27498222796878335, 'ffn_dropout': 0.10106305554874051, 'lr': 0.003010254562290115, 'weight_decay': 0.0007990732381014862, 'batch_size': 128} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 12:28:27,878] Trial 39 pruned. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.33647613884595784, 'ffn_dropout': 0.23068937060652434, 'lr': 0.0023683065453830236, 'weight_decay': 0.004772220793430619, 'batch_size': 128} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 12:29:09,365] Trial 40 pruned. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.004668 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.24170352568107886, 'ffn_dropout': 0.27320327162473107, 'lr': 0.0064182492270721874, 'weight_decay': 0.0006868973544424706, 'batch_size': 64} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 12:30:53,915] Trial 41 finished with value: 0.4432548383863472 and parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21442894840157112, 'ffn_dropout': 0.2536226244996936, 'lr': 0.00119279790858343, 'weight_decay': 0.00046909735656588947, 'batch_size': 256}. Best is trial 26 with value: 0.4767443843216419. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.443255 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.21442894840157112, 'ffn_dropout': 0.2536226244996936, 'lr': 0.00119279790858343, 'weight_decay': 0.00046909735656588947, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 12:33:11,100] Trial 42 finished with value: 0.43836557156194456 and parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.17204315883624327, 'ffn_dropout': 0.2970913452341879, 'lr': 0.0013908291982992133, 'weight_decay': 0.00023499211803328977, 'batch_size': 128}. Best is trial 26 with value: 0.4767443843216419. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.438366 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.17204315883624327, 'ffn_dropout': 0.2970913452341879, 'lr': 0.0013908291982992133, 'weight_decay': 0.00023499211803328977, 'batch_size': 128} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 12:34:45,534] Trial 43 finished with value: 0.45792831081826685 and parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.19300956563515426, 'ffn_dropout': 0.274951086710747, 'lr': 0.0018359477440753882, 'weight_decay': 0.0006651895797932327, 'batch_size': 256}. Best is trial 26 with value: 0.4767443843216419. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.457928 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.19300956563515426, 'ffn_dropout': 0.274951086710747, 'lr': 0.0018359477440753882, 'weight_decay': 0.0006651895797932327, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 12:36:14,134] Trial 44 finished with value: 0.44781296908165286 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.19459747063819505, 'ffn_dropout': 0.2359673774249207, 'lr': 0.002686199041070246, 'weight_decay': 0.0007002399788701869, 'batch_size': 256}. Best is trial 26 with value: 0.4767443843216419. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.447813 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.19459747063819505, 'ffn_dropout': 0.2359673774249207, 'lr': 0.002686199041070246, 'weight_decay': 0.0007002399788701869, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 12:37:40,975] Trial 45 finished with value: 0.43429106394375055 and parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.18349811919206152, 'ffn_dropout': 0.27210552749275896, 'lr': 0.0017882424833161135, 'weight_decay': 0.0010650304290993054, 'batch_size': 256}. Best is trial 26 with value: 0.4767443843216419. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.434291 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.18349811919206152, 'ffn_dropout': 0.27210552749275896, 'lr': 0.0017882424833161135, 'weight_decay': 0.0010650304290993054, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 12:37:56,909] Trial 46 pruned. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.349702 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.23512782123032513, 'ffn_dropout': 0.28290905658305787, 'lr': 0.0037882761495605668, 'weight_decay': 0.0004039271254178031, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 12:38:09,066] Trial 47 pruned. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.092641 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.21573245938899244, 'ffn_dropout': 0.21495692369075922, 'lr': 0.009720235780386135, 'weight_decay': 0.0006121095219552117, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 12:39:04,250] Trial 48 pruned. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.004668 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.26132839148089715, 'ffn_dropout': 0.2498396892887335, 'lr': 0.0010639289903272486, 'weight_decay': 0.0008835451023645825, 'batch_size': 64} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 12:40:36,377] Trial 49 finished with value: 0.44638112902088684 and parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.20038029984918965, 'ffn_dropout': 0.22801701758856963, 'lr': 0.002044924819234204, 'weight_decay': 0.0013061859978170346, 'batch_size': 256}. Best is trial 26 with value: 0.4767443843216419. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.446381 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.20038029984918965, 'ffn_dropout': 0.22801701758856963, 'lr': 0.002044924819234204, 'weight_decay': 0.0013061859978170346, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 12:41:23,197] Trial 50 pruned. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.406926 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.22038572765297593, 'ffn_dropout': 0.26328282286031385, 'lr': 0.0041615310992015675, 'weight_decay': 0.00030653859589027606, 'batch_size': 128} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 12:44:19,499] Trial 51 pruned. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.400000 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.16209085374141619, 'ffn_dropout': 0.29527028962375274, 'lr': 0.0015858959187675845, 'weight_decay': 0.00039400453291148186, 'batch_size': 32} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) -[I 2025-12-25 12:45:42,714] Trial 52 pruned. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.426877 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1796278826805889, 'ffn_dropout': 0.31663745436780005, 'lr': 0.0008068804753937475, 'weight_decay': 0.0002697292599594479, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 12:47:02,135] Trial 53 pruned. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.004668 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1542855149569205, 'ffn_dropout': 0.2781352035156275, 'lr': 0.0023408978903296843, 'weight_decay': 0.0007517709148853159, 'batch_size': 32} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 12:47:55,037] Trial 54 pruned. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.396914 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13355752977927926, 'ffn_dropout': 0.2873678562458577, 'lr': 0.0013315563981777404, 'weight_decay': 0.00014503650100020933, 'batch_size': 128} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 12:50:19,391] Trial 55 finished with value: 0.4477208974610482 and parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.20556965219383766, 'ffn_dropout': 0.30318561656949145, 'lr': 0.0029513881689173615, 'weight_decay': 0.00030823779822582273, 'batch_size': 256}. Best is trial 26 with value: 0.4767443843216419. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.447721 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.20556965219383766, 'ffn_dropout': 0.30318561656949145, 'lr': 0.0029513881689173615, 'weight_decay': 0.00030823779822582273, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 12:51:13,645] Trial 56 pruned. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.061589 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.1880518977674063, 'ffn_dropout': 0.26378903749028887, 'lr': 0.0017076999086395417, 'weight_decay': 0.0002019816068498807, 'batch_size': 64} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 12:52:36,078] Trial 57 pruned. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.004668 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.17367351928327762, 'ffn_dropout': 0.24276020662709846, 'lr': 0.003829845858565007, 'weight_decay': 0.00045350566394309515, 'batch_size': 32} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 12:54:14,619] Trial 58 finished with value: 0.4485453920164563 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.23596847220344994, 'ffn_dropout': 0.2860331822153345, 'lr': 0.001004302849736342, 'weight_decay': 0.0005461495466577174, 'batch_size': 256}. Best is trial 26 with value: 0.4767443843216419. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.448545 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.23596847220344994, 'ffn_dropout': 0.2860331822153345, 'lr': 0.001004302849736342, 'weight_decay': 0.0005461495466577174, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 12:56:29,248] Trial 59 finished with value: 0.44764605129092994 and parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.1558555872688101, 'ffn_dropout': 0.20937378508056, 'lr': 0.0026143118088420743, 'weight_decay': 0.0003560535380561429, 'batch_size': 256}. Best is trial 26 with value: 0.4767443843216419. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.447646 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.1558555872688101, 'ffn_dropout': 0.20937378508056, 'lr': 0.0026143118088420743, 'weight_decay': 0.0003560535380561429, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 12:57:47,163] Trial 60 pruned. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.004668 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.14591972908377313, 'ffn_dropout': 0.3168685346989308, 'lr': 0.005278085047247906, 'weight_decay': 0.00018510869809902777, 'batch_size': 32} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 12:59:42,775] Trial 61 finished with value: 0.4343295904088773 and parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.12111348917800016, 'ffn_dropout': 0.22450585140308096, 'lr': 0.0016261024089102825, 'weight_decay': 0.00027771549677127244, 'batch_size': 256}. Best is trial 26 with value: 0.4767443843216419. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.434330 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.12111348917800016, 'ffn_dropout': 0.22450585140308096, 'lr': 0.0016261024089102825, 'weight_decay': 0.00027771549677127244, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 13:02:19,547] Trial 62 finished with value: 0.44727311482205767 and parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.13675895180796033, 'ffn_dropout': 0.24135928789648842, 'lr': 0.001641537296760403, 'weight_decay': 0.00024049104092538592, 'batch_size': 256}. Best is trial 26 with value: 0.4767443843216419. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.447273 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.13675895180796033, 'ffn_dropout': 0.24135928789648842, 'lr': 0.001641537296760403, 'weight_decay': 0.00024049104092538592, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 13:03:03,869] Trial 63 pruned. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.303783 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1614682576384173, 'ffn_dropout': 0.21986918623551294, 'lr': 0.0013173238779889344, 'weight_decay': 0.00013811047196461305, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 13:03:18,125] Trial 64 pruned. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.392097 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.17395643494080115, 'ffn_dropout': 0.2546248707573335, 'lr': 0.001955895803664305, 'weight_decay': 0.0006113378243539122, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 13:05:07,950] Trial 65 pruned. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.386152 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1471760112175249, 'ffn_dropout': 0.23103662499327637, 'lr': 0.0007064036220485846, 'weight_decay': 0.00039440791250799803, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 13:05:38,521] Trial 66 pruned. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.004668 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.19874051388878247, 'ffn_dropout': 0.19989186987659546, 'lr': 0.003139275096295501, 'weight_decay': 0.0004980026490418165, 'batch_size': 128} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 13:07:14,797] Trial 67 pruned. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.402359 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.18578567489309727, 'ffn_dropout': 0.2689772906729125, 'lr': 0.0010212360193576702, 'weight_decay': 0.00010121793759897493, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 13:07:55,458] Trial 68 pruned. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.349927 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.12989656633884922, 'ffn_dropout': 0.27832858603318666, 'lr': 0.0025800493805933, 'weight_decay': 0.0002851527118980638, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 13:09:11,387] Trial 69 pruned. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.322857 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.14575578516483903, 'ffn_dropout': 0.2595723253946006, 'lr': 0.002166208603057765, 'weight_decay': 0.0003372911671447349, 'batch_size': 32} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 13:09:43,184] Trial 70 pruned. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.061589 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.22172560008854497, 'ffn_dropout': 0.18611970634527436, 'lr': 0.003416925235799461, 'weight_decay': 0.0006400860611992313, 'batch_size': 128} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 13:11:05,378] Trial 71 finished with value: 0.43727493667397604 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2299812398008903, 'ffn_dropout': 0.28951452939872824, 'lr': 0.0011296486566212524, 'weight_decay': 0.0005357081939401283, 'batch_size': 256}. Best is trial 26 with value: 0.4767443843216419. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.437275 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2299812398008903, 'ffn_dropout': 0.28951452939872824, 'lr': 0.0011296486566212524, 'weight_decay': 0.0005357081939401283, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 13:12:28,652] Trial 72 finished with value: 0.4508269593267591 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.20954554063239353, 'ffn_dropout': 0.26729106198578784, 'lr': 0.0008699145965059325, 'weight_decay': 0.00044598589602363434, 'batch_size': 256}. Best is trial 26 with value: 0.4767443843216419. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.450827 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.20954554063239353, 'ffn_dropout': 0.26729106198578784, 'lr': 0.0008699145965059325, 'weight_decay': 0.00044598589602363434, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 13:13:49,239] Trial 73 finished with value: 0.4457799796788053 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.20925642964016827, 'ffn_dropout': 0.24550210091933392, 'lr': 0.0013803726469153025, 'weight_decay': 0.00020536946467730074, 'batch_size': 256}. Best is trial 26 with value: 0.4767443843216419. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.445780 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.20925642964016827, 'ffn_dropout': 0.24550210091933392, 'lr': 0.0013803726469153025, 'weight_decay': 0.00020536946467730074, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 13:14:20,474] Trial 74 pruned. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.350440 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.19997454259863945, 'ffn_dropout': 0.2653061392805125, 'lr': 0.0020082310386905808, 'weight_decay': 0.0004317955516948703, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 13:14:39,173] Trial 75 pruned. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.127280 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.19145094682524166, 'ffn_dropout': 0.2394123089105503, 'lr': 0.0008704537692811568, 'weight_decay': 0.0008929605919869173, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) -[I 2025-12-25 13:15:53,841] Trial 76 pruned. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.414734 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.20936079742146912, 'ffn_dropout': 0.2558304996548714, 'lr': 0.0007175362032166997, 'weight_decay': 0.00024727576073098594, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 13:18:31,031] Trial 77 finished with value: 0.4353049272808623 and parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.16798617068196278, 'ffn_dropout': 0.27119271219737767, 'lr': 0.0012035465849626616, 'weight_decay': 0.00077005027567863, 'batch_size': 64}. Best is trial 26 with value: 0.4767443843216419. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.435305 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.16798617068196278, 'ffn_dropout': 0.27119271219737767, 'lr': 0.0012035465849626616, 'weight_decay': 0.00077005027567863, 'batch_size': 64} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 13:19:09,088] Trial 78 pruned. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.347095 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.18001095878381462, 'ffn_dropout': 0.23408812640845247, 'lr': 0.0015745507106356006, 'weight_decay': 0.0003560511242751083, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 13:20:14,873] Trial 79 pruned. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.366569 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.22058274484620521, 'ffn_dropout': 0.2479683783038359, 'lr': 0.002721885488913657, 'weight_decay': 0.00031422804654993237, 'batch_size': 32} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 13:21:01,773] Trial 80 pruned. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.377976 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.1645571631837539, 'ffn_dropout': 0.2801540249322032, 'lr': 0.00048815140060468287, 'weight_decay': 0.00045215352531492904, 'batch_size': 128} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 13:22:23,677] Trial 81 finished with value: 0.44342158925913927 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.23949395157765593, 'ffn_dropout': 0.28516169088004356, 'lr': 0.00177862873661932, 'weight_decay': 0.0005791564201181157, 'batch_size': 256}. Best is trial 26 with value: 0.4767443843216419. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.443422 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.23949395157765593, 'ffn_dropout': 0.28516169088004356, 'lr': 0.00177862873661932, 'weight_decay': 0.0005791564201181157, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 13:22:37,851] Trial 82 pruned. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.328912 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.22963921964335787, 'ffn_dropout': 0.2953795387709227, 'lr': 0.001016223293834828, 'weight_decay': 0.0005513631838511673, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 13:24:33,212] Trial 83 finished with value: 0.44200615007649885 and parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.21477681423892453, 'ffn_dropout': 0.27301781248609386, 'lr': 0.0008811154360055985, 'weight_decay': 0.0006904881590946427, 'batch_size': 256}. Best is trial 26 with value: 0.4767443843216419. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.442006 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.21477681423892453, 'ffn_dropout': 0.27301781248609386, 'lr': 0.0008811154360055985, 'weight_decay': 0.0006904881590946427, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 13:25:57,980] Trial 84 finished with value: 0.43591809167017853 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1944336826695229, 'ffn_dropout': 0.2595312906204113, 'lr': 0.002312878182430955, 'weight_decay': 0.0004992953474476886, 'batch_size': 256}. Best is trial 26 with value: 0.4767443843216419. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.435918 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1944336826695229, 'ffn_dropout': 0.2595312906204113, 'lr': 0.002312878182430955, 'weight_decay': 0.0004992953474476886, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 13:27:34,610] Trial 85 finished with value: 0.45379546343927757 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.23389064223050793, 'ffn_dropout': 0.22574850679595787, 'lr': 0.001209902687215429, 'weight_decay': 0.0003776482013280144, 'batch_size': 256}. Best is trial 26 with value: 0.4767443843216419. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.453795 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.23389064223050793, 'ffn_dropout': 0.22574850679595787, 'lr': 0.001209902687215429, 'weight_decay': 0.0003776482013280144, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 13:29:25,193] Trial 86 pruned. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.415827 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.20335416220973243, 'ffn_dropout': 0.22078457777913976, 'lr': 0.001225448950414053, 'weight_decay': 0.00039523348627829307, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 13:30:49,358] Trial 87 finished with value: 0.4481764108945782 and parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.18459312504361913, 'ffn_dropout': 0.2088536777654395, 'lr': 0.0015382352593427025, 'weight_decay': 0.00022295602812081225, 'batch_size': 256}. Best is trial 26 with value: 0.4767443843216419. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.448176 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.18459312504361913, 'ffn_dropout': 0.2088536777654395, 'lr': 0.0015382352593427025, 'weight_decay': 0.00022295602812081225, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 13:33:52,953] Trial 88 finished with value: 0.43881177682217104 and parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.24445913363263616, 'ffn_dropout': 0.2274176009402284, 'lr': 0.0019429232426047135, 'weight_decay': 0.00028048274169079795, 'batch_size': 256}. Best is trial 26 with value: 0.4767443843216419. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.438812 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.24445913363263616, 'ffn_dropout': 0.2274176009402284, 'lr': 0.0019429232426047135, 'weight_decay': 0.00028048274169079795, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 13:34:14,990] Trial 89 pruned. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.327869 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.22546690012764933, 'ffn_dropout': 0.2378127370348176, 'lr': 0.003542657296544944, 'weight_decay': 0.0008292420493707163, 'batch_size': 128} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 13:35:17,682] Trial 90 pruned. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.358321 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.21274242045157313, 'ffn_dropout': 0.24757680156487985, 'lr': 0.0014322813214320508, 'weight_decay': 0.00033168463301260496, 'batch_size': 32} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 13:36:36,774] Trial 91 finished with value: 0.45584749594739965 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.23659430501328768, 'ffn_dropout': 0.25217763130284376, 'lr': 0.0011216261024502136, 'weight_decay': 0.0004536580664805107, 'batch_size': 256}. Best is trial 26 with value: 0.4767443843216419. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.455847 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.23659430501328768, 'ffn_dropout': 0.25217763130284376, 'lr': 0.0011216261024502136, 'weight_decay': 0.0004536580664805107, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 13:38:04,403] Trial 92 pruned. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.423797 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.25633764664896436, 'ffn_dropout': 0.2559445689181434, 'lr': 0.0011462914280164582, 'weight_decay': 0.00045652983978617577, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 13:39:31,705] Trial 93 finished with value: 0.4562458293150851 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.23431524980338062, 'ffn_dropout': 0.2512117962644169, 'lr': 0.002196245833875562, 'weight_decay': 0.0003750763072098404, 'batch_size': 256}. Best is trial 26 with value: 0.4767443843216419. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.456246 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.23431524980338062, 'ffn_dropout': 0.2512117962644169, 'lr': 0.002196245833875562, 'weight_decay': 0.0003750763072098404, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 13:40:53,029] Trial 94 finished with value: 0.4460688604413024 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.234533702528838, 'ffn_dropout': 0.2651576417195823, 'lr': 0.0022589405028382637, 'weight_decay': 0.00039770844459943516, 'batch_size': 256}. Best is trial 26 with value: 0.4767443843216419. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.446069 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.234533702528838, 'ffn_dropout': 0.2651576417195823, 'lr': 0.0022589405028382637, 'weight_decay': 0.00039770844459943516, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 13:41:18,293] Trial 95 pruned. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.405099 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2491636599070996, 'ffn_dropout': 0.2504839351187191, 'lr': 0.002789580035851807, 'weight_decay': 0.000621740963362935, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 13:42:40,398] Trial 96 finished with value: 0.4465462052436331 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.22182721903843003, 'ffn_dropout': 0.2771213482151742, 'lr': 0.001858129385679077, 'weight_decay': 0.0007164613081364762, 'batch_size': 256}. Best is trial 26 with value: 0.4767443843216419. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.446546 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.22182721903843003, 'ffn_dropout': 0.2771213482151742, 'lr': 0.001858129385679077, 'weight_decay': 0.0007164613081364762, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 13:43:14,386] Trial 97 pruned. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.310510 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.24270225591523936, 'ffn_dropout': 0.2603582696876636, 'lr': 0.0013876410889136514, 'weight_decay': 0.00048647542976102147, 'batch_size': 64} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) - Fold 2 - 클래스별 가중치: {0: 0.9440162601626017, 1: 0.917172195892575, 2: 1.1759332401612284} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16457}) - Fold 3 - 클래스별 가중치: {0: 0.9437235772357724, 1: 0.9168878357030016, 2: 1.1768558509236167} (클래스별 샘플 수: {0: 20500, 1: 21100, 2: 16439}) -[I 2025-12-25 13:44:29,629] Trial 98 finished with value: 0.4375087866651546 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.23158883506630323, 'ffn_dropout': 0.23940430218123515, 'lr': 0.0009048369010170756, 'weight_decay': 0.0003552041684477496, 'batch_size': 256}. Best is trial 26 with value: 0.4767443843216419. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.437509 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.23158883506630323, 'ffn_dropout': 0.23940430218123515, 'lr': 0.0009048369010170756, 'weight_decay': 0.0003552041684477496, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.9205079365079365, 2: 1.1721238580321771} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16492}) -[I 2025-12-25 13:44:55,942] Trial 99 pruned. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.388393 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.21901671005651235, 'ffn_dropout': 0.26663476728373237, 'lr': 0.003090794691045327, 'weight_decay': 0.0011005644409549972, 'batch_size': 256} - Best Value (CSI): 0.476744 - Best Trial: 26 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.4767 -Best Hyperparameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1711218539171086, 'ffn_dropout': 0.2636519595986711, 'lr': 0.004358575253869887, 'weight_decay': 0.00046754184762985804, 'batch_size': 256} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.3465 - - 최종 CSI: 0.3884 - - 최고 CSI: 0.4767 - - 최저 CSI: 0.0000 - - 평균 CSI: 0.3293 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/ft_transformer_smotenc_ctgan20000_busan_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 34, Best CSI: 0.4090 - Fold 1 학습 완료 (검증 CSI: 0.4090) -Fold 2 학습 중... - Early stopping at epoch 27, Best CSI: 0.4633 - Fold 2 학습 완료 (검증 CSI: 0.4633) -Fold 3 학습 중... - Early stopping at epoch 26, Best CSI: 0.4595 - Fold 3 학습 완료 (검증 CSI: 0.4595) - -모든 모델 저장 완료: ../save_model/ft_transformer_optima/ft_transformer_smotenc_ctgan20000_busan.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/ft_transformer_optima/scaler/ft_transformer_smotenc_ctgan20000_busan_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: ../save_model/ft_transformer_optima/ft_transformer_smotenc_ctgan20000_busan.pkl - -✓ 완료: ft_transformer_smotenc_ctgan20000/ft_transformer_smotenc_ctgan20000_busan.py (소요 시간: 11314초) - ----------------------------------------- -실행 중: ft_transformer_smotenc_ctgan20000/ft_transformer_smotenc_ctgan20000_daegu.py -시작 시간: 2025-12-25 13:46:50 ----------------------------------------- -[I 2025-12-25 13:46:51,481] A new study created in memory with name: no-name-ebfebfd3-460d-41c6-8fba-a613964ee40f - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 13:53:02,977] Trial 0 finished with value: 0.042102182465420246 and parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.22373849472659352, 'ffn_dropout': 0.32070096985053376, 'lr': 0.0019790253731626012, 'weight_decay': 0.0006384926201532275, 'batch_size': 32}. Best is trial 0 with value: 0.042102182465420246. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.042102 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.22373849472659352, 'ffn_dropout': 0.32070096985053376, 'lr': 0.0019790253731626012, 'weight_decay': 0.0006384926201532275, 'batch_size': 32} - Best Value (CSI): 0.042102 - Best Trial: 0 - Best Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.22373849472659352, 'ffn_dropout': 0.32070096985053376, 'lr': 0.0019790253731626012, 'weight_decay': 0.0006384926201532275, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 13:57:02,485] Trial 1 finished with value: 0.30470810284824434 and parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.39529505612299487, 'ffn_dropout': 0.22292791306323964, 'lr': 0.00012355914818925324, 'weight_decay': 0.001249888240644133, 'batch_size': 256}. Best is trial 1 with value: 0.30470810284824434. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.304708 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.39529505612299487, 'ffn_dropout': 0.22292791306323964, 'lr': 0.00012355914818925324, 'weight_decay': 0.001249888240644133, 'batch_size': 256} - Best Value (CSI): 0.304708 - Best Trial: 1 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.39529505612299487, 'ffn_dropout': 0.22292791306323964, 'lr': 0.00012355914818925324, 'weight_decay': 0.001249888240644133, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 14:00:02,249] Trial 2 finished with value: 0.23828369286120762 and parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.24585643478091307, 'ffn_dropout': 0.1464242213311127, 'lr': 2.4677199058197017e-05, 'weight_decay': 0.044445717056118515, 'batch_size': 256}. Best is trial 1 with value: 0.30470810284824434. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.238284 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.24585643478091307, 'ffn_dropout': 0.1464242213311127, 'lr': 2.4677199058197017e-05, 'weight_decay': 0.044445717056118515, 'batch_size': 256} - Best Value (CSI): 0.304708 - Best Trial: 1 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.39529505612299487, 'ffn_dropout': 0.22292791306323964, 'lr': 0.00012355914818925324, 'weight_decay': 0.001249888240644133, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 14:09:48,524] Trial 3 finished with value: 0.35272681852751653 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.38165461340293505, 'ffn_dropout': 0.32931183191765345, 'lr': 1.3552201555910686e-05, 'weight_decay': 0.00015233697308913776, 'batch_size': 32}. Best is trial 3 with value: 0.35272681852751653. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.352727 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.38165461340293505, 'ffn_dropout': 0.32931183191765345, 'lr': 1.3552201555910686e-05, 'weight_decay': 0.00015233697308913776, 'batch_size': 32} - Best Value (CSI): 0.352727 - Best Trial: 3 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.38165461340293505, 'ffn_dropout': 0.32931183191765345, 'lr': 1.3552201555910686e-05, 'weight_decay': 0.00015233697308913776, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 14:10:35,241] Trial 4 finished with value: 0.16609721777200534 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.37473877714284076, 'ffn_dropout': 0.23664665139877103, 'lr': 3.8767596427033246e-05, 'weight_decay': 0.040454646192775924, 'batch_size': 256}. Best is trial 3 with value: 0.35272681852751653. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.166097 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.37473877714284076, 'ffn_dropout': 0.23664665139877103, 'lr': 3.8767596427033246e-05, 'weight_decay': 0.040454646192775924, 'batch_size': 256} - Best Value (CSI): 0.352727 - Best Trial: 3 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.38165461340293505, 'ffn_dropout': 0.32931183191765345, 'lr': 1.3552201555910686e-05, 'weight_decay': 0.00015233697308913776, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 14:11:14,545] Trial 5 pruned. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.076829 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.24425686746220862, 'ffn_dropout': 0.36690109151448547, 'lr': 1.5972459152149538e-05, 'weight_decay': 0.00015147111838214575, 'batch_size': 128} - Best Value (CSI): 0.352727 - Best Trial: 3 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.38165461340293505, 'ffn_dropout': 0.32931183191765345, 'lr': 1.3552201555910686e-05, 'weight_decay': 0.00015233697308913776, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 14:11:33,093] Trial 6 pruned. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.065677 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.17771823539241854, 'ffn_dropout': 0.2531888453953537, 'lr': 1.3535553162706174e-05, 'weight_decay': 0.06928670732774551, 'batch_size': 256} - Best Value (CSI): 0.352727 - Best Trial: 3 - Best Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.38165461340293505, 'ffn_dropout': 0.32931183191765345, 'lr': 1.3552201555910686e-05, 'weight_decay': 0.00015233697308913776, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 14:14:38,848] Trial 7 finished with value: 0.4093411664728011 and parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2523799981722453, 'ffn_dropout': 0.15161999966061837, 'lr': 0.0011407391014086007, 'weight_decay': 0.00035291112597680513, 'batch_size': 256}. Best is trial 7 with value: 0.4093411664728011. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.409341 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2523799981722453, 'ffn_dropout': 0.15161999966061837, 'lr': 0.0011407391014086007, 'weight_decay': 0.00035291112597680513, 'batch_size': 256} - Best Value (CSI): 0.409341 - Best Trial: 7 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2523799981722453, 'ffn_dropout': 0.15161999966061837, 'lr': 0.0011407391014086007, 'weight_decay': 0.00035291112597680513, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 14:16:49,266] Trial 8 pruned. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 224, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3545171657919054, 'ffn_dropout': 0.3903844851320618, 'lr': 0.0015641178749648144, 'weight_decay': 0.0013110008141400387, 'batch_size': 32} - Best Value (CSI): 0.409341 - Best Trial: 7 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2523799981722453, 'ffn_dropout': 0.15161999966061837, 'lr': 0.0011407391014086007, 'weight_decay': 0.00035291112597680513, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 14:21:59,999] Trial 9 finished with value: 0.36157051017578823 and parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.3122266820776709, 'ffn_dropout': 0.3824676849458425, 'lr': 0.00010254786073634542, 'weight_decay': 0.0005539618575904669, 'batch_size': 64}. Best is trial 7 with value: 0.4093411664728011. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.361571 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.3122266820776709, 'ffn_dropout': 0.3824676849458425, 'lr': 0.00010254786073634542, 'weight_decay': 0.0005539618575904669, 'batch_size': 64} - Best Value (CSI): 0.409341 - Best Trial: 7 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2523799981722453, 'ffn_dropout': 0.15161999966061837, 'lr': 0.0011407391014086007, 'weight_decay': 0.00035291112597680513, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 14:23:01,476] Trial 10 pruned. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.14019245144217346, 'ffn_dropout': 0.10796135805276377, 'lr': 0.007348654367480772, 'weight_decay': 0.00663628377722228, 'batch_size': 64} - Best Value (CSI): 0.409341 - Best Trial: 7 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2523799981722453, 'ffn_dropout': 0.15161999966061837, 'lr': 0.0011407391014086007, 'weight_decay': 0.00035291112597680513, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 14:25:04,719] Trial 11 pruned. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.307829 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3061886209340515, 'ffn_dropout': 0.17733562339842202, 'lr': 0.00023565861711143294, 'weight_decay': 0.000385836651392465, 'batch_size': 64} - Best Value (CSI): 0.409341 - Best Trial: 7 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2523799981722453, 'ffn_dropout': 0.15161999966061837, 'lr': 0.0011407391014086007, 'weight_decay': 0.00035291112597680513, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 14:29:31,607] Trial 12 finished with value: 0.4228975503441254 and parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.29416852756200534, 'ffn_dropout': 0.28862547716930065, 'lr': 0.0005946469367891827, 'weight_decay': 0.00036944354461153047, 'batch_size': 64}. Best is trial 12 with value: 0.4228975503441254. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.422898 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.29416852756200534, 'ffn_dropout': 0.28862547716930065, 'lr': 0.0005946469367891827, 'weight_decay': 0.00036944354461153047, 'batch_size': 64} - Best Value (CSI): 0.422898 - Best Trial: 12 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.29416852756200534, 'ffn_dropout': 0.28862547716930065, 'lr': 0.0005946469367891827, 'weight_decay': 0.00036944354461153047, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 14:32:15,791] Trial 13 finished with value: 0.41905630342504024 and parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2780500559868799, 'ffn_dropout': 0.27179880540354745, 'lr': 0.0006738530408738695, 'weight_decay': 0.00011420302616417902, 'batch_size': 128}. Best is trial 12 with value: 0.4228975503441254. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.419056 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2780500559868799, 'ffn_dropout': 0.27179880540354745, 'lr': 0.0006738530408738695, 'weight_decay': 0.00011420302616417902, 'batch_size': 128} - Best Value (CSI): 0.422898 - Best Trial: 12 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.29416852756200534, 'ffn_dropout': 0.28862547716930065, 'lr': 0.0005946469367891827, 'weight_decay': 0.00036944354461153047, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 14:35:26,734] Trial 14 finished with value: 0.4290477893490603 and parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.29776300405630485, 'ffn_dropout': 0.2820077166293432, 'lr': 0.0005593670996639488, 'weight_decay': 0.00012351300973894946, 'batch_size': 128}. Best is trial 14 with value: 0.4290477893490603. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.429048 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.29776300405630485, 'ffn_dropout': 0.2820077166293432, 'lr': 0.0005593670996639488, 'weight_decay': 0.00012351300973894946, 'batch_size': 128} - Best Value (CSI): 0.429048 - Best Trial: 14 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.29776300405630485, 'ffn_dropout': 0.2820077166293432, 'lr': 0.0005593670996639488, 'weight_decay': 0.00012351300973894946, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 14:36:09,195] Trial 15 pruned. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.361174 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3332637087202417, 'ffn_dropout': 0.2725412778472139, 'lr': 0.0005431568256396566, 'weight_decay': 0.00012729920238795908, 'batch_size': 128} - Best Value (CSI): 0.429048 - Best Trial: 14 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.29776300405630485, 'ffn_dropout': 0.2820077166293432, 'lr': 0.0005593670996639488, 'weight_decay': 0.00012351300973894946, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 14:37:24,220] Trial 16 pruned. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.378261 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.293939381314013, 'ffn_dropout': 0.3092542221890613, 'lr': 0.00031661882472718613, 'weight_decay': 0.0036117610811707045, 'batch_size': 64} - Best Value (CSI): 0.429048 - Best Trial: 14 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.29776300405630485, 'ffn_dropout': 0.2820077166293432, 'lr': 0.0005593670996639488, 'weight_decay': 0.00012351300973894946, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 14:40:21,853] Trial 17 finished with value: 0.41984762751253807 and parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.33610438694248956, 'ffn_dropout': 0.29439546325411026, 'lr': 0.0031371389163204317, 'weight_decay': 0.00025932893409615906, 'batch_size': 128}. Best is trial 14 with value: 0.4290477893490603. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.419848 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.33610438694248956, 'ffn_dropout': 0.29439546325411026, 'lr': 0.0031371389163204317, 'weight_decay': 0.00025932893409615906, 'batch_size': 128} - Best Value (CSI): 0.429048 - Best Trial: 14 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.29776300405630485, 'ffn_dropout': 0.2820077166293432, 'lr': 0.0005593670996639488, 'weight_decay': 0.00012351300973894946, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 14:44:09,713] Trial 18 finished with value: 0.43513733419092054 and parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2811949376584915, 'ffn_dropout': 0.34863729190015724, 'lr': 0.0006083135438646137, 'weight_decay': 0.0002459627039934996, 'batch_size': 64}. Best is trial 18 with value: 0.43513733419092054. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.435137 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2811949376584915, 'ffn_dropout': 0.34863729190015724, 'lr': 0.0006083135438646137, 'weight_decay': 0.0002459627039934996, 'batch_size': 64} - Best Value (CSI): 0.435137 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2811949376584915, 'ffn_dropout': 0.34863729190015724, 'lr': 0.0006083135438646137, 'weight_decay': 0.0002459627039934996, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 14:44:29,723] Trial 19 pruned. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.151277 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.20179127715129233, 'ffn_dropout': 0.3512882496822588, 'lr': 0.003753285891808834, 'weight_decay': 0.00010129574843856416, 'batch_size': 128} - Best Value (CSI): 0.435137 - Best Trial: 18 - Best Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2811949376584915, 'ffn_dropout': 0.34863729190015724, 'lr': 0.0006083135438646137, 'weight_decay': 0.0002459627039934996, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 14:47:30,240] Trial 20 finished with value: 0.44565383604482484 and parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128}. Best is trial 20 with value: 0.44565383604482484. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.445654 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 14:50:25,010] Trial 21 finished with value: 0.4297531348768415 and parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.271018920333441, 'ffn_dropout': 0.34057342697939436, 'lr': 0.000856170632566966, 'weight_decay': 0.0002048186378826012, 'batch_size': 128}. Best is trial 20 with value: 0.44565383604482484. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.429753 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.271018920333441, 'ffn_dropout': 0.34057342697939436, 'lr': 0.000856170632566966, 'weight_decay': 0.0002048186378826012, 'batch_size': 128} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 14:52:59,479] Trial 22 finished with value: 0.42636388982710133 and parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2629814972306611, 'ffn_dropout': 0.34602367017859964, 'lr': 0.001017414141145606, 'weight_decay': 0.0002533310216156951, 'batch_size': 128}. Best is trial 20 with value: 0.44565383604482484. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.426364 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2629814972306611, 'ffn_dropout': 0.34602367017859964, 'lr': 0.001017414141145606, 'weight_decay': 0.0002533310216156951, 'batch_size': 128} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 14:56:16,619] Trial 23 finished with value: 0.4290113397528379 and parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2720293172342922, 'ffn_dropout': 0.399625521887604, 'lr': 0.002050039476654738, 'weight_decay': 0.0002242056171865219, 'batch_size': 128}. Best is trial 20 with value: 0.44565383604482484. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.429011 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2720293172342922, 'ffn_dropout': 0.399625521887604, 'lr': 0.002050039476654738, 'weight_decay': 0.0002242056171865219, 'batch_size': 128} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 15:01:55,985] Trial 24 finished with value: 0.42436133363982437 and parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.22291081952765757, 'ffn_dropout': 0.3456201229655809, 'lr': 0.00035496344866428766, 'weight_decay': 0.0007756417683272382, 'batch_size': 64}. Best is trial 20 with value: 0.44565383604482484. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.424361 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.22291081952765757, 'ffn_dropout': 0.3456201229655809, 'lr': 0.00035496344866428766, 'weight_decay': 0.0007756417683272382, 'batch_size': 64} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 15:04:58,068] Trial 25 finished with value: 0.4247568988471318 and parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2752634311408573, 'ffn_dropout': 0.36929288860529585, 'lr': 0.001018620011314536, 'weight_decay': 0.00021485792563220738, 'batch_size': 128}. Best is trial 20 with value: 0.44565383604482484. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.424757 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2752634311408573, 'ffn_dropout': 0.36929288860529585, 'lr': 0.001018620011314536, 'weight_decay': 0.00021485792563220738, 'batch_size': 128} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 15:05:22,234] Trial 26 pruned. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.260664 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3209760313229524, 'ffn_dropout': 0.32427999457650303, 'lr': 0.00021470668422626633, 'weight_decay': 0.0009434050516046175, 'batch_size': 128} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 15:06:29,757] Trial 27 pruned. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.28165251094110955, 'ffn_dropout': 0.3657200409257565, 'lr': 0.0009618726195452529, 'weight_decay': 0.0004109478485091645, 'batch_size': 64} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 15:15:29,573] Trial 28 finished with value: 0.4236354666658296 and parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.34543304665159347, 'ffn_dropout': 0.30626213688628234, 'lr': 0.00042021102226545346, 'weight_decay': 0.0002088975651864778, 'batch_size': 32}. Best is trial 20 with value: 0.44565383604482484. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.423635 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.34543304665159347, 'ffn_dropout': 0.30626213688628234, 'lr': 0.00042021102226545346, 'weight_decay': 0.0002088975651864778, 'batch_size': 32} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 15:16:54,722] Trial 29 pruned. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.022245 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.21271070465784858, 'ffn_dropout': 0.3290255350517873, 'lr': 0.001883835465826594, 'weight_decay': 0.0006311312460753538, 'batch_size': 32} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 15:22:54,770] Trial 30 finished with value: 0.4373590336267559 and parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2503963635114413, 'ffn_dropout': 0.31662647509610486, 'lr': 0.000704873743943796, 'weight_decay': 0.0005801482754732712, 'batch_size': 128}. Best is trial 20 with value: 0.44565383604482484. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.437359 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2503963635114413, 'ffn_dropout': 0.31662647509610486, 'lr': 0.000704873743943796, 'weight_decay': 0.0005801482754732712, 'batch_size': 128} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 15:26:36,700] Trial 31 finished with value: 0.44143495408618244 and parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2473644830390838, 'ffn_dropout': 0.3158923885947552, 'lr': 0.0007887530904126435, 'weight_decay': 0.00018443139594636734, 'batch_size': 128}. Best is trial 20 with value: 0.44565383604482484. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.441435 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2473644830390838, 'ffn_dropout': 0.3158923885947552, 'lr': 0.0007887530904126435, 'weight_decay': 0.00018443139594636734, 'batch_size': 128} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 15:27:13,397] Trial 32 pruned. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.414573 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24536614043395086, 'ffn_dropout': 0.309972107402917, 'lr': 0.0004697000357078151, 'weight_decay': 0.0004899676731914714, 'batch_size': 128} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 15:27:44,851] Trial 33 pruned. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.394813 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.23414273943288566, 'ffn_dropout': 0.318386729176253, 'lr': 0.0013779362690567714, 'weight_decay': 0.0003341444341670259, 'batch_size': 128} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 15:28:21,695] Trial 34 pruned. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.396694 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2516929749608977, 'ffn_dropout': 0.3347567304558864, 'lr': 0.0007314054244781615, 'weight_decay': 0.00017792934594624925, 'batch_size': 128} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 15:28:53,260] Trial 35 pruned. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.286190 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.22641001777175374, 'ffn_dropout': 0.29822291442738436, 'lr': 0.00022494210710078083, 'weight_decay': 0.0012244692130644569, 'batch_size': 128} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 15:29:29,483] Trial 36 pruned. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.399390 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.2526265159298003, 'ffn_dropout': 0.3551705653554011, 'lr': 0.0007436715584339134, 'weight_decay': 0.00015921832366397372, 'batch_size': 256} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 15:34:57,046] Trial 37 finished with value: 0.430135938514766 and parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.28520505133613716, 'ffn_dropout': 0.32539768635930943, 'lr': 0.000377446847870552, 'weight_decay': 0.00010015286056914519, 'batch_size': 64}. Best is trial 20 with value: 0.44565383604482484. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.430136 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.28520505133613716, 'ffn_dropout': 0.32539768635930943, 'lr': 0.000377446847870552, 'weight_decay': 0.00010015286056914519, 'batch_size': 64} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 15:36:39,201] Trial 38 pruned. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.019531 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2614549643915971, 'ffn_dropout': 0.3741910840162522, 'lr': 0.0013189051767496373, 'weight_decay': 0.0002728360940386126, 'batch_size': 32} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 15:37:18,079] Trial 39 pruned. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.122563 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.23603543270056088, 'ffn_dropout': 0.3599204518434015, 'lr': 0.00012590957725494025, 'weight_decay': 0.0005016621949092936, 'batch_size': 256} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 15:40:11,214] Trial 40 finished with value: 0.3972974610624272 and parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1992840527805449, 'ffn_dropout': 0.38551878631008984, 'lr': 0.0022532488015387137, 'weight_decay': 0.0001570398834024946, 'batch_size': 128}. Best is trial 20 with value: 0.44565383604482484. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.397297 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1992840527805449, 'ffn_dropout': 0.38551878631008984, 'lr': 0.0022532488015387137, 'weight_decay': 0.0001570398834024946, 'batch_size': 128} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 15:41:04,006] Trial 41 pruned. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.373802 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2860066669306585, 'ffn_dropout': 0.3186501592091506, 'lr': 0.0004791753600682789, 'weight_decay': 0.00010162762121725131, 'batch_size': 64} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 15:46:35,274] Trial 42 finished with value: 0.4369753438628481 and parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3063769734169772, 'ffn_dropout': 0.3332729253111573, 'lr': 0.0003650414778648299, 'weight_decay': 0.00014489452057993453, 'batch_size': 64}. Best is trial 20 with value: 0.44565383604482484. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.436975 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3063769734169772, 'ffn_dropout': 0.3332729253111573, 'lr': 0.0003650414778648299, 'weight_decay': 0.00014489452057993453, 'batch_size': 64} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 15:52:41,306] Trial 43 finished with value: 0.4152604224129819 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3173565039266777, 'ffn_dropout': 0.3387627300063364, 'lr': 0.000769913867814789, 'weight_decay': 0.0003060696134870798, 'batch_size': 64}. Best is trial 20 with value: 0.44565383604482484. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.415260 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3173565039266777, 'ffn_dropout': 0.3387627300063364, 'lr': 0.000769913867814789, 'weight_decay': 0.0003060696134870798, 'batch_size': 64} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 15:53:35,158] Trial 44 pruned. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.406250 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3052812025682606, 'ffn_dropout': 0.36023996111785533, 'lr': 0.000292679397509848, 'weight_decay': 0.00016994190306074508, 'batch_size': 64} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 15:54:37,985] Trial 45 pruned. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.180233 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.26440266626365233, 'ffn_dropout': 0.33471368051070705, 'lr': 0.001103047889117419, 'weight_decay': 0.00031686606909199163, 'batch_size': 64} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 15:55:38,565] Trial 46 pruned. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.412256 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2937791671269213, 'ffn_dropout': 0.37586800738479276, 'lr': 0.0006288120570718583, 'weight_decay': 0.00014563129342049392, 'batch_size': 64} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 15:55:56,869] Trial 47 pruned. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.226415 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2568620213143568, 'ffn_dropout': 0.3002702560518785, 'lr': 0.00046374955030586187, 'weight_decay': 0.0004600093185821793, 'batch_size': 256} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 15:56:35,468] Trial 48 pruned. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.018300 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2393575897281876, 'ffn_dropout': 0.2830572426908611, 'lr': 0.0014803410334349573, 'weight_decay': 0.0006633062829247622, 'batch_size': 128} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 15:58:15,528] Trial 49 pruned. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.336484 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3052586300665928, 'ffn_dropout': 0.26041807957991087, 'lr': 0.0001708568225803354, 'weight_decay': 0.0002759977572403951, 'batch_size': 32} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 15:58:57,786] Trial 50 pruned. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.136531 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2687389109962908, 'ffn_dropout': 0.3153002165800571, 'lr': 0.0002791833490887351, 'weight_decay': 0.0003930429918475948, 'batch_size': 64} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 15:59:50,545] Trial 51 pruned. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.397333 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2832449566506923, 'ffn_dropout': 0.3270723781753643, 'lr': 0.00038462261608652825, 'weight_decay': 0.0001323640837247549, 'batch_size': 64} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 16:00:44,023] Trial 52 pruned. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.390501 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.28763737210835755, 'ffn_dropout': 0.3508889248314076, 'lr': 0.0005861413277040807, 'weight_decay': 0.00012012125415079218, 'batch_size': 64} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 16:06:10,120] Trial 53 finished with value: 0.4297641812074244 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.32137450837987064, 'ffn_dropout': 0.32962833650837536, 'lr': 0.0003672621016063087, 'weight_decay': 0.00018244274511385844, 'batch_size': 64}. Best is trial 20 with value: 0.44565383604482484. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.429764 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.32137450837987064, 'ffn_dropout': 0.32962833650837536, 'lr': 0.0003672621016063087, 'weight_decay': 0.00018244274511385844, 'batch_size': 64} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 16:07:01,582] Trial 54 pruned. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.334917 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.295997981511976, 'ffn_dropout': 0.29467516045228304, 'lr': 0.0008092230858342665, 'weight_decay': 0.00010399714671474918, 'batch_size': 64} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 16:10:26,560] Trial 55 finished with value: 0.4277875352976745 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2476956859259068, 'ffn_dropout': 0.34604557428964133, 'lr': 0.0005833141163033772, 'weight_decay': 0.00022684955374918414, 'batch_size': 128}. Best is trial 20 with value: 0.44565383604482484. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.427788 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2476956859259068, 'ffn_dropout': 0.34604557428964133, 'lr': 0.0005833141163033772, 'weight_decay': 0.00022684955374918414, 'batch_size': 128} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 16:16:50,907] Trial 56 finished with value: 0.4428356928356001 and parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2765009292878459, 'ffn_dropout': 0.3087708940644889, 'lr': 0.00034606923586879835, 'weight_decay': 0.00013213913959388208, 'batch_size': 64}. Best is trial 20 with value: 0.44565383604482484. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.442836 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2765009292878459, 'ffn_dropout': 0.3087708940644889, 'lr': 0.00034606923586879835, 'weight_decay': 0.00013213913959388208, 'batch_size': 64} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 16:20:52,420] Trial 57 finished with value: 0.41699711883732854 and parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2713997327355868, 'ffn_dropout': 0.3071282152355634, 'lr': 0.0008711671069827462, 'weight_decay': 0.000146925016570197, 'batch_size': 128}. Best is trial 20 with value: 0.44565383604482484. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.416997 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2713997327355868, 'ffn_dropout': 0.3071282152355634, 'lr': 0.0008711671069827462, 'weight_decay': 0.000146925016570197, 'batch_size': 128} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 16:21:51,892] Trial 58 pruned. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.404255 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2567238633996431, 'ffn_dropout': 0.2862008309943923, 'lr': 0.00027862226778022434, 'weight_decay': 0.00019773582687683503, 'batch_size': 64} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 16:25:35,708] Trial 59 finished with value: 0.4249903880857026 and parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.276102075308705, 'ffn_dropout': 0.3412273134531852, 'lr': 0.0011115008996664618, 'weight_decay': 0.00033721948899681915, 'batch_size': 128}. Best is trial 20 with value: 0.44565383604482484. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.424990 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.276102075308705, 'ffn_dropout': 0.3412273134531852, 'lr': 0.0011115008996664618, 'weight_decay': 0.00033721948899681915, 'batch_size': 128} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 16:26:07,960] Trial 60 pruned. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.417790 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.31097099437162795, 'ffn_dropout': 0.24301331954442668, 'lr': 0.0005010640026722295, 'weight_decay': 0.0002481093067681523, 'batch_size': 256} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 16:27:00,178] Trial 61 pruned. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.417344 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2838265592962881, 'ffn_dropout': 0.3226536185722171, 'lr': 0.0003627618714482206, 'weight_decay': 0.00012819115860098282, 'batch_size': 64} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 16:32:51,761] Trial 62 finished with value: 0.4280044296923005 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.29489505370257785, 'ffn_dropout': 0.3118359317030168, 'lr': 0.0006255241461543979, 'weight_decay': 0.0001824321621601028, 'batch_size': 64}. Best is trial 20 with value: 0.44565383604482484. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.428004 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.29489505370257785, 'ffn_dropout': 0.3118359317030168, 'lr': 0.0006255241461543979, 'weight_decay': 0.0001824321621601028, 'batch_size': 64} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 16:38:33,066] Trial 63 finished with value: 0.4224328068132311 and parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2634136763614034, 'ffn_dropout': 0.3567055225918818, 'lr': 0.0004135976927174367, 'weight_decay': 0.00010138058843339546, 'batch_size': 64}. Best is trial 20 with value: 0.44565383604482484. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.422433 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2634136763614034, 'ffn_dropout': 0.3567055225918818, 'lr': 0.0004135976927174367, 'weight_decay': 0.00010138058843339546, 'batch_size': 64} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 16:39:44,867] Trial 64 pruned. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.286424 - Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.2764292326139092, 'ffn_dropout': 0.32376631697240765, 'lr': 0.00018643911647629163, 'weight_decay': 0.0001328401503689507, 'batch_size': 64} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 16:45:20,072] Trial 65 finished with value: 0.42733745375354876 and parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24682165138114437, 'ffn_dropout': 0.3027044437787846, 'lr': 0.00030482141919957754, 'weight_decay': 0.0002428599611914463, 'batch_size': 64}. Best is trial 20 with value: 0.44565383604482484. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.427337 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24682165138114437, 'ffn_dropout': 0.3027044437787846, 'lr': 0.00030482141919957754, 'weight_decay': 0.0002428599611914463, 'batch_size': 64} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 16:45:50,332] Trial 66 pruned. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.404494 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3002048012557123, 'ffn_dropout': 0.3350056632921656, 'lr': 0.0008784447200063704, 'weight_decay': 0.00019051124320190762, 'batch_size': 128} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 16:50:07,814] Trial 67 finished with value: 0.4411378781919329 and parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.26605342111546326, 'ffn_dropout': 0.31698039374513054, 'lr': 0.0006602100935109063, 'weight_decay': 0.00038344881204052314, 'batch_size': 128}. Best is trial 20 with value: 0.44565383604482484. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.441138 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.26605342111546326, 'ffn_dropout': 0.31698039374513054, 'lr': 0.0006602100935109063, 'weight_decay': 0.00038344881204052314, 'batch_size': 128} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 16:50:47,437] Trial 68 pruned. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.420765 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2665570166186157, 'ffn_dropout': 0.29150413329383884, 'lr': 0.000638198025266631, 'weight_decay': 0.0005489155486710685, 'batch_size': 128} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 16:55:02,964] Trial 69 finished with value: 0.4193408397477951 and parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.254046115681946, 'ffn_dropout': 0.314859409581231, 'lr': 0.0005008329439402987, 'weight_decay': 0.00030770181496716375, 'batch_size': 128}. Best is trial 20 with value: 0.44565383604482484. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.419341 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.254046115681946, 'ffn_dropout': 0.314859409581231, 'lr': 0.0005008329439402987, 'weight_decay': 0.00030770181496716375, 'batch_size': 128} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 16:59:37,695] Trial 70 finished with value: 0.4359370574487215 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.24059297017891687, 'ffn_dropout': 0.3486161632446498, 'lr': 0.00122816427576568, 'weight_decay': 0.00035872165978396634, 'batch_size': 128}. Best is trial 20 with value: 0.44565383604482484. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.435937 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.24059297017891687, 'ffn_dropout': 0.3486161632446498, 'lr': 0.00122816427576568, 'weight_decay': 0.00035872165978396634, 'batch_size': 128} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 17:00:17,035] Trial 71 pruned. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.408805 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.2411151533247906, 'ffn_dropout': 0.34697590812645107, 'lr': 0.0012984402083438854, 'weight_decay': 0.00042891649449793294, 'batch_size': 128} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 17:00:53,068] Trial 72 pruned. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.417219 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2301370511206682, 'ffn_dropout': 0.33662415615222135, 'lr': 0.00074460903633313, 'weight_decay': 0.0002283668044353261, 'batch_size': 128} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 17:01:30,895] Trial 73 pruned. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.402597 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.2234088387888748, 'ffn_dropout': 0.3660858638920145, 'lr': 0.0010541548706066387, 'weight_decay': 0.0003919538311744339, 'batch_size': 128} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 17:06:38,793] Trial 74 finished with value: 0.43980936061056664 and parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2579485184322372, 'ffn_dropout': 0.35124433876186906, 'lr': 0.000704999901365369, 'weight_decay': 0.000278878242479798, 'batch_size': 128}. Best is trial 20 with value: 0.44565383604482484. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.439809 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2579485184322372, 'ffn_dropout': 0.35124433876186906, 'lr': 0.000704999901365369, 'weight_decay': 0.000278878242479798, 'batch_size': 128} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 17:07:14,094] Trial 75 pruned. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2439635517395078, 'ffn_dropout': 0.3048137183467508, 'lr': 0.001727329188671797, 'weight_decay': 0.0002931598674597234, 'batch_size': 128} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 17:11:44,052] Trial 76 finished with value: 0.4263765338008092 and parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.23359875313745668, 'ffn_dropout': 0.31724029395326814, 'lr': 0.0009192318120950146, 'weight_decay': 0.0003639158968788778, 'batch_size': 128}. Best is trial 20 with value: 0.44565383604482484. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.426377 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.23359875313745668, 'ffn_dropout': 0.31724029395326814, 'lr': 0.0009192318120950146, 'weight_decay': 0.0003639158968788778, 'batch_size': 128} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 17:12:32,893] Trial 77 pruned. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.25859503520428556, 'ffn_dropout': 0.35582349552859777, 'lr': 0.001164719992234743, 'weight_decay': 0.00015895987995834514, 'batch_size': 128} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 17:13:14,559] Trial 78 pruned. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.372611 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2711362483152081, 'ffn_dropout': 0.3414071145739233, 'lr': 0.0007132312500061725, 'weight_decay': 0.0005835311905576641, 'batch_size': 128} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 17:16:27,299] Trial 79 finished with value: 0.4442374908164279 and parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2532584882883464, 'ffn_dropout': 0.32898091417617686, 'lr': 0.0016250382920016395, 'weight_decay': 0.00046445576310957766, 'batch_size': 128}. Best is trial 20 with value: 0.44565383604482484. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.444237 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2532584882883464, 'ffn_dropout': 0.32898091417617686, 'lr': 0.0016250382920016395, 'weight_decay': 0.00046445576310957766, 'batch_size': 128} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 17:17:05,569] Trial 80 pruned. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.188494 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.25048116795186987, 'ffn_dropout': 0.33057635073689456, 'lr': 0.0015872160892602947, 'weight_decay': 0.0008128244947153063, 'batch_size': 128} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 17:17:38,091] Trial 81 pruned. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.405759 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2642523383089439, 'ffn_dropout': 0.3233129718922543, 'lr': 0.0012865220820286322, 'weight_decay': 0.0002770344227596575, 'batch_size': 128} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 17:18:09,924] Trial 82 pruned. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.412399 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2375511814781494, 'ffn_dropout': 0.3121622703466007, 'lr': 0.0009261388463196586, 'weight_decay': 0.00047590779535238147, 'batch_size': 128} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 17:18:46,785] Trial 83 pruned. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.305026 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.2546823654135693, 'ffn_dropout': 0.3492092852506024, 'lr': 0.0005323325079629694, 'weight_decay': 0.00021607492884982354, 'batch_size': 128} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 17:20:46,231] Trial 84 pruned. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.000000 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.27823914882413997, 'ffn_dropout': 0.33268007829673685, 'lr': 0.0023383393327619, 'weight_decay': 0.0003663117258039221, 'batch_size': 32} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 17:21:14,095] Trial 85 pruned. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.300181 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2435980137364067, 'ffn_dropout': 0.34187525925837076, 'lr': 0.00044655402479278864, 'weight_decay': 0.00017418810289728963, 'batch_size': 128} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 17:26:03,331] Trial 86 finished with value: 0.4285227922448283 and parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2598860629783809, 'ffn_dropout': 0.29915755356571166, 'lr': 0.0006711225142468216, 'weight_decay': 0.00045389887313516215, 'batch_size': 128}. Best is trial 20 with value: 0.44565383604482484. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.428523 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2598860629783809, 'ffn_dropout': 0.29915755356571166, 'lr': 0.0006711225142468216, 'weight_decay': 0.00045389887313516215, 'batch_size': 128} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 17:30:23,260] Trial 87 finished with value: 0.43315656520201856 and parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.21779844557374647, 'ffn_dropout': 0.36214619523421837, 'lr': 0.0008072043862456097, 'weight_decay': 0.0003238031034467025, 'batch_size': 128}. Best is trial 20 with value: 0.44565383604482484. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.433157 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.21779844557374647, 'ffn_dropout': 0.36214619523421837, 'lr': 0.0008072043862456097, 'weight_decay': 0.0003238031034467025, 'batch_size': 128} - Best Value (CSI): 0.445654 - Best Trial: 20 - Best Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.27385238400721007, 'ffn_dropout': 0.33877847565621105, 'lr': 0.0008249754545236409, 'weight_decay': 0.00020807971621931862, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 17:33:02,605] Trial 88 finished with value: 0.4488825045464337 and parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.270864990314075, 'ffn_dropout': 0.3735925199999471, 'lr': 0.0016588396308948813, 'weight_decay': 0.00014669112268617685, 'batch_size': 128}. Best is trial 88 with value: 0.4488825045464337. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.448883 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.270864990314075, 'ffn_dropout': 0.3735925199999471, 'lr': 0.0016588396308948813, 'weight_decay': 0.00014669112268617685, 'batch_size': 128} - Best Value (CSI): 0.448883 - Best Trial: 88 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.270864990314075, 'ffn_dropout': 0.3735925199999471, 'lr': 0.0016588396308948813, 'weight_decay': 0.00014669112268617685, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 17:33:18,505] Trial 89 pruned. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.292929 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.287807503865382, 'ffn_dropout': 0.37314081551900496, 'lr': 0.0014852481635785053, 'weight_decay': 0.00011967032969329024, 'batch_size': 256} - Best Value (CSI): 0.448883 - Best Trial: 88 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.270864990314075, 'ffn_dropout': 0.3735925199999471, 'lr': 0.0016588396308948813, 'weight_decay': 0.00014669112268617685, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 17:33:47,113] Trial 90 pruned. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.396907 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.26695974298966485, 'ffn_dropout': 0.37974041467952135, 'lr': 0.001007717133726572, 'weight_decay': 0.00014527009694552672, 'batch_size': 128} - Best Value (CSI): 0.448883 - Best Trial: 88 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.270864990314075, 'ffn_dropout': 0.3735925199999471, 'lr': 0.0016588396308948813, 'weight_decay': 0.00014669112268617685, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 17:34:15,607] Trial 91 pruned. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.388489 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.25168467165596403, 'ffn_dropout': 0.3692794439689718, 'lr': 0.0019435077204741735, 'weight_decay': 0.00020325101429873797, 'batch_size': 128} - Best Value (CSI): 0.448883 - Best Trial: 88 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.270864990314075, 'ffn_dropout': 0.3735925199999471, 'lr': 0.0016588396308948813, 'weight_decay': 0.00014669112268617685, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) - Fold 2 - 클래스별 가중치: {0: 0.9447642276422764, 1: 0.9311378205128205, 2: 1.1526314745382769} (클래스별 샘플 수: {0: 20500, 1: 20800, 2: 16803}) - Fold 3 - 클래스별 가중치: {0: 0.9433008130081301, 1: 0.9387216828478965, 2: 1.143361122607856} (클래스별 샘플 수: {0: 20500, 1: 20600, 2: 16913}) -[I 2025-12-25 17:37:36,554] Trial 92 finished with value: 0.4352788144325841 and parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.26003652652278686, 'ffn_dropout': 0.35427207373151814, 'lr': 0.0012003286503815822, 'weight_decay': 0.00026479843326258326, 'batch_size': 128}. Best is trial 88 with value: 0.4488825045464337. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.435279 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.26003652652278686, 'ffn_dropout': 0.35427207373151814, 'lr': 0.0012003286503815822, 'weight_decay': 0.00026479843326258326, 'batch_size': 128} - Best Value (CSI): 0.448883 - Best Trial: 88 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.270864990314075, 'ffn_dropout': 0.3735925199999471, 'lr': 0.0016588396308948813, 'weight_decay': 0.00014669112268617685, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 17:38:09,741] Trial 93 pruned. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.026301 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.27031634673735644, 'ffn_dropout': 0.3204649306649655, 'lr': 0.0016618505984493056, 'weight_decay': 0.00016059919608208962, 'batch_size': 128} - Best Value (CSI): 0.448883 - Best Trial: 88 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.270864990314075, 'ffn_dropout': 0.3735925199999471, 'lr': 0.0016588396308948813, 'weight_decay': 0.00014669112268617685, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 17:38:43,131] Trial 94 pruned. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.338318 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2311716955172398, 'ffn_dropout': 0.3305375214650534, 'lr': 0.0005715905893603646, 'weight_decay': 0.00023590969561102713, 'batch_size': 128} - Best Value (CSI): 0.448883 - Best Trial: 88 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.270864990314075, 'ffn_dropout': 0.3735925199999471, 'lr': 0.0016588396308948813, 'weight_decay': 0.00014669112268617685, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 17:39:15,749] Trial 95 pruned. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.431250 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2775991121572725, 'ffn_dropout': 0.363609920716802, 'lr': 0.0007214826481700036, 'weight_decay': 0.00013497219951856564, 'batch_size': 128} - Best Value (CSI): 0.448883 - Best Trial: 88 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.270864990314075, 'ffn_dropout': 0.3735925199999471, 'lr': 0.0016588396308948813, 'weight_decay': 0.00014669112268617685, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 17:41:04,175] Trial 96 pruned. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.364322 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2494223529450214, 'ffn_dropout': 0.3389806213065006, 'lr': 0.0013763857095719582, 'weight_decay': 0.0001960642114127266, 'batch_size': 32} - Best Value (CSI): 0.448883 - Best Trial: 88 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.270864990314075, 'ffn_dropout': 0.3735925199999471, 'lr': 0.0016588396308948813, 'weight_decay': 0.00014669112268617685, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 17:41:47,136] Trial 97 pruned. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.413889 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.24304923066931705, 'ffn_dropout': 0.34695489252702016, 'lr': 0.0009668084444298899, 'weight_decay': 0.00011915297867117992, 'batch_size': 128} - Best Value (CSI): 0.448883 - Best Trial: 88 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.270864990314075, 'ffn_dropout': 0.3735925199999471, 'lr': 0.0016588396308948813, 'weight_decay': 0.00014669112268617685, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 17:42:09,972] Trial 98 pruned. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.147604 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2909166353820615, 'ffn_dropout': 0.3092605775801698, 'lr': 0.000444323116299147, 'weight_decay': 0.0004129425167692841, 'batch_size': 128} - Best Value (CSI): 0.448883 - Best Trial: 88 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.270864990314075, 'ffn_dropout': 0.3735925199999471, 'lr': 0.0016588396308948813, 'weight_decay': 0.00014669112268617685, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9444227642276423, 1: 0.9219365079365079, 2: 1.167571262011016} (클래스별 샘플 수: {0: 20500, 1: 21000, 2: 16582}) -[I 2025-12-25 17:42:48,076] Trial 99 pruned. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.120859 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.28090400843827085, 'ffn_dropout': 0.32705154264897696, 'lr': 0.0011679069021254063, 'weight_decay': 0.00027939919309894525, 'batch_size': 128} - Best Value (CSI): 0.448883 - Best Trial: 88 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.270864990314075, 'ffn_dropout': 0.3735925199999471, 'lr': 0.0016588396308948813, 'weight_decay': 0.00014669112268617685, 'batch_size': 128} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.4489 -Best Hyperparameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.270864990314075, 'ffn_dropout': 0.3735925199999471, 'lr': 0.0016588396308948813, 'weight_decay': 0.00014669112268617685, 'batch_size': 128} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.0421 - - 최종 CSI: 0.1209 - - 최고 CSI: 0.4489 - - 최저 CSI: 0.0000 - - 평균 CSI: 0.3269 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/ft_transformer_smotenc_ctgan20000_daegu_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 26, Best CSI: 0.4518 - Fold 1 학습 완료 (검증 CSI: 0.4518) -Fold 2 학습 중... - Early stopping at epoch 27, Best CSI: 0.4355 - Fold 2 학습 완료 (검증 CSI: 0.4355) -Fold 3 학습 중... - Early stopping at epoch 38, Best CSI: 0.3924 - Fold 3 학습 완료 (검증 CSI: 0.3924) - -모든 모델 저장 완료: ../save_model/ft_transformer_optima/ft_transformer_smotenc_ctgan20000_daegu.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/ft_transformer_optima/scaler/ft_transformer_smotenc_ctgan20000_daegu_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: ../save_model/ft_transformer_optima/ft_transformer_smotenc_ctgan20000_daegu.pkl - -✓ 완료: ft_transformer_smotenc_ctgan20000/ft_transformer_smotenc_ctgan20000_daegu.py (소요 시간: 14385초) - ----------------------------------------- -실행 중: ft_transformer_smotenc_ctgan20000/ft_transformer_smotenc_ctgan20000_daejeon.py -시작 시간: 2025-12-25 17:46:35 ----------------------------------------- -[I 2025-12-25 17:46:36,437] A new study created in memory with name: no-name-f760f634-d259-461a-b45c-6aa451ac1793 - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 0.9433658536585365, 1: 0.8871100917431193, 2: 1.2304511039002355} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 0.9428292682926829, 1: 0.8906912442396313, 2: 1.2245311708058795} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15784}) -[I 2025-12-25 17:53:10,752] Trial 0 finished with value: 0.10114217631060095 and parameters: {'d_token': 256, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.2831606899487012, 'ffn_dropout': 0.24865706134225704, 'lr': 0.0037188515388611276, 'weight_decay': 0.0002672168816784975, 'batch_size': 64}. Best is trial 0 with value: 0.10114217631060095. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.101142 - Parameters: {'d_token': 256, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.2831606899487012, 'ffn_dropout': 0.24865706134225704, 'lr': 0.0037188515388611276, 'weight_decay': 0.0002672168816784975, 'batch_size': 64} - Best Value (CSI): 0.101142 - Best Trial: 0 - Best Parameters: {'d_token': 256, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.2831606899487012, 'ffn_dropout': 0.24865706134225704, 'lr': 0.0037188515388611276, 'weight_decay': 0.0002672168816784975, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 0.9433658536585365, 1: 0.8871100917431193, 2: 1.2304511039002355} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 0.9428292682926829, 1: 0.8906912442396313, 2: 1.2245311708058795} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15784}) -[I 2025-12-25 18:00:24,681] Trial 1 finished with value: 0.10114217631060095 and parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3089381546308435, 'ffn_dropout': 0.14980007078493468, 'lr': 0.0037053730305581577, 'weight_decay': 0.001682732357942515, 'batch_size': 32}. Best is trial 0 with value: 0.10114217631060095. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.101142 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.3089381546308435, 'ffn_dropout': 0.14980007078493468, 'lr': 0.0037053730305581577, 'weight_decay': 0.001682732357942515, 'batch_size': 32} - Best Value (CSI): 0.101142 - Best Trial: 0 - Best Parameters: {'d_token': 256, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.2831606899487012, 'ffn_dropout': 0.24865706134225704, 'lr': 0.0037188515388611276, 'weight_decay': 0.0002672168816784975, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 0.9433658536585365, 1: 0.8871100917431193, 2: 1.2304511039002355} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 0.9428292682926829, 1: 0.8906912442396313, 2: 1.2245311708058795} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15784}) -[I 2025-12-25 18:06:34,660] Trial 2 finished with value: 0.47203183874296967 and parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2896406488248088, 'ffn_dropout': 0.18477055022949218, 'lr': 0.0003707417380713788, 'weight_decay': 0.004126913652613803, 'batch_size': 64}. Best is trial 2 with value: 0.47203183874296967. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.472032 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2896406488248088, 'ffn_dropout': 0.18477055022949218, 'lr': 0.0003707417380713788, 'weight_decay': 0.004126913652613803, 'batch_size': 64} - Best Value (CSI): 0.472032 - Best Trial: 2 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2896406488248088, 'ffn_dropout': 0.18477055022949218, 'lr': 0.0003707417380713788, 'weight_decay': 0.004126913652613803, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 0.9433658536585365, 1: 0.8871100917431193, 2: 1.2304511039002355} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 0.9428292682926829, 1: 0.8906912442396313, 2: 1.2245311708058795} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15784}) -[I 2025-12-25 18:13:41,848] Trial 3 finished with value: 0.45890343496941116 and parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.32543210817110235, 'ffn_dropout': 0.1848348738583612, 'lr': 0.0009013655283200891, 'weight_decay': 0.07820717354315297, 'batch_size': 64}. Best is trial 2 with value: 0.47203183874296967. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.458903 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.32543210817110235, 'ffn_dropout': 0.1848348738583612, 'lr': 0.0009013655283200891, 'weight_decay': 0.07820717354315297, 'batch_size': 64} - Best Value (CSI): 0.472032 - Best Trial: 2 - Best Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2896406488248088, 'ffn_dropout': 0.18477055022949218, 'lr': 0.0003707417380713788, 'weight_decay': 0.004126913652613803, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 0.9433658536585365, 1: 0.8871100917431193, 2: 1.2304511039002355} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 0.9428292682926829, 1: 0.8906912442396313, 2: 1.2245311708058795} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15784}) -[I 2025-12-25 18:23:53,938] Trial 4 finished with value: 0.4794390839030278 and parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32}. Best is trial 4 with value: 0.4794390839030278. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.479439 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 18:24:56,307] Trial 5 pruned. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.246758 - Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1653151790239713, 'ffn_dropout': 0.1665962154626497, 'lr': 3.062385100457289e-05, 'weight_decay': 0.00012134567069726468, 'batch_size': 256} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 0.9433658536585365, 1: 0.8871100917431193, 2: 1.2304511039002355} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 0.9428292682926829, 1: 0.8906912442396313, 2: 1.2245311708058795} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15784}) -[I 2025-12-25 18:28:05,132] Trial 6 finished with value: 0.4756308234375424 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.11627819455002496, 'ffn_dropout': 0.36123197269066665, 'lr': 0.0006178552667773511, 'weight_decay': 0.04320635278916393, 'batch_size': 64}. Best is trial 4 with value: 0.4794390839030278. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.475631 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.11627819455002496, 'ffn_dropout': 0.36123197269066665, 'lr': 0.0006178552667773511, 'weight_decay': 0.04320635278916393, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 18:30:04,504] Trial 7 pruned. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.404642 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.1745596229714939, 'ffn_dropout': 0.33919471385910616, 'lr': 0.00024774475543946206, 'weight_decay': 0.0042919879350441685, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 18:31:55,311] Trial 8 pruned. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.389121 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.22074840807641544, 'ffn_dropout': 0.12837975154990003, 'lr': 0.00010095750891989077, 'weight_decay': 0.0035331011895194703, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 18:32:50,608] Trial 9 pruned. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.258306 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3123260979035447, 'ffn_dropout': 0.20622984347989892, 'lr': 1.0294198202353091e-05, 'weight_decay': 0.004187917980314604, 'batch_size': 256} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 18:33:53,241] Trial 10 pruned. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.061059 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.37706189293207976, 'ffn_dropout': 0.10645776655943859, 'lr': 0.009105845738232036, 'weight_decay': 0.0005535862355039157, 'batch_size': 32} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 18:34:26,402] Trial 11 pruned. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.389302 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.1073531277781145, 'ffn_dropout': 0.37761622896988717, 'lr': 0.0009131767066424821, 'weight_decay': 0.07147770763740706, 'batch_size': 128} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 18:36:56,898] Trial 12 pruned. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.423117 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.10166373554107444, 'ffn_dropout': 0.30681506472886777, 'lr': 0.0008859270832480185, 'weight_decay': 0.021805314234993285, 'batch_size': 32} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 18:37:29,267] Trial 13 pruned. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.284981 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.13931220309807268, 'ffn_dropout': 0.27919494326809063, 'lr': 0.00019428694512364493, 'weight_decay': 0.015664044000754614, 'batch_size': 128} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 18:40:30,497] Trial 14 pruned. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.412008 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.19401266018089117, 'ffn_dropout': 0.39390438465530014, 'lr': 0.0005025656825689997, 'weight_decay': 0.000492079911359133, 'batch_size': 32} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 18:42:42,876] Trial 15 pruned. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.393416 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.1389064501384776, 'ffn_dropout': 0.10619944901071887, 'lr': 9.546364128811673e-05, 'weight_decay': 0.0012449962569268554, 'batch_size': 32} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 18:43:19,473] Trial 16 pruned. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.392379 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2226214097093998, 'ffn_dropout': 0.23434476653157024, 'lr': 0.001699248303276072, 'weight_decay': 0.012521468719373421, 'batch_size': 128} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 18:43:59,026] Trial 17 pruned. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.054401 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13794992294854577, 'ffn_dropout': 0.29071346385367247, 'lr': 0.001959642994819157, 'weight_decay': 0.03128963010573255, 'batch_size': 256} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 18:45:20,316] Trial 18 pruned. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.405242 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.20629649427096433, 'ffn_dropout': 0.23097383987731035, 'lr': 0.0004925861540373041, 'weight_decay': 0.009297892584514023, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 18:47:05,805] Trial 19 pruned. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.356349 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2476364237496872, 'ffn_dropout': 0.34944546508001484, 'lr': 0.00018136227405473536, 'weight_decay': 0.04160864730792858, 'batch_size': 32} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 18:48:43,274] Trial 20 pruned. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.413823 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.16936384287934592, 'ffn_dropout': 0.26865541062398524, 'lr': 0.0005776795732574341, 'weight_decay': 0.0073564225063171935, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 18:50:03,339] Trial 21 pruned. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.402462 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.25325318573029115, 'ffn_dropout': 0.20794175728955364, 'lr': 0.0003401966799381887, 'weight_decay': 0.0019387629287274028, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 18:52:11,663] Trial 22 pruned. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.427046 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.11521018712447549, 'ffn_dropout': 0.14942265348307068, 'lr': 0.00033418021746793646, 'weight_decay': 0.09983442308921685, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 18:53:15,795] Trial 23 pruned. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.400810 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.1258699970708025, 'ffn_dropout': 0.18210640875400272, 'lr': 0.001135196552593845, 'weight_decay': 0.0064765679299096275, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 0.9433658536585365, 1: 0.8871100917431193, 2: 1.2304511039002355} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 0.9428292682926829, 1: 0.8906912442396313, 2: 1.2245311708058795} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15784}) -[I 2025-12-25 18:57:00,865] Trial 24 finished with value: 0.4677657623496904 and parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.1584452402432232, 'ffn_dropout': 0.1292130079096412, 'lr': 0.000516193359242554, 'weight_decay': 0.023680904366061867, 'batch_size': 64}. Best is trial 4 with value: 0.4794390839030278. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.467766 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.1584452402432232, 'ffn_dropout': 0.1292130079096412, 'lr': 0.000516193359242554, 'weight_decay': 0.023680904366061867, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 19:00:57,445] Trial 25 pruned. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.433699 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.10288384573925327, 'ffn_dropout': 0.2040925817344531, 'lr': 0.00012359477864719908, 'weight_decay': 0.0025848651206527304, 'batch_size': 32} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 19:01:23,328] Trial 26 pruned. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.272674 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1374488612610574, 'ffn_dropout': 0.30864906939774184, 'lr': 0.0003005750477526622, 'weight_decay': 0.0009779403918960246, 'batch_size': 128} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 19:01:54,985] Trial 27 pruned. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.376180 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.18920369637341222, 'ffn_dropout': 0.25953876791943514, 'lr': 0.001338173629224841, 'weight_decay': 0.050694037281934966, 'batch_size': 256} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 19:03:17,769] Trial 28 pruned. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.400822 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.15817475626527164, 'ffn_dropout': 0.10155769587048034, 'lr': 0.0020451271552376325, 'weight_decay': 0.014471872941430068, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 19:04:06,405] Trial 29 pruned. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.082650 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.27290433537992126, 'ffn_dropout': 0.24758403876072382, 'lr': 0.0028432268893370536, 'weight_decay': 0.005446082742481839, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 19:06:19,674] Trial 30 pruned. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.409465 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.10060880282629787, 'ffn_dropout': 0.225589635561244, 'lr': 0.0007539056605546439, 'weight_decay': 0.009369354194789096, 'batch_size': 32} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 19:08:10,120] Trial 31 pruned. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.405248 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.14921461850365655, 'ffn_dropout': 0.13514691252719796, 'lr': 0.0005662527815879305, 'weight_decay': 0.03295886913021135, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 19:09:17,568] Trial 32 pruned. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.301535 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13007051544416964, 'ffn_dropout': 0.12617017680792592, 'lr': 0.0013762058715205867, 'weight_decay': 0.026050961633456503, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 19:11:27,790] Trial 33 pruned. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.412138 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12546465984997884, 'ffn_dropout': 0.16308183815788133, 'lr': 0.0004197171631293649, 'weight_decay': 0.01936302063023497, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 19:13:45,450] Trial 34 pruned. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.409135 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.16282088985500462, 'ffn_dropout': 0.15313936109300752, 'lr': 0.0007714598715442097, 'weight_decay': 0.04521226855018762, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 19:15:14,611] Trial 35 pruned. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.398014 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.14747465289345918, 'ffn_dropout': 0.13772034165602898, 'lr': 0.0006285713070553023, 'weight_decay': 0.002953862859363485, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 19:17:03,640] Trial 36 pruned. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.420849 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.17846884806635216, 'ffn_dropout': 0.17705562376457767, 'lr': 0.00041148374666929457, 'weight_decay': 0.00017617977610049414, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 19:17:23,451] Trial 37 pruned. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.275663 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.15543373306910985, 'ffn_dropout': 0.16731376811386386, 'lr': 0.000237876987870936, 'weight_decay': 0.059860490810864836, 'batch_size': 256} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 19:19:19,984] Trial 38 pruned. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.355509 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.12358355965225964, 'ffn_dropout': 0.1295793088814544, 'lr': 0.0009554123880235912, 'weight_decay': 0.02370552192220478, 'batch_size': 32} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 19:20:20,200] Trial 39 pruned. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.082650 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.11694997112012975, 'ffn_dropout': 0.11960793764174257, 'lr': 0.0035095500195400876, 'weight_decay': 0.004544944261338899, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 19:21:40,228] Trial 40 pruned. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.426148 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.292961776544581, 'ffn_dropout': 0.147980816724813, 'lr': 0.0007109321843460932, 'weight_decay': 0.07045732762669117, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 19:24:10,584] Trial 41 pruned. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.363248 - Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.3292501944580009, 'ffn_dropout': 0.18843079365418286, 'lr': 0.0008522031751486062, 'weight_decay': 0.041684913486344705, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 19:25:57,419] Trial 42 pruned. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.395349 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.34466674646638334, 'ffn_dropout': 0.11902370832870246, 'lr': 0.001048005681887154, 'weight_decay': 0.08381392619114733, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 19:27:20,975] Trial 43 pruned. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.407244 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.30188602265450204, 'ffn_dropout': 0.11406282219488198, 'lr': 0.0004960511995101767, 'weight_decay': 0.06553174307739905, 'batch_size': 128} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 19:29:14,950] Trial 44 pruned. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.202658 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2865504361525316, 'ffn_dropout': 0.14003699720467983, 'lr': 0.001355617156989053, 'weight_decay': 0.09071203719000302, 'batch_size': 32} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 19:30:57,205] Trial 45 pruned. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.397045 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.31480448481654544, 'ffn_dropout': 0.1658969307013161, 'lr': 0.0002742831439835242, 'weight_decay': 0.01864650115014211, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 19:32:15,061] Trial 46 pruned. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.373989 - Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.1141601379785131, 'ffn_dropout': 0.10062672818502483, 'lr': 0.0004061678313692881, 'weight_decay': 0.03036175602510023, 'batch_size': 256} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 19:36:51,788] Trial 47 pruned. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.415254 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.14548045921647523, 'ffn_dropout': 0.15554616074537697, 'lr': 0.0006621093694505821, 'weight_decay': 0.012333887153231204, 'batch_size': 32} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 19:38:28,966] Trial 48 pruned. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.407470 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.17545953091534366, 'ffn_dropout': 0.19484751242465392, 'lr': 0.001778759658774027, 'weight_decay': 0.055505023751457556, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 19:38:57,753] Trial 49 pruned. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.032212 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.27370134697034115, 'ffn_dropout': 0.11617320669249372, 'lr': 0.007229461392893837, 'weight_decay': 0.0004235117381729491, 'batch_size': 128} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 19:40:09,315] Trial 50 pruned. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.003188 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1612280144770974, 'ffn_dropout': 0.17290455146496678, 'lr': 0.0010280872436310574, 'weight_decay': 0.0009357016846392856, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 19:41:33,937] Trial 51 pruned. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.082650 - Parameters: {'d_token': 256, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.23518690871609854, 'ffn_dropout': 0.2222788375296622, 'lr': 0.004722472801902956, 'weight_decay': 0.003573172692283876, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 19:42:52,245] Trial 52 pruned. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.082650 - Parameters: {'d_token': 224, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.32339680871922655, 'ffn_dropout': 0.24676223595818417, 'lr': 0.002522087020224437, 'weight_decay': 0.03711396732470164, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 19:45:00,152] Trial 53 pruned. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.423391 - Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.21135007142431328, 'ffn_dropout': 0.2086257012595508, 'lr': 0.00020468701078824812, 'weight_decay': 0.0022724437645208857, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 19:47:17,060] Trial 54 pruned. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.082650 - Parameters: {'d_token': 224, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.2657835395508201, 'ffn_dropout': 0.19312542201783683, 'lr': 0.0014874934903712975, 'weight_decay': 0.0016796977183618632, 'batch_size': 32} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 19:49:36,696] Trial 55 pruned. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.423110 - Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.11170933092699961, 'ffn_dropout': 0.274396481837994, 'lr': 0.0005139578822059886, 'weight_decay': 0.02640626923356078, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 19:49:55,763] Trial 56 pruned. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.280748 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.13532033468671903, 'ffn_dropout': 0.17997657323154861, 'lr': 0.00032768529749598686, 'weight_decay': 0.04668784700965264, 'batch_size': 256} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 19:51:42,952] Trial 57 pruned. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.396504 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2886045714592196, 'ffn_dropout': 0.3630055912369151, 'lr': 0.0011518289090853555, 'weight_decay': 0.09962982372399778, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 19:53:07,292] Trial 58 pruned. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.311475 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.24858273118604002, 'ffn_dropout': 0.322842570854772, 'lr': 0.002132507790924421, 'weight_decay': 0.03579267899422179, 'batch_size': 32} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 19:54:28,146] Trial 59 pruned. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.424755 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.19215905543399633, 'ffn_dropout': 0.2846413100096474, 'lr': 0.0008065144690646186, 'weight_decay': 0.0710565194893732, 'batch_size': 128} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 0.9433658536585365, 1: 0.8871100917431193, 2: 1.2304511039002355} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 0.9428292682926829, 1: 0.8906912442396313, 2: 1.2245311708058795} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15784}) -[I 2025-12-25 20:00:20,038] Trial 60 pruned. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.449287 - Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.12264865753939296, 'ffn_dropout': 0.24079961316377688, 'lr': 0.0006024962282526384, 'weight_decay': 0.017169356369336183, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 20:01:39,909] Trial 61 pruned. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.197459 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2992065689410639, 'ffn_dropout': 0.39995176286322554, 'lr': 0.004134011707966688, 'weight_decay': 0.0014969343967866642, 'batch_size': 32} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 20:02:58,129] Trial 62 pruned. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.003188 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.33841761320614483, 'ffn_dropout': 0.14522852259834734, 'lr': 0.006127787841994441, 'weight_decay': 0.003254926791999708, 'batch_size': 32} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 20:04:17,698] Trial 63 pruned. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.104179 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.30933347359625135, 'ffn_dropout': 0.25907247236742115, 'lr': 0.0016515004066333357, 'weight_decay': 0.002395468478823066, 'batch_size': 32} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 20:05:26,698] Trial 64 pruned. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.036662 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.13315599600645578, 'ffn_dropout': 0.12972339544693665, 'lr': 0.0028329453685656558, 'weight_decay': 0.0010431889757109675, 'batch_size': 32} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 20:06:57,928] Trial 65 pruned. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.405431 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.10719642701745037, 'ffn_dropout': 0.16049610165175582, 'lr': 0.0003852295794037518, 'weight_decay': 0.0005554246893080671, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 20:07:39,723] Trial 66 pruned. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.352941 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.10059901900531157, 'ffn_dropout': 0.2998273280116266, 'lr': 0.002305614903516311, 'weight_decay': 0.053855444737070046, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 20:08:42,298] Trial 67 pruned. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.012556 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.14595860207567957, 'ffn_dropout': 0.14420879496953956, 'lr': 0.0034280375656768358, 'weight_decay': 0.006944972110591257, 'batch_size': 32} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 20:09:23,333] Trial 68 pruned. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.082650 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.27899825992146077, 'ffn_dropout': 0.21813400245749803, 'lr': 0.00966755020662718, 'weight_decay': 0.004544103971695636, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 20:10:13,472] Trial 69 pruned. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.399592 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2570911299643366, 'ffn_dropout': 0.15570247721535913, 'lr': 0.0012002406363328035, 'weight_decay': 0.020939722992630912, 'batch_size': 256} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 20:11:58,780] Trial 70 pruned. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.386214 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.28216790995107677, 'ffn_dropout': 0.2363839130722406, 'lr': 0.0004704997818598726, 'weight_decay': 0.030931665299920617, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 20:13:10,163] Trial 71 pruned. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.418944 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.11371479101016399, 'ffn_dropout': 0.1376807971117434, 'lr': 0.0003105693077327873, 'weight_decay': 0.08291829224335837, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 20:14:48,857] Trial 72 pruned. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.405767 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.12051503578072004, 'ffn_dropout': 0.10968455758342585, 'lr': 0.0006730880969401189, 'weight_decay': 0.06473198955673239, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 20:16:05,095] Trial 73 pruned. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.406635 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13483113013071477, 'ffn_dropout': 0.1278215893123774, 'lr': 0.0008956325649525063, 'weight_decay': 0.05014545227134472, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 20:17:05,813] Trial 74 pruned. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.380591 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.12837974942219846, 'ffn_dropout': 0.1521228143947659, 'lr': 0.00024522257199356397, 'weight_decay': 0.08106946489169191, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 0.9433658536585365, 1: 0.8871100917431193, 2: 1.2304511039002355} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 0.9428292682926829, 1: 0.8906912442396313, 2: 1.2245311708058795} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15784}) -[I 2025-12-25 20:22:03,037] Trial 75 finished with value: 0.4773165864934213 and parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.29563392885065054, 'ffn_dropout': 0.17095574759777818, 'lr': 0.00034033123094662194, 'weight_decay': 0.04015055968468594, 'batch_size': 64}. Best is trial 4 with value: 0.4794390839030278. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.477317 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.29563392885065054, 'ffn_dropout': 0.17095574759777818, 'lr': 0.00034033123094662194, 'weight_decay': 0.04015055968468594, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 20:24:22,081] Trial 76 pruned. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.395325 - Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.2960171562771131, 'ffn_dropout': 0.18591150151111346, 'lr': 0.0005476244398874502, 'weight_decay': 0.0437533436074344, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 20:25:00,157] Trial 77 pruned. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.348929 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.29432980925398594, 'ffn_dropout': 0.17426045851921362, 'lr': 0.00034540181468466425, 'weight_decay': 0.022267182456778684, 'batch_size': 128} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 0.9433658536585365, 1: 0.8871100917431193, 2: 1.2304511039002355} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 0.9428292682926829, 1: 0.8906912442396313, 2: 1.2245311708058795} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15784}) -[I 2025-12-25 20:33:02,154] Trial 78 finished with value: 0.4478985477356674 and parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3025037976818863, 'ffn_dropout': 0.164336674096795, 'lr': 0.00015785653431335504, 'weight_decay': 0.027369715520844218, 'batch_size': 32}. Best is trial 4 with value: 0.4794390839030278. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.447899 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3025037976818863, 'ffn_dropout': 0.164336674096795, 'lr': 0.00015785653431335504, 'weight_decay': 0.027369715520844218, 'batch_size': 32} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 20:34:40,102] Trial 79 pruned. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.376268 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.30928922647348045, 'ffn_dropout': 0.1684020371909276, 'lr': 0.00013394683004977983, 'weight_decay': 0.0287445276166224, 'batch_size': 32} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) - Fold 2 - 클래스별 가중치: {0: 0.9433658536585365, 1: 0.8871100917431193, 2: 1.2304511039002355} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15717}) - Fold 3 - 클래스별 가중치: {0: 0.9428292682926829, 1: 0.8906912442396313, 2: 1.2245311708058795} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15784}) -[I 2025-12-25 20:39:00,125] Trial 80 finished with value: 0.4742279530628539 and parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.31881358314770847, 'ffn_dropout': 0.18114516366382494, 'lr': 0.0001596395229069402, 'weight_decay': 0.0382848539558849, 'batch_size': 64}. Best is trial 4 with value: 0.4794390839030278. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.474228 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.31881358314770847, 'ffn_dropout': 0.18114516366382494, 'lr': 0.0001596395229069402, 'weight_decay': 0.0382848539558849, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 20:40:33,979] Trial 81 pruned. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.397273 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.31969652633807716, 'ffn_dropout': 0.2004922949872361, 'lr': 0.0001658870789949671, 'weight_decay': 0.024961224212949204, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 20:42:06,129] Trial 82 pruned. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.413333 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.30566118516918206, 'ffn_dropout': 0.18045230170051724, 'lr': 0.00027281813846264416, 'weight_decay': 0.038799985361987276, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 20:43:30,036] Trial 83 pruned. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.423903 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.30333087492976024, 'ffn_dropout': 0.1916818169812485, 'lr': 0.00038890730221628983, 'weight_decay': 0.03461308318929088, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 20:44:47,702] Trial 84 pruned. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.397345 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.31653642765808443, 'ffn_dropout': 0.1601265001101481, 'lr': 9.490417572145297e-05, 'weight_decay': 0.059518118095511836, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 20:46:34,925] Trial 85 pruned. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.414070 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.2899714211697524, 'ffn_dropout': 0.21487409503851498, 'lr': 0.0004430036484603725, 'weight_decay': 0.014041664050612496, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 20:48:01,907] Trial 86 pruned. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.392644 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3280103497270644, 'ffn_dropout': 0.19834812408967606, 'lr': 0.0007843068835696079, 'weight_decay': 0.041618608986185746, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 20:49:19,766] Trial 87 pruned. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.390198 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.27895794420115694, 'ffn_dropout': 0.18487559651889107, 'lr': 0.0006274832859211233, 'weight_decay': 0.029987020112709966, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 20:52:43,014] Trial 88 pruned. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.412910 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.2692521022237785, 'ffn_dropout': 0.17086749713092725, 'lr': 0.00021391070211560395, 'weight_decay': 0.05189751607881994, 'batch_size': 32} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 20:53:43,308] Trial 89 pruned. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.393548 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.31028806393352665, 'ffn_dropout': 0.2099972860252744, 'lr': 0.0009073257738796153, 'weight_decay': 0.019200806302852667, 'batch_size': 256} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 20:55:16,484] Trial 90 pruned. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.416298 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.29731367912144385, 'ffn_dropout': 0.202084809410184, 'lr': 0.0004962018152795354, 'weight_decay': 0.02477358178714799, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 20:57:31,680] Trial 91 pruned. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.400822 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2861227426532186, 'ffn_dropout': 0.17701686236937117, 'lr': 0.00028591162940486733, 'weight_decay': 0.035369503117015984, 'batch_size': 32} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 20:59:06,944] Trial 92 pruned. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.082650 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.30288823609327237, 'ffn_dropout': 0.164262795369077, 'lr': 0.0017279496869866112, 'weight_decay': 0.011902433111238696, 'batch_size': 32} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:01:17,513] Trial 93 pruned. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.339683 - Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.3144773612555949, 'ffn_dropout': 0.22800817381972965, 'lr': 0.00036372302064352805, 'weight_decay': 0.005761892405685662, 'batch_size': 32} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:03:30,052] Trial 94 pruned. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.386680 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3249967477542412, 'ffn_dropout': 0.12223068443015965, 'lr': 0.000571239963582788, 'weight_decay': 0.016487883676002034, 'batch_size': 32} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:04:16,116] Trial 95 pruned. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.243590 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.335356679112468, 'ffn_dropout': 0.1468402412289941, 'lr': 0.0011158648895417571, 'weight_decay': 0.008354986946457607, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:05:16,155] Trial 96 pruned. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.434365 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.353710192212825, 'ffn_dropout': 0.18443457693172816, 'lr': 0.0013940875661769393, 'weight_decay': 0.06472545372275262, 'batch_size': 128} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:07:26,217] Trial 97 pruned. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.003188 - Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.29126991275036723, 'ffn_dropout': 0.15679500623530732, 'lr': 0.0007257018965523121, 'weight_decay': 0.0026881448423374038, 'batch_size': 32} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:08:56,807] Trial 98 pruned. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.428713 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.3197359148582833, 'ffn_dropout': 0.1322304232782615, 'lr': 0.00042528323713952713, 'weight_decay': 0.04859494333518805, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.942130081300813, 1: 0.8778939393939394, 2: 1.2508041361742548} (클래스별 샘플 수: {0: 20500, 1: 22000, 2: 15441}) -[I 2025-12-25 21:10:08,489] Trial 99 pruned. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.082650 - Parameters: {'d_token': 224, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.15265276804699845, 'ffn_dropout': 0.10810151959425085, 'lr': 0.0009859949042432773, 'weight_decay': 0.0019720817063937405, 'batch_size': 64} - Best Value (CSI): 0.479439 - Best Trial: 4 - Best Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.4794 -Best Hyperparameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13096961306141697, 'ffn_dropout': 0.10368225384926379, 'lr': 0.0008212785631177437, 'weight_decay': 0.0007599672775598784, 'batch_size': 32} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.1011 - - 최종 CSI: 0.0827 - - 최고 CSI: 0.4794 - - 최저 CSI: 0.0032 - - 평균 CSI: 0.3266 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/ft_transformer_smotenc_ctgan20000_daejeon_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 37, Best CSI: 0.4054 - Fold 1 학습 완료 (검증 CSI: 0.4054) -Fold 2 학습 중... - Early stopping at epoch 21, Best CSI: 0.4771 - Fold 2 학습 완료 (검증 CSI: 0.4771) -Fold 3 학습 중... - Early stopping at epoch 25, Best CSI: 0.4971 - Fold 3 학습 완료 (검증 CSI: 0.4971) - -모든 모델 저장 완료: ../save_model/ft_transformer_optima/ft_transformer_smotenc_ctgan20000_daejeon.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/ft_transformer_optima/scaler/ft_transformer_smotenc_ctgan20000_daejeon_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: ../save_model/ft_transformer_optima/ft_transformer_smotenc_ctgan20000_daejeon.pkl - -✓ 완료: ft_transformer_smotenc_ctgan20000/ft_transformer_smotenc_ctgan20000_daejeon.py (소요 시간: 12810초) - ----------------------------------------- -실행 중: ft_transformer_smotenc_ctgan20000/ft_transformer_smotenc_ctgan20000_gwangju.py -시작 시간: 2025-12-25 21:20:05 ----------------------------------------- -[I 2025-12-25 21:20:06,390] A new study created in memory with name: no-name-2ee8af21-624d-478a-bc09-265641d0fda7 - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-25 21:25:23,147] Trial 0 finished with value: 0.48372288996217055 and parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.21346320964398893, 'ffn_dropout': 0.3725640866886927, 'lr': 0.0001820770604878082, 'weight_decay': 0.00118470509914376, 'batch_size': 128}. Best is trial 0 with value: 0.48372288996217055. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.483723 - Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.21346320964398893, 'ffn_dropout': 0.3725640866886927, 'lr': 0.0001820770604878082, 'weight_decay': 0.00118470509914376, 'batch_size': 128} - Best Value (CSI): 0.483723 - Best Trial: 0 - Best Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.21346320964398893, 'ffn_dropout': 0.3725640866886927, 'lr': 0.0001820770604878082, 'weight_decay': 0.00118470509914376, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-25 21:32:41,980] Trial 1 finished with value: 0.4647832727791206 and parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.2668608884600342, 'ffn_dropout': 0.3217467248145599, 'lr': 0.00024876380934079186, 'weight_decay': 0.0008122595007764616, 'batch_size': 64}. Best is trial 0 with value: 0.48372288996217055. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.464783 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.2668608884600342, 'ffn_dropout': 0.3217467248145599, 'lr': 0.00024876380934079186, 'weight_decay': 0.0008122595007764616, 'batch_size': 64} - Best Value (CSI): 0.483723 - Best Trial: 0 - Best Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.21346320964398893, 'ffn_dropout': 0.3725640866886927, 'lr': 0.0001820770604878082, 'weight_decay': 0.00118470509914376, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-25 21:39:00,243] Trial 2 finished with value: 0.4848504186984368 and parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2084981846598, 'ffn_dropout': 0.11820171074339306, 'lr': 0.0001859499149751709, 'weight_decay': 0.02231654929905672, 'batch_size': 32}. Best is trial 2 with value: 0.4848504186984368. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.484850 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2084981846598, 'ffn_dropout': 0.11820171074339306, 'lr': 0.0001859499149751709, 'weight_decay': 0.02231654929905672, 'batch_size': 32} - Best Value (CSI): 0.484850 - Best Trial: 2 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2084981846598, 'ffn_dropout': 0.11820171074339306, 'lr': 0.0001859499149751709, 'weight_decay': 0.02231654929905672, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-25 21:53:14,742] Trial 3 finished with value: 0.4861335251119714 and parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1158420998787305, 'ffn_dropout': 0.2569632294108326, 'lr': 0.00012778869825819076, 'weight_decay': 0.0002891406493568458, 'batch_size': 32}. Best is trial 3 with value: 0.4861335251119714. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.486134 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1158420998787305, 'ffn_dropout': 0.2569632294108326, 'lr': 0.00012778869825819076, 'weight_decay': 0.0002891406493568458, 'batch_size': 32} - Best Value (CSI): 0.486134 - Best Trial: 3 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1158420998787305, 'ffn_dropout': 0.2569632294108326, 'lr': 0.00012778869825819076, 'weight_decay': 0.0002891406493568458, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-25 22:01:49,008] Trial 4 finished with value: 0.4737587078036308 and parameters: {'d_token': 256, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.2910083355043665, 'ffn_dropout': 0.3142987264987416, 'lr': 0.0003037958177521694, 'weight_decay': 0.019150555613368023, 'batch_size': 64}. Best is trial 3 with value: 0.4861335251119714. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.473759 - Parameters: {'d_token': 256, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.2910083355043665, 'ffn_dropout': 0.3142987264987416, 'lr': 0.0003037958177521694, 'weight_decay': 0.019150555613368023, 'batch_size': 64} - Best Value (CSI): 0.486134 - Best Trial: 3 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1158420998787305, 'ffn_dropout': 0.2569632294108326, 'lr': 0.00012778869825819076, 'weight_decay': 0.0002891406493568458, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:02:04,561] Trial 5 pruned. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.349873 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.36928433154536466, 'ffn_dropout': 0.28726241199716074, 'lr': 0.005183204060432148, 'weight_decay': 0.0001835316742210229, 'batch_size': 256} - Best Value (CSI): 0.486134 - Best Trial: 3 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1158420998787305, 'ffn_dropout': 0.2569632294108326, 'lr': 0.00012778869825819076, 'weight_decay': 0.0002891406493568458, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:03:22,223] Trial 6 pruned. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.414433 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3989143284975655, 'ffn_dropout': 0.3374225566938547, 'lr': 0.0013105743424169658, 'weight_decay': 0.005332348842462533, 'batch_size': 256} - Best Value (CSI): 0.486134 - Best Trial: 3 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1158420998787305, 'ffn_dropout': 0.2569632294108326, 'lr': 0.00012778869825819076, 'weight_decay': 0.0002891406493568458, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:04:03,069] Trial 7 pruned. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.357095 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.10036107003792832, 'ffn_dropout': 0.18536539823371878, 'lr': 0.00011631102748288045, 'weight_decay': 0.0001691767062242687, 'batch_size': 64} - Best Value (CSI): 0.486134 - Best Trial: 3 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1158420998787305, 'ffn_dropout': 0.2569632294108326, 'lr': 0.00012778869825819076, 'weight_decay': 0.0002891406493568458, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:05:18,154] Trial 8 pruned. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.003985 - Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.22910923445557219, 'ffn_dropout': 0.367468113285742, 'lr': 0.0014420011531592653, 'weight_decay': 0.00041874464555023564, 'batch_size': 64} - Best Value (CSI): 0.486134 - Best Trial: 3 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1158420998787305, 'ffn_dropout': 0.2569632294108326, 'lr': 0.00012778869825819076, 'weight_decay': 0.0002891406493568458, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:07:39,461] Trial 9 pruned. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.003985 - Parameters: {'d_token': 224, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.2534596619484337, 'ffn_dropout': 0.30891008169786094, 'lr': 0.0013534476758457214, 'weight_decay': 0.000277652105103073, 'batch_size': 32} - Best Value (CSI): 0.486134 - Best Trial: 3 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1158420998787305, 'ffn_dropout': 0.2569632294108326, 'lr': 0.00012778869825819076, 'weight_decay': 0.0002891406493568458, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:08:57,771] Trial 10 pruned. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.303637 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.10561022099260317, 'ffn_dropout': 0.2415968754556495, 'lr': 2.0576233693315415e-05, 'weight_decay': 0.00010591559131705319, 'batch_size': 32} - Best Value (CSI): 0.486134 - Best Trial: 3 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1158420998787305, 'ffn_dropout': 0.2569632294108326, 'lr': 0.00012778869825819076, 'weight_decay': 0.0002891406493568458, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:10:58,486] Trial 11 pruned. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.372064 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.16491776483594744, 'ffn_dropout': 0.11156706892985568, 'lr': 5.320417136828853e-05, 'weight_decay': 0.034185522828103075, 'batch_size': 32} - Best Value (CSI): 0.486134 - Best Trial: 3 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1158420998787305, 'ffn_dropout': 0.2569632294108326, 'lr': 0.00012778869825819076, 'weight_decay': 0.0002891406493568458, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:12:19,424] Trial 12 pruned. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.337257 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1638700319307705, 'ffn_dropout': 0.2116835405822817, 'lr': 4.172195885248482e-05, 'weight_decay': 0.00598491877836218, 'batch_size': 32} - Best Value (CSI): 0.486134 - Best Trial: 3 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1158420998787305, 'ffn_dropout': 0.2569632294108326, 'lr': 0.00012778869825819076, 'weight_decay': 0.0002891406493568458, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:13:24,383] Trial 13 pruned. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.349175 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.16268262741554726, 'ffn_dropout': 0.10207407217855827, 'lr': 1.10970849901695e-05, 'weight_decay': 0.0958546095301826, 'batch_size': 32} - Best Value (CSI): 0.486134 - Best Trial: 3 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1158420998787305, 'ffn_dropout': 0.2569632294108326, 'lr': 0.00012778869825819076, 'weight_decay': 0.0002891406493568458, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:14:24,868] Trial 14 pruned. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.438557 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2001412865708697, 'ffn_dropout': 0.15646809855569482, 'lr': 8.389734663664799e-05, 'weight_decay': 0.0020424981324430264, 'batch_size': 128} - Best Value (CSI): 0.486134 - Best Trial: 3 - Best Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1158420998787305, 'ffn_dropout': 0.2569632294108326, 'lr': 0.00012778869825819076, 'weight_decay': 0.0002891406493568458, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-25 22:23:04,220] Trial 15 finished with value: 0.49840606228991896 and parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32}. Best is trial 15 with value: 0.49840606228991896. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.498406 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:24:43,460] Trial 16 pruned. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.388514 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1345538345329726, 'ffn_dropout': 0.27139784167526165, 'lr': 0.0005088221407454512, 'weight_decay': 0.0005163965817761533, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:27:21,176] Trial 17 pruned. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.367718 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.12374580584307766, 'ffn_dropout': 0.24495773412177177, 'lr': 0.0004003683799215408, 'weight_decay': 0.0008330297840615228, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:27:59,229] Trial 18 pruned. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.345178 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.1253283154703022, 'ffn_dropout': 0.21995748770090606, 'lr': 0.0005959844151283836, 'weight_decay': 0.0003693720940468745, 'batch_size': 256} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:28:32,619] Trial 19 pruned. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.374412 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.15013928857235548, 'ffn_dropout': 0.27512249744191375, 'lr': 9.893426694289239e-05, 'weight_decay': 0.0017356165834729361, 'batch_size': 128} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:29:58,702] Trial 20 pruned. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.399332 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1846727807103707, 'ffn_dropout': 0.2630914045820804, 'lr': 3.692796855756947e-05, 'weight_decay': 0.0006692920901051421, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:32:05,822] Trial 21 pruned. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.397180 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.18662242308563035, 'ffn_dropout': 0.17226796755895085, 'lr': 0.00011614853214262054, 'weight_decay': 0.003566901011920947, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:33:47,825] Trial 22 pruned. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.390300 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.13113935977572894, 'ffn_dropout': 0.22170190360714037, 'lr': 0.00017863103271983206, 'weight_decay': 0.00024806460126083354, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:36:42,644] Trial 23 pruned. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.312977 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1471682791665036, 'ffn_dropout': 0.13782715469011264, 'lr': 0.000181884372640476, 'weight_decay': 0.00010529123424150662, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-25 22:43:26,586] Trial 24 finished with value: 0.4764436806404675 and parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.10525906977006419, 'ffn_dropout': 0.20255555931103614, 'lr': 0.0005360630268797583, 'weight_decay': 0.0013394903534300244, 'batch_size': 32}. Best is trial 15 with value: 0.49840606228991896. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.476444 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.10525906977006419, 'ffn_dropout': 0.20255555931103614, 'lr': 0.0005360630268797583, 'weight_decay': 0.0013394903534300244, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:45:47,702] Trial 25 pruned. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.364583 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.17932355887090837, 'ffn_dropout': 0.25083694085087843, 'lr': 5.759886786602365e-05, 'weight_decay': 0.00040627701515435854, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:46:50,778] Trial 26 pruned. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.370930 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.21742816645076501, 'ffn_dropout': 0.19250484949230043, 'lr': 0.0002776139063729696, 'weight_decay': 0.0025460699063219387, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:47:17,857] Trial 27 pruned. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.358189 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.14601369050456345, 'ffn_dropout': 0.2251443650150529, 'lr': 7.226301910039722e-05, 'weight_decay': 0.0009680928395234776, 'batch_size': 128} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:48:01,703] Trial 28 pruned. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.364596 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.12215940993954488, 'ffn_dropout': 0.28797316769320874, 'lr': 0.0008845190239282522, 'weight_decay': 0.00964270351675896, 'batch_size': 256} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:48:53,102] Trial 29 pruned. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.412924 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.20775014114500034, 'ffn_dropout': 0.17009076042431676, 'lr': 0.00014732278211788751, 'weight_decay': 0.0012656990317928849, 'batch_size': 128} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-25 22:55:18,851] Trial 30 finished with value: 0.4794767051181757 and parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.22765300895402485, 'ffn_dropout': 0.23533338983618107, 'lr': 0.00023698867844648312, 'weight_decay': 0.0031319339049720334, 'batch_size': 32}. Best is trial 15 with value: 0.49840606228991896. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.479477 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.22765300895402485, 'ffn_dropout': 0.23533338983618107, 'lr': 0.00023698867844648312, 'weight_decay': 0.0031319339049720334, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:56:30,559] Trial 31 pruned. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.371084 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.19743742679889356, 'ffn_dropout': 0.39344071648568013, 'lr': 0.00018779852688157267, 'weight_decay': 0.0007569336738398527, 'batch_size': 128} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 22:57:26,059] Trial 32 pruned. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.388209 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.27502270201561896, 'ffn_dropout': 0.3485991752416561, 'lr': 0.00022373961088201802, 'weight_decay': 0.0005989696291618829, 'batch_size': 128} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-25 23:03:51,938] Trial 33 finished with value: 0.4793027385233059 and parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.2292849883394241, 'ffn_dropout': 0.3019156760644556, 'lr': 0.00038461768440998026, 'weight_decay': 0.0012044984960641071, 'batch_size': 64}. Best is trial 15 with value: 0.49840606228991896. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.479303 - Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.2292849883394241, 'ffn_dropout': 0.3019156760644556, 'lr': 0.00038461768440998026, 'weight_decay': 0.0012044984960641071, 'batch_size': 64} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-25 23:07:17,742] Trial 34 finished with value: 0.4733494127719579 and parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.24963627845141828, 'ffn_dropout': 0.3244614374723655, 'lr': 0.00031911080108400853, 'weight_decay': 0.001710596215202563, 'batch_size': 128}. Best is trial 15 with value: 0.49840606228991896. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.473349 - Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.24963627845141828, 'ffn_dropout': 0.3244614374723655, 'lr': 0.00031911080108400853, 'weight_decay': 0.001710596215202563, 'batch_size': 128} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:08:43,018] Trial 35 pruned. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.397129 - Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.1703643058212566, 'ffn_dropout': 0.29405151691864834, 'lr': 0.00012937867056012845, 'weight_decay': 0.0009236400754227986, 'batch_size': 256} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:09:28,821] Trial 36 pruned. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.394253 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.30620669243371457, 'ffn_dropout': 0.3208939682041325, 'lr': 0.00027121555858332385, 'weight_decay': 0.0005366237368653677, 'batch_size': 64} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:09:56,854] Trial 37 pruned. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.388935 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.1891470886541938, 'ffn_dropout': 0.25472778042717115, 'lr': 9.179925425745212e-05, 'weight_decay': 0.0002918659038130922, 'batch_size': 128} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:10:58,147] Trial 38 pruned. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.385965 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.11233985153813573, 'ffn_dropout': 0.2869525863561352, 'lr': 0.0001501468922693348, 'weight_decay': 0.00018799518076128812, 'batch_size': 64} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:13:02,069] Trial 39 pruned. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.003985 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.1419027472128915, 'ffn_dropout': 0.33772077965792113, 'lr': 0.0029429976482076756, 'weight_decay': 0.00046425546188629067, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:14:06,976] Trial 40 pruned. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.364269 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.15736988450283235, 'ffn_dropout': 0.267147624353145, 'lr': 0.000745933053051001, 'weight_decay': 0.015101682543261271, 'batch_size': 256} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-25 23:20:49,815] Trial 41 finished with value: 0.4840420164606394 and parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.22250268522197666, 'ffn_dropout': 0.24025013432134437, 'lr': 0.00023618381355069466, 'weight_decay': 0.00372158304962893, 'batch_size': 32}. Best is trial 15 with value: 0.49840606228991896. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.484042 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.22250268522197666, 'ffn_dropout': 0.24025013432134437, 'lr': 0.00023618381355069466, 'weight_decay': 0.00372158304962893, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:22:34,617] Trial 42 pruned. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.363966 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.20824440080044282, 'ffn_dropout': 0.20056978746002252, 'lr': 0.00035376847697482646, 'weight_decay': 0.004126338818967217, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:24:29,932] Trial 43 pruned. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.321644 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.17232848895142716, 'ffn_dropout': 0.23721590443495988, 'lr': 0.00023815410540797924, 'weight_decay': 0.005868285694195187, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:26:50,346] Trial 44 pruned. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.330402 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.10186356641277763, 'ffn_dropout': 0.36314294045827233, 'lr': 0.00014245837726324005, 'weight_decay': 0.002573738386246996, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-25 23:34:04,201] Trial 45 finished with value: 0.48126775000682104 and parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.15671686359834947, 'ffn_dropout': 0.3041481780014057, 'lr': 0.0004733778108757363, 'weight_decay': 0.04243617742110823, 'batch_size': 32}. Best is trial 15 with value: 0.49840606228991896. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.481268 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.15671686359834947, 'ffn_dropout': 0.3041481780014057, 'lr': 0.0004733778108757363, 'weight_decay': 0.04243617742110823, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:36:06,763] Trial 46 pruned. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.374684 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2461632862898201, 'ffn_dropout': 0.13362127910286659, 'lr': 0.00033247129312286694, 'weight_decay': 0.011751152579042997, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:37:42,961] Trial 47 pruned. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.364350 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1373207466783949, 'ffn_dropout': 0.2777889012670552, 'lr': 0.0001173590164683733, 'weight_decay': 0.02229856124815205, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:38:29,675] Trial 48 pruned. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.400605 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.17615878073448846, 'ffn_dropout': 0.3171659734077421, 'lr': 7.508491176820663e-05, 'weight_decay': 0.0006347971539466756, 'batch_size': 64} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:40:01,997] Trial 49 pruned. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.405183 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.19487913689755446, 'ffn_dropout': 0.2590131615752733, 'lr': 0.00020367442077653028, 'weight_decay': 0.004849485149429755, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:40:48,189] Trial 50 pruned. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.392857 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.11243643055013398, 'ffn_dropout': 0.209191947355023, 'lr': 0.0007559400253317549, 'weight_decay': 0.007289460502867801, 'batch_size': 128} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:42:33,856] Trial 51 pruned. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.371910 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1612915395208359, 'ffn_dropout': 0.3058586604484493, 'lr': 0.00046405792620229583, 'weight_decay': 0.047419535173522875, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:44:23,338] Trial 52 pruned. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.357809 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.15530088570029416, 'ffn_dropout': 0.2769846463459473, 'lr': 0.0004498876497406829, 'weight_decay': 0.043145651101506394, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:46:08,640] Trial 53 pruned. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.369089 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.13267993228721928, 'ffn_dropout': 0.23788551262357863, 'lr': 0.00024905903420021584, 'weight_decay': 0.024711872785764352, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:48:15,180] Trial 54 pruned. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.364882 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1684088734647707, 'ffn_dropout': 0.25687243386155856, 'lr': 0.0003162688105841667, 'weight_decay': 0.08066343726445575, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:50:02,538] Trial 55 pruned. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.400239 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.18414487034172705, 'ffn_dropout': 0.29840066587945235, 'lr': 0.00018187137314994116, 'weight_decay': 0.00034135487229599757, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:51:28,823] Trial 56 pruned. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.364084 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1199982070967209, 'ffn_dropout': 0.31137989280061507, 'lr': 0.0005845148928921555, 'weight_decay': 0.014571603616598783, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:53:22,840] Trial 57 pruned. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.400877 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.14365207076992628, 'ffn_dropout': 0.22701431640008574, 'lr': 0.0001554764291016946, 'weight_decay': 0.02923202475484064, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:53:35,814] Trial 58 pruned. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.200366 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.13023617943613297, 'ffn_dropout': 0.25213452527318975, 'lr': 0.00011114170457518931, 'weight_decay': 0.01861131042369739, 'batch_size': 256} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:55:59,434] Trial 59 pruned. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.392576 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.1534191524766948, 'ffn_dropout': 0.26730969064263477, 'lr': 0.0004391029284786918, 'weight_decay': 0.0004963848679784123, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:56:24,387] Trial 60 pruned. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.238242 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1772132767961795, 'ffn_dropout': 0.18672271161535092, 'lr': 0.00010030994600401824, 'weight_decay': 0.008003966625878442, 'batch_size': 128} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-25 23:57:58,125] Trial 61 pruned. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.349941 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.21825459811141232, 'ffn_dropout': 0.24512643902822306, 'lr': 0.00027498098024077145, 'weight_decay': 0.0020962939323636138, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-26 00:03:16,301] Trial 62 finished with value: 0.4718399687681063 and parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.23042266663893285, 'ffn_dropout': 0.23436062896301588, 'lr': 0.0002230692069938929, 'weight_decay': 0.0039796509597071405, 'batch_size': 32}. Best is trial 15 with value: 0.49840606228991896. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.471840 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.23042266663893285, 'ffn_dropout': 0.23436062896301588, 'lr': 0.0002230692069938929, 'weight_decay': 0.0039796509597071405, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-26 00:04:56,558] Trial 63 pruned. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.371859 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.23909958883614, 'ffn_dropout': 0.21532198212059442, 'lr': 0.00020499871619712303, 'weight_decay': 0.002976737471477156, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-26 00:11:21,309] Trial 64 finished with value: 0.48181230905597205 and parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.20079879517764765, 'ffn_dropout': 0.24661332840907887, 'lr': 0.00037292442852595356, 'weight_decay': 0.0007646956101587916, 'batch_size': 32}. Best is trial 15 with value: 0.49840606228991896. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.481812 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.20079879517764765, 'ffn_dropout': 0.24661332840907887, 'lr': 0.00037292442852595356, 'weight_decay': 0.0007646956101587916, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-26 00:15:24,915] Trial 65 pruned. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.428249 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2045930628883914, 'ffn_dropout': 0.2838112011876339, 'lr': 0.00037283474999213833, 'weight_decay': 0.0008266932202585447, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-26 00:16:58,140] Trial 66 pruned. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.411236 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.21561365545612102, 'ffn_dropout': 0.2715999812294845, 'lr': 0.0004985470667659301, 'weight_decay': 0.00040676032786569487, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-26 00:18:13,381] Trial 67 pruned. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.361461 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.1943555674672662, 'ffn_dropout': 0.24559586237932152, 'lr': 0.00017296542457151265, 'weight_decay': 0.0010439206925488033, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-26 00:19:09,701] Trial 68 pruned. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.422149 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.1833908972936007, 'ffn_dropout': 0.2616105082481707, 'lr': 0.0003014540526410793, 'weight_decay': 0.0005677941629566493, 'batch_size': 128} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-26 00:20:59,593] Trial 69 pruned. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.003985 - Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.20138962194582646, 'ffn_dropout': 0.2298291742015669, 'lr': 0.0006769220801408388, 'weight_decay': 0.001386574105603196, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-26 00:21:48,924] Trial 70 pruned. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.364532 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.19034136159535947, 'ffn_dropout': 0.2964249909006615, 'lr': 0.000534030213298193, 'weight_decay': 0.0002279146259718452, 'batch_size': 64} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-26 00:25:46,291] Trial 71 pruned. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.442563 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.22239433841977418, 'ffn_dropout': 0.22147789480978314, 'lr': 0.00025016340377996316, 'weight_decay': 0.0032638902083724484, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-26 00:31:00,777] Trial 72 finished with value: 0.4823952479730737 and parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2093950634104731, 'ffn_dropout': 0.23177092967447208, 'lr': 0.0004042750866433493, 'weight_decay': 0.0007810132677050465, 'batch_size': 32}. Best is trial 15 with value: 0.49840606228991896. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.482395 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2093950634104731, 'ffn_dropout': 0.23177092967447208, 'lr': 0.0004042750866433493, 'weight_decay': 0.0007810132677050465, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-26 00:32:11,334] Trial 73 pruned. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.375144 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.20855637979164285, 'ffn_dropout': 0.24421242977966104, 'lr': 0.00038930074915543634, 'weight_decay': 0.0007938370979948668, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-26 00:33:26,621] Trial 74 pruned. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.383897 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.16424863453097832, 'ffn_dropout': 0.2652225582064566, 'lr': 0.00013453555328428205, 'weight_decay': 0.0007434815518792257, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-26 00:33:38,657] Trial 75 pruned. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.382725 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2133946895874894, 'ffn_dropout': 0.20966121608580546, 'lr': 0.00032830372994374255, 'weight_decay': 0.0010222855239881133, 'batch_size': 256} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-26 00:34:54,639] Trial 76 pruned. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.334214 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2001280951771686, 'ffn_dropout': 0.25121392242751894, 'lr': 0.0009254964638918736, 'weight_decay': 0.00035987075241262015, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-26 00:35:30,662] Trial 77 pruned. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.354610 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.23480092176962009, 'ffn_dropout': 0.2823491296560678, 'lr': 0.00039326269144103064, 'weight_decay': 0.0006055053620312649, 'batch_size': 128} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-26 00:48:15,544] Trial 78 finished with value: 0.4814932578525175 and parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.2217962504149459, 'ffn_dropout': 0.22980442371103418, 'lr': 0.0001652848481714356, 'weight_decay': 0.000447714763969572, 'batch_size': 32}. Best is trial 15 with value: 0.49840606228991896. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.481493 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.2217962504149459, 'ffn_dropout': 0.22980442371103418, 'lr': 0.0001652848481714356, 'weight_decay': 0.000447714763969572, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-26 00:59:16,957] Trial 79 finished with value: 0.4686812399457628 and parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.22423083791449172, 'ffn_dropout': 0.21921961800738346, 'lr': 0.0001552345637589303, 'weight_decay': 0.00046261429580583667, 'batch_size': 32}. Best is trial 15 with value: 0.49840606228991896. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.468681 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.22423083791449172, 'ffn_dropout': 0.21921961800738346, 'lr': 0.0001552345637589303, 'weight_decay': 0.00046261429580583667, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-26 01:09:52,548] Trial 80 finished with value: 0.4722945104732808 and parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.23727503974846959, 'ffn_dropout': 0.19920833057507337, 'lr': 0.00018826300515392566, 'weight_decay': 0.0006685746353840874, 'batch_size': 32}. Best is trial 15 with value: 0.49840606228991896. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.472295 - Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.23727503974846959, 'ffn_dropout': 0.19920833057507337, 'lr': 0.00018826300515392566, 'weight_decay': 0.0006685746353840874, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-26 01:11:24,970] Trial 81 pruned. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.390387 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.2114466654278321, 'ffn_dropout': 0.23210198229714407, 'lr': 0.0002622823751044674, 'weight_decay': 0.0004884166804740916, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-26 01:13:58,279] Trial 82 pruned. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.406024 - Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.22292019845024202, 'ffn_dropout': 0.24304915323325194, 'lr': 0.00011612270077331507, 'weight_decay': 0.0009666362607698635, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-26 01:15:13,376] Trial 83 pruned. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.370234 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.20199258856633617, 'ffn_dropout': 0.27411901212952505, 'lr': 0.00021419603016494137, 'weight_decay': 0.0003188956129505065, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-26 01:22:39,190] Trial 84 finished with value: 0.467950232346922 and parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2145978875499715, 'ffn_dropout': 0.25972453067361007, 'lr': 0.0002794421961033291, 'weight_decay': 0.0012083715972301568, 'batch_size': 32}. Best is trial 15 with value: 0.49840606228991896. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.467950 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2145978875499715, 'ffn_dropout': 0.25972453067361007, 'lr': 0.0002794421961033291, 'weight_decay': 0.0012083715972301568, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-26 01:24:08,027] Trial 85 pruned. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.391414 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.19320473540751415, 'ffn_dropout': 0.22647039949025233, 'lr': 0.00044225869853118147, 'weight_decay': 0.0003900274543658891, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-26 01:24:46,093] Trial 86 pruned. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.393782 - Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.1498431471072864, 'ffn_dropout': 0.23820110940713038, 'lr': 8.929024312875033e-05, 'weight_decay': 0.0002631785448196263, 'batch_size': 128} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-26 01:25:25,667] Trial 87 pruned. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.396752 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.18155429302831538, 'ffn_dropout': 0.2900744341178435, 'lr': 0.00016698247295297746, 'weight_decay': 0.0014815568644873638, 'batch_size': 64} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-26 01:26:52,944] Trial 88 pruned. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.348259 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2572422299994559, 'ffn_dropout': 0.33079585053669136, 'lr': 0.00013761407775061133, 'weight_decay': 0.0006998092188927516, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-26 01:27:40,450] Trial 89 pruned. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.390387 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.17175370475871432, 'ffn_dropout': 0.17379694395494105, 'lr': 0.00033959809938205785, 'weight_decay': 0.0005827683213173623, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-26 01:28:18,191] Trial 90 pruned. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.414751 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.14020711510622844, 'ffn_dropout': 0.3112556144434017, 'lr': 0.00020847321366042757, 'weight_decay': 0.0016544886887722172, 'batch_size': 256} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-26 01:29:05,385] Trial 91 pruned. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.395577 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2306639261644685, 'ffn_dropout': 0.21475596788541843, 'lr': 0.00024860368117781795, 'weight_decay': 0.0011404590259588762, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-26 01:30:18,565] Trial 92 pruned. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.383815 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.22380127864261556, 'ffn_dropout': 0.23270778074437465, 'lr': 0.0005767066682694046, 'weight_decay': 0.0009184452913840088, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-26 01:31:31,379] Trial 93 pruned. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.367844 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.20468385731444175, 'ffn_dropout': 0.25135711390281634, 'lr': 0.00030244725826305673, 'weight_decay': 0.0007793149186865472, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-26 01:32:40,559] Trial 94 pruned. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.392567 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.24334665174251408, 'ffn_dropout': 0.30334761006116434, 'lr': 0.0001760323027388513, 'weight_decay': 0.004993294428686409, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-26 01:33:53,578] Trial 95 pruned. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.368481 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2090896605534632, 'ffn_dropout': 0.24013058161112336, 'lr': 0.00022001922851678924, 'weight_decay': 0.0004177782467367, 'batch_size': 32} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-26 01:35:40,921] Trial 96 finished with value: 0.48073714088047953 and parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.21807894416859547, 'ffn_dropout': 0.25967167581415096, 'lr': 0.0004003183185930734, 'weight_decay': 0.0018834733866838996, 'batch_size': 128}. Best is trial 15 with value: 0.49840606228991896. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.480737 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.21807894416859547, 'ffn_dropout': 0.25967167581415096, 'lr': 0.0004003183185930734, 'weight_decay': 0.0018834733866838996, 'batch_size': 128} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) -[I 2025-12-26 01:36:08,163] Trial 97 pruned. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.369512 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.19782007782479602, 'ffn_dropout': 0.2583659718400824, 'lr': 0.0004837659770634386, 'weight_decay': 0.0018369626149392479, 'batch_size': 128} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-26 01:37:49,286] Trial 98 finished with value: 0.4768151330715296 and parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.23317845175778534, 'ffn_dropout': 0.2478400727936002, 'lr': 0.00042188261827584106, 'weight_decay': 0.0022596816955623455, 'batch_size': 128}. Best is trial 15 with value: 0.49840606228991896. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.476815 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.23317845175778534, 'ffn_dropout': 0.2478400727936002, 'lr': 0.00042188261827584106, 'weight_decay': 0.0022596816955623455, 'batch_size': 128} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9429593495934959, 1: 0.8867278287461774, 2: 1.2318803636672615} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15692}) - Fold 2 - 클래스별 가중치: {0: 0.9440650406504065, 1: 0.8877675840978593, 2: 1.2280033840947546} (클래스별 샘플 수: {0: 20500, 1: 21800, 2: 15760}) - Fold 3 - 클래스별 가중치: {0: 0.9438048780487804, 1: 0.9041121495327102, 2: 1.1984638255698712} (클래스별 샘플 수: {0: 20500, 1: 21400, 2: 16144}) -[I 2025-12-26 01:39:34,059] Trial 99 finished with value: 0.48425770398094525 and parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.18795685699999037, 'ffn_dropout': 0.27011524870091175, 'lr': 0.00035455567649456284, 'weight_decay': 0.0014623785738583832, 'batch_size': 128}. Best is trial 15 with value: 0.49840606228991896. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.484258 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.18795685699999037, 'ffn_dropout': 0.27011524870091175, 'lr': 0.00035455567649456284, 'weight_decay': 0.0014623785738583832, 'batch_size': 128} - Best Value (CSI): 0.498406 - Best Trial: 15 - Best Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.4984 -Best Hyperparameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13369638195384545, 'ffn_dropout': 0.25693944180246137, 'lr': 0.00046073450640759476, 'weight_decay': 0.0005511169366746759, 'batch_size': 32} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.4837 - - 최종 CSI: 0.4843 - - 최고 CSI: 0.4984 - - 최저 CSI: 0.0040 - - 평균 CSI: 0.3818 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/ft_transformer_smotenc_ctgan20000_gwangju_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 16, Best CSI: 0.4030 - Fold 1 학습 완료 (검증 CSI: 0.4030) -Fold 2 학습 중... - Early stopping at epoch 36, Best CSI: 0.5059 - Fold 2 학습 완료 (검증 CSI: 0.5059) -Fold 3 학습 중... - Early stopping at epoch 25, Best CSI: 0.5004 - Fold 3 학습 완료 (검증 CSI: 0.5004) - -모든 모델 저장 완료: ../save_model/ft_transformer_optima/ft_transformer_smotenc_ctgan20000_gwangju.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/ft_transformer_optima/scaler/ft_transformer_smotenc_ctgan20000_gwangju_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: ../save_model/ft_transformer_optima/ft_transformer_smotenc_ctgan20000_gwangju.pkl - -✓ 완료: ft_transformer_smotenc_ctgan20000/ft_transformer_smotenc_ctgan20000_gwangju.py (소요 시간: 15992초) - ----------------------------------------- -실행 중: ft_transformer_smotenc_ctgan20000/ft_transformer_smotenc_ctgan20000_incheon.py -시작 시간: 2025-12-26 01:46:37 ----------------------------------------- -[I 2025-12-26 01:46:38,340] A new study created in memory with name: no-name-dab50be9-0d0e-44ba-aab7-5fc722c6a634 - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 01:53:52,792] Trial 0 finished with value: 0.5587702310628659 and parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64}. Best is trial 0 with value: 0.5587702310628659. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.558770 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 01:55:55,961] Trial 1 finished with value: 0.5444175090297078 and parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.37366052951658524, 'ffn_dropout': 0.1554614841862499, 'lr': 0.0007456957121307549, 'weight_decay': 0.05910777817785268, 'batch_size': 128}. Best is trial 0 with value: 0.5587702310628659. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.544418 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.37366052951658524, 'ffn_dropout': 0.1554614841862499, 'lr': 0.0007456957121307549, 'weight_decay': 0.05910777817785268, 'batch_size': 128} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 01:58:32,854] Trial 2 finished with value: 0.1479627758232053 and parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.3567165989348816, 'ffn_dropout': 0.21003687602439788, 'lr': 0.003600001169654458, 'weight_decay': 0.020976315827953736, 'batch_size': 128}. Best is trial 0 with value: 0.5587702310628659. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.147963 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.3567165989348816, 'ffn_dropout': 0.21003687602439788, 'lr': 0.003600001169654458, 'weight_decay': 0.020976315827953736, 'batch_size': 128} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 02:15:33,157] Trial 3 finished with value: 0.5486416156141098 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3394516106937555, 'ffn_dropout': 0.37332923639965376, 'lr': 0.005758780377306426, 'weight_decay': 0.07858084935356081, 'batch_size': 32}. Best is trial 0 with value: 0.5587702310628659. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.548642 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3394516106937555, 'ffn_dropout': 0.37332923639965376, 'lr': 0.005758780377306426, 'weight_decay': 0.07858084935356081, 'batch_size': 32} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 02:23:02,830] Trial 4 finished with value: 0.5419096499150071 and parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.3394681276879379, 'ffn_dropout': 0.12466375992691184, 'lr': 3.969256123556905e-05, 'weight_decay': 0.0012067172469772617, 'batch_size': 64}. Best is trial 0 with value: 0.5587702310628659. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.541910 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.3394681276879379, 'ffn_dropout': 0.12466375992691184, 'lr': 3.969256123556905e-05, 'weight_decay': 0.0012067172469772617, 'batch_size': 64} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 02:24:26,995] Trial 5 pruned. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.448430 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.3252319864546302, 'ffn_dropout': 0.1570061045687427, 'lr': 0.0005346131581778342, 'weight_decay': 0.00034303429824904, 'batch_size': 128} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 02:26:35,797] Trial 6 finished with value: 0.5456357389894592 and parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.15583526489723185, 'ffn_dropout': 0.36201990892015046, 'lr': 0.0016324128364924048, 'weight_decay': 0.00018271164419523874, 'batch_size': 256}. Best is trial 0 with value: 0.5587702310628659. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.545636 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.15583526489723185, 'ffn_dropout': 0.36201990892015046, 'lr': 0.0016324128364924048, 'weight_decay': 0.00018271164419523874, 'batch_size': 256} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 02:27:07,698] Trial 7 pruned. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.426996 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13097386149286785, 'ffn_dropout': 0.23653013079710455, 'lr': 8.100850454221868e-05, 'weight_decay': 0.010234899113584356, 'batch_size': 128} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 02:36:51,692] Trial 8 finished with value: 0.5376998025464391 and parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.2735731488225443, 'ffn_dropout': 0.24290212406639408, 'lr': 0.0009644959938096378, 'weight_decay': 0.0007570896459389863, 'batch_size': 32}. Best is trial 0 with value: 0.5587702310628659. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.537700 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.2735731488225443, 'ffn_dropout': 0.24290212406639408, 'lr': 0.0009644959938096378, 'weight_decay': 0.0007570896459389863, 'batch_size': 32} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 02:38:21,864] Trial 9 pruned. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.457962 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.21704772551348434, 'ffn_dropout': 0.14245530009532142, 'lr': 0.0003383735656637399, 'weight_decay': 0.011812341381667908, 'batch_size': 128} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 02:40:06,823] Trial 10 pruned. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.492893 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.3944818682627955, 'ffn_dropout': 0.2996352306142834, 'lr': 1.0625684684013198e-05, 'weight_decay': 0.003454209599392831, 'batch_size': 64} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 02:42:21,021] Trial 11 pruned. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.017077 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.2929995180767028, 'ffn_dropout': 0.3912987345273517, 'lr': 0.008881396088303772, 'weight_decay': 0.08303942560348745, 'batch_size': 32} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 02:47:29,209] Trial 12 finished with value: 0.5476982047207368 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.31433864553697427, 'ffn_dropout': 0.3070001735791416, 'lr': 0.00014192351623897297, 'weight_decay': 0.09688561746838062, 'batch_size': 64}. Best is trial 0 with value: 0.5587702310628659. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.547698 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.31433864553697427, 'ffn_dropout': 0.3070001735791416, 'lr': 0.00014192351623897297, 'weight_decay': 0.09688561746838062, 'batch_size': 64} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 02:49:18,025] Trial 13 pruned. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.017077 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.25467441879554586, 'ffn_dropout': 0.29057477857230096, 'lr': 0.0025575166805039073, 'weight_decay': 0.03318639166926802, 'batch_size': 32} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 02:49:33,719] Trial 14 pruned. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.008523 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.39575561092416006, 'ffn_dropout': 0.2002158944438344, 'lr': 0.008208789078701212, 'weight_decay': 0.03652214710280682, 'batch_size': 256} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 02:52:33,646] Trial 15 pruned. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.491514 - Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34021313031687933, 'ffn_dropout': 0.34021402537487067, 'lr': 0.00028902231299442974, 'weight_decay': 0.0160124234830787, 'batch_size': 32} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 02:53:20,726] Trial 16 pruned. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.496463 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.2978192449270944, 'ffn_dropout': 0.26653291844792887, 'lr': 0.0014956485849632298, 'weight_decay': 0.005641381119051794, 'batch_size': 64} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 02:55:16,738] Trial 17 pruned. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.497781 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.22993481104432578, 'ffn_dropout': 0.3947220489683638, 'lr': 0.0003213161506453874, 'weight_decay': 0.0423051819085012, 'batch_size': 32} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 02:56:11,836] Trial 18 pruned. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.033309 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.3686743811524074, 'ffn_dropout': 0.33343385003388093, 'lr': 0.004180150220150227, 'weight_decay': 0.02870673903038044, 'batch_size': 64} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 02:59:52,850] Trial 19 finished with value: 0.5449075911553761 and parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.31785641706736023, 'ffn_dropout': 0.27501601274473847, 'lr': 0.0009220421338596502, 'weight_decay': 0.09642272226486212, 'batch_size': 256}. Best is trial 0 with value: 0.5587702310628659. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.544908 - Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.31785641706736023, 'ffn_dropout': 0.27501601274473847, 'lr': 0.0009220421338596502, 'weight_decay': 0.09642272226486212, 'batch_size': 256} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 03:00:41,135] Trial 20 pruned. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.474555 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3432513002912038, 'ffn_dropout': 0.10481777939669683, 'lr': 0.0017911989310436922, 'weight_decay': 0.05032855661357391, 'batch_size': 64} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 03:01:28,414] Trial 21 pruned. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.529281 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3050055821243847, 'ffn_dropout': 0.31779605843547565, 'lr': 0.0001997396087260459, 'weight_decay': 0.09095883872273372, 'batch_size': 64} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 03:02:15,706] Trial 22 pruned. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.518937 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3158459077590512, 'ffn_dropout': 0.36148891305190595, 'lr': 0.0001428175243801761, 'weight_decay': 0.09876551013677735, 'batch_size': 64} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 03:07:20,696] Trial 23 pruned. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.543694 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3641285046766046, 'ffn_dropout': 0.30606415776811735, 'lr': 0.00011671993373643644, 'weight_decay': 0.021809483760609667, 'batch_size': 64} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 03:08:52,346] Trial 24 pruned. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.481095 - Parameters: {'d_token': 128, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2884063257585626, 'ffn_dropout': 0.27836583872121223, 'lr': 0.000498232444212991, 'weight_decay': 0.056471684271283795, 'batch_size': 32} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 03:09:50,229] Trial 25 pruned. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.484888 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.328496960499703, 'ffn_dropout': 0.3187558117501914, 'lr': 6.86758512561796e-05, 'weight_decay': 0.04936710655798688, 'batch_size': 64} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 03:10:58,263] Trial 26 pruned. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.452290 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.2754073613459495, 'ffn_dropout': 0.25962007579682406, 'lr': 0.000195050352315866, 'weight_decay': 0.02601444706683067, 'batch_size': 64} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 03:12:34,352] Trial 27 pruned. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.446244 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.3526311214388148, 'ffn_dropout': 0.35604873132457343, 'lr': 0.0005297621205886926, 'weight_decay': 0.010833300048001615, 'batch_size': 32} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 03:12:53,491] Trial 28 pruned. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.017077 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.31364187064330856, 'ffn_dropout': 0.3766912911113559, 'lr': 0.005488369928528254, 'weight_decay': 0.06386073227943485, 'batch_size': 256} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 03:13:37,562] Trial 29 pruned. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.331518 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3701353585774312, 'ffn_dropout': 0.2912238953259189, 'lr': 0.001104776368291479, 'weight_decay': 0.057957601813492604, 'batch_size': 64} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 03:15:31,229] Trial 30 pruned. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.460399 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3944521832218051, 'ffn_dropout': 0.33921658457660214, 'lr': 0.0006810037123950648, 'weight_decay': 0.0349236381556746, 'batch_size': 32} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 03:16:02,898] Trial 31 pruned. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.417437 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.10873825653860342, 'ffn_dropout': 0.35731703576127, 'lr': 0.0024873349391287634, 'weight_decay': 0.00017124193805569858, 'batch_size': 256} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 03:16:21,364] Trial 32 pruned. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.121998 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.16962947186775582, 'ffn_dropout': 0.37234590435134973, 'lr': 0.006105326805699287, 'weight_decay': 0.00015146783729774158, 'batch_size': 256} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 03:16:46,727] Trial 33 pruned. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.039922 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.35047810526270873, 'ffn_dropout': 0.39422586195497084, 'lr': 0.0033174968854580967, 'weight_decay': 0.0013272529038535967, 'batch_size': 256} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 03:17:08,859] Trial 34 pruned. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.474187 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.33955333971263807, 'ffn_dropout': 0.3256558953276691, 'lr': 0.0014642331794051905, 'weight_decay': 0.018148307737328173, 'batch_size': 256} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 03:19:54,136] Trial 35 finished with value: 0.5339611530702174 and parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.3264977953457961, 'ffn_dropout': 0.346697371154064, 'lr': 0.002198410666590786, 'weight_decay': 0.06612535476528124, 'batch_size': 128}. Best is trial 0 with value: 0.5587702310628659. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.533961 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.3264977953457961, 'ffn_dropout': 0.346697371154064, 'lr': 0.002198410666590786, 'weight_decay': 0.06612535476528124, 'batch_size': 128} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 03:20:40,748] Trial 36 pruned. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.017077 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.18442273932969286, 'ffn_dropout': 0.36916684939564665, 'lr': 0.004358860413575937, 'weight_decay': 0.0001162605104800144, 'batch_size': 64} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 03:21:23,815] Trial 37 pruned. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.017077 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.2787377892218927, 'ffn_dropout': 0.21519853151373214, 'lr': 0.0034286887654630446, 'weight_decay': 0.007271204842256108, 'batch_size': 128} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 03:21:40,692] Trial 38 pruned. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.496145 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.25894394321263703, 'ffn_dropout': 0.31267292228130494, 'lr': 0.0007306386624073975, 'weight_decay': 0.0003806805495906629, 'batch_size': 256} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 03:22:54,049] Trial 39 pruned. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.481433 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.37853357123343684, 'ffn_dropout': 0.3483419847618282, 'lr': 0.0011192372991976915, 'weight_decay': 0.0020118526860901566, 'batch_size': 64} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 03:26:48,916] Trial 40 pruned. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.548163 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.30562889376323454, 'ffn_dropout': 0.3268429956354424, 'lr': 0.00044967570977719656, 'weight_decay': 0.014638646464557276, 'batch_size': 128} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 03:27:45,391] Trial 41 pruned. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.504750 - Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3251327484903447, 'ffn_dropout': 0.2787120311528673, 'lr': 0.0009496097869045288, 'weight_decay': 0.09941542717293726, 'batch_size': 256} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 03:28:40,645] Trial 42 pruned. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.458627 - Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.35487590341736064, 'ffn_dropout': 0.23232113523139056, 'lr': 0.0008305761272990338, 'weight_decay': 0.0696939484952942, 'batch_size': 256} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 03:29:23,458] Trial 43 pruned. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.017077 - Parameters: {'d_token': 224, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.2911110213303823, 'ffn_dropout': 0.3796300237966227, 'lr': 0.009219372701657994, 'weight_decay': 0.08068782584322115, 'batch_size': 256} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 03:30:18,718] Trial 44 pruned. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.431258 - Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.31875395800769496, 'ffn_dropout': 0.1820822764065428, 'lr': 0.0017546932169052812, 'weight_decay': 0.04055312976291704, 'batch_size': 256} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 03:32:59,793] Trial 45 pruned. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.473786 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.26466471962921145, 'ffn_dropout': 0.30258494186221385, 'lr': 0.00034787724738879, 'weight_decay': 0.04422716130326381, 'batch_size': 32} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 03:34:54,759] Trial 46 finished with value: 0.5546426748172475 and parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.2437694108716114, 'ffn_dropout': 0.2614000041894434, 'lr': 0.0013158290173757813, 'weight_decay': 0.02774449986183839, 'batch_size': 256}. Best is trial 0 with value: 0.5587702310628659. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.554643 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.2437694108716114, 'ffn_dropout': 0.2614000041894434, 'lr': 0.0013158290173757813, 'weight_decay': 0.02774449986183839, 'batch_size': 256} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 03:36:40,031] Trial 47 pruned. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.017077 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.24049035138845282, 'ffn_dropout': 0.25044777289841696, 'lr': 0.0032829686310000875, 'weight_decay': 0.02307993350820701, 'batch_size': 32} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 03:37:59,627] Trial 48 pruned. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.448208 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.217709849550182, 'ffn_dropout': 0.2925094483114275, 'lr': 0.0006224024651950728, 'weight_decay': 0.02957828264801411, 'batch_size': 64} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 03:38:25,030] Trial 49 pruned. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.477848 - Parameters: {'d_token': 96, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2448678863692198, 'ffn_dropout': 0.3335781172614827, 'lr': 0.0013564132389009965, 'weight_decay': 0.07031037439933467, 'batch_size': 256} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 03:40:12,106] Trial 50 pruned. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.017077 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.2676447502080628, 'ffn_dropout': 0.39910408848492335, 'lr': 0.006233443737029244, 'weight_decay': 0.03549223531914368, 'batch_size': 32} - Best Value (CSI): 0.558770 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.34182762434629993, 'ffn_dropout': 0.20516720144542075, 'lr': 0.0002648398993978442, 'weight_decay': 0.09055429230610533, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 03:42:25,766] Trial 51 finished with value: 0.5658689261675397 and parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256}. Best is trial 51 with value: 0.5658689261675397. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.565869 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 03:42:54,796] Trial 52 pruned. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.448525 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3369916147028472, 'ffn_dropout': 0.2384710142361171, 'lr': 0.001983867570345685, 'weight_decay': 0.07421274401986226, 'batch_size': 256} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 03:43:23,962] Trial 53 pruned. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.461736 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3011333661299567, 'ffn_dropout': 0.2192878500373079, 'lr': 0.00221228430500615, 'weight_decay': 0.0542532735466507, 'batch_size': 256} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 03:43:58,241] Trial 54 pruned. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.481577 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.28564160114361326, 'ffn_dropout': 0.2535238144758982, 'lr': 0.0030702604305415464, 'weight_decay': 0.04652265726168276, 'batch_size': 256} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) -[I 2025-12-26 03:46:23,982] Trial 55 pruned. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.289520 - Parameters: {'d_token': 64, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.31025309991562644, 'ffn_dropout': 0.2005509724476892, 'lr': 0.0025946828722431974, 'weight_decay': 0.09993578178655149, 'batch_size': 64} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 03:46:48,666] Trial 56 pruned. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.505168 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.30150819719947775, 'ffn_dropout': 0.26263038823774343, 'lr': 0.004976801571747986, 'weight_decay': 0.07781628477953773, 'batch_size': 128} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 03:47:48,142] Trial 57 pruned. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.017077 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.33270081613368596, 'ffn_dropout': 0.2320750162754175, 'lr': 0.006807582895674544, 'weight_decay': 0.027160347978731854, 'batch_size': 64} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 03:49:58,236] Trial 58 finished with value: 0.5322014325820453 and parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3486084492616679, 'ffn_dropout': 0.270327731231985, 'lr': 0.0012402631709711417, 'weight_decay': 0.05320979909211251, 'batch_size': 256}. Best is trial 51 with value: 0.5658689261675397. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.532201 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.3486084492616679, 'ffn_dropout': 0.270327731231985, 'lr': 0.0012402631709711417, 'weight_decay': 0.05320979909211251, 'batch_size': 256} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 03:51:24,173] Trial 59 pruned. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.473552 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.28447165057221024, 'ffn_dropout': 0.2490009127855201, 'lr': 0.00026868782595524667, 'weight_decay': 0.0398268912584212, 'batch_size': 32} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 03:52:24,912] Trial 60 pruned. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.017077 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.2968437790003496, 'ffn_dropout': 0.38482004514285456, 'lr': 0.004359944425711276, 'weight_decay': 0.02006440278686655, 'batch_size': 64} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 03:55:31,023] Trial 61 finished with value: 0.5450508140944997 and parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3198731416179766, 'ffn_dropout': 0.27527101224591716, 'lr': 0.0016462273550450141, 'weight_decay': 0.08317967616738514, 'batch_size': 256}. Best is trial 51 with value: 0.5658689261675397. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.545051 - Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3198731416179766, 'ffn_dropout': 0.27527101224591716, 'lr': 0.0016462273550450141, 'weight_decay': 0.08317967616738514, 'batch_size': 256} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 03:56:13,226] Trial 62 pruned. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.461883 - Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.33261824111498284, 'ffn_dropout': 0.28423526554144224, 'lr': 0.0015569422963970742, 'weight_decay': 0.08508354783995578, 'batch_size': 256} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 03:56:55,492] Trial 63 pruned. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.017077 - Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3212619423613564, 'ffn_dropout': 0.26886544373879984, 'lr': 0.002567915025224402, 'weight_decay': 0.06011487982790014, 'batch_size': 256} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 03:57:25,940] Trial 64 pruned. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.448163 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.36344780860775383, 'ffn_dropout': 0.296932701929482, 'lr': 0.001576536821155656, 'weight_decay': 0.07750017039682405, 'batch_size': 256} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 03:58:08,067] Trial 65 pruned. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.474286 - Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3107608246222477, 'ffn_dropout': 0.36656817431058897, 'lr': 0.0010761913793068286, 'weight_decay': 0.032329491706285976, 'batch_size': 256} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 03:58:55,338] Trial 66 pruned. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.482211 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.34750741173424293, 'ffn_dropout': 0.2608319512182219, 'lr': 0.0019808723197397085, 'weight_decay': 0.04758611157509047, 'batch_size': 64} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 04:01:46,993] Trial 67 pruned. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.375590 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.33913572374527795, 'ffn_dropout': 0.28596577997945843, 'lr': 0.0008570337378510212, 'weight_decay': 0.06369129680426544, 'batch_size': 32} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 04:02:15,197] Trial 68 pruned. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.490966 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2744632096023234, 'ffn_dropout': 0.30213475097103315, 'lr': 0.003859904706032665, 'weight_decay': 0.09814784969942256, 'batch_size': 256} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 04:03:06,529] Trial 69 pruned. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.486554 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.31527667458553676, 'ffn_dropout': 0.3858930644586859, 'lr': 0.0028821445485241242, 'weight_decay': 0.06013200840206882, 'batch_size': 256} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 04:03:55,080] Trial 70 pruned. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.017077 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3249956645113395, 'ffn_dropout': 0.3544276371417385, 'lr': 0.007418846761471996, 'weight_decay': 0.08339003455991001, 'batch_size': 64} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 04:07:18,389] Trial 71 finished with value: 0.5501107093998284 and parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.29859079796797616, 'ffn_dropout': 0.27523091934211247, 'lr': 0.0014003363724514725, 'weight_decay': 0.08501374495474277, 'batch_size': 256}. Best is trial 51 with value: 0.5658689261675397. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.550111 - Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.29859079796797616, 'ffn_dropout': 0.27523091934211247, 'lr': 0.0014003363724514725, 'weight_decay': 0.08501374495474277, 'batch_size': 256} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 04:08:15,566] Trial 72 pruned. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.514042 - Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.29262886047835307, 'ffn_dropout': 0.2732673810668396, 'lr': 0.0012709731614241459, 'weight_decay': 0.04114192462631701, 'batch_size': 256} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 04:10:41,022] Trial 73 finished with value: 0.5513811044783637 and parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3043996281161073, 'ffn_dropout': 0.2823773607327542, 'lr': 0.0019422549755146704, 'weight_decay': 0.06940157866788899, 'batch_size': 256}. Best is trial 51 with value: 0.5658689261675397. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.551381 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3043996281161073, 'ffn_dropout': 0.2823773607327542, 'lr': 0.0019422549755146704, 'weight_decay': 0.06940157866788899, 'batch_size': 256} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 04:11:23,772] Trial 74 pruned. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.017077 - Parameters: {'d_token': 224, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3037769532916815, 'ffn_dropout': 0.30672189866491917, 'lr': 0.004902494281930458, 'weight_decay': 0.05770459961710986, 'batch_size': 256} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 04:13:28,618] Trial 75 finished with value: 0.5577779866662523 and parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.2569368000656096, 'ffn_dropout': 0.24513264783114322, 'lr': 0.004057601993852997, 'weight_decay': 0.0682571195021235, 'batch_size': 256}. Best is trial 51 with value: 0.5658689261675397. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.557778 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.2569368000656096, 'ffn_dropout': 0.24513264783114322, 'lr': 0.004057601993852997, 'weight_decay': 0.0682571195021235, 'batch_size': 256} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 04:13:57,132] Trial 76 pruned. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.491206 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.2825481611165924, 'ffn_dropout': 0.2557235316091041, 'lr': 0.003718000209654103, 'weight_decay': 0.070561157276761, 'batch_size': 256} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 04:14:28,543] Trial 77 pruned. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.017077 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.2679529710371297, 'ffn_dropout': 0.24458189304250455, 'lr': 0.005823602362200398, 'weight_decay': 0.04979759137222155, 'batch_size': 128} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 04:16:23,518] Trial 78 pruned. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.017077 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.2970944117666119, 'ffn_dropout': 0.2855175565872237, 'lr': 0.0099405692942946, 'weight_decay': 0.06664365240325425, 'batch_size': 32} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 04:16:53,040] Trial 79 pruned. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.460492 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.25641819019827256, 'ffn_dropout': 0.2587634995617249, 'lr': 0.002262554808755784, 'weight_decay': 0.03494627620990865, 'batch_size': 256} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 04:17:51,119] Trial 80 pruned. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.017077 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.310888641840111, 'ffn_dropout': 0.2646628416948956, 'lr': 0.007763323517462201, 'weight_decay': 0.09088488914713594, 'batch_size': 64} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 04:18:28,264] Trial 81 pruned. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.485911 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.2816668644969869, 'ffn_dropout': 0.2244908855479126, 'lr': 0.002835804076381769, 'weight_decay': 0.09987968487707476, 'batch_size': 256} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 04:21:00,239] Trial 82 pruned. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.142694 - Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.2517016982937829, 'ffn_dropout': 0.24309179393491268, 'lr': 0.002112750446263649, 'weight_decay': 0.0515581867806668, 'batch_size': 256} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 04:21:29,939] Trial 83 pruned. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.501784 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.32955545499661293, 'ffn_dropout': 0.28112703363639135, 'lr': 0.003710932988746407, 'weight_decay': 0.07189749432607226, 'batch_size': 256} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 04:21:45,175] Trial 84 pruned. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.515596 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.23179822628753727, 'ffn_dropout': 0.2958671165060939, 'lr': 0.001813504711427063, 'weight_decay': 0.04196535933913575, 'batch_size': 256} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 04:24:02,288] Trial 85 finished with value: 0.5411055162243366 and parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.19931091141522436, 'ffn_dropout': 0.2510033275950906, 'lr': 0.001058756680273705, 'weight_decay': 0.08418023518317508, 'batch_size': 256}. Best is trial 51 with value: 0.5658689261675397. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.541106 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.19931091141522436, 'ffn_dropout': 0.2510033275950906, 'lr': 0.001058756680273705, 'weight_decay': 0.08418023518317508, 'batch_size': 256} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 04:25:07,558] Trial 86 pruned. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.462783 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.14919229222854158, 'ffn_dropout': 0.3164730567145671, 'lr': 0.0013390269673914, 'weight_decay': 0.06363543567790979, 'batch_size': 64} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 04:26:49,499] Trial 87 pruned. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.037403 - Parameters: {'d_token': 96, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.2893620687025783, 'ffn_dropout': 0.24129197125595728, 'lr': 0.0030624009447195507, 'weight_decay': 0.024039799499175667, 'batch_size': 32} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 04:27:35,148] Trial 88 pruned. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.454078 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.27766665525715245, 'ffn_dropout': 0.26941244791913194, 'lr': 0.0007966558212129106, 'weight_decay': 0.030573935998079005, 'batch_size': 256} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 04:27:53,604] Trial 89 pruned. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.116741 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3437990125426006, 'ffn_dropout': 0.23145135546840231, 'lr': 0.00450481413047273, 'weight_decay': 0.00421564411463884, 'batch_size': 256} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 04:30:47,646] Trial 90 finished with value: 0.4448669709848068 and parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.2621606639275094, 'ffn_dropout': 0.3650302990297463, 'lr': 0.0017090975482176654, 'weight_decay': 0.05235108387429086, 'batch_size': 128}. Best is trial 51 with value: 0.5658689261675397. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.444867 - Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.2621606639275094, 'ffn_dropout': 0.3650302990297463, 'lr': 0.0017090975482176654, 'weight_decay': 0.05235108387429086, 'batch_size': 128} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 04:31:27,168] Trial 91 pruned. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.514845 - Parameters: {'d_token': 128, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.31885940339009533, 'ffn_dropout': 0.2755639001090285, 'lr': 0.001620038326626115, 'weight_decay': 0.08176756491184979, 'batch_size': 256} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 04:31:55,884] Trial 92 pruned. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.510638 - Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.30642937754215466, 'ffn_dropout': 0.2906986493269853, 'lr': 0.002278808501888205, 'weight_decay': 0.07619065376875979, 'batch_size': 256} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 04:32:30,337] Trial 93 pruned. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.535737 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3221586900537614, 'ffn_dropout': 0.27492374370082184, 'lr': 0.001968199861289408, 'weight_decay': 0.08811661729639704, 'batch_size': 256} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 04:33:18,167] Trial 94 pruned. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.469726 - Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.2966394760046305, 'ffn_dropout': 0.2661165967785283, 'lr': 0.0012301327989768663, 'weight_decay': 0.05913679450390294, 'batch_size': 256} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) -[I 2025-12-26 04:35:55,327] Trial 95 pruned. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.545614 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.33632093826913656, 'ffn_dropout': 0.3743898976242319, 'lr': 0.000961230058076095, 'weight_decay': 0.07115713580941216, 'batch_size': 64} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 04:37:02,142] Trial 96 finished with value: 0.5510847527121311 and parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3134473238026919, 'ffn_dropout': 0.256487201536107, 'lr': 0.002575371332372382, 'weight_decay': 0.038711800127264356, 'batch_size': 256}. Best is trial 51 with value: 0.5658689261675397. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.551085 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3134473238026919, 'ffn_dropout': 0.256487201536107, 'lr': 0.002575371332372382, 'weight_decay': 0.038711800127264356, 'batch_size': 256} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 04:37:59,200] Trial 97 finished with value: 0.5460650987185982 and parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.27114183677806286, 'ffn_dropout': 0.2551734544682139, 'lr': 0.002605850363629184, 'weight_decay': 0.045336571392682525, 'batch_size': 256}. Best is trial 51 with value: 0.5658689261675397. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.546065 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.27114183677806286, 'ffn_dropout': 0.2551734544682139, 'lr': 0.002605850363629184, 'weight_decay': 0.045336571392682525, 'batch_size': 256} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) - Fold 2 - 클래스별 가중치: {0: 0.9388130081300813, 1: 0.8515781710914454, 2: 1.3148641570449318} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14637}) - Fold 3 - 클래스별 가중치: {0: 0.9397560975609756, 1: 0.8486784140969162, 2: 1.3199725933538884} (클래스별 샘플 수: {0: 20500, 1: 22700, 2: 14595}) -[I 2025-12-26 04:39:09,590] Trial 98 finished with value: 0.5533642404853625 and parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.27069786190748896, 'ffn_dropout': 0.24753378048750502, 'lr': 0.0026305097846398957, 'weight_decay': 0.044367807795891306, 'batch_size': 256}. Best is trial 51 with value: 0.5658689261675397. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.553364 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.27069786190748896, 'ffn_dropout': 0.24753378048750502, 'lr': 0.0026305097846398957, 'weight_decay': 0.044367807795891306, 'batch_size': 256} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9374634146341464, 1: 0.850353982300885, 2: 1.3204617287343685} (클래스별 샘플 수: {0: 20500, 1: 22600, 2: 14554}) -[I 2025-12-26 04:40:34,855] Trial 99 pruned. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.431462 - Parameters: {'d_token': 64, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.25993940851357394, 'ffn_dropout': 0.24676514789840534, 'lr': 0.0038300438906361638, 'weight_decay': 0.037463970644995855, 'batch_size': 32} - Best Value (CSI): 0.565869 - Best Trial: 51 - Best Parameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.5659 -Best Hyperparameters: {'d_token': 64, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.3014135618352386, 'ffn_dropout': 0.2377846194971104, 'lr': 0.0023493513093616647, 'weight_decay': 0.0983836135411264, 'batch_size': 256} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.5588 - - 최종 CSI: 0.4315 - - 최고 CSI: 0.5659 - - 최저 CSI: 0.0085 - - 평균 CSI: 0.3834 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/ft_transformer_smotenc_ctgan20000_incheon_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 16, Best CSI: 0.5238 - Fold 1 학습 완료 (검증 CSI: 0.5238) -Fold 2 학습 중... - Early stopping at epoch 23, Best CSI: 0.5849 - Fold 2 학습 완료 (검증 CSI: 0.5849) -Fold 3 학습 중... - Early stopping at epoch 40, Best CSI: 0.5523 - Fold 3 학습 완료 (검증 CSI: 0.5523) - -모든 모델 저장 완료: ../save_model/ft_transformer_optima/ft_transformer_smotenc_ctgan20000_incheon.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/ft_transformer_optima/scaler/ft_transformer_smotenc_ctgan20000_incheon_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: ../save_model/ft_transformer_optima/ft_transformer_smotenc_ctgan20000_incheon.pkl - -✓ 완료: ft_transformer_smotenc_ctgan20000/ft_transformer_smotenc_ctgan20000_incheon.py (소요 시간: 10576초) - ----------------------------------------- -실행 중: ft_transformer_smotenc_ctgan20000/ft_transformer_smotenc_ctgan20000_seoul.py -시작 시간: 2025-12-26 04:42:53 ----------------------------------------- -[I 2025-12-26 04:42:54,995] A new study created in memory with name: no-name-f385d293-c956-432c-9643-52ef34236b1a - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 04:46:31,065] Trial 0 finished with value: 0.09805561793547309 and parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.1688610819529528, 'ffn_dropout': 0.3226200636504205, 'lr': 0.006607342610437163, 'weight_decay': 0.0004396458346270925, 'batch_size': 64}. Best is trial 0 with value: 0.09805561793547309. - -================================================================================ -Trial 0 완료 - Value (CSI): 0.098056 - Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.1688610819529528, 'ffn_dropout': 0.3226200636504205, 'lr': 0.006607342610437163, 'weight_decay': 0.0004396458346270925, 'batch_size': 64} - Best Value (CSI): 0.098056 - Best Trial: 0 - Best Parameters: {'d_token': 96, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.1688610819529528, 'ffn_dropout': 0.3226200636504205, 'lr': 0.006607342610437163, 'weight_decay': 0.0004396458346270925, 'batch_size': 64} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 04:48:09,391] Trial 1 finished with value: 0.42844022011491356 and parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2971145798427403, 'ffn_dropout': 0.294642450983742, 'lr': 2.7743800867557626e-05, 'weight_decay': 0.004230079098902941, 'batch_size': 256}. Best is trial 1 with value: 0.42844022011491356. - -================================================================================ -Trial 1 완료 - Value (CSI): 0.428440 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2971145798427403, 'ffn_dropout': 0.294642450983742, 'lr': 2.7743800867557626e-05, 'weight_decay': 0.004230079098902941, 'batch_size': 256} - Best Value (CSI): 0.428440 - Best Trial: 1 - Best Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.2971145798427403, 'ffn_dropout': 0.294642450983742, 'lr': 2.7743800867557626e-05, 'weight_decay': 0.004230079098902941, 'batch_size': 256} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 04:51:34,541] Trial 2 finished with value: 0.5225703811194782 and parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.21625816762576203, 'ffn_dropout': 0.11978634458609289, 'lr': 0.0015697537035869965, 'weight_decay': 0.00021316541587130725, 'batch_size': 128}. Best is trial 2 with value: 0.5225703811194782. - -================================================================================ -Trial 2 완료 - Value (CSI): 0.522570 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.21625816762576203, 'ffn_dropout': 0.11978634458609289, 'lr': 0.0015697537035869965, 'weight_decay': 0.00021316541587130725, 'batch_size': 128} - Best Value (CSI): 0.522570 - Best Trial: 2 - Best Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.21625816762576203, 'ffn_dropout': 0.11978634458609289, 'lr': 0.0015697537035869965, 'weight_decay': 0.00021316541587130725, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 04:55:53,949] Trial 3 finished with value: 0.5559722627339405 and parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.11853427090474081, 'ffn_dropout': 0.311703173134966, 'lr': 0.0007608332786345335, 'weight_decay': 0.0069341697758805, 'batch_size': 128}. Best is trial 3 with value: 0.5559722627339405. - -================================================================================ -Trial 3 완료 - Value (CSI): 0.555972 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.11853427090474081, 'ffn_dropout': 0.311703173134966, 'lr': 0.0007608332786345335, 'weight_decay': 0.0069341697758805, 'batch_size': 128} - Best Value (CSI): 0.555972 - Best Trial: 3 - Best Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.11853427090474081, 'ffn_dropout': 0.311703173134966, 'lr': 0.0007608332786345335, 'weight_decay': 0.0069341697758805, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 05:10:21,196] Trial 4 finished with value: 0.5582312292430999 and parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1252900892246469, 'ffn_dropout': 0.21889680181862703, 'lr': 0.00016422484766125022, 'weight_decay': 0.06486652525850926, 'batch_size': 32}. Best is trial 4 with value: 0.5582312292430999. - -================================================================================ -Trial 4 완료 - Value (CSI): 0.558231 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1252900892246469, 'ffn_dropout': 0.21889680181862703, 'lr': 0.00016422484766125022, 'weight_decay': 0.06486652525850926, 'batch_size': 32} - Best Value (CSI): 0.558231 - Best Trial: 4 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1252900892246469, 'ffn_dropout': 0.21889680181862703, 'lr': 0.00016422484766125022, 'weight_decay': 0.06486652525850926, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 05:11:12,491] Trial 5 pruned. - -================================================================================ -Trial 5 완료 - Value (CSI): 0.386555 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.34476617335932724, 'ffn_dropout': 0.2649695188597106, 'lr': 0.00022833581461653455, 'weight_decay': 0.0013868451340478152, 'batch_size': 256} - Best Value (CSI): 0.558231 - Best Trial: 4 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1252900892246469, 'ffn_dropout': 0.21889680181862703, 'lr': 0.00016422484766125022, 'weight_decay': 0.06486652525850926, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 05:11:57,224] Trial 6 pruned. - -================================================================================ -Trial 6 완료 - Value (CSI): 0.475424 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.3113443424202794, 'ffn_dropout': 0.34065669725379666, 'lr': 0.0026520458769820135, 'weight_decay': 0.002169850273465297, 'batch_size': 256} - Best Value (CSI): 0.558231 - Best Trial: 4 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1252900892246469, 'ffn_dropout': 0.21889680181862703, 'lr': 0.00016422484766125022, 'weight_decay': 0.06486652525850926, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 05:14:52,952] Trial 7 pruned. - -================================================================================ -Trial 7 완료 - Value (CSI): 0.457215 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2949855905950483, 'ffn_dropout': 0.25396522173604835, 'lr': 0.0004563801961685499, 'weight_decay': 0.0003354640785081885, 'batch_size': 32} - Best Value (CSI): 0.558231 - Best Trial: 4 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1252900892246469, 'ffn_dropout': 0.21889680181862703, 'lr': 0.00016422484766125022, 'weight_decay': 0.06486652525850926, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 05:15:43,944] Trial 8 pruned. - -================================================================================ -Trial 8 완료 - Value (CSI): 0.353226 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.32672083229329896, 'ffn_dropout': 0.3396227511637848, 'lr': 6.525871176676631e-05, 'weight_decay': 0.004323520998985153, 'batch_size': 128} - Best Value (CSI): 0.558231 - Best Trial: 4 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1252900892246469, 'ffn_dropout': 0.21889680181862703, 'lr': 0.00016422484766125022, 'weight_decay': 0.06486652525850926, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 05:17:21,179] Trial 9 pruned. - -================================================================================ -Trial 9 완료 - Value (CSI): 0.332024 - Parameters: {'d_token': 256, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.1537125440702668, 'ffn_dropout': 0.17552289360256784, 'lr': 3.254287192729668e-05, 'weight_decay': 0.022299898199725738, 'batch_size': 64} - Best Value (CSI): 0.558231 - Best Trial: 4 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1252900892246469, 'ffn_dropout': 0.21889680181862703, 'lr': 0.00016422484766125022, 'weight_decay': 0.06486652525850926, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 05:26:16,505] Trial 10 finished with value: 0.43981404481401754 and parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.10049678476923007, 'ffn_dropout': 0.38806735190491165, 'lr': 1.0790110964686756e-05, 'weight_decay': 0.07546346225011095, 'batch_size': 32}. Best is trial 4 with value: 0.5582312292430999. - -================================================================================ -Trial 10 완료 - Value (CSI): 0.439814 - Parameters: {'d_token': 192, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.10049678476923007, 'ffn_dropout': 0.38806735190491165, 'lr': 1.0790110964686756e-05, 'weight_decay': 0.07546346225011095, 'batch_size': 32} - Best Value (CSI): 0.558231 - Best Trial: 4 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1252900892246469, 'ffn_dropout': 0.21889680181862703, 'lr': 0.00016422484766125022, 'weight_decay': 0.06486652525850926, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 05:27:14,276] Trial 11 pruned. - -================================================================================ -Trial 11 완료 - Value (CSI): 0.418780 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.10276663406539158, 'ffn_dropout': 0.20485456849692446, 'lr': 0.00028733321051008925, 'weight_decay': 0.02006106103797667, 'batch_size': 128} - Best Value (CSI): 0.558231 - Best Trial: 4 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1252900892246469, 'ffn_dropout': 0.21889680181862703, 'lr': 0.00016422484766125022, 'weight_decay': 0.06486652525850926, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 05:29:59,088] Trial 12 pruned. - -================================================================================ -Trial 12 완료 - Value (CSI): 0.360478 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.22532988450482666, 'ffn_dropout': 0.21518871928307048, 'lr': 0.0006956104807009871, 'weight_decay': 0.08837824376237668, 'batch_size': 32} - Best Value (CSI): 0.558231 - Best Trial: 4 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1252900892246469, 'ffn_dropout': 0.21889680181862703, 'lr': 0.00016422484766125022, 'weight_decay': 0.06486652525850926, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 05:36:20,676] Trial 13 finished with value: 0.5572770116485796 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.15916677593841122, 'ffn_dropout': 0.2862085192021495, 'lr': 0.00011383966413904215, 'weight_decay': 0.017884308977802375, 'batch_size': 32}. Best is trial 4 with value: 0.5582312292430999. - -================================================================================ -Trial 13 완료 - Value (CSI): 0.557277 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.15916677593841122, 'ffn_dropout': 0.2862085192021495, 'lr': 0.00011383966413904215, 'weight_decay': 0.017884308977802375, 'batch_size': 32} - Best Value (CSI): 0.558231 - Best Trial: 4 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1252900892246469, 'ffn_dropout': 0.21889680181862703, 'lr': 0.00016422484766125022, 'weight_decay': 0.06486652525850926, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 05:38:35,923] Trial 14 pruned. - -================================================================================ -Trial 14 완료 - Value (CSI): 0.439297 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.17488396418605945, 'ffn_dropout': 0.23344036973866344, 'lr': 0.00013997797799289745, 'weight_decay': 0.031538423369213524, 'batch_size': 32} - Best Value (CSI): 0.558231 - Best Trial: 4 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1252900892246469, 'ffn_dropout': 0.21889680181862703, 'lr': 0.00016422484766125022, 'weight_decay': 0.06486652525850926, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 05:40:46,063] Trial 15 pruned. - -================================================================================ -Trial 15 완료 - Value (CSI): 0.457429 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.3762048670393106, 'ffn_dropout': 0.2737106098691968, 'lr': 0.00011903351118449938, 'weight_decay': 0.012557219928246585, 'batch_size': 32} - Best Value (CSI): 0.558231 - Best Trial: 4 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1252900892246469, 'ffn_dropout': 0.21889680181862703, 'lr': 0.00016422484766125022, 'weight_decay': 0.06486652525850926, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 05:45:45,699] Trial 16 pruned. - -================================================================================ -Trial 16 완료 - Value (CSI): 0.452043 - Parameters: {'d_token': 224, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.15111017828776924, 'ffn_dropout': 0.1697342529930378, 'lr': 0.00014090463438264832, 'weight_decay': 0.05199525683196024, 'batch_size': 32} - Best Value (CSI): 0.558231 - Best Trial: 4 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1252900892246469, 'ffn_dropout': 0.21889680181862703, 'lr': 0.00016422484766125022, 'weight_decay': 0.06486652525850926, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 05:47:31,073] Trial 17 pruned. - -================================================================================ -Trial 17 완료 - Value (CSI): 0.388784 - Parameters: {'d_token': 64, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.2002270386208052, 'ffn_dropout': 0.24122020788608434, 'lr': 5.7279962000947914e-05, 'weight_decay': 0.03973594312933733, 'batch_size': 32} - Best Value (CSI): 0.558231 - Best Trial: 4 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1252900892246469, 'ffn_dropout': 0.21889680181862703, 'lr': 0.00016422484766125022, 'weight_decay': 0.06486652525850926, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 05:53:35,616] Trial 18 finished with value: 0.5589080541781382 and parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.25491350496954723, 'ffn_dropout': 0.2840802831515487, 'lr': 0.0002681546741118081, 'weight_decay': 0.012340150271613571, 'batch_size': 32}. Best is trial 18 with value: 0.5589080541781382. - -================================================================================ -Trial 18 완료 - Value (CSI): 0.558908 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.25491350496954723, 'ffn_dropout': 0.2840802831515487, 'lr': 0.0002681546741118081, 'weight_decay': 0.012340150271613571, 'batch_size': 32} - Best Value (CSI): 0.558908 - Best Trial: 18 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.25491350496954723, 'ffn_dropout': 0.2840802831515487, 'lr': 0.0002681546741118081, 'weight_decay': 0.012340150271613571, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 05:54:59,629] Trial 19 pruned. - -================================================================================ -Trial 19 완료 - Value (CSI): 0.465531 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.2571091210032936, 'ffn_dropout': 0.19812013260351238, 'lr': 0.000352155428022985, 'weight_decay': 0.010376275243431897, 'batch_size': 64} - Best Value (CSI): 0.558908 - Best Trial: 18 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.25491350496954723, 'ffn_dropout': 0.2840802831515487, 'lr': 0.0002681546741118081, 'weight_decay': 0.012340150271613571, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 05:58:50,734] Trial 20 pruned. - -================================================================================ -Trial 20 완료 - Value (CSI): 0.482940 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.24822767460525183, 'ffn_dropout': 0.2414696722808476, 'lr': 0.0008206330613921693, 'weight_decay': 0.04448666931918938, 'batch_size': 32} - Best Value (CSI): 0.558908 - Best Trial: 18 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.25491350496954723, 'ffn_dropout': 0.2840802831515487, 'lr': 0.0002681546741118081, 'weight_decay': 0.012340150271613571, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) -[I 2025-12-26 06:03:52,696] Trial 21 pruned. - -================================================================================ -Trial 21 완료 - Value (CSI): 0.560547 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.13425432487457994, 'ffn_dropout': 0.2832458024514293, 'lr': 0.00020192621601288505, 'weight_decay': 0.017475385751380256, 'batch_size': 32} - Best Value (CSI): 0.558908 - Best Trial: 18 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.25491350496954723, 'ffn_dropout': 0.2840802831515487, 'lr': 0.0002681546741118081, 'weight_decay': 0.012340150271613571, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 06:13:10,295] Trial 22 finished with value: 0.5538997909516382 and parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.19031336847949304, 'ffn_dropout': 0.29914122716822283, 'lr': 8.386528876957199e-05, 'weight_decay': 0.09844156790506807, 'batch_size': 32}. Best is trial 18 with value: 0.5589080541781382. - -================================================================================ -Trial 22 완료 - Value (CSI): 0.553900 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.19031336847949304, 'ffn_dropout': 0.29914122716822283, 'lr': 8.386528876957199e-05, 'weight_decay': 0.09844156790506807, 'batch_size': 32} - Best Value (CSI): 0.558908 - Best Trial: 18 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.25491350496954723, 'ffn_dropout': 0.2840802831515487, 'lr': 0.0002681546741118081, 'weight_decay': 0.012340150271613571, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 06:20:51,000] Trial 23 finished with value: 0.557984425765537 and parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.13742681475275587, 'ffn_dropout': 0.26550617685610817, 'lr': 0.00021333202559997727, 'weight_decay': 0.008847371863804887, 'batch_size': 32}. Best is trial 18 with value: 0.5589080541781382. - -================================================================================ -Trial 23 완료 - Value (CSI): 0.557984 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.13742681475275587, 'ffn_dropout': 0.26550617685610817, 'lr': 0.00021333202559997727, 'weight_decay': 0.008847371863804887, 'batch_size': 32} - Best Value (CSI): 0.558908 - Best Trial: 18 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.25491350496954723, 'ffn_dropout': 0.2840802831515487, 'lr': 0.0002681546741118081, 'weight_decay': 0.012340150271613571, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 06:22:46,013] Trial 24 pruned. - -================================================================================ -Trial 24 완료 - Value (CSI): 0.443532 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13202885647435936, 'ffn_dropout': 0.26332091310253297, 'lr': 0.0004367296225453023, 'weight_decay': 0.008044223907887267, 'batch_size': 32} - Best Value (CSI): 0.558908 - Best Trial: 18 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.25491350496954723, 'ffn_dropout': 0.2840802831515487, 'lr': 0.0002681546741118081, 'weight_decay': 0.012340150271613571, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 06:30:58,007] Trial 25 pruned. - -================================================================================ -Trial 25 완료 - Value (CSI): 0.526638 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.18380191217429342, 'ffn_dropout': 0.22761013022093174, 'lr': 0.00019651143582082896, 'weight_decay': 0.029402480972531838, 'batch_size': 32} - Best Value (CSI): 0.558908 - Best Trial: 18 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.25491350496954723, 'ffn_dropout': 0.2840802831515487, 'lr': 0.0002681546741118081, 'weight_decay': 0.012340150271613571, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 06:42:19,312] Trial 26 pruned. - -================================================================================ -Trial 26 완료 - Value (CSI): 0.551038 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.13165908296294712, 'ffn_dropout': 0.2538067928396913, 'lr': 0.0003568638720323078, 'weight_decay': 0.007247399355216826, 'batch_size': 32} - Best Value (CSI): 0.558908 - Best Trial: 18 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.25491350496954723, 'ffn_dropout': 0.2840802831515487, 'lr': 0.0002681546741118081, 'weight_decay': 0.012340150271613571, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 06:43:12,982] Trial 27 pruned. - -================================================================================ -Trial 27 완료 - Value (CSI): 0.449367 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.20552347302812257, 'ffn_dropout': 0.267683438782757, 'lr': 0.0002494887672954075, 'weight_decay': 0.013866475990470587, 'batch_size': 64} - Best Value (CSI): 0.558908 - Best Trial: 18 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.25491350496954723, 'ffn_dropout': 0.2840802831515487, 'lr': 0.0002681546741118081, 'weight_decay': 0.012340150271613571, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 06:43:52,876] Trial 28 pruned. - -================================================================================ -Trial 28 완료 - Value (CSI): 0.467606 - Parameters: {'d_token': 96, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.24412332057344857, 'ffn_dropout': 0.22015027754255817, 'lr': 0.000516707175702527, 'weight_decay': 0.053400000726829946, 'batch_size': 256} - Best Value (CSI): 0.558908 - Best Trial: 18 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.25491350496954723, 'ffn_dropout': 0.2840802831515487, 'lr': 0.0002681546741118081, 'weight_decay': 0.012340150271613571, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 06:45:10,285] Trial 29 pruned. - -================================================================================ -Trial 29 완료 - Value (CSI): 0.444147 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.16892274801099114, 'ffn_dropout': 0.3216132848063601, 'lr': 0.001216375764828957, 'weight_decay': 0.02707157529795893, 'batch_size': 64} - Best Value (CSI): 0.558908 - Best Trial: 18 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.25491350496954723, 'ffn_dropout': 0.2840802831515487, 'lr': 0.0002681546741118081, 'weight_decay': 0.012340150271613571, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 06:47:02,172] Trial 30 pruned. - -================================================================================ -Trial 30 완료 - Value (CSI): 0.000683 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.18465705902587348, 'ffn_dropout': 0.3005424780022715, 'lr': 0.007844134828955313, 'weight_decay': 0.0012886620128377576, 'batch_size': 32} - Best Value (CSI): 0.558908 - Best Trial: 18 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.25491350496954723, 'ffn_dropout': 0.2840802831515487, 'lr': 0.0002681546741118081, 'weight_decay': 0.012340150271613571, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 06:48:39,330] Trial 31 pruned. - -================================================================================ -Trial 31 완료 - Value (CSI): 0.463706 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.151050957762616, 'ffn_dropout': 0.28545951413312814, 'lr': 0.00010606242532533244, 'weight_decay': 0.017911699241124474, 'batch_size': 32} - Best Value (CSI): 0.558908 - Best Trial: 18 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.25491350496954723, 'ffn_dropout': 0.2840802831515487, 'lr': 0.0002681546741118081, 'weight_decay': 0.012340150271613571, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 06:50:24,385] Trial 32 pruned. - -================================================================================ -Trial 32 완료 - Value (CSI): 0.474235 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.1591410219927958, 'ffn_dropout': 0.2806235555673639, 'lr': 0.0001888707395731759, 'weight_decay': 0.0111874920866003, 'batch_size': 32} - Best Value (CSI): 0.558908 - Best Trial: 18 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.25491350496954723, 'ffn_dropout': 0.2840802831515487, 'lr': 0.0002681546741118081, 'weight_decay': 0.012340150271613571, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 06:52:05,591] Trial 33 pruned. - -================================================================================ -Trial 33 완료 - Value (CSI): 0.400859 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.12129565836950536, 'ffn_dropout': 0.24059813536774002, 'lr': 7.615684819995783e-05, 'weight_decay': 0.004697494362548353, 'batch_size': 32} - Best Value (CSI): 0.558908 - Best Trial: 18 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.25491350496954723, 'ffn_dropout': 0.2840802831515487, 'lr': 0.0002681546741118081, 'weight_decay': 0.012340150271613571, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 06:53:24,247] Trial 34 pruned. - -================================================================================ -Trial 34 완료 - Value (CSI): 0.426067 - Parameters: {'d_token': 96, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.14272431632481877, 'ffn_dropout': 0.30668416163627715, 'lr': 0.0001478563857527373, 'weight_decay': 0.02620245567780444, 'batch_size': 32} - Best Value (CSI): 0.558908 - Best Trial: 18 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.25491350496954723, 'ffn_dropout': 0.2840802831515487, 'lr': 0.0002681546741118081, 'weight_decay': 0.012340150271613571, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 06:56:20,320] Trial 35 finished with value: 0.556433945616672 and parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11748441041502432, 'ffn_dropout': 0.2564727048241845, 'lr': 0.000292120524391473, 'weight_decay': 0.01448291496661086, 'batch_size': 128}. Best is trial 18 with value: 0.5589080541781382. - -================================================================================ -Trial 35 완료 - Value (CSI): 0.556434 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11748441041502432, 'ffn_dropout': 0.2564727048241845, 'lr': 0.000292120524391473, 'weight_decay': 0.01448291496661086, 'batch_size': 128} - Best Value (CSI): 0.558908 - Best Trial: 18 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.25491350496954723, 'ffn_dropout': 0.2840802831515487, 'lr': 0.0002681546741118081, 'weight_decay': 0.012340150271613571, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 06:56:49,147] Trial 36 pruned. - -================================================================================ -Trial 36 완료 - Value (CSI): 0.242852 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.16381823375028498, 'ffn_dropout': 0.2918241258101949, 'lr': 4.782270775092767e-05, 'weight_decay': 0.006649588737678475, 'batch_size': 256} - Best Value (CSI): 0.558908 - Best Trial: 18 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.25491350496954723, 'ffn_dropout': 0.2840802831515487, 'lr': 0.0002681546741118081, 'weight_decay': 0.012340150271613571, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 07:00:02,228] Trial 37 pruned. - -================================================================================ -Trial 37 완료 - Value (CSI): 0.480903 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.1706847005555509, 'ffn_dropout': 0.3206472396380816, 'lr': 0.00012196971099112249, 'weight_decay': 0.059300169437347276, 'batch_size': 32} - Best Value (CSI): 0.558908 - Best Trial: 18 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.25491350496954723, 'ffn_dropout': 0.2840802831515487, 'lr': 0.0002681546741118081, 'weight_decay': 0.012340150271613571, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 07:00:20,957] Trial 38 pruned. - -================================================================================ -Trial 38 완료 - Value (CSI): 0.161017 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.27547454679715894, 'ffn_dropout': 0.26888049963285454, 'lr': 9.626509664513916e-05, 'weight_decay': 0.038174256214686945, 'batch_size': 256} - Best Value (CSI): 0.558908 - Best Trial: 18 - Best Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.25491350496954723, 'ffn_dropout': 0.2840802831515487, 'lr': 0.0002681546741118081, 'weight_decay': 0.012340150271613571, 'batch_size': 32} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 07:03:55,801] Trial 39 finished with value: 0.5624926645546813 and parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.11580183737987138, 'ffn_dropout': 0.33625819783295235, 'lr': 0.00017970360665618638, 'weight_decay': 0.0033452951102042527, 'batch_size': 128}. Best is trial 39 with value: 0.5624926645546813. - -================================================================================ -Trial 39 완료 - Value (CSI): 0.562493 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.11580183737987138, 'ffn_dropout': 0.33625819783295235, 'lr': 0.00017970360665618638, 'weight_decay': 0.0033452951102042527, 'batch_size': 128} - Best Value (CSI): 0.562493 - Best Trial: 39 - Best Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.11580183737987138, 'ffn_dropout': 0.33625819783295235, 'lr': 0.00017970360665618638, 'weight_decay': 0.0033452951102042527, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 07:06:52,144] Trial 40 pruned. - -================================================================================ -Trial 40 완료 - Value (CSI): 0.538526 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.11206939474131507, 'ffn_dropout': 0.3348633073716394, 'lr': 0.00023164557010490794, 'weight_decay': 0.0027719583469081794, 'batch_size': 128} - Best Value (CSI): 0.562493 - Best Trial: 39 - Best Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.11580183737987138, 'ffn_dropout': 0.33625819783295235, 'lr': 0.00017970360665618638, 'weight_decay': 0.0033452951102042527, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) -[I 2025-12-26 07:08:58,558] Trial 41 pruned. - -================================================================================ -Trial 41 완료 - Value (CSI): 0.568144 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1368240492713909, 'ffn_dropout': 0.3501170442480443, 'lr': 0.00017674197331864227, 'weight_decay': 0.005941344609698836, 'batch_size': 128} - Best Value (CSI): 0.562493 - Best Trial: 39 - Best Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.11580183737987138, 'ffn_dropout': 0.33625819783295235, 'lr': 0.00017970360665618638, 'weight_decay': 0.0033452951102042527, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 07:12:35,656] Trial 42 finished with value: 0.560158118123303 and parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.12225070497470589, 'ffn_dropout': 0.2935806986131965, 'lr': 0.00026754166060578263, 'weight_decay': 0.00891119192369517, 'batch_size': 128}. Best is trial 39 with value: 0.5624926645546813. - -================================================================================ -Trial 42 완료 - Value (CSI): 0.560158 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.12225070497470589, 'ffn_dropout': 0.2935806986131965, 'lr': 0.00026754166060578263, 'weight_decay': 0.00891119192369517, 'batch_size': 128} - Best Value (CSI): 0.562493 - Best Trial: 39 - Best Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.11580183737987138, 'ffn_dropout': 0.33625819783295235, 'lr': 0.00017970360665618638, 'weight_decay': 0.0033452951102042527, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) -[I 2025-12-26 07:15:05,348] Trial 43 pruned. - -================================================================================ -Trial 43 완료 - Value (CSI): 0.573230 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10092530700498725, 'ffn_dropout': 0.31049522346380426, 'lr': 0.0003022926173915944, 'weight_decay': 0.0030088351972531635, 'batch_size': 128} - Best Value (CSI): 0.562493 - Best Trial: 39 - Best Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.11580183737987138, 'ffn_dropout': 0.33625819783295235, 'lr': 0.00017970360665618638, 'weight_decay': 0.0033452951102042527, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 07:18:45,401] Trial 44 finished with value: 0.5636322643892201 and parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.12076140929675035, 'ffn_dropout': 0.3557009918748616, 'lr': 0.0005330325142258028, 'weight_decay': 0.009069279144723356, 'batch_size': 128}. Best is trial 44 with value: 0.5636322643892201. - -================================================================================ -Trial 44 완료 - Value (CSI): 0.563632 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.12076140929675035, 'ffn_dropout': 0.3557009918748616, 'lr': 0.0005330325142258028, 'weight_decay': 0.009069279144723356, 'batch_size': 128} - Best Value (CSI): 0.563632 - Best Trial: 44 - Best Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.12076140929675035, 'ffn_dropout': 0.3557009918748616, 'lr': 0.0005330325142258028, 'weight_decay': 0.009069279144723356, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) -[I 2025-12-26 07:21:43,514] Trial 45 pruned. - -================================================================================ -Trial 45 완료 - Value (CSI): 0.542636 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.11420743517754864, 'ffn_dropout': 0.35433243608831055, 'lr': 0.000492263785766198, 'weight_decay': 0.004864294628969225, 'batch_size': 128} - Best Value (CSI): 0.563632 - Best Trial: 44 - Best Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.12076140929675035, 'ffn_dropout': 0.3557009918748616, 'lr': 0.0005330325142258028, 'weight_decay': 0.009069279144723356, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) -[I 2025-12-26 07:24:02,084] Trial 46 pruned. - -================================================================================ -Trial 46 완료 - Value (CSI): 0.572744 - Parameters: {'d_token': 128, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.12176424161074156, 'ffn_dropout': 0.3349948354892894, 'lr': 0.0005987764164801227, 'weight_decay': 0.009977173987129443, 'batch_size': 128} - Best Value (CSI): 0.563632 - Best Trial: 44 - Best Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.12076140929675035, 'ffn_dropout': 0.3557009918748616, 'lr': 0.0005330325142258028, 'weight_decay': 0.009069279144723356, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 07:27:59,680] Trial 47 finished with value: 0.5675273679868712 and parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128}. Best is trial 47 with value: 0.5675273679868712. - -================================================================================ -Trial 47 완료 - Value (CSI): 0.567527 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 07:28:35,742] Trial 48 pruned. - -================================================================================ -Trial 48 완료 - Value (CSI): 0.486755 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10941350113365345, 'ffn_dropout': 0.3808076529026461, 'lr': 0.0007604109787544506, 'weight_decay': 0.001701281949741284, 'batch_size': 128} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 07:29:11,649] Trial 49 pruned. - -================================================================================ -Trial 49 완료 - Value (CSI): 0.484493 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.14627870356211692, 'ffn_dropout': 0.3714998960011087, 'lr': 0.0003832688166203088, 'weight_decay': 0.003447000258758838, 'batch_size': 128} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 07:29:37,085] Trial 50 pruned. - -================================================================================ -Trial 50 완료 - Value (CSI): 0.468826 - Parameters: {'d_token': 64, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10118385023446878, 'ffn_dropout': 0.3954874744013941, 'lr': 0.0010002363818656897, 'weight_decay': 0.0010993168808721542, 'batch_size': 128} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 07:30:13,070] Trial 51 pruned. - -================================================================================ -Trial 51 완료 - Value (CSI): 0.482548 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.12183508328105874, 'ffn_dropout': 0.3663671855918084, 'lr': 0.0002984286118670387, 'weight_decay': 0.0023561418986706335, 'batch_size': 128} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) -[I 2025-12-26 07:32:39,068] Trial 52 pruned. - -================================================================================ -Trial 52 완료 - Value (CSI): 0.579782 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.12644771953654546, 'ffn_dropout': 0.36094501550076546, 'lr': 0.0005626318008587873, 'weight_decay': 0.0018864563881669058, 'batch_size': 128} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 07:33:09,476] Trial 53 pruned. - -================================================================================ -Trial 53 완료 - Value (CSI): 0.473810 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.11366893308503163, 'ffn_dropout': 0.381757678203216, 'lr': 0.00040388583517611114, 'weight_decay': 0.004171213303272343, 'batch_size': 128} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 07:33:51,690] Trial 54 pruned. - -================================================================================ -Trial 54 완료 - Value (CSI): 0.483564 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.14968603549384013, 'ffn_dropout': 0.3432098399134266, 'lr': 0.00015444921185456037, 'weight_decay': 0.005895574974935588, 'batch_size': 128} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 07:34:33,421] Trial 55 pruned. - -================================================================================ -Trial 55 완료 - Value (CSI): 0.488196 - Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.1292216294046759, 'ffn_dropout': 0.39953983687651645, 'lr': 0.0002650551462800435, 'weight_decay': 0.021293800021610607, 'batch_size': 128} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) -[I 2025-12-26 07:36:59,527] Trial 56 pruned. - -================================================================================ -Trial 56 완료 - Value (CSI): 0.587440 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1074654847497368, 'ffn_dropout': 0.3288152921530378, 'lr': 0.0006408413481010924, 'weight_decay': 0.0728327640504423, 'batch_size': 128} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 07:37:47,447] Trial 57 pruned. - -================================================================================ -Trial 57 완료 - Value (CSI): 0.462520 - Parameters: {'d_token': 224, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.14521588615982284, 'ffn_dropout': 0.3466339361900702, 'lr': 0.0004297717687119151, 'weight_decay': 0.008349229687656761, 'batch_size': 128} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 07:38:31,482] Trial 58 pruned. - -================================================================================ -Trial 58 완료 - Value (CSI): 0.419536 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10057563806540154, 'ffn_dropout': 0.35797777641088185, 'lr': 0.00017343902243899137, 'weight_decay': 0.013106306937740347, 'batch_size': 64} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 07:39:07,640] Trial 59 pruned. - -================================================================================ -Trial 59 완료 - Value (CSI): 0.463082 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 8, 'attention_dropout': 0.13738710246242358, 'ffn_dropout': 0.32066398241938077, 'lr': 0.0002295729421291729, 'weight_decay': 0.009702153817306878, 'batch_size': 128} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 07:39:56,274] Trial 60 pruned. - -================================================================================ -Trial 60 완료 - Value (CSI): 0.432210 - Parameters: {'d_token': 224, 'n_blocks': 6, 'n_heads': 8, 'attention_dropout': 0.1608341074130449, 'ffn_dropout': 0.3677433359732003, 'lr': 0.0003430394139685012, 'weight_decay': 0.015785700042893286, 'batch_size': 256} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 07:41:15,606] Trial 61 pruned. - -================================================================================ -Trial 61 완료 - Value (CSI): 0.474124 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.1295022528512118, 'ffn_dropout': 0.2941687185217535, 'lr': 0.0002236611066128808, 'weight_decay': 0.008243595567930868, 'batch_size': 32} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 07:41:45,950] Trial 62 pruned. - -================================================================================ -Trial 62 완료 - Value (CSI): 0.465116 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.13895636898704083, 'ffn_dropout': 0.31258770765164035, 'lr': 0.00013324458779655348, 'weight_decay': 0.02263897632421655, 'batch_size': 128} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 07:43:20,540] Trial 63 pruned. - -================================================================================ -Trial 63 완료 - Value (CSI): 0.482385 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.12139289946939415, 'ffn_dropout': 0.2775841183205525, 'lr': 0.0004738619088724872, 'weight_decay': 0.011951245976885452, 'batch_size': 32} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) -[I 2025-12-26 07:46:41,047] Trial 64 pruned. - -================================================================================ -Trial 64 완료 - Value (CSI): 0.580739 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.11670677641944645, 'ffn_dropout': 0.25875051072396443, 'lr': 0.00026468618708351066, 'weight_decay': 0.003788388646117577, 'batch_size': 64} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 07:48:02,709] Trial 65 pruned. - -================================================================================ -Trial 65 완료 - Value (CSI): 0.464371 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.10913134089304281, 'ffn_dropout': 0.2498584969839813, 'lr': 0.00032579146952854145, 'weight_decay': 0.004920741140730303, 'batch_size': 32} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 07:48:39,880] Trial 66 pruned. - -================================================================================ -Trial 66 완료 - Value (CSI): 0.455453 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.15427971524313006, 'ffn_dropout': 0.2750827790264202, 'lr': 0.00017236268013326317, 'weight_decay': 0.006843578392433049, 'batch_size': 128} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 07:51:25,934] Trial 67 pruned. - -================================================================================ -Trial 67 완료 - Value (CSI): 0.472527 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.1298547141802462, 'ffn_dropout': 0.3008547844613563, 'lr': 0.0002077361565892292, 'weight_decay': 0.03579486068983126, 'batch_size': 32} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 07:54:10,512] Trial 68 pruned. - -================================================================================ -Trial 68 완료 - Value (CSI): 0.470978 - Parameters: {'d_token': 128, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13973883205017848, 'ffn_dropout': 0.28870008467242264, 'lr': 0.00012151475777189404, 'weight_decay': 0.018662297821748716, 'batch_size': 32} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 07:54:43,538] Trial 69 pruned. - -================================================================================ -Trial 69 완료 - Value (CSI): 0.295637 - Parameters: {'d_token': 160, 'n_blocks': 6, 'n_heads': 4, 'attention_dropout': 0.17643713606874145, 'ffn_dropout': 0.32855082772183686, 'lr': 8.773615744512145e-05, 'weight_decay': 0.009250613795033088, 'batch_size': 256} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 07:55:15,232] Trial 70 pruned. - -================================================================================ -Trial 70 완료 - Value (CSI): 0.459574 - Parameters: {'d_token': 160, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.22475552638191593, 'ffn_dropout': 0.346357955926274, 'lr': 0.00014843641853427324, 'weight_decay': 0.012442137145564296, 'batch_size': 128} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 07:56:28,292] Trial 71 pruned. - -================================================================================ -Trial 71 완료 - Value (CSI): 0.461184 - Parameters: {'d_token': 256, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.1592986627065734, 'ffn_dropout': 0.2672817037357714, 'lr': 0.00011660028864257202, 'weight_decay': 0.014752096814575046, 'batch_size': 32} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 07:57:36,369] Trial 72 pruned. - -================================================================================ -Trial 72 완료 - Value (CSI): 0.475652 - Parameters: {'d_token': 192, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.12343086569819173, 'ffn_dropout': 0.2881291466114159, 'lr': 0.00010219634546836681, 'weight_decay': 0.02475505677609892, 'batch_size': 32} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 07:58:53,138] Trial 73 pruned. - -================================================================================ -Trial 73 완료 - Value (CSI): 0.479012 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.10978514015914548, 'ffn_dropout': 0.2788031029878565, 'lr': 0.00019485540663805902, 'weight_decay': 0.016182724230456212, 'batch_size': 32} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 08:00:11,270] Trial 74 pruned. - -================================================================================ -Trial 74 완료 - Value (CSI): 0.483165 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.1354826176520879, 'ffn_dropout': 0.2970464048664643, 'lr': 0.00036081955349028655, 'weight_decay': 0.010784526690023074, 'batch_size': 32} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 08:01:27,480] Trial 75 pruned. - -================================================================================ -Trial 75 완료 - Value (CSI): 0.483401 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.14373450788002587, 'ffn_dropout': 0.24636087967638234, 'lr': 7.457079193808878e-05, 'weight_decay': 0.0320392540892686, 'batch_size': 32} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 08:02:09,134] Trial 76 pruned. - -================================================================================ -Trial 76 완료 - Value (CSI): 0.483348 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.15142900083514055, 'ffn_dropout': 0.2601919596512191, 'lr': 0.0002538956207809392, 'weight_decay': 0.007305447302753266, 'batch_size': 64} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 08:04:01,417] Trial 77 pruned. - -================================================================================ -Trial 77 완료 - Value (CSI): 0.469847 - Parameters: {'d_token': 192, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.11663081428185883, 'ffn_dropout': 0.30684883250866046, 'lr': 0.000533929428108255, 'weight_decay': 0.018490539990745226, 'batch_size': 32} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 08:04:48,066] Trial 78 pruned. - -================================================================================ -Trial 78 완료 - Value (CSI): 0.470425 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1294428590631095, 'ffn_dropout': 0.2718004224247295, 'lr': 0.00016366359026890654, 'weight_decay': 0.008465626364797856, 'batch_size': 128} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) - Fold 3 - 클래스별 가중치: {0: 0.9442764227642276, 1: 0.8920583717357911, 2: 1.2195342195342196} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15873}) -[I 2025-12-26 08:13:19,067] Trial 79 pruned. - -================================================================================ -Trial 79 완료 - Value (CSI): 0.535273 - Parameters: {'d_token': 192, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.10050562050678905, 'ffn_dropout': 0.31619062612848553, 'lr': 0.0003017450455988339, 'weight_decay': 0.01096008383042621, 'batch_size': 32} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 08:13:39,221] Trial 80 pruned. - -================================================================================ -Trial 80 완료 - Value (CSI): 0.434454 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.10898248441404615, 'ffn_dropout': 0.23331505811337236, 'lr': 0.00040519827033918697, 'weight_decay': 0.005458751538759343, 'batch_size': 128} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) -[I 2025-12-26 08:15:53,172] Trial 81 pruned. - -================================================================================ -Trial 81 완료 - Value (CSI): 0.574634 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.11887761881971026, 'ffn_dropout': 0.25142969473855525, 'lr': 0.00026907457916991977, 'weight_decay': 0.014899676172530808, 'batch_size': 128} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 08:16:16,897] Trial 82 pruned. - -================================================================================ -Trial 82 완료 - Value (CSI): 0.417317 - Parameters: {'d_token': 224, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.12267563718825111, 'ffn_dropout': 0.2628816906490939, 'lr': 0.00021258598498135573, 'weight_decay': 0.02210986744212482, 'batch_size': 128} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 08:16:58,471] Trial 83 pruned. - -================================================================================ -Trial 83 완료 - Value (CSI): 0.464542 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.11518124465767132, 'ffn_dropout': 0.2821071734086055, 'lr': 0.0003109915716140392, 'weight_decay': 0.01346092959768805, 'batch_size': 128} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 08:17:35,127] Trial 84 pruned. - -================================================================================ -Trial 84 완료 - Value (CSI): 0.442582 - Parameters: {'d_token': 256, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.13993413543377442, 'ffn_dropout': 0.30167069305455413, 'lr': 0.00014124497872665889, 'weight_decay': 0.007158660797733339, 'batch_size': 128} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 08:18:13,072] Trial 85 pruned. - -================================================================================ -Trial 85 완료 - Value (CSI): 0.484202 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10735460626230944, 'ffn_dropout': 0.2704669426176276, 'lr': 0.0004600109000244126, 'weight_decay': 0.042007378096406006, 'batch_size': 128} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 08:19:21,065] Trial 86 pruned. - -================================================================================ -Trial 86 완료 - Value (CSI): 0.470992 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.13167354559922217, 'ffn_dropout': 0.2548108702644709, 'lr': 0.0006790463414972025, 'weight_decay': 0.005926029009911852, 'batch_size': 32} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 08:19:49,032] Trial 87 pruned. - -================================================================================ -Trial 87 완료 - Value (CSI): 0.425532 - Parameters: {'d_token': 224, 'n_blocks': 3, 'n_heads': 8, 'attention_dropout': 0.14648776369909616, 'ffn_dropout': 0.2858057231847173, 'lr': 0.0002467562327513418, 'weight_decay': 0.025948258357794303, 'batch_size': 256} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 08:20:16,267] Trial 88 pruned. - -================================================================================ -Trial 88 완료 - Value (CSI): 0.452672 - Parameters: {'d_token': 128, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.126085073914152, 'ffn_dropout': 0.3504710632226909, 'lr': 0.00018768425963584974, 'weight_decay': 0.009282718208764397, 'batch_size': 128} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 08:20:37,730] Trial 89 pruned. - -================================================================================ -Trial 89 완료 - Value (CSI): 0.458636 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 8, 'attention_dropout': 0.11522942412483318, 'ffn_dropout': 0.33818437061165557, 'lr': 0.00036335541898907563, 'weight_decay': 0.019710593946545188, 'batch_size': 128} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 08:22:13,139] Trial 90 pruned. - -================================================================================ -Trial 90 완료 - Value (CSI): 0.479557 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.16674634146579193, 'ffn_dropout': 0.2434636668206483, 'lr': 0.0005552460087136023, 'weight_decay': 0.0038956875477894354, 'batch_size': 32} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 08:23:40,852] Trial 91 pruned. - -================================================================================ -Trial 91 완료 - Value (CSI): 0.472344 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.13565023427066697, 'ffn_dropout': 0.2927328934981082, 'lr': 0.0008648529537750946, 'weight_decay': 0.01093563246951345, 'batch_size': 128} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) -[I 2025-12-26 08:26:32,743] Trial 92 pruned. - -================================================================================ -Trial 92 완료 - Value (CSI): 0.584834 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.1052943089473327, 'ffn_dropout': 0.31461114611148727, 'lr': 0.00043928883736237933, 'weight_decay': 0.004581947922618611, 'batch_size': 128} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) -[I 2025-12-26 08:29:24,877] Trial 93 pruned. - -================================================================================ -Trial 93 완료 - Value (CSI): 0.567729 - Parameters: {'d_token': 256, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.12544451588071365, 'ffn_dropout': 0.3291986425955673, 'lr': 0.00022361828593185916, 'weight_decay': 0.012581210622794905, 'batch_size': 128} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) - Fold 2 - 클래스별 가중치: {0: 0.9434634146341463, 1: 0.8912903225806451, 2: 1.222334576249763} (클래스별 샘플 수: {0: 20500, 1: 21700, 2: 15823}) -[I 2025-12-26 08:31:43,224] Trial 94 pruned. - -================================================================================ -Trial 94 완료 - Value (CSI): 0.559454 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 4, 'attention_dropout': 0.11423719304064564, 'ffn_dropout': 0.2791250004543338, 'lr': 0.0002904797604294979, 'weight_decay': 0.016595865885934657, 'batch_size': 128} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 08:32:38,759] Trial 95 pruned. - -================================================================================ -Trial 95 완료 - Value (CSI): 0.484333 - Parameters: {'d_token': 160, 'n_blocks': 5, 'n_heads': 4, 'attention_dropout': 0.13344642131481305, 'ffn_dropout': 0.305892682163834, 'lr': 0.00016199629000824292, 'weight_decay': 0.006240636413650678, 'batch_size': 64} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 08:33:20,122] Trial 96 pruned. - -================================================================================ -Trial 96 완료 - Value (CSI): 0.483871 - Parameters: {'d_token': 224, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10009757682561016, 'ffn_dropout': 0.293280782423687, 'lr': 0.0006232383137033992, 'weight_decay': 0.008123225318447719, 'batch_size': 128} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 08:36:18,967] Trial 97 pruned. - -================================================================================ -Trial 97 완료 - Value (CSI): 0.448931 - Parameters: {'d_token': 160, 'n_blocks': 3, 'n_heads': 4, 'attention_dropout': 0.15549397359785894, 'ffn_dropout': 0.2654014265014536, 'lr': 0.00034453476810476666, 'weight_decay': 0.003215402726501743, 'batch_size': 32} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 08:36:56,503] Trial 98 pruned. - -================================================================================ -Trial 98 완료 - Value (CSI): 0.475083 - Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.1198965059408194, 'ffn_dropout': 0.27411460182273667, 'lr': 0.00013211272281279872, 'weight_decay': 0.03134100954934849, 'batch_size': 128} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - Fold 1 - 클래스별 가중치: {0: 0.9443252032520325, 1: 0.8839573820395739, 2: 1.2349238751382154} (클래스별 샘플 수: {0: 20500, 1: 21900, 2: 15676}) -[I 2025-12-26 08:38:03,826] Trial 99 pruned. - -================================================================================ -Trial 99 완료 - Value (CSI): 0.481513 - Parameters: {'d_token': 160, 'n_blocks': 2, 'n_heads': 4, 'attention_dropout': 0.14186306208737332, 'ffn_dropout': 0.21984845218479535, 'lr': 0.0007287434441488795, 'weight_decay': 0.009587787472770745, 'batch_size': 32} - Best Value (CSI): 0.567527 - Best Trial: 47 - Best Parameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} -================================================================================ - - -최적화 완료. -Best CSI Score: 0.5675 -Best Hyperparameters: {'d_token': 192, 'n_blocks': 4, 'n_heads': 8, 'attention_dropout': 0.10255871141670557, 'ffn_dropout': 0.3735851591876593, 'lr': 0.00038893486056538687, 'weight_decay': 0.0020864133600508325, 'batch_size': 128} - -최적화 과정 요약: - - 총 시도 횟수: 100 - - 성공한 시도: 100 - - 최초 CSI: 0.0981 - - 최종 CSI: 0.4815 - - 최고 CSI: 0.5874 - - 최저 CSI: 0.0007 - - 평균 CSI: 0.4694 - -최적화 Study 객체가 /workspace/visibility_prediction/Analysis_code/optimization_history/ft_transformer_smotenc_ctgan20000_seoul_trials.pkl에 저장되었습니다. - -================================================== -최적화된 하이퍼파라미터로 최종 모델 학습 시작 -================================================== -최종 모델 학습 시작... -Fold 1 학습 중... - Early stopping at epoch 24, Best CSI: 0.4959 - Fold 1 학습 완료 (검증 CSI: 0.4959) -Fold 2 학습 중... - Early stopping at epoch 27, Best CSI: 0.5828 - Fold 2 학습 완료 (검증 CSI: 0.5828) -Fold 3 학습 중... - Early stopping at epoch 27, Best CSI: 0.5595 - Fold 3 학습 완료 (검증 CSI: 0.5595) - -모든 모델 저장 완료: ../save_model/ft_transformer_optima/ft_transformer_smotenc_ctgan20000_seoul.pkl (총 3개 fold) -Scaler 저장 완료: ../save_model/ft_transformer_optima/scaler/ft_transformer_smotenc_ctgan20000_seoul_scaler.pkl (총 3개 fold) - -최종 모델 학습 및 저장 완료! -저장된 모델 경로: ../save_model/ft_transformer_optima/ft_transformer_smotenc_ctgan20000_seoul.pkl - -✓ 완료: ft_transformer_smotenc_ctgan20000/ft_transformer_smotenc_ctgan20000_seoul.py (소요 시간: 14369초) - -========================================== -FT-Transformer SMOTENC CTGAN20000 파일 실행 완료 -종료 시간: 2025-12-26 08:42:22 -총 소요 시간: 22시간 4분 7초 -성공: 6개 -실패: 0개 -========================================== diff --git a/Analysis_code/5.optima/run_bash/ft_transformer/run_ft_transformer_ctgan10000.sh b/Analysis_code/5.optima/run_bash/ft_transformer/run_ft_transformer_ctgan10000.sh deleted file mode 100755 index 77c18800d9c1d987af15d0c616b28c458757f795..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/run_bash/ft_transformer/run_ft_transformer_ctgan10000.sh +++ /dev/null @@ -1,80 +0,0 @@ -#!/bin/bash - -# 스크립트 디렉토리로 이동 (상위 디렉토리인 5.optima로 이동) -cd "$(dirname "$0")/../.." - -# 시작 시간 기록 -START_TIME=$(date +%s) -echo "==========================================" -echo "FT-Transformer CTGAN10000 파일 실행 시작" -echo "시작 시간: $(date '+%Y-%m-%d %H:%M:%S')" -echo "GPU: 1번 (CUDA_VISIBLE_DEVICES=1)" -echo "==========================================" -echo "" - -# 실행할 파일 목록 -FILES=( - "ft_transformer_ctgan10000_busan.py" - "ft_transformer_ctgan10000_daegu.py" - "ft_transformer_ctgan10000_daejeon.py" - "ft_transformer_ctgan10000_gwangju.py" - "ft_transformer_ctgan10000_incheon.py" - "ft_transformer_ctgan10000_seoul.py" -) - -# 에러 발생 시 중단 여부 (set -e를 사용하면 에러 발생 시 즉시 중단) -set -e - -# 각 파일 실행 -SUCCESS_COUNT=0 -FAIL_COUNT=0 - -for file in "${FILES[@]}"; do - filepath="ft_transformer_ctgan10000/$file" - if [ ! -f "$filepath" ]; then - echo "⚠️ 경고: $filepath 파일을 찾을 수 없습니다. 건너뜁니다." - FAIL_COUNT=$((FAIL_COUNT + 1)) - continue - fi - - echo "----------------------------------------" - echo "실행 중: $filepath" - echo "시작 시간: $(date '+%Y-%m-%d %H:%M:%S')" - echo "----------------------------------------" - - FILE_START=$(date +%s) - - # Python 스크립트 실행 (GPU 1번 설정, 색상 코드 비활성화) - if NO_COLOR=1 TERM=dumb CUDA_VISIBLE_DEVICES=1 python3 -u "$filepath"; then - FILE_END=$(date +%s) - FILE_DURATION=$((FILE_END - FILE_START)) - echo "" - echo "✓ 완료: $filepath (소요 시간: ${FILE_DURATION}초)" - SUCCESS_COUNT=$((SUCCESS_COUNT + 1)) - else - FILE_END=$(date +%s) - FILE_DURATION=$((FILE_END - FILE_START)) - echo "" - echo "✗ 실패: $filepath (소요 시간: ${FILE_DURATION}초)" - FAIL_COUNT=$((FAIL_COUNT + 1)) - echo "에러 발생으로 인해 스크립트를 중단합니다." - exit 1 - fi - echo "" -done - -# 종료 시간 기록 -END_TIME=$(date +%s) -TOTAL_DURATION=$((END_TIME - START_TIME)) -HOURS=$((TOTAL_DURATION / 3600)) -MINUTES=$(((TOTAL_DURATION % 3600) / 60)) -SECONDS=$((TOTAL_DURATION % 60)) - -echo "==========================================" -echo "FT-Transformer CTGAN10000 파일 실행 완료" -echo "종료 시간: $(date '+%Y-%m-%d %H:%M:%S')" -echo "총 소요 시간: ${HOURS}시간 ${MINUTES}분 ${SECONDS}초" -echo "성공: ${SUCCESS_COUNT}개" -echo "실패: ${FAIL_COUNT}개" -echo "==========================================" - diff --git a/Analysis_code/5.optima/run_bash/ft_transformer/run_ft_transformer_pure.sh b/Analysis_code/5.optima/run_bash/ft_transformer/run_ft_transformer_pure.sh deleted file mode 100755 index af42bee2a5e629906cc8aa40071baad4200410c5..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/run_bash/ft_transformer/run_ft_transformer_pure.sh +++ /dev/null @@ -1,80 +0,0 @@ -#!/bin/bash - -# 스크립트 디렉토리로 이동 (상위 디렉토리인 5.optima로 이동) -cd "$(dirname "$0")/../.." - -# 시작 시간 기록 -START_TIME=$(date +%s) -echo "==========================================" -echo "FT-Transformer Pure 파일 실행 시작" -echo "시작 시간: $(date '+%Y-%m-%d %H:%M:%S')" -echo "GPU: 0번 (CUDA_VISIBLE_DEVICES=0)" -echo "==========================================" -echo "" - -# 실행할 파일 목록 -FILES=( - "ft_transforemer_pure_busan.py" - "ft_transforemer_pure_daegu.py" - "ft_transforemer_pure_daejeon.py" - "ft_transforemer_pure_gwangju.py" - "ft_transforemer_pure_incheon.py" - "ft_transforemer_pure_seoul.py" -) - -# 에러 발생 시 중단 여부 (set -e를 사용하면 에러 발생 시 즉시 중단) -set -e - -# 각 파일 실행 -SUCCESS_COUNT=0 -FAIL_COUNT=0 - -for file in "${FILES[@]}"; do - filepath="ft_transformer_pure/$file" - if [ ! -f "$filepath" ]; then - echo "⚠️ 경고: $filepath 파일을 찾을 수 없습니다. 건너뜁니다." - FAIL_COUNT=$((FAIL_COUNT + 1)) - continue - fi - - echo "----------------------------------------" - echo "실행 중: $filepath" - echo "시작 시간: $(date '+%Y-%m-%d %H:%M:%S')" - echo "----------------------------------------" - - FILE_START=$(date +%s) - - # Python 스크립트 실행 (GPU 0번 설정) - if CUDA_VISIBLE_DEVICES=1 python3 -u "$filepath"; then - FILE_END=$(date +%s) - FILE_DURATION=$((FILE_END - FILE_START)) - echo "" - echo "✓ 완료: $filepath (소요 시간: ${FILE_DURATION}초)" - SUCCESS_COUNT=$((SUCCESS_COUNT + 1)) - else - FILE_END=$(date +%s) - FILE_DURATION=$((FILE_END - FILE_START)) - echo "" - echo "✗ 실패: $filepath (소요 시간: ${FILE_DURATION}초)" - FAIL_COUNT=$((FAIL_COUNT + 1)) - echo "에러 발생으로 인해 스크립트를 중단합니다." - exit 1 - fi - echo "" -done - -# 종료 시간 기록 -END_TIME=$(date +%s) -TOTAL_DURATION=$((END_TIME - START_TIME)) -HOURS=$((TOTAL_DURATION / 3600)) -MINUTES=$(((TOTAL_DURATION % 3600) / 60)) -SECONDS=$((TOTAL_DURATION % 60)) - -echo "==========================================" -echo "FT-Transformer Pure 파일 실행 완료" -echo "종료 시간: $(date '+%Y-%m-%d %H:%M:%S')" -echo "총 소요 시간: ${HOURS}시간 ${MINUTES}분 ${SECONDS}초" -echo "성공: ${SUCCESS_COUNT}개" -echo "실패: ${FAIL_COUNT}개" -echo "==========================================" - diff --git a/Analysis_code/5.optima/run_bash/ft_transformer/run_ft_transformer_smote.sh b/Analysis_code/5.optima/run_bash/ft_transformer/run_ft_transformer_smote.sh deleted file mode 100755 index 523f89a21b5398ba40051cd5b0ca23a61fea0a36..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/run_bash/ft_transformer/run_ft_transformer_smote.sh +++ /dev/null @@ -1,80 +0,0 @@ -#!/bin/bash - -# 스크립트 디렉토리로 이동 (상위 디렉토리인 5.optima로 이동) -cd "$(dirname "$0")/../.." - -# 시작 시간 기록 -START_TIME=$(date +%s) -echo "==========================================" -echo "FT-Transformer SMOTE 파일 실행 시작" -echo "시작 시간: $(date '+%Y-%m-%d %H:%M:%S')" -echo "GPU: 0번 (CUDA_VISIBLE_DEVICES=0)" -echo "==========================================" -echo "" - -# 실행할 파일 목록 -FILES=( - "ft_transformer_smote_busan.py" - "ft_transformer_smote_daegu.py" - "ft_transformer_smote_daejeon.py" - "ft_transformer_smote_gwangju.py" - "ft_transformer_smote_incheon.py" - "ft_transformer_smote_seoul.py" -) - -# 에러 발생 시 중단 여부 (set -e를 사용하면 에러 발생 시 즉시 중단) -set -e - -# 각 파일 실행 -SUCCESS_COUNT=0 -FAIL_COUNT=0 - -for file in "${FILES[@]}"; do - filepath="ft_transformer_smote/$file" - if [ ! -f "$filepath" ]; then - echo "⚠️ 경고: $filepath 파일을 찾을 수 없습니다. 건너뜁니다." - FAIL_COUNT=$((FAIL_COUNT + 1)) - continue - fi - - echo "----------------------------------------" - echo "실행 중: $filepath" - echo "시작 시간: $(date '+%Y-%m-%d %H:%M:%S')" - echo "----------------------------------------" - - FILE_START=$(date +%s) - - # Python 스크립트 실행 (GPU 0번 설정) - if CUDA_VISIBLE_DEVICES=1 python3 -u "$filepath"; then - FILE_END=$(date +%s) - FILE_DURATION=$((FILE_END - FILE_START)) - echo "" - echo "✓ 완료: $filepath (소요 시간: ${FILE_DURATION}초)" - SUCCESS_COUNT=$((SUCCESS_COUNT + 1)) - else - FILE_END=$(date +%s) - FILE_DURATION=$((FILE_END - FILE_START)) - echo "" - echo "✗ 실패: $filepath (소요 시간: ${FILE_DURATION}초)" - FAIL_COUNT=$((FAIL_COUNT + 1)) - echo "에러 발생으로 인해 스크립트를 중단합니다." - exit 1 - fi - echo "" -done - -# 종료 시간 기록 -END_TIME=$(date +%s) -TOTAL_DURATION=$((END_TIME - START_TIME)) -HOURS=$((TOTAL_DURATION / 3600)) -MINUTES=$(((TOTAL_DURATION % 3600) / 60)) -SECONDS=$((TOTAL_DURATION % 60)) - -echo "==========================================" -echo "FT-Transformer SMOTE 파일 실행 완료" -echo "종료 시간: $(date '+%Y-%m-%d %H:%M:%S')" -echo "총 소요 시간: ${HOURS}시간 ${MINUTES}분 ${SECONDS}초" -echo "성공: ${SUCCESS_COUNT}개" -echo "실패: ${FAIL_COUNT}개" -echo "==========================================" - diff --git a/Analysis_code/5.optima/run_bash/ft_transformer/run_ft_transformer_smotenc_ctgan20000.sh b/Analysis_code/5.optima/run_bash/ft_transformer/run_ft_transformer_smotenc_ctgan20000.sh deleted file mode 100755 index 1e99b1d77ead9565e4976959d59285944ffe6259..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/run_bash/ft_transformer/run_ft_transformer_smotenc_ctgan20000.sh +++ /dev/null @@ -1,80 +0,0 @@ -#!/bin/bash - -# 스크립트 디렉토리로 이동 (상위 디렉토리인 5.optima로 이동) -cd "$(dirname "$0")/../.." - -# 시작 시간 기록 -START_TIME=$(date +%s) -echo "==========================================" -echo "FT-Transformer SMOTENC CTGAN20000 파일 실행 시작" -echo "시작 시간: $(date '+%Y-%m-%d %H:%M:%S')" -echo "GPU: 0번 (CUDA_VISIBLE_DEVICES=0)" -echo "==========================================" -echo "" - -# 실행할 파일 목록 -FILES=( - "ft_transformer_smotenc_ctgan20000_busan.py" - "ft_transformer_smotenc_ctgan20000_daegu.py" - "ft_transformer_smotenc_ctgan20000_daejeon.py" - "ft_transformer_smotenc_ctgan20000_gwangju.py" - "ft_transformer_smotenc_ctgan20000_incheon.py" - "ft_transformer_smotenc_ctgan20000_seoul.py" -) - -# 에러 발생 시 중단 여부 (set -e를 사용하면 에러 발생 시 즉시 중단) -set -e - -# 각 파일 실행 -SUCCESS_COUNT=0 -FAIL_COUNT=0 - -for file in "${FILES[@]}"; do - filepath="ft_transformer_smotenc_ctgan20000/$file" - if [ ! -f "$filepath" ]; then - echo "⚠️ 경고: $filepath 파일을 찾을 수 없습니다. 건너뜁니다." - FAIL_COUNT=$((FAIL_COUNT + 1)) - continue - fi - - echo "----------------------------------------" - echo "실행 중: $filepath" - echo "시작 시간: $(date '+%Y-%m-%d %H:%M:%S')" - echo "----------------------------------------" - - FILE_START=$(date +%s) - - # Python 스크립트 실행 (GPU 0번 설정) - if CUDA_VISIBLE_DEVICES=0 python3 -u "$filepath"; then - FILE_END=$(date +%s) - FILE_DURATION=$((FILE_END - FILE_START)) - echo "" - echo "✓ 완료: $filepath (소요 시간: ${FILE_DURATION}초)" - SUCCESS_COUNT=$((SUCCESS_COUNT + 1)) - else - FILE_END=$(date +%s) - FILE_DURATION=$((FILE_END - FILE_START)) - echo "" - echo "✗ 실패: $filepath (소요 시간: ${FILE_DURATION}초)" - FAIL_COUNT=$((FAIL_COUNT + 1)) - echo "에러 발생으로 인해 스크립트를 중단합니다." - exit 1 - fi - echo "" -done - -# 종료 시간 기록 -END_TIME=$(date +%s) -TOTAL_DURATION=$((END_TIME - START_TIME)) -HOURS=$((TOTAL_DURATION / 3600)) -MINUTES=$(((TOTAL_DURATION % 3600) / 60)) -SECONDS=$((TOTAL_DURATION % 60)) - -echo "==========================================" -echo "FT-Transformer SMOTENC CTGAN20000 파일 실행 완료" -echo "종료 시간: $(date '+%Y-%m-%d %H:%M:%S')" -echo "총 소요 시간: ${HOURS}시간 ${MINUTES}분 ${SECONDS}초" -echo "성공: ${SUCCESS_COUNT}개" -echo "실패: ${FAIL_COUNT}개" -echo "==========================================" - diff --git a/Analysis_code/5.optima/run_bash/lgb/lgb_ctgan10000.log b/Analysis_code/5.optima/run_bash/lgb/lgb_ctgan10000.log deleted file mode 100644 index 926dbb169d81b9a297b4255db8cb4453e6f11d0c..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/run_bash/lgb/lgb_ctgan10000.log +++ /dev/null @@ -1,219 +0,0 @@ -nohup: ignoring input -/bin/bash: /opt/conda/lib/libtinfo.so.6: no version information available (required by /bin/bash) -========================================== -LGB CTGAN10000 파일 실행 시작 -시작 시간: 2025-12-28 04:29:39 -GPU: 1번 (CUDA_VISIBLE_DEVICES=1) -========================================== - ----------------------------------------- -실행 중: lgb_ctgan10000/LGB_ctgan10000_busan.py -시작 시간: 2025-12-28 04:29:39 ----------------------------------------- -데이터 로딩 중... -데이터 전처리 중... -하이퍼파라미터 최적화 시작... - 0%| | 0/100 [00:00 pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - -def create_xgb_model(search_space=None, best_params=None): - """XGBoost 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - XGBClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'tree_method': 'hist', - 'device': 'cuda', - 'enable_categorical': True, - 'eval_metric': eval_metric_csi, - 'objective': 'multi:softprob', - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'min_child_weight': int(search_space['min_child_weight']), - 'gamma': search_space['gamma'], - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'min_child_weight': int(best_params['min_child_weight']), - 'gamma': best_params['gamma'], - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return XGBClassifier(**params) - - -# 데이터 로딩 및 전처리 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_busan = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/busan_train.csv")) -df_ctgan_busan_1 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/ctgan10000/ctgan10000_1_busan.csv")) -df_ctgan_busan_2 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/ctgan10000/ctgan10000_2_busan.csv")) -df_ctgan_busan_3 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/ctgan10000/ctgan10000_3_busan.csv")) - -print("데이터 전처리 중...") -df_ctgan_busan_1 = preprocessing(df_ctgan_busan_1) -df_ctgan_busan_2 = preprocessing(df_ctgan_busan_2) -df_ctgan_busan_3 = preprocessing(df_ctgan_busan_3) -df_busan = preprocessing(df_busan) - -# CTGAN 데이터 리스트 (fold 순서와 일치) -df_ctgan_list = [df_ctgan_busan_1, df_ctgan_busan_2, df_ctgan_busan_3] - -def split_data(df_sampled, df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_sampled: 샘플링된 데이터프레임 - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: 샘플링된 데이터에서 train_years에 해당하는 데이터 - train_mask = df_sampled['year'].isin(train_years) - X_train = df_sampled.loc[train_mask, df_sampled.columns != 'multi_class'].copy() - y_train = df_sampled.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - X_train.drop(columns=['year'], inplace=True) - X_val.drop(columns=['year'], inplace=True) - - return X_train, X_val, y_train, y_val - - -# 하이퍼파라미터 검색 공간 정의 -xgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 12, 1), - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'gamma': hp.uniform('gamma', 0, 5), # 트리 분할을 위한 최소 손실 감소 값 - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - xgb_model = create_xgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for df_sampled, (train_years, val_year) in zip(df_ctgan_list, FOLD_CONFIGS): - X_train, X_val, y_train, y_val = split_data( - df_sampled, df_busan, train_years, val_year - ) - - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - csi = calculate_csi(y_val, xgb_model.predict(X_val)) - csi_scores.append(csi) - - return -1*round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -xgb_best = fmin( - fn=objective_func, - space=xgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) - -# 최적화 결과 분석 및 출력 -print(f"\n최적화 완료. 최적 파라미터: {xgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/xgb_ctgan10000_busan_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (df_sampled, (train_years, val_year)) in enumerate( - zip(df_ctgan_list, FOLD_CONFIGS), start=1 -): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_sampled, df_busan, train_years, val_year - ) - - xgb_model = create_xgb_model(best_params=xgb_best) - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, xgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(xgb_model) - - -# 모델 저장 -print("모델 저장 중...") -model_save_path = os.path.join(base_dir, "save_model/xgb_optima/xgb_ctgan10000_busan.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") diff --git a/Analysis_code/5.optima/xgb_ctgan10000/XGB_ctgan10000_daegu.py b/Analysis_code/5.optima/xgb_ctgan10000/XGB_ctgan10000_daegu.py deleted file mode 100644 index 31d6f5cd3d080d960dad7114cc0a649c78082697..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/xgb_ctgan10000/XGB_ctgan10000_daegu.py +++ /dev/null @@ -1,305 +0,0 @@ -import pandas as pd -import os -import numpy as np -import joblib -from xgboost import XGBClassifier -from warnings import filterwarnings -filterwarnings('ignore') -from sklearn.metrics import confusion_matrix -from hyperopt import fmin, tpe, Trials, hp - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(Y_test, pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - Y_test: 실제 레이블 - pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(Y_test, pred) - H = (cm[0, 0] + cm[1, 1]) - F = (cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1]) - M = (cm[0, 2] + cm[1, 2]) - CSI = H / (H + F + M + 1e-10) - return CSI - -def eval_metric_csi(y_true, pred_prob): - """XGBoost용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 - - Returns: - CSI 점수의 음수값 - """ - pred = np.argmax(pred_prob, axis=1) - csi = calculate_csi(y_true, pred) - return -1*csi - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - -def create_xgb_model(search_space=None, best_params=None): - """XGBoost 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - XGBClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'tree_method': 'hist', - 'device': 'cuda', - 'enable_categorical': True, - 'eval_metric': eval_metric_csi, - 'objective': 'multi:softprob', - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'min_child_weight': int(search_space['min_child_weight']), - 'gamma': search_space['gamma'], - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'min_child_weight': int(best_params['min_child_weight']), - 'gamma': best_params['gamma'], - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return XGBClassifier(**params) - - -# 데이터 로딩 및 전처리 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_daegu = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/daegu_train.csv")) -df_ctgan_daegu_1 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/ctgan10000/ctgan10000_1_daegu.csv")) -df_ctgan_daegu_2 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/ctgan10000/ctgan10000_2_daegu.csv")) -df_ctgan_daegu_3 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/ctgan10000/ctgan10000_3_daegu.csv")) - -print("데이터 전처리 중...") -df_ctgan_daegu_1 = preprocessing(df_ctgan_daegu_1) -df_ctgan_daegu_2 = preprocessing(df_ctgan_daegu_2) -df_ctgan_daegu_3 = preprocessing(df_ctgan_daegu_3) -df_daegu = preprocessing(df_daegu) - -# CTGAN 데이터 리스트 (fold 순서와 일치) -df_ctgan_list = [df_ctgan_daegu_1, df_ctgan_daegu_2, df_ctgan_daegu_3] - -def split_data(df_sampled, df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_sampled: 샘플링된 데이터프레임 - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: 샘플링된 데이터에서 train_years에 해당하는 데이터 - train_mask = df_sampled['year'].isin(train_years) - X_train = df_sampled.loc[train_mask, df_sampled.columns != 'multi_class'].copy() - y_train = df_sampled.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - X_train.drop(columns=['year'], inplace=True) - X_val.drop(columns=['year'], inplace=True) - - return X_train, X_val, y_train, y_val - - -# 하이퍼파라미터 검색 공간 정의 -xgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 12, 1), - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'gamma': hp.uniform('gamma', 0, 5), # 트리 분할을 위한 최소 손실 감소 값 - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - xgb_model = create_xgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for df_sampled, (train_years, val_year) in zip(df_ctgan_list, FOLD_CONFIGS): - X_train, X_val, y_train, y_val = split_data( - df_sampled, df_daegu, train_years, val_year - ) - - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - csi = calculate_csi(y_val, xgb_model.predict(X_val)) - csi_scores.append(csi) - - return -1*round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -xgb_best = fmin( - fn=objective_func, - space=xgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) - -# 최적화 결과 분석 및 출력 -print(f"\n최적화 완료. 최적 파라미터: {xgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -# 파일 위치 기반으로 base 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/xgb_ctgan10000_daegu_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (df_sampled, (train_years, val_year)) in enumerate( - zip(df_ctgan_list, FOLD_CONFIGS), start=1 -): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_sampled, df_daegu, train_years, val_year - ) - - xgb_model = create_xgb_model(best_params=xgb_best) - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, xgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(xgb_model) - - -# 모델 저장 -print("모델 저장 중...") -os.makedirs(os.path.join(base_dir, "save_model/xgb_optima"), exist_ok=True) -model_save_path = os.path.join(base_dir, "save_model/xgb_optima/xgb_ctgan10000_daegu.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") - diff --git a/Analysis_code/5.optima/xgb_ctgan10000/XGB_ctgan10000_daejeon.py b/Analysis_code/5.optima/xgb_ctgan10000/XGB_ctgan10000_daejeon.py deleted file mode 100644 index ac858e0ec1435484a07a08dca02a70f3379f4d17..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/xgb_ctgan10000/XGB_ctgan10000_daejeon.py +++ /dev/null @@ -1,305 +0,0 @@ -import pandas as pd -import os -import numpy as np -import joblib -from xgboost import XGBClassifier -from warnings import filterwarnings -filterwarnings('ignore') -from sklearn.metrics import confusion_matrix -from hyperopt import fmin, tpe, Trials, hp - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(Y_test, pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - Y_test: 실제 레이블 - pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(Y_test, pred) - H = (cm[0, 0] + cm[1, 1]) - F = (cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1]) - M = (cm[0, 2] + cm[1, 2]) - CSI = H / (H + F + M + 1e-10) - return CSI - -def eval_metric_csi(y_true, pred_prob): - """XGBoost용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 - - Returns: - CSI 점수의 음수값 - """ - pred = np.argmax(pred_prob, axis=1) - csi = calculate_csi(y_true, pred) - return -1*csi - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - -def create_xgb_model(search_space=None, best_params=None): - """XGBoost 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - XGBClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'tree_method': 'hist', - 'device': 'cuda', - 'enable_categorical': True, - 'eval_metric': eval_metric_csi, - 'objective': 'multi:softprob', - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'min_child_weight': int(search_space['min_child_weight']), - 'gamma': search_space['gamma'], - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'min_child_weight': int(best_params['min_child_weight']), - 'gamma': best_params['gamma'], - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return XGBClassifier(**params) - - -# 데이터 로딩 및 전처리 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_daejeon = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/daejeon_train.csv")) -df_ctgan_daejeon_1 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/ctgan10000/ctgan10000_1_daejeon.csv")) -df_ctgan_daejeon_2 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/ctgan10000/ctgan10000_2_daejeon.csv")) -df_ctgan_daejeon_3 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/ctgan10000/ctgan10000_3_daejeon.csv")) - -print("데이터 전처리 중...") -df_ctgan_daejeon_1 = preprocessing(df_ctgan_daejeon_1) -df_ctgan_daejeon_2 = preprocessing(df_ctgan_daejeon_2) -df_ctgan_daejeon_3 = preprocessing(df_ctgan_daejeon_3) -df_daejeon = preprocessing(df_daejeon) - -# CTGAN 데이터 리스트 (fold 순서와 일치) -df_ctgan_list = [df_ctgan_daejeon_1, df_ctgan_daejeon_2, df_ctgan_daejeon_3] - -def split_data(df_sampled, df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_sampled: 샘플링된 데이터프레임 - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: 샘플링된 데이터에서 train_years에 해당하는 데이터 - train_mask = df_sampled['year'].isin(train_years) - X_train = df_sampled.loc[train_mask, df_sampled.columns != 'multi_class'].copy() - y_train = df_sampled.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - X_train.drop(columns=['year'], inplace=True) - X_val.drop(columns=['year'], inplace=True) - - return X_train, X_val, y_train, y_val - - -# 하이퍼파라미터 검색 공간 정의 -xgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 12, 1), - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'gamma': hp.uniform('gamma', 0, 5), # 트리 분할을 위한 최소 손실 감소 값 - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - xgb_model = create_xgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for df_sampled, (train_years, val_year) in zip(df_ctgan_list, FOLD_CONFIGS): - X_train, X_val, y_train, y_val = split_data( - df_sampled, df_daejeon, train_years, val_year - ) - - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - csi = calculate_csi(y_val, xgb_model.predict(X_val)) - csi_scores.append(csi) - - return -1*round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -xgb_best = fmin( - fn=objective_func, - space=xgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) - -# 최적화 결과 분석 및 출력 -print(f"\n최적화 완료. 최적 파라미터: {xgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -# 파일 위치 기반으로 base 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/xgb_ctgan10000_daejeon_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (df_sampled, (train_years, val_year)) in enumerate( - zip(df_ctgan_list, FOLD_CONFIGS), start=1 -): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_sampled, df_daejeon, train_years, val_year - ) - - xgb_model = create_xgb_model(best_params=xgb_best) - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, xgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(xgb_model) - - -# 모델 저장 -print("모델 저장 중...") -os.makedirs(os.path.join(base_dir, "save_model/xgb_optima"), exist_ok=True) -model_save_path = os.path.join(base_dir, "save_model/xgb_optima/xgb_ctgan10000_daejeon.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") - diff --git a/Analysis_code/5.optima/xgb_ctgan10000/XGB_ctgan10000_gwangju.py b/Analysis_code/5.optima/xgb_ctgan10000/XGB_ctgan10000_gwangju.py deleted file mode 100644 index 6217b2b9fcb4d82e5b6023ca91d1d52e6dffafb5..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/xgb_ctgan10000/XGB_ctgan10000_gwangju.py +++ /dev/null @@ -1,305 +0,0 @@ -import pandas as pd -import os -import numpy as np -import joblib -from xgboost import XGBClassifier -from warnings import filterwarnings -filterwarnings('ignore') -from sklearn.metrics import confusion_matrix -from hyperopt import fmin, tpe, Trials, hp - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(Y_test, pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - Y_test: 실제 레이블 - pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(Y_test, pred) - H = (cm[0, 0] + cm[1, 1]) - F = (cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1]) - M = (cm[0, 2] + cm[1, 2]) - CSI = H / (H + F + M + 1e-10) - return CSI - -def eval_metric_csi(y_true, pred_prob): - """XGBoost용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 - - Returns: - CSI 점수의 음수값 - """ - pred = np.argmax(pred_prob, axis=1) - csi = calculate_csi(y_true, pred) - return -1*csi - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - -def create_xgb_model(search_space=None, best_params=None): - """XGBoost 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - XGBClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'tree_method': 'hist', - 'device': 'cuda', - 'enable_categorical': True, - 'eval_metric': eval_metric_csi, - 'objective': 'multi:softprob', - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'min_child_weight': int(search_space['min_child_weight']), - 'gamma': search_space['gamma'], - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'min_child_weight': int(best_params['min_child_weight']), - 'gamma': best_params['gamma'], - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return XGBClassifier(**params) - - -# 데이터 로딩 및 전처리 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_gwangju = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/gwangju_train.csv")) -df_ctgan_gwangju_1 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/ctgan10000/ctgan10000_1_gwangju.csv")) -df_ctgan_gwangju_2 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/ctgan10000/ctgan10000_2_gwangju.csv")) -df_ctgan_gwangju_3 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/ctgan10000/ctgan10000_3_gwangju.csv")) - -print("데이터 전처리 중...") -df_ctgan_gwangju_1 = preprocessing(df_ctgan_gwangju_1) -df_ctgan_gwangju_2 = preprocessing(df_ctgan_gwangju_2) -df_ctgan_gwangju_3 = preprocessing(df_ctgan_gwangju_3) -df_gwangju = preprocessing(df_gwangju) - -# CTGAN 데이터 리스트 (fold 순서와 일치) -df_ctgan_list = [df_ctgan_gwangju_1, df_ctgan_gwangju_2, df_ctgan_gwangju_3] - -def split_data(df_sampled, df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_sampled: 샘플링된 데이터프레임 - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: 샘플링된 데이터에서 train_years에 해당하는 데이터 - train_mask = df_sampled['year'].isin(train_years) - X_train = df_sampled.loc[train_mask, df_sampled.columns != 'multi_class'].copy() - y_train = df_sampled.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - X_train.drop(columns=['year'], inplace=True) - X_val.drop(columns=['year'], inplace=True) - - return X_train, X_val, y_train, y_val - - -# 하이퍼파라미터 검색 공간 정의 -xgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 12, 1), - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'gamma': hp.uniform('gamma', 0, 5), # 트리 분할을 위한 최소 손실 감소 값 - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - xgb_model = create_xgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for df_sampled, (train_years, val_year) in zip(df_ctgan_list, FOLD_CONFIGS): - X_train, X_val, y_train, y_val = split_data( - df_sampled, df_gwangju, train_years, val_year - ) - - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - csi = calculate_csi(y_val, xgb_model.predict(X_val)) - csi_scores.append(csi) - - return -1*round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -xgb_best = fmin( - fn=objective_func, - space=xgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) - -# 최적화 결과 분석 및 출력 -print(f"\n최적화 완료. 최적 파라미터: {xgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -# 파일 위치 기반으로 base 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/xgb_ctgan10000_gwangju_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (df_sampled, (train_years, val_year)) in enumerate( - zip(df_ctgan_list, FOLD_CONFIGS), start=1 -): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_sampled, df_gwangju, train_years, val_year - ) - - xgb_model = create_xgb_model(best_params=xgb_best) - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, xgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(xgb_model) - - -# 모델 저장 -print("모델 저장 중...") -os.makedirs(os.path.join(base_dir, "save_model/xgb_optima"), exist_ok=True) -model_save_path = os.path.join(base_dir, "save_model/xgb_optima/xgb_ctgan10000_gwangju.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") - diff --git a/Analysis_code/5.optima/xgb_ctgan10000/XGB_ctgan10000_incheon.py b/Analysis_code/5.optima/xgb_ctgan10000/XGB_ctgan10000_incheon.py deleted file mode 100644 index 22426b878fd4d36fbc62413868f66bc26c5cafef..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/xgb_ctgan10000/XGB_ctgan10000_incheon.py +++ /dev/null @@ -1,305 +0,0 @@ -import pandas as pd -import os -import numpy as np -import joblib -from xgboost import XGBClassifier -from warnings import filterwarnings -filterwarnings('ignore') -from sklearn.metrics import confusion_matrix -from hyperopt import fmin, tpe, Trials, hp - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(Y_test, pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - Y_test: 실제 레이블 - pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(Y_test, pred) - H = (cm[0, 0] + cm[1, 1]) - F = (cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1]) - M = (cm[0, 2] + cm[1, 2]) - CSI = H / (H + F + M + 1e-10) - return CSI - -def eval_metric_csi(y_true, pred_prob): - """XGBoost용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 - - Returns: - CSI 점수의 음수값 - """ - pred = np.argmax(pred_prob, axis=1) - csi = calculate_csi(y_true, pred) - return -1*csi - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - -def create_xgb_model(search_space=None, best_params=None): - """XGBoost 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - XGBClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'tree_method': 'hist', - 'device': 'cuda', - 'enable_categorical': True, - 'eval_metric': eval_metric_csi, - 'objective': 'multi:softprob', - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'min_child_weight': int(search_space['min_child_weight']), - 'gamma': search_space['gamma'], - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'min_child_weight': int(best_params['min_child_weight']), - 'gamma': best_params['gamma'], - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return XGBClassifier(**params) - - -# 데이터 로딩 및 전처리 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_incheon = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/incheon_train.csv")) -df_ctgan_incheon_1 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/ctgan10000/ctgan10000_1_incheon.csv")) -df_ctgan_incheon_2 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/ctgan10000/ctgan10000_2_incheon.csv")) -df_ctgan_incheon_3 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/ctgan10000/ctgan10000_3_incheon.csv")) - -print("데이터 전처리 중...") -df_ctgan_incheon_1 = preprocessing(df_ctgan_incheon_1) -df_ctgan_incheon_2 = preprocessing(df_ctgan_incheon_2) -df_ctgan_incheon_3 = preprocessing(df_ctgan_incheon_3) -df_incheon = preprocessing(df_incheon) - -# CTGAN 데이터 리스트 (fold 순서와 일치) -df_ctgan_list = [df_ctgan_incheon_1, df_ctgan_incheon_2, df_ctgan_incheon_3] - -def split_data(df_sampled, df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_sampled: 샘플링된 데이터프레임 - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: 샘플링된 데이터에서 train_years에 해당하는 데이터 - train_mask = df_sampled['year'].isin(train_years) - X_train = df_sampled.loc[train_mask, df_sampled.columns != 'multi_class'].copy() - y_train = df_sampled.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - X_train.drop(columns=['year'], inplace=True) - X_val.drop(columns=['year'], inplace=True) - - return X_train, X_val, y_train, y_val - - -# 하이퍼파라미터 검색 공간 정의 -xgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 12, 1), - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'gamma': hp.uniform('gamma', 0, 5), # 트리 분할을 위한 최소 손실 감소 값 - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - xgb_model = create_xgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for df_sampled, (train_years, val_year) in zip(df_ctgan_list, FOLD_CONFIGS): - X_train, X_val, y_train, y_val = split_data( - df_sampled, df_incheon, train_years, val_year - ) - - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - csi = calculate_csi(y_val, xgb_model.predict(X_val)) - csi_scores.append(csi) - - return -1*round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -xgb_best = fmin( - fn=objective_func, - space=xgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) - -# 최적화 결과 분석 및 출력 -print(f"\n최적화 완료. 최적 파라미터: {xgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -# 파일 위치 기반으로 base 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/xgb_ctgan10000_incheon_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (df_sampled, (train_years, val_year)) in enumerate( - zip(df_ctgan_list, FOLD_CONFIGS), start=1 -): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_sampled, df_incheon, train_years, val_year - ) - - xgb_model = create_xgb_model(best_params=xgb_best) - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, xgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(xgb_model) - - -# 모델 저장 -print("모델 저장 중...") -os.makedirs(os.path.join(base_dir, "save_model/xgb_optima"), exist_ok=True) -model_save_path = os.path.join(base_dir, "save_model/xgb_optima/xgb_ctgan10000_incheon.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") - diff --git a/Analysis_code/5.optima/xgb_ctgan10000/XGB_ctgan10000_seoul.py b/Analysis_code/5.optima/xgb_ctgan10000/XGB_ctgan10000_seoul.py deleted file mode 100644 index 733713bb198b6c4300557945a4186ee7cbb7d650..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/xgb_ctgan10000/XGB_ctgan10000_seoul.py +++ /dev/null @@ -1,305 +0,0 @@ -import pandas as pd -import os -import numpy as np -import joblib -from xgboost import XGBClassifier -from warnings import filterwarnings -filterwarnings('ignore') -from sklearn.metrics import confusion_matrix -from hyperopt import fmin, tpe, Trials, hp - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(Y_test, pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - Y_test: 실제 레이블 - pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(Y_test, pred) - H = (cm[0, 0] + cm[1, 1]) - F = (cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1]) - M = (cm[0, 2] + cm[1, 2]) - CSI = H / (H + F + M + 1e-10) - return CSI - -def eval_metric_csi(y_true, pred_prob): - """XGBoost용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 - - Returns: - CSI 점수의 음수값 - """ - pred = np.argmax(pred_prob, axis=1) - csi = calculate_csi(y_true, pred) - return -1*csi - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - -def create_xgb_model(search_space=None, best_params=None): - """XGBoost 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - XGBClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'tree_method': 'hist', - 'device': 'cuda', - 'enable_categorical': True, - 'eval_metric': eval_metric_csi, - 'objective': 'multi:softprob', - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'min_child_weight': int(search_space['min_child_weight']), - 'gamma': search_space['gamma'], - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'min_child_weight': int(best_params['min_child_weight']), - 'gamma': best_params['gamma'], - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return XGBClassifier(**params) - - -# 데이터 로딩 및 전처리 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_seoul = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/seoul_train.csv")) -df_ctgan_seoul_1 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/ctgan10000/ctgan10000_1_seoul.csv")) -df_ctgan_seoul_2 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/ctgan10000/ctgan10000_2_seoul.csv")) -df_ctgan_seoul_3 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/ctgan10000/ctgan10000_3_seoul.csv")) - -print("데이터 전처리 중...") -df_ctgan_seoul_1 = preprocessing(df_ctgan_seoul_1) -df_ctgan_seoul_2 = preprocessing(df_ctgan_seoul_2) -df_ctgan_seoul_3 = preprocessing(df_ctgan_seoul_3) -df_seoul = preprocessing(df_seoul) - -# CTGAN 데이터 리스트 (fold 순서와 일치) -df_ctgan_list = [df_ctgan_seoul_1, df_ctgan_seoul_2, df_ctgan_seoul_3] - -def split_data(df_sampled, df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_sampled: 샘플링된 데이터프레임 - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: 샘플링된 데이터에서 train_years에 해당하는 데이터 - train_mask = df_sampled['year'].isin(train_years) - X_train = df_sampled.loc[train_mask, df_sampled.columns != 'multi_class'].copy() - y_train = df_sampled.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - X_train.drop(columns=['year'], inplace=True) - X_val.drop(columns=['year'], inplace=True) - - return X_train, X_val, y_train, y_val - - -# 하이퍼파라미터 검색 공간 정의 -xgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 12, 1), - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'gamma': hp.uniform('gamma', 0, 5), # 트리 분할을 위한 최소 손실 감소 값 - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - xgb_model = create_xgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for df_sampled, (train_years, val_year) in zip(df_ctgan_list, FOLD_CONFIGS): - X_train, X_val, y_train, y_val = split_data( - df_sampled, df_seoul, train_years, val_year - ) - - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - csi = calculate_csi(y_val, xgb_model.predict(X_val)) - csi_scores.append(csi) - - return -1*round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -xgb_best = fmin( - fn=objective_func, - space=xgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) - -# 최적화 결과 분석 및 출력 -print(f"\n최적화 완료. 최적 파라미터: {xgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -# 파일 위치 기반으로 base 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/xgb_ctgan10000_seoul_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (df_sampled, (train_years, val_year)) in enumerate( - zip(df_ctgan_list, FOLD_CONFIGS), start=1 -): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_sampled, df_seoul, train_years, val_year - ) - - xgb_model = create_xgb_model(best_params=xgb_best) - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, xgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(xgb_model) - - -# 모델 저장 -print("모델 저장 중...") -os.makedirs(os.path.join(base_dir, "save_model/xgb_optima"), exist_ok=True) -model_save_path = os.path.join(base_dir, "save_model/xgb_optima/xgb_ctgan10000_seoul.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") - diff --git a/Analysis_code/5.optima/xgb_pure/XGB_pure_busan.py b/Analysis_code/5.optima/xgb_pure/XGB_pure_busan.py deleted file mode 100644 index edca037d24da966f2f5d6aa30c046bf116b346c9..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/xgb_pure/XGB_pure_busan.py +++ /dev/null @@ -1,280 +0,0 @@ -import pandas as pd -import os -import numpy as np -import joblib -from xgboost import XGBClassifier -from warnings import filterwarnings -filterwarnings('ignore') -from sklearn.metrics import confusion_matrix -from hyperopt import fmin, tpe, Trials, hp - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(Y_test, pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - Y_test: 실제 레이블 - pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(Y_test, pred) - H = (cm[0, 0] + cm[1, 1]) - F = (cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1]) - M = (cm[0, 2] + cm[1, 2]) - CSI = H / (H + F + M + 1e-10) - return CSI - -def eval_metric_csi(y_true, pred_prob): - """XGBoost용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 - - Returns: - CSI 점수의 음수값 - """ - pred = np.argmax(pred_prob, axis=1) - csi = calculate_csi(y_true, pred) - return -1*csi - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - -def split_data_pure(df_original, train_years, val_year): - """Pure 데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - X_train = df_original.loc[df_original['year'].isin(train_years), df_original.columns != 'multi_class'].copy() - X_val = df_original.loc[df_original['year'] == val_year, df_original.columns != 'multi_class'].copy() - y_train = df_original.loc[df_original['year'].isin(train_years), 'multi_class'] - y_val = df_original.loc[df_original['year'] == val_year, 'multi_class'] - - X_train.drop(columns=['year'], inplace=True) - X_val.drop(columns=['year'], inplace=True) - - return X_train, X_val, y_train, y_val - -def create_xgb_model(search_space=None, best_params=None): - """XGBoost 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - XGBClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'tree_method': 'hist', - 'device': 'cuda', - 'enable_categorical': True, - 'eval_metric': eval_metric_csi, - 'objective': 'multi:softprob', - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'min_child_weight': int(search_space['min_child_weight']), - 'gamma': search_space['gamma'], - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'min_child_weight': int(best_params['min_child_weight']), - 'gamma': best_params['gamma'], - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return XGBClassifier(**params) - -# 데이터 로딩 및 전처리 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_busan = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/busan_train.csv")) -df_busan = preprocessing(df_busan) - -# 하이퍼파라미터 검색 공간 정의 -xgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 12, 1), - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'gamma': hp.uniform('gamma', 0, 5), # 트리 분할을 위한 최소 손실 감소 값 - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - xgb_model = create_xgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for train_years, val_year in FOLD_CONFIGS: - X_train, X_val, y_train, y_val = split_data_pure( - df_busan, train_years, val_year - ) - - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - csi = calculate_csi(y_val, xgb_model.predict(X_val)) - csi_scores.append(csi) - - return -1*round(np.mean(csi_scores), 4) - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -xgb_best = fmin( - fn=objective_func, - space=xgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) - -# 최적화 결과 분석 및 출력 -print(f"\n최적화 완료. 최적 파라미터: {xgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -# 파일 위치 기반으로 base 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/xgb_pure_busan_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (train_years, val_year) in enumerate(FOLD_CONFIGS, start=1): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data_pure( - df_busan, train_years, val_year - ) - - xgb_model = create_xgb_model(best_params=xgb_best) - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, xgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(xgb_model) - -# 모델 저장 -print("모델 저장 중...") -model_save_path = os.path.join(base_dir, "save_model/xgb_optima/xgb_pure_busan.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") diff --git a/Analysis_code/5.optima/xgb_pure/XGB_pure_daegu.py b/Analysis_code/5.optima/xgb_pure/XGB_pure_daegu.py deleted file mode 100644 index 2006c338af3fd690c3f3e327afa673c12395a0db..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/xgb_pure/XGB_pure_daegu.py +++ /dev/null @@ -1,282 +0,0 @@ -import pandas as pd -import os -import numpy as np -import joblib -from xgboost import XGBClassifier -from warnings import filterwarnings -filterwarnings('ignore') -from sklearn.metrics import confusion_matrix -from hyperopt import fmin, tpe, Trials, hp - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(Y_test, pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - Y_test: 실제 레이블 - pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(Y_test, pred) - H = (cm[0, 0] + cm[1, 1]) - F = (cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1]) - M = (cm[0, 2] + cm[1, 2]) - CSI = H / (H + F + M + 1e-10) - return CSI - -def eval_metric_csi(y_true, pred_prob): - """XGBoost용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 - - Returns: - CSI 점수의 음수값 - """ - pred = np.argmax(pred_prob, axis=1) - csi = calculate_csi(y_true, pred) - return -1*csi - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - -def create_xgb_model(search_space=None, best_params=None): - """XGBoost 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - XGBClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'tree_method': 'hist', - 'device': 'cuda', - 'enable_categorical': True, - 'eval_metric': eval_metric_csi, - 'objective': 'multi:softprob', - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'min_child_weight': int(search_space['min_child_weight']), - 'gamma': search_space['gamma'], - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'min_child_weight': int(best_params['min_child_weight']), - 'gamma': best_params['gamma'], - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return XGBClassifier(**params) - - -# 데이터 로딩 및 전처리 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_daegu = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/daegu_train.csv")) -df_daegu = preprocessing(df_daegu) - -def split_data(df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - X_train = df_original.loc[df_original['year'].isin(train_years), df_original.columns != 'multi_class'].copy() - X_val = df_original.loc[df_original['year'] == val_year, df_original.columns != 'multi_class'].copy() - y_train = df_original.loc[df_original['year'].isin(train_years), 'multi_class'] - y_val = df_original.loc[df_original['year'] == val_year, 'multi_class'] - - X_train.drop(columns=['year'], inplace=True) - X_val.drop(columns=['year'], inplace=True) - - return X_train, X_val, y_train, y_val - - -# 하이퍼파라미터 검색 공간 정의 -xgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 12, 1), - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'gamma': hp.uniform('gamma', 0, 5), # 트리 분할을 위한 최소 손실 감소 값 - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - xgb_model = create_xgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for train_years, val_year in FOLD_CONFIGS: - X_train, X_val, y_train, y_val = split_data( - df_daegu, train_years, val_year - ) - - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - csi = calculate_csi(y_val, xgb_model.predict(X_val)) - csi_scores.append(csi) - - return -1*round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -xgb_best = fmin( - fn=objective_func, - space=xgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) - -# 최적화 결과 분석 및 출력 -print(f"\n최적화 완료. 최적 파라미터: {xgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/xgb_pure_daegu_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (train_years, val_year) in enumerate(FOLD_CONFIGS, start=1): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_daegu, train_years, val_year - ) - - xgb_model = create_xgb_model(best_params=xgb_best) - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, xgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(xgb_model) - - -# 모델 저장 -print("모델 저장 중...") -model_save_path = os.path.join(base_dir, "save_model/xgb_optima/xgb_pure_daegu.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") diff --git a/Analysis_code/5.optima/xgb_pure/XGB_pure_daejeon.py b/Analysis_code/5.optima/xgb_pure/XGB_pure_daejeon.py deleted file mode 100644 index c540eef60bb7cc98e68bc2df60750f9cf1fa978a..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/xgb_pure/XGB_pure_daejeon.py +++ /dev/null @@ -1,282 +0,0 @@ -import pandas as pd -import os -import numpy as np -import joblib -from xgboost import XGBClassifier -from warnings import filterwarnings -filterwarnings('ignore') -from sklearn.metrics import confusion_matrix -from hyperopt import fmin, tpe, Trials, hp - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(Y_test, pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - Y_test: 실제 레이블 - pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(Y_test, pred) - H = (cm[0, 0] + cm[1, 1]) - F = (cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1]) - M = (cm[0, 2] + cm[1, 2]) - CSI = H / (H + F + M + 1e-10) - return CSI - -def eval_metric_csi(y_true, pred_prob): - """XGBoost용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 - - Returns: - CSI 점수의 음수값 - """ - pred = np.argmax(pred_prob, axis=1) - csi = calculate_csi(y_true, pred) - return -1*csi - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - -def create_xgb_model(search_space=None, best_params=None): - """XGBoost 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - XGBClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'tree_method': 'hist', - 'device': 'cuda', - 'enable_categorical': True, - 'eval_metric': eval_metric_csi, - 'objective': 'multi:softprob', - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'min_child_weight': int(search_space['min_child_weight']), - 'gamma': search_space['gamma'], - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'min_child_weight': int(best_params['min_child_weight']), - 'gamma': best_params['gamma'], - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return XGBClassifier(**params) - - -# 데이터 로딩 및 전처리 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_daejeon = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/daejeon_train.csv")) -df_daejeon = preprocessing(df_daejeon) - -def split_data(df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - X_train = df_original.loc[df_original['year'].isin(train_years), df_original.columns != 'multi_class'].copy() - X_val = df_original.loc[df_original['year'] == val_year, df_original.columns != 'multi_class'].copy() - y_train = df_original.loc[df_original['year'].isin(train_years), 'multi_class'] - y_val = df_original.loc[df_original['year'] == val_year, 'multi_class'] - - X_train.drop(columns=['year'], inplace=True) - X_val.drop(columns=['year'], inplace=True) - - return X_train, X_val, y_train, y_val - - -# 하이퍼파라미터 검색 공간 정의 -xgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 12, 1), - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'gamma': hp.uniform('gamma', 0, 5), # 트리 분할을 위한 최소 손실 감소 값 - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - xgb_model = create_xgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for train_years, val_year in FOLD_CONFIGS: - X_train, X_val, y_train, y_val = split_data( - df_daejeon, train_years, val_year - ) - - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - csi = calculate_csi(y_val, xgb_model.predict(X_val)) - csi_scores.append(csi) - - return -1*round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -xgb_best = fmin( - fn=objective_func, - space=xgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) - -# 최적화 결과 분석 및 출력 -print(f"\n최적화 완료. 최적 파라미터: {xgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/xgb_pure_daejeon_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (train_years, val_year) in enumerate(FOLD_CONFIGS, start=1): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_daejeon, train_years, val_year - ) - - xgb_model = create_xgb_model(best_params=xgb_best) - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, xgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(xgb_model) - - -# 모델 저장 -print("모델 저장 중...") -model_save_path = os.path.join(base_dir, "save_model/xgb_optima/xgb_pure_daejeon.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") diff --git a/Analysis_code/5.optima/xgb_pure/XGB_pure_gwangju.py b/Analysis_code/5.optima/xgb_pure/XGB_pure_gwangju.py deleted file mode 100644 index 6f41b8ad9471eed5822c6c7a5e6646ec787e1dbd..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/xgb_pure/XGB_pure_gwangju.py +++ /dev/null @@ -1,282 +0,0 @@ -import pandas as pd -import os -import numpy as np -import joblib -from xgboost import XGBClassifier -from warnings import filterwarnings -filterwarnings('ignore') -from sklearn.metrics import confusion_matrix -from hyperopt import fmin, tpe, Trials, hp - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(Y_test, pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - Y_test: 실제 레이블 - pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(Y_test, pred) - H = (cm[0, 0] + cm[1, 1]) - F = (cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1]) - M = (cm[0, 2] + cm[1, 2]) - CSI = H / (H + F + M + 1e-10) - return CSI - -def eval_metric_csi(y_true, pred_prob): - """XGBoost용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 - - Returns: - CSI 점수의 음수값 - """ - pred = np.argmax(pred_prob, axis=1) - csi = calculate_csi(y_true, pred) - return -1*csi - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - -def create_xgb_model(search_space=None, best_params=None): - """XGBoost 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - XGBClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'tree_method': 'hist', - 'device': 'cuda', - 'enable_categorical': True, - 'eval_metric': eval_metric_csi, - 'objective': 'multi:softprob', - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'min_child_weight': int(search_space['min_child_weight']), - 'gamma': search_space['gamma'], - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'min_child_weight': int(best_params['min_child_weight']), - 'gamma': best_params['gamma'], - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return XGBClassifier(**params) - - -# 데이터 로딩 및 전처리 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_gwangju = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/gwangju_train.csv")) -df_gwangju = preprocessing(df_gwangju) - -def split_data(df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - X_train = df_original.loc[df_original['year'].isin(train_years), df_original.columns != 'multi_class'].copy() - X_val = df_original.loc[df_original['year'] == val_year, df_original.columns != 'multi_class'].copy() - y_train = df_original.loc[df_original['year'].isin(train_years), 'multi_class'] - y_val = df_original.loc[df_original['year'] == val_year, 'multi_class'] - - X_train.drop(columns=['year'], inplace=True) - X_val.drop(columns=['year'], inplace=True) - - return X_train, X_val, y_train, y_val - - -# 하이퍼파라미터 검색 공간 정의 -xgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 12, 1), - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'gamma': hp.uniform('gamma', 0, 5), # 트리 분할을 위한 최소 손실 감소 값 - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - xgb_model = create_xgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for train_years, val_year in FOLD_CONFIGS: - X_train, X_val, y_train, y_val = split_data( - df_gwangju, train_years, val_year - ) - - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - csi = calculate_csi(y_val, xgb_model.predict(X_val)) - csi_scores.append(csi) - - return -1*round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -xgb_best = fmin( - fn=objective_func, - space=xgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) - -# 최적화 결과 분석 및 출력 -print(f"\n최적화 완료. 최적 파라미터: {xgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/xgb_pure_gwangju_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (train_years, val_year) in enumerate(FOLD_CONFIGS, start=1): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_gwangju, train_years, val_year - ) - - xgb_model = create_xgb_model(best_params=xgb_best) - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, xgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(xgb_model) - - -# 모델 저장 -print("모델 저장 중...") -model_save_path = os.path.join(base_dir, "save_model/xgb_optima/xgb_pure_gwangju.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") diff --git a/Analysis_code/5.optima/xgb_pure/XGB_pure_incheon.py b/Analysis_code/5.optima/xgb_pure/XGB_pure_incheon.py deleted file mode 100644 index 1267e7c241e70ef4f3ecbc3bac02da6f89e83f15..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/xgb_pure/XGB_pure_incheon.py +++ /dev/null @@ -1,282 +0,0 @@ -import pandas as pd -import os -import numpy as np -import joblib -from xgboost import XGBClassifier -from warnings import filterwarnings -filterwarnings('ignore') -from sklearn.metrics import confusion_matrix -from hyperopt import fmin, tpe, Trials, hp - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(Y_test, pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - Y_test: 실제 레이블 - pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(Y_test, pred) - H = (cm[0, 0] + cm[1, 1]) - F = (cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1]) - M = (cm[0, 2] + cm[1, 2]) - CSI = H / (H + F + M + 1e-10) - return CSI - -def eval_metric_csi(y_true, pred_prob): - """XGBoost용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 - - Returns: - CSI 점수의 음수값 - """ - pred = np.argmax(pred_prob, axis=1) - csi = calculate_csi(y_true, pred) - return -1*csi - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - -def create_xgb_model(search_space=None, best_params=None): - """XGBoost 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - XGBClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'tree_method': 'hist', - 'device': 'cuda', - 'enable_categorical': True, - 'eval_metric': eval_metric_csi, - 'objective': 'multi:softprob', - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'min_child_weight': int(search_space['min_child_weight']), - 'gamma': search_space['gamma'], - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'min_child_weight': int(best_params['min_child_weight']), - 'gamma': best_params['gamma'], - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return XGBClassifier(**params) - - -# 데이터 로딩 및 전처리 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_incheon = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/incheon_train.csv")) -df_incheon = preprocessing(df_incheon) - -def split_data(df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - X_train = df_original.loc[df_original['year'].isin(train_years), df_original.columns != 'multi_class'].copy() - X_val = df_original.loc[df_original['year'] == val_year, df_original.columns != 'multi_class'].copy() - y_train = df_original.loc[df_original['year'].isin(train_years), 'multi_class'] - y_val = df_original.loc[df_original['year'] == val_year, 'multi_class'] - - X_train.drop(columns=['year'], inplace=True) - X_val.drop(columns=['year'], inplace=True) - - return X_train, X_val, y_train, y_val - - -# 하이퍼파라미터 검색 공간 정의 -xgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 12, 1), - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'gamma': hp.uniform('gamma', 0, 5), # 트리 분할을 위한 최소 손실 감소 값 - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - xgb_model = create_xgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for train_years, val_year in FOLD_CONFIGS: - X_train, X_val, y_train, y_val = split_data( - df_incheon, train_years, val_year - ) - - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - csi = calculate_csi(y_val, xgb_model.predict(X_val)) - csi_scores.append(csi) - - return -1*round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -xgb_best = fmin( - fn=objective_func, - space=xgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) - -# 최적화 결과 분석 및 출력 -print(f"\n최적화 완료. 최적 파라미터: {xgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/xgb_pure_incheon_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (train_years, val_year) in enumerate(FOLD_CONFIGS, start=1): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_incheon, train_years, val_year - ) - - xgb_model = create_xgb_model(best_params=xgb_best) - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, xgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(xgb_model) - - -# 모델 저장 -print("모델 저장 중...") -model_save_path = os.path.join(base_dir, "save_model/xgb_optima/xgb_pure_incheon.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") diff --git a/Analysis_code/5.optima/xgb_pure/XGB_pure_seoul.py b/Analysis_code/5.optima/xgb_pure/XGB_pure_seoul.py deleted file mode 100644 index d6f68238970813459dca99d85e0e1ed467aa3737..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/xgb_pure/XGB_pure_seoul.py +++ /dev/null @@ -1,282 +0,0 @@ -import pandas as pd -import os -import numpy as np -import joblib -from xgboost import XGBClassifier -from warnings import filterwarnings -filterwarnings('ignore') -from sklearn.metrics import confusion_matrix -from hyperopt import fmin, tpe, Trials, hp - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(Y_test, pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - Y_test: 실제 레이블 - pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(Y_test, pred) - H = (cm[0, 0] + cm[1, 1]) - F = (cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1]) - M = (cm[0, 2] + cm[1, 2]) - CSI = H / (H + F + M + 1e-10) - return CSI - -def eval_metric_csi(y_true, pred_prob): - """XGBoost용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 - - Returns: - CSI 점수의 음수값 - """ - pred = np.argmax(pred_prob, axis=1) - csi = calculate_csi(y_true, pred) - return -1*csi - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - -def create_xgb_model(search_space=None, best_params=None): - """XGBoost 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - XGBClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'tree_method': 'hist', - 'device': 'cuda', - 'enable_categorical': True, - 'eval_metric': eval_metric_csi, - 'objective': 'multi:softprob', - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'min_child_weight': int(search_space['min_child_weight']), - 'gamma': search_space['gamma'], - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'min_child_weight': int(best_params['min_child_weight']), - 'gamma': best_params['gamma'], - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return XGBClassifier(**params) - - -# 데이터 로딩 및 전처리 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_seoul = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/seoul_train.csv")) -df_seoul = preprocessing(df_seoul) - -def split_data(df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - X_train = df_original.loc[df_original['year'].isin(train_years), df_original.columns != 'multi_class'].copy() - X_val = df_original.loc[df_original['year'] == val_year, df_original.columns != 'multi_class'].copy() - y_train = df_original.loc[df_original['year'].isin(train_years), 'multi_class'] - y_val = df_original.loc[df_original['year'] == val_year, 'multi_class'] - - X_train.drop(columns=['year'], inplace=True) - X_val.drop(columns=['year'], inplace=True) - - return X_train, X_val, y_train, y_val - - -# 하이퍼파라미터 검색 공간 정의 -xgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 12, 1), - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'gamma': hp.uniform('gamma', 0, 5), # 트리 분할을 위한 최소 손실 감소 값 - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - xgb_model = create_xgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for train_years, val_year in FOLD_CONFIGS: - X_train, X_val, y_train, y_val = split_data( - df_seoul, train_years, val_year - ) - - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - csi = calculate_csi(y_val, xgb_model.predict(X_val)) - csi_scores.append(csi) - - return -1*round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -xgb_best = fmin( - fn=objective_func, - space=xgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) - -# 최적화 결과 분석 및 출력 -print(f"\n최적화 완료. 최적 파라미터: {xgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/xgb_pure_seoul_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (train_years, val_year) in enumerate(FOLD_CONFIGS, start=1): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_seoul, train_years, val_year - ) - - xgb_model = create_xgb_model(best_params=xgb_best) - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, xgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(xgb_model) - - -# 모델 저장 -print("모델 저장 중...") -model_save_path = os.path.join(base_dir, "save_model/xgb_optima/xgb_pure_seoul.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") diff --git a/Analysis_code/5.optima/xgb_smote/XGB_smote_busan.py b/Analysis_code/5.optima/xgb_smote/XGB_smote_busan.py deleted file mode 100644 index 7355ddb02871a63b54e4de6aa1cc66a780ab27ff..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/xgb_smote/XGB_smote_busan.py +++ /dev/null @@ -1,301 +0,0 @@ -import pandas as pd -import os -import numpy as np -import joblib -from xgboost import XGBClassifier -from warnings import filterwarnings -filterwarnings('ignore') -from sklearn.metrics import confusion_matrix -from hyperopt import fmin, tpe, Trials, hp - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(Y_test, pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - Y_test: 실제 레이블 - pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(Y_test, pred) - H = (cm[0, 0] + cm[1, 1]) - F = (cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1]) - M = (cm[0, 2] + cm[1, 2]) - CSI = H / (H + F + M + 1e-10) - return CSI - -def eval_metric_csi(y_true, pred_prob): - """XGBoost용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 - - Returns: - CSI 점수의 음수값 - """ - pred = np.argmax(pred_prob, axis=1) - csi = calculate_csi(y_true, pred) - return -1*csi - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - -def create_xgb_model(search_space=None, best_params=None): - """XGBoost 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - XGBClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'tree_method': 'hist', - 'device': 'cuda', - 'enable_categorical': True, - 'eval_metric': eval_metric_csi, - 'objective': 'multi:softprob', - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'min_child_weight': int(search_space['min_child_weight']), - 'gamma': search_space['gamma'], - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'min_child_weight': int(best_params['min_child_weight']), - 'gamma': best_params['gamma'], - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return XGBClassifier(**params) - - -# 데이터 로딩 및 전처리 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_busan = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/busan_train.csv")) -df_smote_busan_1 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smote/smote_1_busan.csv")) -df_smote_busan_2 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smote/smote_2_busan.csv")) -df_smote_busan_3 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smote/smote_3_busan.csv")) - -print("데이터 전처리 중...") -df_smote_busan_1 = preprocessing(df_smote_busan_1) -df_smote_busan_2 = preprocessing(df_smote_busan_2) -df_smote_busan_3 = preprocessing(df_smote_busan_3) -df_busan = preprocessing(df_busan) - -# SMOTE 데이터 리스트 (fold 순서와 일치) -df_smote_list = [df_smote_busan_1, df_smote_busan_2, df_smote_busan_3] - -def split_data(df_sampled, df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_sampled: 샘플링된 데이터프레임 - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: 샘플링된 데이터에서 train_years에 해당하는 데이터 - train_mask = df_sampled['year'].isin(train_years) - X_train = df_sampled.loc[train_mask, df_sampled.columns != 'multi_class'].copy() - y_train = df_sampled.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - X_train.drop(columns=['year'], inplace=True) - X_val.drop(columns=['year'], inplace=True) - - return X_train, X_val, y_train, y_val - - -# 하이퍼파라미터 검색 공간 정의 -xgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 12, 1), - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'gamma': hp.uniform('gamma', 0, 5), # 트리 분할을 위한 최소 손실 감소 값 - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - xgb_model = create_xgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for df_sampled, (train_years, val_year) in zip(df_smote_list, FOLD_CONFIGS): - X_train, X_val, y_train, y_val = split_data( - df_sampled, df_busan, train_years, val_year - ) - - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - csi = calculate_csi(y_val, xgb_model.predict(X_val)) - csi_scores.append(csi) - - return -1*round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -xgb_best = fmin( - fn=objective_func, - space=xgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) - -# 최적화 결과 분석 및 출력 -print(f"\n최적화 완료. 최적 파라미터: {xgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/xgb_smote_busan_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (df_sampled, (train_years, val_year)) in enumerate( - zip(df_smote_list, FOLD_CONFIGS), start=1 -): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_sampled, df_busan, train_years, val_year - ) - - xgb_model = create_xgb_model(best_params=xgb_best) - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, xgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(xgb_model) - - -# 모델 저장 -print("모델 저장 중...") -model_save_path = os.path.join(base_dir, "save_model/xgb_optima/xgb_smote_busan.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") diff --git a/Analysis_code/5.optima/xgb_smote/XGB_smote_daegu.py b/Analysis_code/5.optima/xgb_smote/XGB_smote_daegu.py deleted file mode 100644 index 4c17d3b5ae9a0fb4bfbf1371f70691b5cf299847..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/xgb_smote/XGB_smote_daegu.py +++ /dev/null @@ -1,301 +0,0 @@ -import pandas as pd -import os -import numpy as np -import joblib -from xgboost import XGBClassifier -from warnings import filterwarnings -filterwarnings('ignore') -from sklearn.metrics import confusion_matrix -from hyperopt import fmin, tpe, Trials, hp - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(Y_test, pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - Y_test: 실제 레이블 - pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(Y_test, pred) - H = (cm[0, 0] + cm[1, 1]) - F = (cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1]) - M = (cm[0, 2] + cm[1, 2]) - CSI = H / (H + F + M + 1e-10) - return CSI - -def eval_metric_csi(y_true, pred_prob): - """XGBoost용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 - - Returns: - CSI 점수의 음수값 - """ - pred = np.argmax(pred_prob, axis=1) - csi = calculate_csi(y_true, pred) - return -1*csi - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - -def create_xgb_model(search_space=None, best_params=None): - """XGBoost 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - XGBClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'tree_method': 'hist', - 'device': 'cuda', - 'enable_categorical': True, - 'eval_metric': eval_metric_csi, - 'objective': 'multi:softprob', - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'min_child_weight': int(search_space['min_child_weight']), - 'gamma': search_space['gamma'], - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'min_child_weight': int(best_params['min_child_weight']), - 'gamma': best_params['gamma'], - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return XGBClassifier(**params) - - -# 데이터 로딩 및 전처리 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_daegu = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/daegu_train.csv")) -df_smote_daegu_1 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smote/smote_1_daegu.csv")) -df_smote_daegu_2 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smote/smote_2_daegu.csv")) -df_smote_daegu_3 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smote/smote_3_daegu.csv")) - -print("데이터 전처리 중...") -df_smote_daegu_1 = preprocessing(df_smote_daegu_1) -df_smote_daegu_2 = preprocessing(df_smote_daegu_2) -df_smote_daegu_3 = preprocessing(df_smote_daegu_3) -df_daegu = preprocessing(df_daegu) - -# SMOTE 데이터 리스트 (fold 순서와 일치) -df_smote_list = [df_smote_daegu_1, df_smote_daegu_2, df_smote_daegu_3] - -def split_data(df_sampled, df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_sampled: 샘플링된 데이터프레임 - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: 샘플링된 데이터에서 train_years에 해당하는 데이터 - train_mask = df_sampled['year'].isin(train_years) - X_train = df_sampled.loc[train_mask, df_sampled.columns != 'multi_class'].copy() - y_train = df_sampled.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - X_train.drop(columns=['year'], inplace=True) - X_val.drop(columns=['year'], inplace=True) - - return X_train, X_val, y_train, y_val - - -# 하이퍼파라미터 검색 공간 정의 -xgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 12, 1), - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'gamma': hp.uniform('gamma', 0, 5), # 트리 분할을 위한 최소 손실 감소 값 - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - xgb_model = create_xgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for df_sampled, (train_years, val_year) in zip(df_smote_list, FOLD_CONFIGS): - X_train, X_val, y_train, y_val = split_data( - df_sampled, df_daegu, train_years, val_year - ) - - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - csi = calculate_csi(y_val, xgb_model.predict(X_val)) - csi_scores.append(csi) - - return -1*round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -xgb_best = fmin( - fn=objective_func, - space=xgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) - -# 최적화 결과 분석 및 출력 -print(f"\n최적화 완료. 최적 파라미터: {xgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/xgb_smote_daegu_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (df_sampled, (train_years, val_year)) in enumerate( - zip(df_smote_list, FOLD_CONFIGS), start=1 -): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_sampled, df_daegu, train_years, val_year - ) - - xgb_model = create_xgb_model(best_params=xgb_best) - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, xgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(xgb_model) - - -# 모델 저장 -print("모델 저장 중...") -model_save_path = os.path.join(base_dir, "save_model/xgb_optima/xgb_smote_daegu.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") diff --git a/Analysis_code/5.optima/xgb_smote/XGB_smote_daejeon.py b/Analysis_code/5.optima/xgb_smote/XGB_smote_daejeon.py deleted file mode 100644 index 203a082591da88e69fb63f135cd22d72aa2279e7..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/xgb_smote/XGB_smote_daejeon.py +++ /dev/null @@ -1,301 +0,0 @@ -import pandas as pd -import os -import numpy as np -import joblib -from xgboost import XGBClassifier -from warnings import filterwarnings -filterwarnings('ignore') -from sklearn.metrics import confusion_matrix -from hyperopt import fmin, tpe, Trials, hp - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(Y_test, pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - Y_test: 실제 레이블 - pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(Y_test, pred) - H = (cm[0, 0] + cm[1, 1]) - F = (cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1]) - M = (cm[0, 2] + cm[1, 2]) - CSI = H / (H + F + M + 1e-10) - return CSI - -def eval_metric_csi(y_true, pred_prob): - """XGBoost용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 - - Returns: - CSI 점수의 음수값 - """ - pred = np.argmax(pred_prob, axis=1) - csi = calculate_csi(y_true, pred) - return -1*csi - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - -def create_xgb_model(search_space=None, best_params=None): - """XGBoost 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - XGBClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'tree_method': 'hist', - 'device': 'cuda', - 'enable_categorical': True, - 'eval_metric': eval_metric_csi, - 'objective': 'multi:softprob', - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'min_child_weight': int(search_space['min_child_weight']), - 'gamma': search_space['gamma'], - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'min_child_weight': int(best_params['min_child_weight']), - 'gamma': best_params['gamma'], - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return XGBClassifier(**params) - - -# 데이터 로딩 및 전처리 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_daejeon = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/daejeon_train.csv")) -df_smote_daejeon_1 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smote/smote_1_daejeon.csv")) -df_smote_daejeon_2 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smote/smote_2_daejeon.csv")) -df_smote_daejeon_3 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smote/smote_3_daejeon.csv")) - -print("데이터 전처리 중...") -df_smote_daejeon_1 = preprocessing(df_smote_daejeon_1) -df_smote_daejeon_2 = preprocessing(df_smote_daejeon_2) -df_smote_daejeon_3 = preprocessing(df_smote_daejeon_3) -df_daejeon = preprocessing(df_daejeon) - -# SMOTE 데이터 리스트 (fold 순서와 일치) -df_smote_list = [df_smote_daejeon_1, df_smote_daejeon_2, df_smote_daejeon_3] - -def split_data(df_sampled, df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_sampled: 샘플링된 데이터프레임 - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: 샘플링된 데이터에서 train_years에 해당하는 데이터 - train_mask = df_sampled['year'].isin(train_years) - X_train = df_sampled.loc[train_mask, df_sampled.columns != 'multi_class'].copy() - y_train = df_sampled.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - X_train.drop(columns=['year'], inplace=True) - X_val.drop(columns=['year'], inplace=True) - - return X_train, X_val, y_train, y_val - - -# 하이퍼파라미터 검색 공간 정의 -xgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 12, 1), - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'gamma': hp.uniform('gamma', 0, 5), # 트리 분할을 위한 최소 손실 감소 값 - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - xgb_model = create_xgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for df_sampled, (train_years, val_year) in zip(df_smote_list, FOLD_CONFIGS): - X_train, X_val, y_train, y_val = split_data( - df_sampled, df_daejeon, train_years, val_year - ) - - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - csi = calculate_csi(y_val, xgb_model.predict(X_val)) - csi_scores.append(csi) - - return -1*round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -xgb_best = fmin( - fn=objective_func, - space=xgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) - -# 최적화 결과 분석 및 출력 -print(f"\n최적화 완료. 최적 파라미터: {xgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/xgb_smote_daejeon_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (df_sampled, (train_years, val_year)) in enumerate( - zip(df_smote_list, FOLD_CONFIGS), start=1 -): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_sampled, df_daejeon, train_years, val_year - ) - - xgb_model = create_xgb_model(best_params=xgb_best) - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, xgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(xgb_model) - - -# 모델 저장 -print("모델 저장 중...") -model_save_path = os.path.join(base_dir, "save_model/xgb_optima/xgb_smote_daejeon.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") diff --git a/Analysis_code/5.optima/xgb_smote/XGB_smote_gwangju.py b/Analysis_code/5.optima/xgb_smote/XGB_smote_gwangju.py deleted file mode 100644 index 84044646011ad663e617076a65aaeb06904b6a28..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/xgb_smote/XGB_smote_gwangju.py +++ /dev/null @@ -1,301 +0,0 @@ -import pandas as pd -import os -import numpy as np -import joblib -from xgboost import XGBClassifier -from warnings import filterwarnings -filterwarnings('ignore') -from sklearn.metrics import confusion_matrix -from hyperopt import fmin, tpe, Trials, hp - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(Y_test, pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - Y_test: 실제 레이블 - pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(Y_test, pred) - H = (cm[0, 0] + cm[1, 1]) - F = (cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1]) - M = (cm[0, 2] + cm[1, 2]) - CSI = H / (H + F + M + 1e-10) - return CSI - -def eval_metric_csi(y_true, pred_prob): - """XGBoost용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 - - Returns: - CSI 점수의 음수값 - """ - pred = np.argmax(pred_prob, axis=1) - csi = calculate_csi(y_true, pred) - return -1*csi - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - -def create_xgb_model(search_space=None, best_params=None): - """XGBoost 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - XGBClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'tree_method': 'hist', - 'device': 'cuda', - 'enable_categorical': True, - 'eval_metric': eval_metric_csi, - 'objective': 'multi:softprob', - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'min_child_weight': int(search_space['min_child_weight']), - 'gamma': search_space['gamma'], - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'min_child_weight': int(best_params['min_child_weight']), - 'gamma': best_params['gamma'], - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return XGBClassifier(**params) - - -# 데이터 로딩 및 전처리 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_gwangju = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/gwangju_train.csv")) -df_smote_gwangju_1 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smote/smote_1_gwangju.csv")) -df_smote_gwangju_2 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smote/smote_2_gwangju.csv")) -df_smote_gwangju_3 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smote/smote_3_gwangju.csv")) - -print("데이터 전처리 중...") -df_smote_gwangju_1 = preprocessing(df_smote_gwangju_1) -df_smote_gwangju_2 = preprocessing(df_smote_gwangju_2) -df_smote_gwangju_3 = preprocessing(df_smote_gwangju_3) -df_gwangju = preprocessing(df_gwangju) - -# SMOTE 데이터 리스트 (fold 순서와 일치) -df_smote_list = [df_smote_gwangju_1, df_smote_gwangju_2, df_smote_gwangju_3] - -def split_data(df_sampled, df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_sampled: 샘플링된 데이터프레임 - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: 샘플링된 데이터에서 train_years에 해당하는 데이터 - train_mask = df_sampled['year'].isin(train_years) - X_train = df_sampled.loc[train_mask, df_sampled.columns != 'multi_class'].copy() - y_train = df_sampled.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - X_train.drop(columns=['year'], inplace=True) - X_val.drop(columns=['year'], inplace=True) - - return X_train, X_val, y_train, y_val - - -# 하이퍼파라미터 검색 공간 정의 -xgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 12, 1), - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'gamma': hp.uniform('gamma', 0, 5), # 트리 분할을 위한 최소 손실 감소 값 - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - xgb_model = create_xgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for df_sampled, (train_years, val_year) in zip(df_smote_list, FOLD_CONFIGS): - X_train, X_val, y_train, y_val = split_data( - df_sampled, df_gwangju, train_years, val_year - ) - - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - csi = calculate_csi(y_val, xgb_model.predict(X_val)) - csi_scores.append(csi) - - return -1*round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -xgb_best = fmin( - fn=objective_func, - space=xgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) - -# 최적화 결과 분석 및 출력 -print(f"\n최적화 완료. 최적 파라미터: {xgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/xgb_smote_gwangju_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (df_sampled, (train_years, val_year)) in enumerate( - zip(df_smote_list, FOLD_CONFIGS), start=1 -): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_sampled, df_gwangju, train_years, val_year - ) - - xgb_model = create_xgb_model(best_params=xgb_best) - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, xgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(xgb_model) - - -# 모델 저장 -print("모델 저장 중...") -model_save_path = os.path.join(base_dir, "save_model/xgb_optima/xgb_smote_gwangju.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") diff --git a/Analysis_code/5.optima/xgb_smote/XGB_smote_incheon.py b/Analysis_code/5.optima/xgb_smote/XGB_smote_incheon.py deleted file mode 100644 index 6e16e7476aad6ebc4bfcb537bae352d391985d5a..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/xgb_smote/XGB_smote_incheon.py +++ /dev/null @@ -1,301 +0,0 @@ -import pandas as pd -import os -import numpy as np -import joblib -from xgboost import XGBClassifier -from warnings import filterwarnings -filterwarnings('ignore') -from sklearn.metrics import confusion_matrix -from hyperopt import fmin, tpe, Trials, hp - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(Y_test, pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - Y_test: 실제 레이블 - pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(Y_test, pred) - H = (cm[0, 0] + cm[1, 1]) - F = (cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1]) - M = (cm[0, 2] + cm[1, 2]) - CSI = H / (H + F + M + 1e-10) - return CSI - -def eval_metric_csi(y_true, pred_prob): - """XGBoost용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 - - Returns: - CSI 점수의 음수값 - """ - pred = np.argmax(pred_prob, axis=1) - csi = calculate_csi(y_true, pred) - return -1*csi - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - -def create_xgb_model(search_space=None, best_params=None): - """XGBoost 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - XGBClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'tree_method': 'hist', - 'device': 'cuda', - 'enable_categorical': True, - 'eval_metric': eval_metric_csi, - 'objective': 'multi:softprob', - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'min_child_weight': int(search_space['min_child_weight']), - 'gamma': search_space['gamma'], - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'min_child_weight': int(best_params['min_child_weight']), - 'gamma': best_params['gamma'], - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return XGBClassifier(**params) - - -# 데이터 로딩 및 전처리 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_incheon = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/incheon_train.csv")) -df_smote_incheon_1 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smote/smote_1_incheon.csv")) -df_smote_incheon_2 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smote/smote_2_incheon.csv")) -df_smote_incheon_3 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smote/smote_3_incheon.csv")) - -print("데이터 전처리 중...") -df_smote_incheon_1 = preprocessing(df_smote_incheon_1) -df_smote_incheon_2 = preprocessing(df_smote_incheon_2) -df_smote_incheon_3 = preprocessing(df_smote_incheon_3) -df_incheon = preprocessing(df_incheon) - -# SMOTE 데이터 리스트 (fold 순서와 일치) -df_smote_list = [df_smote_incheon_1, df_smote_incheon_2, df_smote_incheon_3] - -def split_data(df_sampled, df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_sampled: 샘플링된 데이터프레임 - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: 샘플링된 데이터에서 train_years에 해당하는 데이터 - train_mask = df_sampled['year'].isin(train_years) - X_train = df_sampled.loc[train_mask, df_sampled.columns != 'multi_class'].copy() - y_train = df_sampled.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - X_train.drop(columns=['year'], inplace=True) - X_val.drop(columns=['year'], inplace=True) - - return X_train, X_val, y_train, y_val - - -# 하이퍼파라미터 검색 공간 정의 -xgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 12, 1), - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'gamma': hp.uniform('gamma', 0, 5), # 트리 분할을 위한 최소 손실 감소 값 - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - xgb_model = create_xgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for df_sampled, (train_years, val_year) in zip(df_smote_list, FOLD_CONFIGS): - X_train, X_val, y_train, y_val = split_data( - df_sampled, df_incheon, train_years, val_year - ) - - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - csi = calculate_csi(y_val, xgb_model.predict(X_val)) - csi_scores.append(csi) - - return -1*round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -xgb_best = fmin( - fn=objective_func, - space=xgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) - -# 최적화 결과 분석 및 출력 -print(f"\n최적화 완료. 최적 파라미터: {xgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/xgb_smote_incheon_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (df_sampled, (train_years, val_year)) in enumerate( - zip(df_smote_list, FOLD_CONFIGS), start=1 -): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_sampled, df_incheon, train_years, val_year - ) - - xgb_model = create_xgb_model(best_params=xgb_best) - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, xgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(xgb_model) - - -# 모델 저장 -print("모델 저장 중...") -model_save_path = os.path.join(base_dir, "save_model/xgb_optima/xgb_smote_incheon.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") diff --git a/Analysis_code/5.optima/xgb_smote/XGB_smote_seoul.py b/Analysis_code/5.optima/xgb_smote/XGB_smote_seoul.py deleted file mode 100644 index 6225566b6c0c26d3b5dcb7b4a989e402faa5eedc..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/xgb_smote/XGB_smote_seoul.py +++ /dev/null @@ -1,301 +0,0 @@ -import pandas as pd -import os -import numpy as np -import joblib -from xgboost import XGBClassifier -from warnings import filterwarnings -filterwarnings('ignore') -from sklearn.metrics import confusion_matrix -from hyperopt import fmin, tpe, Trials, hp - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(Y_test, pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - Y_test: 실제 레이블 - pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(Y_test, pred) - H = (cm[0, 0] + cm[1, 1]) - F = (cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1]) - M = (cm[0, 2] + cm[1, 2]) - CSI = H / (H + F + M + 1e-10) - return CSI - -def eval_metric_csi(y_true, pred_prob): - """XGBoost용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 - - Returns: - CSI 점수의 음수값 - """ - pred = np.argmax(pred_prob, axis=1) - csi = calculate_csi(y_true, pred) - return -1*csi - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - -def create_xgb_model(search_space=None, best_params=None): - """XGBoost 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - XGBClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'tree_method': 'hist', - 'device': 'cuda', - 'enable_categorical': True, - 'eval_metric': eval_metric_csi, - 'objective': 'multi:softprob', - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'min_child_weight': int(search_space['min_child_weight']), - 'gamma': search_space['gamma'], - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'min_child_weight': int(best_params['min_child_weight']), - 'gamma': best_params['gamma'], - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return XGBClassifier(**params) - - -# 데이터 로딩 및 전처리 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_seoul = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/seoul_train.csv")) -df_smote_seoul_1 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smote/smote_1_seoul.csv")) -df_smote_seoul_2 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smote/smote_2_seoul.csv")) -df_smote_seoul_3 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smote/smote_3_seoul.csv")) - -print("데이터 전처리 중...") -df_smote_seoul_1 = preprocessing(df_smote_seoul_1) -df_smote_seoul_2 = preprocessing(df_smote_seoul_2) -df_smote_seoul_3 = preprocessing(df_smote_seoul_3) -df_seoul = preprocessing(df_seoul) - -# SMOTE 데이터 리스트 (fold 순서와 일치) -df_smote_list = [df_smote_seoul_1, df_smote_seoul_2, df_smote_seoul_3] - -def split_data(df_sampled, df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_sampled: 샘플링된 데이터프레임 - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: 샘플링된 데이터에서 train_years에 해당하는 데이터 - train_mask = df_sampled['year'].isin(train_years) - X_train = df_sampled.loc[train_mask, df_sampled.columns != 'multi_class'].copy() - y_train = df_sampled.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - X_train.drop(columns=['year'], inplace=True) - X_val.drop(columns=['year'], inplace=True) - - return X_train, X_val, y_train, y_val - - -# 하이퍼파라미터 검색 공간 정의 -xgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 12, 1), - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'gamma': hp.uniform('gamma', 0, 5), # 트리 분할을 위한 최소 손실 감소 값 - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - xgb_model = create_xgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for df_sampled, (train_years, val_year) in zip(df_smote_list, FOLD_CONFIGS): - X_train, X_val, y_train, y_val = split_data( - df_sampled, df_seoul, train_years, val_year - ) - - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - csi = calculate_csi(y_val, xgb_model.predict(X_val)) - csi_scores.append(csi) - - return -1*round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -xgb_best = fmin( - fn=objective_func, - space=xgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) - -# 최적화 결과 분석 및 출력 -print(f"\n최적화 완료. 최적 파라미터: {xgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/xgb_smote_seoul_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (df_sampled, (train_years, val_year)) in enumerate( - zip(df_smote_list, FOLD_CONFIGS), start=1 -): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_sampled, df_seoul, train_years, val_year - ) - - xgb_model = create_xgb_model(best_params=xgb_best) - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, xgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(xgb_model) - - -# 모델 저장 -print("모델 저장 중...") -model_save_path = os.path.join(base_dir, "save_model/xgb_optima/xgb_smote_seoul.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") diff --git a/Analysis_code/5.optima/xgb_smotenc_ctgan20000/XGB_smotenc_ctgan20000_busan.py b/Analysis_code/5.optima/xgb_smotenc_ctgan20000/XGB_smotenc_ctgan20000_busan.py deleted file mode 100644 index ceaf301a690d9034b0d016c5a89844cd438ab001..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/xgb_smotenc_ctgan20000/XGB_smotenc_ctgan20000_busan.py +++ /dev/null @@ -1,304 +0,0 @@ -import pandas as pd -import os -import numpy as np -import joblib -from xgboost import XGBClassifier -from warnings import filterwarnings -filterwarnings('ignore') -from sklearn.metrics import confusion_matrix -from hyperopt import fmin, tpe, Trials, hp - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(Y_test, pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - Y_test: 실제 레이블 - pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(Y_test, pred) - H = (cm[0, 0] + cm[1, 1]) - F = (cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1]) - M = (cm[0, 2] + cm[1, 2]) - CSI = H / (H + F + M + 1e-10) - return CSI - -def eval_metric_csi(y_true, pred_prob): - """XGBoost용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 - - Returns: - CSI 점수의 음수값 - """ - pred = np.argmax(pred_prob, axis=1) - csi = calculate_csi(y_true, pred) - return -1*csi - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - -def create_xgb_model(search_space=None, best_params=None): - """XGBoost 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - XGBClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'tree_method': 'hist', - 'device': 'cuda', - 'enable_categorical': True, - 'eval_metric': eval_metric_csi, - 'objective': 'multi:softprob', - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'min_child_weight': int(search_space['min_child_weight']), - 'gamma': search_space['gamma'], - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'min_child_weight': int(best_params['min_child_weight']), - 'gamma': best_params['gamma'], - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return XGBClassifier(**params) - - -# 데이터 로딩 및 전처리 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_busan = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/busan_train.csv")) -df_smotenc_ctgan_busan_1 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smotenc_ctgan20000/smotenc_ctgan20000_1_busan.csv")) -df_smotenc_ctgan_busan_2 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smotenc_ctgan20000/smotenc_ctgan20000_2_busan.csv")) -df_smotenc_ctgan_busan_3 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smotenc_ctgan20000/smotenc_ctgan20000_3_busan.csv")) - -print("데이터 전처리 중...") -df_smotenc_ctgan_busan_1 = preprocessing(df_smotenc_ctgan_busan_1) -df_smotenc_ctgan_busan_2 = preprocessing(df_smotenc_ctgan_busan_2) -df_smotenc_ctgan_busan_3 = preprocessing(df_smotenc_ctgan_busan_3) -df_busan = preprocessing(df_busan) - -# SMOTENC+CTGAN 데이터 리스트 (fold 순서와 일치) -df_smotenc_ctgan_list = [df_smotenc_ctgan_busan_1, df_smotenc_ctgan_busan_2, df_smotenc_ctgan_busan_3] - -def split_data(df_sampled, df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_sampled: 샘플링된 데이터프레임 - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: 샘플링된 데이터에서 train_years에 해당하는 데이터 - train_mask = df_sampled['year'].isin(train_years) - X_train = df_sampled.loc[train_mask, df_sampled.columns != 'multi_class'].copy() - y_train = df_sampled.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - X_train.drop(columns=['year'], inplace=True) - X_val.drop(columns=['year'], inplace=True) - - return X_train, X_val, y_train, y_val - - -# 하이퍼파라미터 검색 공간 정의 -xgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 12, 1), - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'gamma': hp.uniform('gamma', 0, 5), # 트리 분할을 위한 최소 손실 감소 값 - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - xgb_model = create_xgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for df_sampled, (train_years, val_year) in zip(df_smotenc_ctgan_list, FOLD_CONFIGS): - X_train, X_val, y_train, y_val = split_data( - df_sampled, df_busan, train_years, val_year - ) - - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - csi = calculate_csi(y_val, xgb_model.predict(X_val)) - csi_scores.append(csi) - - return -1*round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -xgb_best = fmin( - fn=objective_func, - space=xgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) - -# 최적화 결과 분석 및 출력 -print(f"\n최적화 완료. 최적 파라미터: {xgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -# 파일 위치 기반으로 base 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/xgb_smotenc_ctgan20000_busan_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (df_sampled, (train_years, val_year)) in enumerate( - zip(df_smotenc_ctgan_list, FOLD_CONFIGS), start=1 -): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_sampled, df_busan, train_years, val_year - ) - - xgb_model = create_xgb_model(best_params=xgb_best) - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, xgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(xgb_model) - - -# 모델 저장 -print("모델 저장 중...") -os.makedirs(os.path.join(base_dir, "save_model/xgb_optima"), exist_ok=True) -model_save_path = os.path.join(base_dir, "save_model/xgb_optima/xgb_smotenc_ctgan20000_busan.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") diff --git a/Analysis_code/5.optima/xgb_smotenc_ctgan20000/XGB_smotenc_ctgan20000_daegu.py b/Analysis_code/5.optima/xgb_smotenc_ctgan20000/XGB_smotenc_ctgan20000_daegu.py deleted file mode 100644 index f43b74296c785394da8a48db590e96ac19106b37..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/xgb_smotenc_ctgan20000/XGB_smotenc_ctgan20000_daegu.py +++ /dev/null @@ -1,304 +0,0 @@ -import pandas as pd -import os -import numpy as np -import joblib -from xgboost import XGBClassifier -from warnings import filterwarnings -filterwarnings('ignore') -from sklearn.metrics import confusion_matrix -from hyperopt import fmin, tpe, Trials, hp - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(Y_test, pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - Y_test: 실제 레이블 - pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(Y_test, pred) - H = (cm[0, 0] + cm[1, 1]) - F = (cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1]) - M = (cm[0, 2] + cm[1, 2]) - CSI = H / (H + F + M + 1e-10) - return CSI - -def eval_metric_csi(y_true, pred_prob): - """XGBoost용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 - - Returns: - CSI 점수의 음수값 - """ - pred = np.argmax(pred_prob, axis=1) - csi = calculate_csi(y_true, pred) - return -1*csi - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - -def create_xgb_model(search_space=None, best_params=None): - """XGBoost 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - XGBClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'tree_method': 'hist', - 'device': 'cuda', - 'enable_categorical': True, - 'eval_metric': eval_metric_csi, - 'objective': 'multi:softprob', - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'min_child_weight': int(search_space['min_child_weight']), - 'gamma': search_space['gamma'], - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'min_child_weight': int(best_params['min_child_weight']), - 'gamma': best_params['gamma'], - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return XGBClassifier(**params) - - -# 데이터 로딩 및 전처리 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_daegu = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/daegu_train.csv")) -df_smotenc_ctgan_daegu_1 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smotenc_ctgan20000/smotenc_ctgan20000_1_daegu.csv")) -df_smotenc_ctgan_daegu_2 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smotenc_ctgan20000/smotenc_ctgan20000_2_daegu.csv")) -df_smotenc_ctgan_daegu_3 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smotenc_ctgan20000/smotenc_ctgan20000_3_daegu.csv")) - -print("데이터 전처리 중...") -df_smotenc_ctgan_daegu_1 = preprocessing(df_smotenc_ctgan_daegu_1) -df_smotenc_ctgan_daegu_2 = preprocessing(df_smotenc_ctgan_daegu_2) -df_smotenc_ctgan_daegu_3 = preprocessing(df_smotenc_ctgan_daegu_3) -df_daegu = preprocessing(df_daegu) - -# SMOTENC+CTGAN 데이터 리스트 (fold 순서와 일치) -df_smotenc_ctgan_list = [df_smotenc_ctgan_daegu_1, df_smotenc_ctgan_daegu_2, df_smotenc_ctgan_daegu_3] - -def split_data(df_sampled, df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_sampled: 샘플링된 데이터프레임 - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: 샘플링된 데이터에서 train_years에 해당하는 데이터 - train_mask = df_sampled['year'].isin(train_years) - X_train = df_sampled.loc[train_mask, df_sampled.columns != 'multi_class'].copy() - y_train = df_sampled.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - X_train.drop(columns=['year'], inplace=True) - X_val.drop(columns=['year'], inplace=True) - - return X_train, X_val, y_train, y_val - - -# 하이퍼파라미터 검색 공간 정의 -xgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 12, 1), - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'gamma': hp.uniform('gamma', 0, 5), # 트리 분할을 위한 최소 손실 감소 값 - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - xgb_model = create_xgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for df_sampled, (train_years, val_year) in zip(df_smotenc_ctgan_list, FOLD_CONFIGS): - X_train, X_val, y_train, y_val = split_data( - df_sampled, df_daegu, train_years, val_year - ) - - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - csi = calculate_csi(y_val, xgb_model.predict(X_val)) - csi_scores.append(csi) - - return -1*round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -xgb_best = fmin( - fn=objective_func, - space=xgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) - -# 최적화 결과 분석 및 출력 -print(f"\n최적화 완료. 최적 파라미터: {xgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -# 파일 위치 기반으로 base 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/xgb_smotenc_ctgan20000_daegu_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (df_sampled, (train_years, val_year)) in enumerate( - zip(df_smotenc_ctgan_list, FOLD_CONFIGS), start=1 -): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_sampled, df_daegu, train_years, val_year - ) - - xgb_model = create_xgb_model(best_params=xgb_best) - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, xgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(xgb_model) - - -# 모델 저장 -print("모델 저장 중...") -os.makedirs(os.path.join(base_dir, "save_model/xgb_optima"), exist_ok=True) -model_save_path = os.path.join(base_dir, "save_model/xgb_optima/xgb_smotenc_ctgan20000_daegu.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") diff --git a/Analysis_code/5.optima/xgb_smotenc_ctgan20000/XGB_smotenc_ctgan20000_daejeon.py b/Analysis_code/5.optima/xgb_smotenc_ctgan20000/XGB_smotenc_ctgan20000_daejeon.py deleted file mode 100644 index 4eb6f0d582239cf43ecef5bf1cbde00a65b84bc9..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/xgb_smotenc_ctgan20000/XGB_smotenc_ctgan20000_daejeon.py +++ /dev/null @@ -1,304 +0,0 @@ -import pandas as pd -import os -import numpy as np -import joblib -from xgboost import XGBClassifier -from warnings import filterwarnings -filterwarnings('ignore') -from sklearn.metrics import confusion_matrix -from hyperopt import fmin, tpe, Trials, hp - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(Y_test, pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - Y_test: 실제 레이블 - pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(Y_test, pred) - H = (cm[0, 0] + cm[1, 1]) - F = (cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1]) - M = (cm[0, 2] + cm[1, 2]) - CSI = H / (H + F + M + 1e-10) - return CSI - -def eval_metric_csi(y_true, pred_prob): - """XGBoost용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 - - Returns: - CSI 점수의 음수값 - """ - pred = np.argmax(pred_prob, axis=1) - csi = calculate_csi(y_true, pred) - return -1*csi - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - -def create_xgb_model(search_space=None, best_params=None): - """XGBoost 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - XGBClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'tree_method': 'hist', - 'device': 'cuda', - 'enable_categorical': True, - 'eval_metric': eval_metric_csi, - 'objective': 'multi:softprob', - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'min_child_weight': int(search_space['min_child_weight']), - 'gamma': search_space['gamma'], - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'min_child_weight': int(best_params['min_child_weight']), - 'gamma': best_params['gamma'], - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return XGBClassifier(**params) - - -# 데이터 로딩 및 전처리 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_daejeon = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/daejeon_train.csv")) -df_smotenc_ctgan_daejeon_1 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smotenc_ctgan20000/smotenc_ctgan20000_1_daejeon.csv")) -df_smotenc_ctgan_daejeon_2 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smotenc_ctgan20000/smotenc_ctgan20000_2_daejeon.csv")) -df_smotenc_ctgan_daejeon_3 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smotenc_ctgan20000/smotenc_ctgan20000_3_daejeon.csv")) - -print("데이터 전처리 중...") -df_smotenc_ctgan_daejeon_1 = preprocessing(df_smotenc_ctgan_daejeon_1) -df_smotenc_ctgan_daejeon_2 = preprocessing(df_smotenc_ctgan_daejeon_2) -df_smotenc_ctgan_daejeon_3 = preprocessing(df_smotenc_ctgan_daejeon_3) -df_daejeon = preprocessing(df_daejeon) - -# SMOTENC+CTGAN 데이터 리스트 (fold 순서와 일치) -df_smotenc_ctgan_list = [df_smotenc_ctgan_daejeon_1, df_smotenc_ctgan_daejeon_2, df_smotenc_ctgan_daejeon_3] - -def split_data(df_sampled, df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_sampled: 샘플링된 데이터프레임 - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: 샘플링된 데이터에서 train_years에 해당하는 데이터 - train_mask = df_sampled['year'].isin(train_years) - X_train = df_sampled.loc[train_mask, df_sampled.columns != 'multi_class'].copy() - y_train = df_sampled.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - X_train.drop(columns=['year'], inplace=True) - X_val.drop(columns=['year'], inplace=True) - - return X_train, X_val, y_train, y_val - - -# 하이퍼파라미터 검색 공간 정의 -xgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 12, 1), - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'gamma': hp.uniform('gamma', 0, 5), # 트리 분할을 위한 최소 손실 감소 값 - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - xgb_model = create_xgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for df_sampled, (train_years, val_year) in zip(df_smotenc_ctgan_list, FOLD_CONFIGS): - X_train, X_val, y_train, y_val = split_data( - df_sampled, df_daejeon, train_years, val_year - ) - - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - csi = calculate_csi(y_val, xgb_model.predict(X_val)) - csi_scores.append(csi) - - return -1*round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -xgb_best = fmin( - fn=objective_func, - space=xgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) - -# 최적화 결과 분석 및 출력 -print(f"\n최적화 완료. 최적 파라미터: {xgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -# 파일 위치 기반으로 base 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/xgb_smotenc_ctgan20000_daejeon_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (df_sampled, (train_years, val_year)) in enumerate( - zip(df_smotenc_ctgan_list, FOLD_CONFIGS), start=1 -): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_sampled, df_daejeon, train_years, val_year - ) - - xgb_model = create_xgb_model(best_params=xgb_best) - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, xgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(xgb_model) - - -# 모델 저장 -print("모델 저장 중...") -os.makedirs(os.path.join(base_dir, "save_model/xgb_optima"), exist_ok=True) -model_save_path = os.path.join(base_dir, "save_model/xgb_optima/xgb_smotenc_ctgan20000_daejeon.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") diff --git a/Analysis_code/5.optima/xgb_smotenc_ctgan20000/XGB_smotenc_ctgan20000_gwangju.py b/Analysis_code/5.optima/xgb_smotenc_ctgan20000/XGB_smotenc_ctgan20000_gwangju.py deleted file mode 100644 index 3226a6d0eeb00a411782daa7bbbe16ebf64721e4..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/xgb_smotenc_ctgan20000/XGB_smotenc_ctgan20000_gwangju.py +++ /dev/null @@ -1,303 +0,0 @@ -import pandas as pd -import os -import numpy as np -import joblib -from xgboost import XGBClassifier -from warnings import filterwarnings -filterwarnings('ignore') -from sklearn.metrics import confusion_matrix -from hyperopt import fmin, tpe, Trials, hp - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(Y_test, pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - Y_test: 실제 레이블 - pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(Y_test, pred) - H = (cm[0, 0] + cm[1, 1]) - F = (cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1]) - M = (cm[0, 2] + cm[1, 2]) - CSI = H / (H + F + M + 1e-10) - return CSI - -def eval_metric_csi(y_true, pred_prob): - """XGBoost용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 - - Returns: - CSI 점수의 음수값 - """ - pred = np.argmax(pred_prob, axis=1) - csi = calculate_csi(y_true, pred) - return -1*csi - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - -def create_xgb_model(search_space=None, best_params=None): - """XGBoost 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - XGBClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'tree_method': 'hist', - 'device': 'cuda', - 'enable_categorical': True, - 'eval_metric': eval_metric_csi, - 'objective': 'multi:softprob', - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'min_child_weight': int(search_space['min_child_weight']), - 'gamma': search_space['gamma'], - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'min_child_weight': int(best_params['min_child_weight']), - 'gamma': best_params['gamma'], - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return XGBClassifier(**params) - - -# 데이터 로딩 및 전처리 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_gwangju = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/gwangju_train.csv")) -df_smotenc_ctgan_gwangju_1 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smotenc_ctgan20000/smotenc_ctgan20000_1_gwangju.csv")) -df_smotenc_ctgan_gwangju_2 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smotenc_ctgan20000/smotenc_ctgan20000_2_gwangju.csv")) -df_smotenc_ctgan_gwangju_3 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smotenc_ctgan20000/smotenc_ctgan20000_3_gwangju.csv")) - -print("데이터 전처리 중...") -df_smotenc_ctgan_gwangju_1 = preprocessing(df_smotenc_ctgan_gwangju_1) -df_smotenc_ctgan_gwangju_2 = preprocessing(df_smotenc_ctgan_gwangju_2) -df_smotenc_ctgan_gwangju_3 = preprocessing(df_smotenc_ctgan_gwangju_3) -df_gwangju = preprocessing(df_gwangju) - -# SMOTENC+CTGAN 데이터 리스트 (fold 순서와 일치) -df_smotenc_ctgan_list = [df_smotenc_ctgan_gwangju_1, df_smotenc_ctgan_gwangju_2, df_smotenc_ctgan_gwangju_3] - -def split_data(df_sampled, df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_sampled: 샘플링된 데이터프레임 - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: 샘플링된 데이터에서 train_years에 해당하는 데이터 - train_mask = df_sampled['year'].isin(train_years) - X_train = df_sampled.loc[train_mask, df_sampled.columns != 'multi_class'].copy() - y_train = df_sampled.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - X_train.drop(columns=['year'], inplace=True) - X_val.drop(columns=['year'], inplace=True) - - return X_train, X_val, y_train, y_val - - -# 하이퍼파라미터 검색 공간 정의 -xgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 12, 1), - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'gamma': hp.uniform('gamma', 0, 5), # 트리 분할을 위한 최소 손실 감소 값 - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - xgb_model = create_xgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for df_sampled, (train_years, val_year) in zip(df_smotenc_ctgan_list, FOLD_CONFIGS): - X_train, X_val, y_train, y_val = split_data( - df_sampled, df_gwangju, train_years, val_year - ) - - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - csi = calculate_csi(y_val, xgb_model.predict(X_val)) - csi_scores.append(csi) - - return -1*round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -xgb_best = fmin( - fn=objective_func, - space=xgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) - -# 최적화 결과 분석 및 출력 -print(f"\n최적화 완료. 최적 파라미터: {xgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -# 파일 위치 기반으로 base 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/xgb_smotenc_ctgan20000_gwangju_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (df_sampled, (train_years, val_year)) in enumerate( - zip(df_smotenc_ctgan_list, FOLD_CONFIGS), start=1 -): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_sampled, df_gwangju, train_years, val_year - ) - - xgb_model = create_xgb_model(best_params=xgb_best) - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, xgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(xgb_model) - - -# 모델 저장 -print("모델 저장 중...") -model_save_path = os.path.join(base_dir, "save_model/xgb_optima/xgb_smotenc_ctgan20000_gwangju.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") diff --git a/Analysis_code/5.optima/xgb_smotenc_ctgan20000/XGB_smotenc_ctgan20000_incheon.py b/Analysis_code/5.optima/xgb_smotenc_ctgan20000/XGB_smotenc_ctgan20000_incheon.py deleted file mode 100644 index cbf206f4506ccb5c114ec05948d5749f2be815cf..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/xgb_smotenc_ctgan20000/XGB_smotenc_ctgan20000_incheon.py +++ /dev/null @@ -1,304 +0,0 @@ -import pandas as pd -import os -import numpy as np -import joblib -from xgboost import XGBClassifier -from warnings import filterwarnings -filterwarnings('ignore') -from sklearn.metrics import confusion_matrix -from hyperopt import fmin, tpe, Trials, hp - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(Y_test, pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - Y_test: 실제 레이블 - pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(Y_test, pred) - H = (cm[0, 0] + cm[1, 1]) - F = (cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1]) - M = (cm[0, 2] + cm[1, 2]) - CSI = H / (H + F + M + 1e-10) - return CSI - -def eval_metric_csi(y_true, pred_prob): - """XGBoost용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 - - Returns: - CSI 점수의 음수값 - """ - pred = np.argmax(pred_prob, axis=1) - csi = calculate_csi(y_true, pred) - return -1*csi - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - -def create_xgb_model(search_space=None, best_params=None): - """XGBoost 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - XGBClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'tree_method': 'hist', - 'device': 'cuda', - 'enable_categorical': True, - 'eval_metric': eval_metric_csi, - 'objective': 'multi:softprob', - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'min_child_weight': int(search_space['min_child_weight']), - 'gamma': search_space['gamma'], - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'min_child_weight': int(best_params['min_child_weight']), - 'gamma': best_params['gamma'], - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return XGBClassifier(**params) - - -# 데이터 로딩 및 전처리 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_incheon = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/incheon_train.csv")) -df_smotenc_ctgan_incheon_1 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smotenc_ctgan20000/smotenc_ctgan20000_1_incheon.csv")) -df_smotenc_ctgan_incheon_2 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smotenc_ctgan20000/smotenc_ctgan20000_2_incheon.csv")) -df_smotenc_ctgan_incheon_3 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smotenc_ctgan20000/smotenc_ctgan20000_3_incheon.csv")) - -print("데이터 전처리 중...") -df_smotenc_ctgan_incheon_1 = preprocessing(df_smotenc_ctgan_incheon_1) -df_smotenc_ctgan_incheon_2 = preprocessing(df_smotenc_ctgan_incheon_2) -df_smotenc_ctgan_incheon_3 = preprocessing(df_smotenc_ctgan_incheon_3) -df_incheon = preprocessing(df_incheon) - -# SMOTENC+CTGAN 데이터 리스트 (fold 순서와 일치) -df_smotenc_ctgan_list = [df_smotenc_ctgan_incheon_1, df_smotenc_ctgan_incheon_2, df_smotenc_ctgan_incheon_3] - -def split_data(df_sampled, df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_sampled: 샘플링된 데이터프레임 - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: 샘플링된 데이터에서 train_years에 해당하는 데이터 - train_mask = df_sampled['year'].isin(train_years) - X_train = df_sampled.loc[train_mask, df_sampled.columns != 'multi_class'].copy() - y_train = df_sampled.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - X_train.drop(columns=['year'], inplace=True) - X_val.drop(columns=['year'], inplace=True) - - return X_train, X_val, y_train, y_val - - -# 하이퍼파라미터 검색 공간 정의 -xgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 12, 1), - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'gamma': hp.uniform('gamma', 0, 5), # 트리 분할을 위한 최소 손실 감소 값 - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - xgb_model = create_xgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for df_sampled, (train_years, val_year) in zip(df_smotenc_ctgan_list, FOLD_CONFIGS): - X_train, X_val, y_train, y_val = split_data( - df_sampled, df_incheon, train_years, val_year - ) - - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - csi = calculate_csi(y_val, xgb_model.predict(X_val)) - csi_scores.append(csi) - - return -1*round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -xgb_best = fmin( - fn=objective_func, - space=xgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) - -# 최적화 결과 분석 및 출력 -print(f"\n최적화 완료. 최적 파라미터: {xgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -# 파일 위치 기반으로 base 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/xgb_smotenc_ctgan20000_incheon_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (df_sampled, (train_years, val_year)) in enumerate( - zip(df_smotenc_ctgan_list, FOLD_CONFIGS), start=1 -): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_sampled, df_incheon, train_years, val_year - ) - - xgb_model = create_xgb_model(best_params=xgb_best) - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, xgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(xgb_model) - - -# 모델 저장 -print("모델 저장 중...") -os.makedirs(os.path.join(base_dir, "save_model/xgb_optima"), exist_ok=True) -model_save_path = os.path.join(base_dir, "save_model/xgb_optima/xgb_smotenc_ctgan20000_incheon.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.") diff --git a/Analysis_code/5.optima/xgb_smotenc_ctgan20000/XGB_smotenc_ctgan20000_seoul.py b/Analysis_code/5.optima/xgb_smotenc_ctgan20000/XGB_smotenc_ctgan20000_seoul.py deleted file mode 100644 index 65d468f4fc52ad50d7b82cb758662558c876c45b..0000000000000000000000000000000000000000 --- a/Analysis_code/5.optima/xgb_smotenc_ctgan20000/XGB_smotenc_ctgan20000_seoul.py +++ /dev/null @@ -1,304 +0,0 @@ -import pandas as pd -import os -import numpy as np -import joblib -from xgboost import XGBClassifier -from warnings import filterwarnings -filterwarnings('ignore') -from sklearn.metrics import confusion_matrix -from hyperopt import fmin, tpe, Trials, hp - -# 상수 정의 -RANDOM_STATE = 42 -N_ESTIMATORS = 4000 -EARLY_STOPPING_ROUNDS = 400 -MAX_EVALS = 100 - -# Fold 설정: (train_years, val_year) -FOLD_CONFIGS = [ - ([2018, 2019], 2020), # Fold 1 - ([2018, 2020], 2019), # Fold 2 - ([2019, 2020], 2018), # Fold 3 -] - -def calculate_csi(Y_test, pred): - """CSI(Critical Success Index) 점수를 계산합니다. - - Args: - Y_test: 실제 레이블 - pred: 예측 레이블 - - Returns: - CSI 점수 (0~1 사이의 값) - """ - cm = confusion_matrix(Y_test, pred) - H = (cm[0, 0] + cm[1, 1]) - F = (cm[1, 0] + cm[2, 0] + cm[0, 1] + cm[2, 1]) - M = (cm[0, 2] + cm[1, 2]) - CSI = H / (H + F + M + 1e-10) - return CSI - -def eval_metric_csi(y_true, pred_prob): - """XGBoost용 CSI 메트릭 함수. - - Args: - y_true: 실제 레이블 - pred_prob: 예측 확률 - - Returns: - CSI 점수의 음수값 - """ - pred = np.argmax(pred_prob, axis=1) - csi = calculate_csi(y_true, pred) - return -1*csi - -def add_derived_features(df: pd.DataFrame) -> pd.DataFrame: - """ - 제거했던 파생 변수들을 복구 - - Args: - df: 데이터프레임 - - Returns: - 파생 변수가 추가된 데이터프레임 - """ - df = df.copy() - df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) - df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) - df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) - df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) - df['ground_temp - temp_C'] = df['groundtemp'] - df['temp_C'] - return df - -def preprocessing(df): - """데이터 전처리 함수. - - Args: - df: 원본 데이터프레임 - - Returns: - 전처리된 데이터프레임 - """ - df = df[df.columns].copy() - df['year'] = df['year'].astype('int') - df['month'] = df['month'].astype('int') - df['hour'] = df['hour'].astype('int') - df = add_derived_features(df).copy() - df['multi_class'] = df['multi_class'].astype('int') - df.loc[df['wind_dir']=='정온', 'wind_dir'] = "0" - df['wind_dir'] = df['wind_dir'].astype('int') - df = df[['temp_C', 'precip_mm', 'wind_speed', 'wind_dir', 'hm', - 'vap_pressure', 'dewpoint_C', 'loc_pressure', 'sea_pressure', - 'solarRad', 'snow_cm', 'cloudcover', 'lm_cloudcover', 'low_cloudbase', - 'groundtemp', 'O3', 'NO2', 'PM10', 'PM25', 'year', - 'month', 'hour', 'ground_temp - temp_C', 'hour_sin', 'hour_cos', - 'month_sin', 'month_cos','multi_class']].copy() - return df - -def create_xgb_model(search_space=None, best_params=None): - """XGBoost 모델을 생성합니다. - - Args: - search_space: 하이퍼파라미터 검색 공간 (objective_func에서 사용) - best_params: 최적화된 하이퍼파라미터 (최종 모델 학습에서 사용) - - Returns: - XGBClassifier 인스턴스 - """ - base_params = { - 'n_estimators': N_ESTIMATORS, - 'tree_method': 'hist', - 'device': 'cuda', - 'enable_categorical': True, - 'eval_metric': eval_metric_csi, - 'objective': 'multi:softprob', - 'random_state': RANDOM_STATE, - 'early_stopping_rounds': EARLY_STOPPING_ROUNDS, - } - - if search_space is not None: - # 하이퍼파라미터 최적화 중 - params = { - **base_params, - 'learning_rate': search_space['learning_rate'], - 'max_depth': int(search_space['max_depth']), - 'min_child_weight': int(search_space['min_child_weight']), - 'gamma': search_space['gamma'], - 'subsample': search_space['subsample'], - 'colsample_bytree': search_space['colsample_bytree'], - 'reg_alpha': search_space['reg_alpha'], - 'reg_lambda': search_space['reg_lambda'], - } - elif best_params is not None: - # 최적화된 파라미터로 최종 모델 생성 - params = { - **base_params, - 'learning_rate': best_params['learning_rate'], - 'max_depth': int(best_params['max_depth']), - 'min_child_weight': int(best_params['min_child_weight']), - 'gamma': best_params['gamma'], - 'subsample': best_params['subsample'], - 'colsample_bytree': best_params['colsample_bytree'], - 'reg_alpha': best_params['reg_alpha'], - 'reg_lambda': best_params['reg_lambda'], - } - else: - params = base_params - - return XGBClassifier(**params) - - -# 데이터 로딩 및 전처리 -print("데이터 로딩 중...") -# 파일 위치 기반으로 데이터 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -data_base_dir = os.path.abspath(os.path.join(current_file_dir, '../../../data')) -df_seoul = pd.read_csv(os.path.join(data_base_dir, "data_for_modeling/seoul_train.csv")) -df_smotenc_ctgan_seoul_1 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smotenc_ctgan20000/smotenc_ctgan20000_1_seoul.csv")) -df_smotenc_ctgan_seoul_2 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smotenc_ctgan20000/smotenc_ctgan20000_2_seoul.csv")) -df_smotenc_ctgan_seoul_3 = pd.read_csv(os.path.join(data_base_dir, "data_oversampled/smotenc_ctgan20000/smotenc_ctgan20000_3_seoul.csv")) - -print("데이터 전처리 중...") -df_smotenc_ctgan_seoul_1 = preprocessing(df_smotenc_ctgan_seoul_1) -df_smotenc_ctgan_seoul_2 = preprocessing(df_smotenc_ctgan_seoul_2) -df_smotenc_ctgan_seoul_3 = preprocessing(df_smotenc_ctgan_seoul_3) -df_seoul = preprocessing(df_seoul) - -# SMOTENC+CTGAN 데이터 리스트 (fold 순서와 일치) -df_smotenc_ctgan_list = [df_smotenc_ctgan_seoul_1, df_smotenc_ctgan_seoul_2, df_smotenc_ctgan_seoul_3] - -def split_data(df_sampled, df_original, train_years, val_year): - """데이터를 학습용과 검증용으로 분할합니다. - - Args: - df_sampled: 샘플링된 데이터프레임 - df_original: 원본 데이터프레임 - train_years: 학습에 사용할 연도 리스트 - val_year: 검증에 사용할 연도 - - Returns: - (X_train, X_val, y_train, y_val) 튜플 - """ - # 학습 데이터: 샘플링된 데이터에서 train_years에 해당하는 데이터 - train_mask = df_sampled['year'].isin(train_years) - X_train = df_sampled.loc[train_mask, df_sampled.columns != 'multi_class'].copy() - y_train = df_sampled.loc[train_mask, 'multi_class'] - - # 검증 데이터: 원본 데이터에서 val_year에 해당하는 데이터 - val_mask = df_original['year'] == val_year - X_val = df_original.loc[val_mask, df_original.columns != 'multi_class'].copy() - y_val = df_original.loc[val_mask, 'multi_class'] - - X_train.drop(columns=['year'], inplace=True) - X_val.drop(columns=['year'], inplace=True) - - return X_train, X_val, y_train, y_val - - -# 하이퍼파라미터 검색 공간 정의 -xgb_search_space = { - 'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)), - 'max_depth': hp.quniform('max_depth', 3, 12, 1), - 'min_child_weight': hp.quniform('min_child_weight', 1, 20, 1), - 'gamma': hp.uniform('gamma', 0, 5), # 트리 분할을 위한 최소 손실 감소 값 - 'subsample': hp.uniform('subsample', 0.6, 1.0), - 'colsample_bytree': hp.uniform('colsample_bytree', 0.6, 1.0), - 'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0), - 'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0) -} - -def objective_func(search_space): - """하이퍼파라미터 최적화를 위한 목적 함수. - - Args: - search_space: 하이퍼파라미터 검색 공간 - - Returns: - 평균 CSI 점수의 음수값 (hyperopt는 최소화를 수행하므로) - """ - xgb_model = create_xgb_model(search_space=search_space) - csi_scores = [] - - # 각 fold에 대해 교차 검증 수행 - for df_sampled, (train_years, val_year) in zip(df_smotenc_ctgan_list, FOLD_CONFIGS): - X_train, X_val, y_train, y_val = split_data( - df_sampled, df_seoul, train_years, val_year - ) - - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - csi = calculate_csi(y_val, xgb_model.predict(X_val)) - csi_scores.append(csi) - - return -1*round(np.mean(csi_scores), 4) - - -# 하이퍼파라미터 최적화 -print("하이퍼파라미터 최적화 시작...") -trials = Trials() -xgb_best = fmin( - fn=objective_func, - space=xgb_search_space, - algo=tpe.suggest, - max_evals=MAX_EVALS, - trials=trials -) - -# 최적화 결과 분석 및 출력 -print(f"\n최적화 완료. 최적 파라미터: {xgb_best}") - -# Best loss (CSI 점수의 음수값이므로, 실제 CSI는 -loss) -best_loss = trials.best_trial['result']['loss'] -best_csi = -best_loss -print(f"최적 CSI 점수: {best_csi:.4f} (loss: {best_loss:.4f})") - -# 모든 trial의 loss 값 추출 -losses = [trial['result']['loss'] for trial in trials.trials if trial['result']['status'] == 'ok'] -csi_scores = [-loss for loss in losses] - -print(f"\n최적화 과정 요약:") -print(f" - 총 시도 횟수: {len(trials.trials)}") -print(f" - 성공한 시도: {len(losses)}") -print(f" - 최초 CSI: {csi_scores[0]:.4f}") -print(f" - 최종 CSI: {csi_scores[-1]:.4f}") -print(f" - 최고 CSI: {max(csi_scores):.4f}") -print(f" - 최저 CSI: {min(csi_scores):.4f}") -print(f" - 평균 CSI: {np.mean(csi_scores):.4f}") - -# Trials 객체 저장 -# 파일 위치 기반으로 base 디렉토리 경로 설정 -current_file_dir = os.path.dirname(os.path.abspath(__file__)) -base_dir = os.path.dirname(os.path.dirname(current_file_dir)) # 5.optima 디렉토리 -os.makedirs(os.path.join(base_dir, "optimization_history"), exist_ok=True) -trials_path = os.path.join(base_dir, "optimization_history/xgb_smotenc_ctgan20000_seoul_trials.pkl") -joblib.dump(trials, trials_path) -print(f"\n최적화 Trials 객체가 {trials_path}에 저장되었습니다.") - -# 최적화된 하이퍼파라미터로 최종 모델 학습 -print("최종 모델 학습 시작...") -models = [] - -for fold_idx, (df_sampled, (train_years, val_year)) in enumerate( - zip(df_smotenc_ctgan_list, FOLD_CONFIGS), start=1 -): - print(f"Fold {fold_idx} 학습 중... (학습 연도: {train_years}, 검증 연도: {val_year})") - - X_train, X_val, y_train, y_val = split_data( - df_sampled, df_seoul, train_years, val_year - ) - - xgb_model = create_xgb_model(best_params=xgb_best) - xgb_model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False) - - # 검증 성능 출력 - val_csi = calculate_csi(y_val, xgb_model.predict(X_val)) - print(f"Fold {fold_idx} 검증 CSI: {val_csi:.4f}") - - models.append(xgb_model) - - -# 모델 저장 -print("모델 저장 중...") -os.makedirs(os.path.join(base_dir, "save_model/xgb_optima"), exist_ok=True) -model_save_path = os.path.join(base_dir, "save_model/xgb_optima/xgb_smotenc_ctgan20000_seoul.pkl") -joblib.dump(models, model_save_path) -print(f"모델이 {model_save_path}에 저장되었습니다.")