diff --git a/fine_tune.py b/fine_tune.py
index a75c4673..86f5b253 100644
--- a/fine_tune.py
+++ b/fine_tune.py
@@ -18,9 +18,11 @@ init_ipex()
 from accelerate.utils import set_seed
 from diffusers import DDPMScheduler
 
-from library.utils import setup_logging
+from library.utils import setup_logging, add_logging_arguments
+
 setup_logging()
 import logging
+
 logger = logging.getLogger(__name__)
 import library.train_util as train_util
 import library.config_util as config_util
@@ -41,6 +43,7 @@ from library.custom_train_functions import (
 def train(args):
     train_util.verify_training_args(args)
     train_util.prepare_dataset_args(args, True)
+    setup_logging(args, reset=True)
 
     cache_latents = args.cache_latents
 
@@ -227,7 +230,9 @@ def train(args):
         args.max_train_steps = args.max_train_epochs * math.ceil(
             len(train_dataloader) / accelerator.num_processes / args.gradient_accumulation_steps
         )
-        accelerator.print(f"override steps. steps for {args.max_train_epochs} epochs is / 指定エポックまでのステップ数: {args.max_train_steps}")
+        accelerator.print(
+            f"override steps. steps for {args.max_train_epochs} epochs is / 指定エポックまでのステップ数: {args.max_train_steps}"
+        )
 
     # データセット側にも学習ステップを送信
     train_dataset_group.set_max_train_steps(args.max_train_steps)
@@ -291,7 +296,7 @@ def train(args):
     if accelerator.is_main_process:
         init_kwargs = {}
         if args.wandb_run_name:
-            init_kwargs['wandb'] = {'name': args.wandb_run_name}
+            init_kwargs["wandb"] = {"name": args.wandb_run_name}
         if args.log_tracker_config is not None:
             init_kwargs = toml.load(args.log_tracker_config)
         accelerator.init_trackers("finetuning" if args.log_tracker_name is None else args.log_tracker_name, init_kwargs=init_kwargs)
@@ -471,6 +476,7 @@ def train(args):
 def setup_parser() -> argparse.ArgumentParser:
     parser = argparse.ArgumentParser()
 
+    add_logging_arguments(parser)  # モジュール指定がないのがちょっと気持ち悪い / bit weird that this does not have module prefix
     train_util.add_sd_models_arguments(parser)
     train_util.add_dataset_arguments(parser, False, True, True)
     train_util.add_training_arguments(parser, False)
@@ -479,7 +485,9 @@ def setup_parser() -> argparse.ArgumentParser:
     config_util.add_config_arguments(parser)
     custom_train_functions.add_custom_train_arguments(parser)
 
-    parser.add_argument("--diffusers_xformers", action="store_true", help="use xformers by diffusers / Diffusersでxformersを使用する")
+    parser.add_argument(
+        "--diffusers_xformers", action="store_true", help="use xformers by diffusers / Diffusersでxformersを使用する"
+    )
     parser.add_argument("--train_text_encoder", action="store_true", help="train text encoder / text encoderも学習する")
     parser.add_argument(
         "--learning_rate_te",
diff --git a/library/utils.py b/library/utils.py
index 1b5d7eb6..af0563df 100644
--- a/library/utils.py
+++ b/library/utils.py
@@ -8,18 +8,53 @@ def fire_in_thread(f, *args, **kwargs):
     threading.Thread(target=f, args=args, kwargs=kwargs).start()
 
 
-def setup_logging(log_level=logging.INFO):
-    if logging.root.handlers:  # Already configured
-        return
+def add_logging_arguments(parser):
+    parser.add_argument(
+        "--console_log_level",
+        type=str,
+        default=None,
+        choices=["DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"],
+        help="Set the logging level, default is INFO / ログレベルを設定する。デフォルトはINFO",
+    )
+    parser.add_argument(
+        "--console_log_file",
+        type=str,
+        default=None,
+        help="Log to a file instead of stdout / 標準出力ではなくファイルにログを出力する",
+    )
+    parser.add_argument("--console_log_simple", action="store_true", help="Simple log output / シンプルなログ出力")
 
-    try:
-        from rich.logging import RichHandler
 
-        handler = RichHandler()
-    except ImportError:
-        print("rich is not installed, using basic logging")
-        handler = logging.StreamHandler(sys.stdout)  # same as print
-        handler.propagate = False
+def setup_logging(args=None, log_level=None, reset=False):
+    if logging.root.handlers:
+        if reset:
+            # remove all handlers
+            for handler in logging.root.handlers[:]:
+                logging.root.removeHandler(handler)
+        else:
+            return
+
+    if log_level is None and args is not None:
+        log_level = args.console_log_level
+    if log_level is None:
+        log_level = "INFO"
+    log_level = getattr(logging, log_level)
+
+    if args is not None and args.console_log_file:
+        handler = logging.FileHandler(args.console_log_file, mode="w")
+    else:
+        handler = None
+        if not args or not args.console_log_simple:
+            try:
+                from rich.logging import RichHandler
+
+                handler = RichHandler()
+            except ImportError:
+                print("rich is not installed, using basic logging")
+
+        if handler is None:
+            handler = logging.StreamHandler(sys.stdout)  # same as print
+            handler.propagate = False
 
     formatter = logging.Formatter(
         fmt="%(message)s",