diff --git a/fine_tune.py b/fine_tune.py
index c7e6bbd2..77a1a4f3 100644
--- a/fine_tune.py
+++ b/fine_tune.py
@@ -310,7 +310,7 @@ def train(args):
             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)
+        accelerator.init_trackers("finetuning" if args.log_tracker_name is None else args.log_tracker_name, config=train_util.filter_sensitive_args(args), init_kwargs=init_kwargs)
 
     # For --sample_at_first
     train_util.sample_images(accelerator, args, 0, global_step, accelerator.device, vae, tokenizer, text_encoder, unet)
diff --git a/library/train_util.py b/library/train_util.py
index 8a69f0be..84764263 100644
--- a/library/train_util.py
+++ b/library/train_util.py
@@ -3388,6 +3388,33 @@ def add_masked_loss_arguments(parser: argparse.ArgumentParser):
         help="apply mask for calculating loss. conditioning_data_dir is required for dataset. / 損失計算時にマスクを適用する。datasetにはconditioning_data_dirが必要",
     )
 
+def filter_sensitive_args(args: argparse.Namespace):
+    sensitive_args = ["wandb_api_key", "huggingface_token"]
+    sensitive_path_args = [
+        "pretrained_model_name_or_path",
+        "vae",
+        "tokenizer_cache_dir",
+        "train_data_dir",
+        "conditioning_data_dir",
+        "reg_data_dir",
+        "output_dir",
+        "logging_dir",
+    ]
+    filtered_args = {}
+    for k, v in vars(args).items():
+    # filter out sensitive values
+        if k not in sensitive_args + sensitive_path_args:
+            #Accelerate values need to have type `bool`,`str`, `float`, `int`, or `None`.
+            if v is None or isinstance(v, bool) or isinstance(v, str) or isinstance(v, float) or isinstance(v, int):
+                filtered_args[k] = v
+            # accelerate does not support lists
+            elif isinstance(v, list):
+                filtered_args[k] = f"{v}"
+            # accelerate does not support objects
+            elif isinstance(v, object):
+                filtered_args[k] = f"{v}"
+
+    return filtered_args
 
 # verify command line args for training
 def verify_command_line_training_args(args: argparse.Namespace):
diff --git a/sdxl_train.py b/sdxl_train.py
index be2b7166..4c4e3872 100644
--- a/sdxl_train.py
+++ b/sdxl_train.py
@@ -589,7 +589,7 @@ def train(args):
             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)
+        accelerator.init_trackers("finetuning" if args.log_tracker_name is None else args.log_tracker_name, config=train_util.filter_sensitive_args(args), init_kwargs=init_kwargs)
 
     # For --sample_at_first
     sdxl_train_util.sample_images(
diff --git a/sdxl_train_control_net_lllite.py b/sdxl_train_control_net_lllite.py
index 09b6d73b..b141965f 100644
--- a/sdxl_train_control_net_lllite.py
+++ b/sdxl_train_control_net_lllite.py
@@ -354,7 +354,7 @@ def train(args):
         if args.log_tracker_config is not None:
             init_kwargs = toml.load(args.log_tracker_config)
         accelerator.init_trackers(
-            "lllite_control_net_train" if args.log_tracker_name is None else args.log_tracker_name, init_kwargs=init_kwargs
+            "lllite_control_net_train" if args.log_tracker_name is None else args.log_tracker_name, config=train_util.filter_sensitive_args(args), init_kwargs=init_kwargs
         )
 
     loss_recorder = train_util.LossRecorder()
diff --git a/sdxl_train_control_net_lllite_old.py b/sdxl_train_control_net_lllite_old.py
index e85e978c..9490cf6f 100644
--- a/sdxl_train_control_net_lllite_old.py
+++ b/sdxl_train_control_net_lllite_old.py
@@ -324,7 +324,7 @@ def train(args):
         if args.log_tracker_config is not None:
             init_kwargs = toml.load(args.log_tracker_config)
         accelerator.init_trackers(
-            "lllite_control_net_train" if args.log_tracker_name is None else args.log_tracker_name, init_kwargs=init_kwargs
+            "lllite_control_net_train" if args.log_tracker_name is None else args.log_tracker_name, config=train_util.filter_sensitive_args(args), init_kwargs=init_kwargs
         )
 
     loss_recorder = train_util.LossRecorder()
diff --git a/train_controlnet.py b/train_controlnet.py
index f4c94e8d..793f79c7 100644
--- a/train_controlnet.py
+++ b/train_controlnet.py
@@ -344,7 +344,7 @@ def train(args):
         if args.log_tracker_config is not None:
             init_kwargs = toml.load(args.log_tracker_config)
         accelerator.init_trackers(
-            "controlnet_train" if args.log_tracker_name is None else args.log_tracker_name, init_kwargs=init_kwargs
+            "controlnet_train" if args.log_tracker_name is None else args.log_tracker_name, config=train_util.filter_sensitive_args(args), init_kwargs=init_kwargs
         )
 
     loss_recorder = train_util.LossRecorder()
diff --git a/train_db.py b/train_db.py
index 1de504ed..4f901829 100644
--- a/train_db.py
+++ b/train_db.py
@@ -290,7 +290,7 @@ def train(args):
             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("dreambooth" if args.log_tracker_name is None else args.log_tracker_name, init_kwargs=init_kwargs)
+        accelerator.init_trackers("dreambooth" if args.log_tracker_name is None else args.log_tracker_name, config=train_util.filter_sensitive_args(args), init_kwargs=init_kwargs)
 
     # For --sample_at_first
     train_util.sample_images(accelerator, args, 0, global_step, accelerator.device, vae, tokenizer, text_encoder, unet)
diff --git a/train_network.py b/train_network.py
index feb455ce..401a1c70 100644
--- a/train_network.py
+++ b/train_network.py
@@ -774,7 +774,7 @@ class NetworkTrainer:
             if args.log_tracker_config is not None:
                 init_kwargs = toml.load(args.log_tracker_config)
             accelerator.init_trackers(
-                "network_train" if args.log_tracker_name is None else args.log_tracker_name, init_kwargs=init_kwargs
+                "network_train" if args.log_tracker_name is None else args.log_tracker_name, config=train_util.filter_sensitive_args(args), init_kwargs=init_kwargs
             )
 
         loss_recorder = train_util.LossRecorder()
diff --git a/train_textual_inversion.py b/train_textual_inversion.py
index 10fce267..56a38739 100644
--- a/train_textual_inversion.py
+++ b/train_textual_inversion.py
@@ -510,7 +510,7 @@ class TextualInversionTrainer:
             if args.log_tracker_config is not None:
                 init_kwargs = toml.load(args.log_tracker_config)
             accelerator.init_trackers(
-                "textual_inversion" if args.log_tracker_name is None else args.log_tracker_name, init_kwargs=init_kwargs
+                "textual_inversion" if args.log_tracker_name is None else args.log_tracker_name, config=train_util.filter_sensitive_args(args), init_kwargs=init_kwargs
             )
 
         # function for saving/removing
diff --git a/train_textual_inversion_XTI.py b/train_textual_inversion_XTI.py
index ddd03d53..69178523 100644
--- a/train_textual_inversion_XTI.py
+++ b/train_textual_inversion_XTI.py
@@ -407,7 +407,7 @@ def train(args):
         if args.log_tracker_config is not None:
             init_kwargs = toml.load(args.log_tracker_config)
         accelerator.init_trackers(
-            "textual_inversion" if args.log_tracker_name is None else args.log_tracker_name, init_kwargs=init_kwargs
+            "textual_inversion" if args.log_tracker_name is None else args.log_tracker_name, config=train_util.filter_sensitive_args(args), init_kwargs=init_kwargs
         )
 
     # function for saving/removing