diff --git a/astrai/serialization.py b/astrai/serialization.py
index 103fada..857d23c 100644
--- a/astrai/serialization.py
+++ b/astrai/serialization.py
@@ -38,7 +38,7 @@ class Checkpoint:
             meta = {
                 "epoch": self.epoch,
                 "iteration": self.iteration,
-                "timestamp": time.time(),
+                "timestamp": time.strftime("%Y-%m-%dT%H:%M:%S"),
             }
             meta.update(self.meta)
             with open(save_path / "meta.json", "w") as f:
diff --git a/astrai/trainer/train_callback.py b/astrai/trainer/train_callback.py
index 3fb4f01..cff728c 100644
--- a/astrai/trainer/train_callback.py
+++ b/astrai/trainer/train_callback.py
@@ -1,9 +1,10 @@
 import json
 import logging
 import os
+import sys
 import time
 from pathlib import Path
-from typing import Callable, List, Optional, Protocol, runtime_checkable
+from typing import IO, Callable, List, Optional, Protocol, runtime_checkable
 
 import torch
 import torch.distributed as dist
@@ -211,8 +212,12 @@ class ProgressBarCallback(TrainCallback):
     Progress bar callback for trainer.
     """
 
-    def __init__(self, num_epoch: int):
+    def __init__(
+        self, num_epoch: int, log_interval: int = 100, file: IO[str] = sys.stdout
+    ):
         self.num_epoch = num_epoch
+        self.log_interval = log_interval
+        self.file = file
         self.progress_bar: tqdm = None
 
     @only_on_rank(0)
@@ -221,6 +226,7 @@ class ProgressBarCallback(TrainCallback):
             context.dataloader,
             desc=f"Epoch {context.epoch + 1}/{self.num_epoch}",
             dynamic_ncols=True,
+            file=self.file,
         )
 
     @only_on_rank(0)
@@ -274,7 +280,7 @@ class MetricLoggerCallback(TrainCallback):
 
     def _get_log_data(self, context: TrainContext):
         return {
-            "timestamp": time.strftime("%Y-%m-%d %H:%M:%S"),
+            "timestamp": time.strftime("%Y-%m-%dT%H:%M:%S"),
             "epoch": context.epoch,
             "iter": context.iteration,
             **{m: self._metric_funcs[m](context) for m in self.metrics},