diff --git a/vall_e/data.py b/vall_e/data.py
index 5f9ab19..ab1ffdb 100755
--- a/vall_e/data.py
+++ b/vall_e/data.py
@@ -903,6 +903,7 @@ class Dataset(_Dataset):
 		state_dict = torch_load(path)
 		if "dataset_hash_key" in state_dict:
 			if self.dataset_hash_key != state_dict["dataset_hash_key"]:
+				_logger.warning(f'Mismatched dataset hash key for {self.dataset_type} dataloader, ignoring loading of state dict.')
 				return
 
 		if self.sampler_type == "path":
diff --git a/vall_e/utils/trainer.py b/vall_e/utils/trainer.py
index cd96d21..58d1a6b 100755
--- a/vall_e/utils/trainer.py
+++ b/vall_e/utils/trainer.py
@@ -103,8 +103,10 @@ def _non_blocking_input():
 
 def _make_infinite_epochs(dl):
 	while True:
-		#_logger.info("New epoch starts.")
-		yield from tqdm(dl, "Epoch progress", dynamic_ncols=True, disable=not is_global_leader()) # , initial=dl.dataset.index(), total=len(dl.dataset)) # to-do: figure out why this number jumps
+		if dl_dataset.index() == 0:
+			_logger.info("New epoch starts.")
+		# this number may jump from the dataloader sampling before the actual training step happens
+		yield from tqdm(dl, "Epoch progress", dynamic_ncols=True, disable=not is_global_leader(), initial=dl.dataset.index(), total=len(dl.dataset))
 
 
 @local_leader_only(default=None)