diff --git a/nequip/scripts/train.py b/nequip/scripts/train.py
index 02460aad..7ba1538b 100644
--- a/nequip/scripts/train.py
+++ b/nequip/scripts/train.py
@@ -24,10 +24,6 @@
 from nequip.utils._global_options import _set_global_options
 from nequip.scripts._logger import set_up_script_logger
 
-warnings.filterwarnings(  # unnecessary e3nn-related JIT warning
-    "ignore",
-    message="The TorchScript type system doesn't support instance-level annotations",
-)
 default_config = dict(
     root="./",
     tensorboard=False,
diff --git a/nequip/train/trainer.py b/nequip/train/trainer.py
index 21c7199d..8788c84a 100644
--- a/nequip/train/trainer.py
+++ b/nequip/train/trainer.py
@@ -1149,14 +1149,14 @@ def _parse_n_train_n_val(
     ) -> tuple[int]:
         # parse n_train and n_val (can be ints or str with percentage):
         n_train_n_val = []
-        for n_name in ["n_train", "n_val"]:
+        for n_name, dataset_size in (
+            ("n_train", train_dataset_size),
+            ("n_val", val_dataset_size),
+        ):
             n = getattr(self, n_name)
             if isinstance(n, str) and "%" in n:
-                dataset_size = (
-                    train_dataset_size if n_name == "n_train" else val_dataset_size
-                )
                 n_train_n_val.append(
-                    (float(n.strip("%")) / 100) * dataset_size
+                    (float(n.rstrip("%")) / 100) * dataset_size
                 )  # convert to float first
             elif isinstance(n, int):
                 n_train_n_val.append(n)