diff --git a/scripts/load_roi_data.py b/scripts/load_roi_data.py
index 9af8a09..ee2263c 100644
--- a/scripts/load_roi_data.py
+++ b/scripts/load_roi_data.py
@@ -15,14 +15,21 @@ import pandas as pd
 
 from config import VIDEO_INFO_TSV
 
-# Reason: tqdm.auto picks the right backend automatically — Jupyter widget
-# inside a notebook, plain text on the CLI. Fall back to a no-op wrapper
-# if tqdm isn't installed so the loader still works in minimal environments.
+# Reason: prefer the explicit Jupyter-widget tqdm when available (it
+# updates reliably in JupyterLab, where text \r-style bars sometimes
+# don't refresh in-place). Fall back to tqdm.auto, then to a no-op.
 try:
-    from tqdm.auto import tqdm
+    from tqdm.notebook import tqdm
 except ImportError:
-    def tqdm(iterable, **_kwargs):  # type: ignore[no-redef]
-        return iterable
+    try:
+        from tqdm.auto import tqdm
+    except ImportError:
+        def tqdm(*_args, **_kwargs):  # type: ignore[no-redef]
+            class _NoOpBar:
+                def update(self, _n=1): pass
+                def set_postfix_str(self, _s): pass
+                def close(self): pass
+            return _NoOpBar()
 
 
 # Metadata columns to copy onto every tracking sample. These are the xlsx
@@ -100,20 +107,27 @@ def load_roi_data(
         # knows whether to grab a coffee.
         print(
             f"Loading ROI data for {n_rows} flies × 2 sessions "
-            f"({2 * n_rows} DB queries). This typically takes 1–3 minutes."
+            f"({2 * n_rows} DB queries). This typically takes 2–5 minutes.",
+            flush=True,
         )
-    iterator = tqdm(
-        meta.itertuples(index=False),
-        total=n_rows,
+    # Reason: tick per-session (2 per fly) instead of per-fly so the bar
+    # advances roughly every second, not every ~2s. set_postfix_str shows
+    # what's being processed — gives the user something visibly changing
+    # even when total ticks are slow.
+    pbar = tqdm(
+        total=2 * n_rows,
         desc="loading flies",
-        unit="fly",
+        unit="session",
         disable=not progress,
+        mininterval=0.5,
     )
 
-    for row in iterator:
+    for row in meta.itertuples(index=False):
         for session in ("training", "testing"):
+            pbar.set_postfix_str(f"{row.machine_name} ROI {int(row.roi)} {session}")
             conn = _open_ro(getattr(row, f"{session}_db_path"), db_cache)
             if conn is None:
+                pbar.update(1)
                 continue
             try:
                 df = pd.read_sql_query(
@@ -123,12 +137,16 @@ def load_roi_data(
                 # Reason: a DB may be missing a ROI table if tracking was
                 # partial — skip rather than abort the whole batch.
                 print(f"  ROI_{row.roi} from {session} DB: {e}")
+                pbar.update(1)
                 continue
             df["session"] = session
             df["ROI"] = int(row.roi)
             for col in _META_COLS:
                 df[col] = getattr(row, col)
             chunks.append(df)
+            pbar.update(1)
+
+    pbar.close()
 
     for conn in db_cache.values():
         if conn is not None: