diff --git a/mltb2/files.py b/mltb2/files.py
index 4eec687..03da345 100644
--- a/mltb2/files.py
+++ b/mltb2/files.py
@@ -150,10 +150,22 @@ def _write_lock_files(self, batch: Sequence[Dict[str, Any]]) -> None:
             (self._result_dir_path / f"{uuid}.lock").touch()
             self._own_lock_uuids.add(uuid)
 
-    def read_batch(self) -> Sequence[Dict[str, Any]]:
-        """Read the next batch of data."""
+    def _get_remaining_data(self) -> List[Dict[str, Any]]:
         locked_or_done_uuids: Set[str] = self._get_locked_or_done_uuids()
         remaining_data = [d for d in self.data if d[self.uuid_name] not in locked_or_done_uuids]
+        return remaining_data
+
+    def read_batch(self) -> Sequence[Dict[str, Any]]:
+        """Read the next batch of data."""
+        remaining_data: List[Dict[str, Any]] = self._get_remaining_data()
+
+        # if we think we are done, delete all lock files and check again
+        # this is because lock files might be orphaned
+        if len(remaining_data) == 0:
+            for lock_file_path in self._result_dir_path.glob("*.lock"):
+                lock_file_path.unlink(missing_ok=True)
+            remaining_data = self._get_remaining_data()
+
         random.shuffle(remaining_data)
         next_batch_size = min(self.batch_size, len(remaining_data))
         next_batch = remaining_data[:next_batch_size]
diff --git a/pyproject.toml b/pyproject.toml
index efa9c0f..bd6d9f4 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "mltb2"
-version = "1.0.0rc1"
+version = "1.0.0rc2"
 description = "Machine Learning Toolbox 2"
 authors = ["PhilipMay <philip@may.la>"]
 readme = "README.md"
diff --git a/tests/test_files.py b/tests/test_files.py
index cdeabc8..14297aa 100644
--- a/tests/test_files.py
+++ b/tests/test_files.py
@@ -225,3 +225,32 @@ def test_FileBasedRestartableBatchDataProcessor_len(tmp_path):
         data=data, batch_size=10, uuid_name="uuid", result_dir=result_dir
     )
     assert len(data_processor) == 77
+
+
+def test_FileBasedRestartableBatchDataProcessor_clear_lock_files(tmp_path):
+    result_dir = tmp_path.absolute()
+    batch_size = 10
+    data = [{"uuid": str(uuid4()), "x": i} for i in range(100)]
+    data_processor = FileBasedRestartableBatchDataProcessor(
+        data=data, batch_size=batch_size, uuid_name="uuid", result_dir=result_dir
+    )
+
+    _ = data_processor.read_batch()  # create empty lock files
+
+    # process all data
+    while True:
+        _data = data_processor.read_batch()
+        if len(_data) == 0:
+            break
+        data_processor.save_batch(_data)
+
+    del data_processor
+    processed_data = FileBasedRestartableBatchDataProcessor.load_data(result_dir)
+
+    assert len(processed_data) == len(data)
+    for d in processed_data:
+        assert "uuid" in d
+        assert "x" in d
+        assert isinstance(d["uuid"], str)
+        assert isinstance(d["x"], int)
+        assert d["x"] < 100