diff --git a/src/accelerate/accelerator.py b/src/accelerate/accelerator.py
index e2faffb1bee..5708926df25 100755
--- a/src/accelerate/accelerator.py
+++ b/src/accelerate/accelerator.py
@@ -463,8 +463,8 @@ def __init__(
         if self.rng_types is None:
             self.rng_types = ["generator"]
 
-        # Tracking tensor for monitoring breakpoints
-        self.flag_tensor = torch.zeros(1, device=self.device)
+        # Set a flag tensor for early stopping and other breakpoints
+        self.flag_tensor = None
 
     @property
     def use_distributed(self):
@@ -1990,7 +1990,7 @@ def set_breakpoint(self):
         ...     break
         ```
         """
-        self.flag_tensor += 1
+        self.flag_tensor = torch.tensor(1, device=self.device)
 
     def check_breakpoint(self):
         """
@@ -2016,9 +2016,12 @@ def check_breakpoint(self):
         ...     break
         ```
         """
+        # Now that we are outside `__init__`, we can initialize it if it is `None` on device
+        if self.flag_tensor is None:
+            self.flag_tensor = torch.tensor(0, device=self.device)
         flag_tensor = self.reduce(self.flag_tensor)
         if flag_tensor.item() == 1:
-            self.flag_tensor = torch.zeros(1, device=self.device)
+            self.flag_tensor = None
             return True
         return False
 
diff --git a/src/accelerate/test_utils/scripts/test_script.py b/src/accelerate/test_utils/scripts/test_script.py
index 93b6ce660e0..78dc445a9bf 100644
--- a/src/accelerate/test_utils/scripts/test_script.py
+++ b/src/accelerate/test_utils/scripts/test_script.py
@@ -558,56 +558,58 @@ def test_breakpoint():
 def main():
     accelerator = Accelerator()
     state = accelerator.state
-    if state.local_process_index == 0:
-        print("**Initialization**")
-    init_state_check()
-    state.wait_for_everyone()
-
-    if state.distributed_type == DistributedType.MULTI_GPU:
-        num_processes_per_node = torch.cuda.device_count()
-    else:
-        num_processes_per_node = state.num_processes
-
-    # We only run this test on non-multinode
-    if num_processes_per_node == state.num_processes:
-        if state.process_index == 0:
-            print("\n**Test process execution**")
-        process_execution_check()
-
-        if state.process_index == 0:
-            print("\n**Test split between processes as a list**")
-        test_split_between_processes_list()
-
-        if state.process_index == 0:
-            print("\n**Test split between processes as a dict**")
-        test_split_between_processes_nested_dict()
-
-        if state.process_index == 0:
-            print("\n**Test split between processes as a tensor**")
-        test_split_between_processes_tensor()
-
-    if state.local_process_index == 0:
-        print("\n**Test random number generator synchronization**")
-    rng_sync_check()
-
-    if state.local_process_index == 0:
-        print("\n**DataLoader integration test**")
-    dl_preparation_check()
-    if state.distributed_type != DistributedType.TPU:
-        central_dl_preparation_check()
-
-    # Trainings are not exactly the same in DeepSpeed and CPU mode
-    if state.distributed_type == DistributedType.DEEPSPEED:
-        return
-
-    if state.local_process_index == 0:
-        print("\n**Training integration test**")
-    training_check()
+    # if state.local_process_index == 0:
+    #     print("**Initialization**")
+    # init_state_check()
+    # state.wait_for_everyone()
+
+    # if state.distributed_type == DistributedType.MULTI_GPU:
+    #     num_processes_per_node = torch.cuda.device_count()
+    # else:
+    #     num_processes_per_node = state.num_processes
+
+    # # We only run this test on non-multinode
+    # if num_processes_per_node == state.num_processes:
+    #     if state.process_index == 0:
+    #         print("\n**Test process execution**")
+    #     process_execution_check()
+
+    #     if state.process_index == 0:
+    #         print("\n**Test split between processes as a list**")
+    #     test_split_between_processes_list()
+
+    #     if state.process_index == 0:
+    #         print("\n**Test split between processes as a dict**")
+    #     test_split_between_processes_nested_dict()
+
+    #     if state.process_index == 0:
+    #         print("\n**Test split between processes as a tensor**")
+    #     test_split_between_processes_tensor()
+
+    # if state.local_process_index == 0:
+    #     print("\n**Test random number generator synchronization**")
+    # rng_sync_check()
+
+    # if state.local_process_index == 0:
+    #     print("\n**DataLoader integration test**")
+    # dl_preparation_check()
+    # if state.distributed_type != DistributedType.TPU:
+    #     central_dl_preparation_check()
+
+    # # Trainings are not exactly the same in DeepSpeed and CPU mode
+    # if state.distributed_type == DistributedType.DEEPSPEED:
+    #     return
+
+    # if state.local_process_index == 0:
+    #     print("\n**Training integration test**")
+    # training_check()
 
     if state.local_process_index == 0:
         print("\n**Breakpoint test**")
     test_breakpoint()
 
+    AcceleratorState()._reset_state()
+
 
 if __name__ == "__main__":
     main()