diff --git a/composer/trainer/trainer.py b/composer/trainer/trainer.py
index eb5080eaee..cb42094f37 100644
--- a/composer/trainer/trainer.py
+++ b/composer/trainer/trainer.py
@@ -1723,9 +1723,12 @@ def __init__(
         # Load Checkpoint
         self._rng_state = None
         # If autoresume is enabled, first check for existing checkpoints to load
-        if autoresume:
+        self.autoresume = autoresume
+        if self.autoresume:
             log.info('Searching for a previous checkpoint to autoresume')
             error_message = ''
+            if max_duration is None:
+                error_message += 'The `max_duration` must be specified on trainer.__init__ when autoresume is enabled. '
             if save_folder is None:
                 error_message += 'The `save_folder` must be specified when autoresume is enabled. '
             if save_overwrite:
@@ -2188,10 +2191,21 @@ def fit(
 
         # Reset Time
         if reset_time:
+            if self.autoresume:
+                raise ValueError(
+                    'Cannot specify `reset_time=True` when autoresume is enabled. Please instead '
+                    'specify `load_ignore_keys` when constructing the Trainer, which will only '
+                    'run on the initial load and not any subsequent autoresumptions.',
+                )
             self.state.timestamp = Timestamp()
 
         # Max Duration
         if duration is not None:
+            if self.autoresume:
+                raise ValueError(
+                    '`duration` cannot be specified when autoresume is enabled. Please instead '
+                    'specify `max_duration` when constructing the Trainer.',
+                )
             duration = ensure_time(duration, TimeUnit.EPOCH)
             if duration.unit == TimeUnit.SECOND:
                 raise ValueError('Wall clock time not an allowed time unit.')
diff --git a/tests/trainer/test_checkpoint.py b/tests/trainer/test_checkpoint.py
index d23b55875f..dc887fa5e2 100644
--- a/tests/trainer/test_checkpoint.py
+++ b/tests/trainer/test_checkpoint.py
@@ -667,6 +667,7 @@ def get_trainer(
         max_duration: str = '2ep',
         latest_filename: str = 'latest-rank{rank}.pt',
         file_extension: str = '.pt',
+        use_scheduler: bool = True,
         **kwargs,
     ):
         if model is None:
@@ -704,7 +705,7 @@ def get_trainer(
             save_filename='ep{epoch}' + file_extension,
             max_duration=max_duration,
             optimizers=optimizer,
-            schedulers=ExponentialScheduler(gamma=0.9),
+            schedulers=ExponentialScheduler(gamma=0.9) if use_scheduler else None,
             callbacks=callbacks,
             **kwargs,
         )
@@ -1212,24 +1213,43 @@ def test_load_weights_object_store(self, tmp_path):
         )
 
     @pytest.mark.parametrize(
-        'run_name,save_folder,save_overwrite,latest_filename',
+        'run_name,save_folder,save_overwrite,latest_filename,max_duration',
         [
-            [None, 'first', False, 'latest-rank{rank}.pt'],
-            ['big-chungus', None, False, 'latest-rank{rank}.pt'],
-            ['big-chungus', 'first', True, 'latest-rank{rank}.pt'],
-            ['big-chungus', 'first', False, None],
+            [None, 'first', False, 'latest-rank{rank}.pt', '2ep'],
+            ['big-chungus', None, False, 'latest-rank{rank}.pt', '2ep'],
+            ['big-chungus', 'first', True, 'latest-rank{rank}.pt', '2ep'],
+            ['big-chungus', 'first', False, None, '2ep'],
+            ['big-chungus', 'first', False, 'latest-rank{rank}.pt', None],
         ],
     )
-    def test_autoresume_fail(self, run_name, save_folder, save_overwrite, latest_filename):
+    def test_autoresume_fail_init(self, run_name, save_folder, save_overwrite, latest_filename, max_duration):
         with pytest.raises(ValueError):
             self.get_trainer(
                 latest_filename=latest_filename,
                 save_overwrite=save_overwrite,
                 save_folder=save_folder,
                 run_name=run_name,
+                max_duration=max_duration,
                 autoresume=True,
+                use_scheduler=False,
             )
 
+    @pytest.mark.parametrize(
+        'duration,reset_time',
+        [
+            ['1ep', False],
+            [None, True],
+        ],
+    )
+    def test_autoresume_fail_fit(self, duration: Optional[str], reset_time: bool):
+        trainer = self.get_trainer(
+            run_name='bigtrainer',
+            save_folder='first',
+            autoresume=True,
+        )
+        with pytest.raises(ValueError):
+            trainer.fit(duration=duration, reset_time=reset_time)
+
     def test_different_run_names(self):
 
         trainer_1 = self.get_trainer(