diff --git a/pufferlib/pufferl.py b/pufferlib/pufferl.py
index 7132a19f9..ad315e4fc 100644
--- a/pufferlib/pufferl.py
+++ b/pufferlib/pufferl.py
@@ -802,9 +802,9 @@ def stop(self):
         self.stopped = True
 
 def downsample(data_list, num_points):
-    if not data_list or num_points <= 0:
+    if not data_list or num_points < 0:
         return []
-    if num_points == 1:
+    if num_points <= 1:
         return [data_list[-1]]
     if len(data_list) <= num_points:
         return data_list
diff --git a/pufferlib/sweep.py b/pufferlib/sweep.py
index 73c510a62..0627f91d0 100644
--- a/pufferlib/sweep.py
+++ b/pufferlib/sweep.py
@@ -559,8 +559,8 @@ def __init__(self,
         self.gp_max_obs = gp_max_obs  # train time bumps after 800?
         self.infer_batch_size = infer_batch_size
 
-        # Probably useful only when downsample=1 and each run is expensive.
-        self.use_success_prob = sweep_config['downsample'] == 1
+        # Probably useful only when downsample is 0 or 1 in a config and each run is expensive.
+        self.use_success_prob = sweep_config['downsample'] in (0, 1)
         self.success_classifier = LogisticRegression(class_weight='balanced')
 
         # This model is conservative. Aggressive early stopping interferes with and hampers GP model learning.