diff --git a/classy_vision/optim/__init__.py b/classy_vision/optim/__init__.py
index 8337b64ecb..d149b4350b 100644
--- a/classy_vision/optim/__init__.py
+++ b/classy_vision/optim/__init__.py
@@ -41,17 +41,6 @@ def build_optimizer(config):
     param_scheduler_config = copy.deepcopy(config.get("param_schedulers", {}))
 
     # build the param schedulers
-    if "lr" in config and isinstance(config["lr"], dict):
-        message = (
-            'Passing an lr schedule in the config using "lr" is deprecated and '
-            "will be removed in version 0.2.0. See the docs for build_optimizer for "
-            "the recommended format."
-        )
-        warnings.warn(message, DeprecationWarning, stacklevel=2)
-        assert (
-            param_scheduler_config == {}
-        ), 'Cannot pass both "lr" and "param_schedulers" to the config'
-        param_scheduler_config = {"lr": config["lr"]}
     for cfg in param_scheduler_config.values():
         cfg["num_epochs"] = config["num_epochs"]
 
diff --git a/test/generic/optim_test_util.py b/test/generic/optim_test_util.py
index 60ca92a6cd..f9c992057f 100644
--- a/test/generic/optim_test_util.py
+++ b/test/generic/optim_test_util.py
@@ -200,7 +200,9 @@ def _test_lr_schedule(optimizer, num_epochs, epochs, targets):
         _test_lr_schedule(opt, num_epochs, epochs, targets)
 
         # Test step learning schedule
-        config["lr"] = {"name": "step", "values": [0.1, 0.01, 0.001]}
+        config["param_schedulers"] = {
+            "lr": {"name": "step", "values": [0.1, 0.01, 0.001]}
+        }
         opt = build_optimizer(config)
         opt.init_pytorch_optimizer(mock_classy_vision_model)
         targets = [0.1] * 8 + [0.01] * 3 + [0.001] * 4
@@ -209,15 +211,17 @@ def _test_lr_schedule(optimizer, num_epochs, epochs, targets):
         # Test step learning schedule with warmup
         init_lr = 0.01
         warmup_epochs = 0.1
-        config["lr"] = {
-            "name": "composite",
-            "schedulers": [
-                {"name": "linear", "start_value": init_lr, "end_value": 0.1},
-                {"name": "step", "values": [0.1, 0.01, 0.001]},
-            ],
-            "update_interval": "epoch",
-            "interval_scaling": ["rescaled", "fixed"],
-            "lengths": [warmup_epochs / num_epochs, 1 - warmup_epochs / num_epochs],
+        config["param_schedulers"] = {
+            "lr": {
+                "name": "composite",
+                "schedulers": [
+                    {"name": "linear", "start_value": init_lr, "end_value": 0.1},
+                    {"name": "step", "values": [0.1, 0.01, 0.001]},
+                ],
+                "update_interval": "epoch",
+                "interval_scaling": ["rescaled", "fixed"],
+                "lengths": [warmup_epochs / num_epochs, 1 - warmup_epochs / num_epochs],
+            }
         }
 
         opt = build_optimizer(config)