diff --git a/src/axolotl/monkeypatch/relora.py b/src/axolotl/monkeypatch/relora.py
index e4352cbe3..5226b9e03 100644
--- a/src/axolotl/monkeypatch/relora.py
+++ b/src/axolotl/monkeypatch/relora.py
@@ -48,6 +48,7 @@ def reset_optimizer(
     optimizer_state_keys: list[str],
     prune_ratio: float = 0.9,
 ):
+    # pylint:disable=unused-argument
     pruning_fn = partial(magnitude_pruning_, prune_ratio=prune_ratio)
     n_zeros = 0
     n_total = 0
@@ -56,16 +57,16 @@ def reset_optimizer(
     if isinstance(optimizer, ZeroRedundancyOptimizer):
         optimizer_state = optimizer.optim.state
 
-    for param in reset_params:
-        param_state = optimizer_state[param]
-        if len(param_state) == 0:  # no state for this param, happens for ZeRo optimizer
-            continue
-        for key in optimizer_state_keys:
-            pruning_fn(
-                param_state[key]
-            )  # pruning fn has to be inplace to keep the same keys in the dict
-            n_total += param_state[key].numel()
-            n_zeros += torch.sum(param_state[key] == 0).item()
+    for group in optimizer.param_groups:
+        for param in group["params"]:
+            state = optimizer_state[param]
+            for key, value in state.items():
+                if key not in optimizer_state_keys:
+                    continue
+                if torch.is_tensor(value):
+                    pruning_fn(value)
+                    n_total += value.numel()
+                    n_zeros += torch.sum(value == 0).item()
 
     _zeroed = n_zeros / (1e-7 + n_total) * 100
     LOG.info(f"Percent of optimizer states zeroed: {_zeroed:.2f}")