diff --git a/config/eval/solver/gradient.yaml b/config/eval/solver/gradient.yaml
index c3e4094..e94d9da 100644
--- a/config/eval/solver/gradient.yaml
+++ b/config/eval/solver/gradient.yaml
@@ -1,8 +1,8 @@
 _target_: stable_worldmodel.solver.GradientSolver
 model: ???
 # Original adam.yaml reference: n_steps=30, num_samples=100, batch_size=1, lr=0.1.
-n_steps: 125
-batch_size: 50
+n_steps: 90
+batch_size: 100
 num_samples: 1
 action_noise: 0
 device: "cuda"
@@ -11,4 +11,4 @@ optimizer_cls:
   _target_: hydra.utils.get_class
   path: torch.optim.AdamW
 optimizer_kwargs:
-  lr: 0.05
+  lr: 0.075
diff --git a/pusht_results.txt b/pusht_results.txt
index bc865a6..163b065 100644
--- a/pusht_results.txt
+++ b/pusht_results.txt
@@ -1490,3 +1490,135 @@ evaluation_time: 16.060093879699707 seconds
 inference_precision: fp16
 inference_compile_target: predictor
 inference_compile_mode: reduce-overhead
+
+==== CONFIG ====
+cache_dir: null
+solver:
+  _target_: stable_worldmodel.solver.GradientSolver
+  model: ???
+  n_steps: 125
+  batch_size: 50
+  num_samples: 1
+  action_noise: 0
+  device: cuda
+  seed: ${seed}
+  optimizer_cls:
+    _target_: hydra.utils.get_class
+    path: torch.optim.AdamW
+  optimizer_kwargs:
+    lr: 0.05
+world:
+  env_name: swm/PushT-v1
+  num_envs: ${eval.num_eval}
+  max_episode_steps: ???
+  history_size: 1
+  frame_skip: 1
+dataset:
+  stats: ${eval.dataset_name}
+  keys_to_cache:
+  - action
+  - proprio
+  - state
+seed: 42
+policy: pusht/lewm
+inference_precision: fp16
+plan_config:
+  horizon: 5
+  receding_horizon: 5
+  action_block: 5
+eval:
+  num_eval: 50
+  goal_offset_steps: 25
+  eval_budget: 50
+  img_size: 224
+  save_video: false
+  dataset_name: pusht_expert_train
+  callables:
+  - method: _set_state
+    args:
+      state:
+        value: state
+  - method: _set_goal_state
+    args:
+      goal_state:
+        value: goal_state
+output:
+  filename: pusht_results.txt
+
+==== RESULTS ====
+metrics: {'success_rate': 90.0, 'episode_successes': array([ True, False,  True,  True,  True,  True,  True,  True,  True,
+        True, False,  True,  True,  True,  True,  True, False,  True,
+        True,  True,  True,  True,  True,  True,  True,  True,  True,
+        True,  True,  True,  True,  True,  True,  True,  True,  True,
+        True,  True,  True, False,  True,  True, False,  True,  True,
+        True,  True,  True,  True,  True]), 'seeds': None}
+evaluation_time: 16.087822437286377 seconds
+inference_precision: fp16
+inference_compile_target: predictor
+inference_compile_mode: reduce-overhead
+
+==== CONFIG ====
+cache_dir: null
+solver:
+  _target_: stable_worldmodel.solver.GradientSolver
+  model: ???
+  n_steps: 90
+  batch_size: 100
+  num_samples: 1
+  action_noise: 0
+  device: cuda
+  seed: ${seed}
+  optimizer_cls:
+    _target_: hydra.utils.get_class
+    path: torch.optim.AdamW
+  optimizer_kwargs:
+    lr: 0.075
+world:
+  env_name: swm/PushT-v1
+  num_envs: ${eval.num_eval}
+  max_episode_steps: ???
+  history_size: 1
+  frame_skip: 1
+dataset:
+  stats: ${eval.dataset_name}
+  keys_to_cache:
+  - action
+  - proprio
+  - state
+seed: 42
+policy: pusht/lewm
+inference_precision: fp16
+plan_config:
+  horizon: 5
+  receding_horizon: 5
+  action_block: 5
+eval:
+  num_eval: 50
+  goal_offset_steps: 25
+  eval_budget: 50
+  img_size: 224
+  save_video: false
+  dataset_name: pusht_expert_train
+  callables:
+  - method: _set_state
+    args:
+      state:
+        value: state
+  - method: _set_goal_state
+    args:
+      goal_state:
+        value: goal_state
+output:
+  filename: pusht_results.txt
+
+==== RESULTS ====
+metrics: {'success_rate': 92.0, 'episode_successes': array([ True, False,  True,  True,  True,  True,  True,  True,  True,
+        True, False,  True,  True,  True,  True,  True, False,  True,
+        True,  True,  True,  True,  True,  True,  True,  True,  True,
+        True,  True,  True,  True,  True,  True,  True,  True,  True,
+        True,  True,  True,  True,  True,  True, False,  True,  True,
+        True,  True,  True,  True,  True]), 'seeds': None}
+evaluation_time: 15.248084306716919 seconds
+inference_precision: fp16
+inference_compile_target: predictor
+inference_compile_mode: reduce-overhead