diff --git a/scripts/ast/run.sh b/scripts/ast/run.sh
index e506c8b..b65c8e3 100755
--- a/scripts/ast/run.sh
+++ b/scripts/ast/run.sh
@@ -1,3 +1,3 @@
 #!/bin/bash
 
-./scripts/ast/train.sh nt2n_base 04Jul_nt2n_base_new_embedding_size
\ No newline at end of file
+./scripts/ast/train.sh nt2n_base_attention_plus_layered 04Jun_nt2n_base_attention_plus_layered_new_embedding_size
\ No newline at end of file
diff --git a/scripts/ast/train.sh b/scripts/ast/train.sh
index d584aeb..357dbb4 100755
--- a/scripts/ast/train.sh
+++ b/scripts/ast/train.sh
@@ -13,7 +13,7 @@ PYTHONPATH=. python3 -m cProfile -o program.prof zerogercrnn/experiments/ast_lev
     --data_limit 100000 \
     --model_save_dir saved/$2 \
     --seq_len 50 \
-    --batch_size 80 \
+    --batch_size 128 \
     --learning_rate 0.001 \
     --epochs 8 \
     --decay_after_epoch 0 \
diff --git a/zerogercrnn/experiments/ast_level/common.py b/zerogercrnn/experiments/ast_level/common.py
index 4b81a24..f7e06a8 100644
--- a/zerogercrnn/experiments/ast_level/common.py
+++ b/zerogercrnn/experiments/ast_level/common.py
@@ -153,7 +153,7 @@ def optimize(self, loss):
         # Backward pass
         loss.backward()
         torch.nn.utils.clip_grad_norm_(filter_requires_grad(self.model.parameters()), 5)
-        # torch.nn.utils.clip_grad_norm_(filter_requires_grad(self.model.sparse_parameters()), 5)
+        torch.nn.utils.clip_grad_norm_(filter_requires_grad(self.model.sparse_parameters()), 5)
 
         # Optimizer step
         for optimizer in self.optimizers: