diff --git a/egs/librispeech/ASR/pruned_transducer_stateless7/scaling.py b/egs/librispeech/ASR/pruned_transducer_stateless7/scaling.py
index 687fd6def..7cc8d9bb0 100644
--- a/egs/librispeech/ASR/pruned_transducer_stateless7/scaling.py
+++ b/egs/librispeech/ASR/pruned_transducer_stateless7/scaling.py
@@ -1216,7 +1216,7 @@ class TanSwish(torch.nn.Module):
 
 class SwooshFunction(torch.autograd.Function):
     """
-      swoosh(x) =  log(1 + exp(x-4)) - 0.08*x - 0.15
+      swoosh(x) =  log(1 + exp(x-1)) - 0.08*x - 0.313261687
 
      derivatives are between -0.08 and 0.92.
     """
@@ -1235,7 +1235,7 @@ class SwooshFunction(torch.autograd.Function):
             with torch.enable_grad():
                 x = x.detach()
                 x.requires_grad = True
-                y = torch.logaddexp(zero, x - 1.125)  - 0.08 * x - 0.3
+                y = torch.logaddexp(zero, x - 1.)  - 0.08 * x - 0.313261687
 
                 if not requires_grad:
                     return y
@@ -1273,7 +1273,7 @@ class Swoosh(torch.nn.Module):
         """
         if torch.jit.is_scripting():
             zero = torch.tensor(0.0, dtype=x.dtype, device=x.device)
-            return torch.logaddexp(zero, x - 1.125)  - 0.08 * x - 0.3
+            return torch.logaddexp(zero, x - 1.)  - 0.08 * x - 0.313261687
         return SwooshFunction.apply(x)
 
 
diff --git a/egs/librispeech/ASR/pruned_transducer_stateless7/zipformer.py b/egs/librispeech/ASR/pruned_transducer_stateless7/zipformer.py
index 80898f7a3..ff898040c 100644
--- a/egs/librispeech/ASR/pruned_transducer_stateless7/zipformer.py
+++ b/egs/librispeech/ASR/pruned_transducer_stateless7/zipformer.py
@@ -1551,7 +1551,7 @@ class ConvolutionModule(nn.Module):
     def __init__(
         self, channels: int, kernel_size: int,
     ) -> None:
-        """Construct an ConvolutionModule object."""
+        """Construct a ConvolutionModule object."""
         super(ConvolutionModule, self).__init__()
         # kernerl_size should be a odd number for 'SAME' padding
         assert (kernel_size - 1) % 2 == 0
@@ -1601,7 +1601,7 @@ class ConvolutionModule(nn.Module):
             min_positive=ScheduledFloat((0.0, 0.1), (8000.0, 0.05)),
             max_positive=1.0,
             min_abs=0.4,
-            max_abs=ScheduledFloat((0.0, 10.0), (8000.0, 20.0), default=10),
+            max_abs=10.0,
         )
 
         self.activation = Swoosh()