diff --git a/codes/models/gpt_voice/unet_diffusion_tts7.py b/codes/models/gpt_voice/unet_diffusion_tts7.py
index b17fc056..fc3e620a 100644
--- a/codes/models/gpt_voice/unet_diffusion_tts7.py
+++ b/codes/models/gpt_voice/unet_diffusion_tts7.py
@@ -426,6 +426,7 @@ class DiffusionTts(nn.Module):
         if not self.component_gradient_boosting:
             return
         MIN_PROPORTIONAL_BOOST_LEVEL = .5
+        MAX_MULTIPLIER = 100
         components = [list(self.contextual_embedder.parameters()), list(self.middle_block.parameters()), list(self.conditioning_encoder.parameters()),
                       list(self.unaligned_encoder.parameters())]
         input_norm = torch.norm(torch.stack([torch.norm(p.grad.detach(), 2) for p in self.input_blocks.parameters()]), 2)
@@ -436,6 +437,7 @@ class DiffusionTts(nn.Module):
             norm = torch.norm(torch.stack([torch.norm(p.grad.detach(), 2) for p in component]), 2)
             if norm < min_norm:
                 mult = min_norm / (norm + 1e-8)
+                mult = min(mult, MAX_MULTIPLIER)
                 for p in component:
                     p.grad.data.mul_(mult)