diff --git a/configs/RectifiedFlow_test.yaml b/configs/RectifiedFlow_test.yaml
index af55342b..d0e8fae2 100644
--- a/configs/RectifiedFlow_test.yaml
+++ b/configs/RectifiedFlow_test.yaml
@@ -8,3 +8,7 @@ T_start: 0
 T_start_infer: 0
 sampling_steps: 10
 time_scale_factor: 1000
+
+diff_speedup: 100
+timestep_type: 'continuous' #discrete
+loss_clip_min: 0.5
\ No newline at end of file
diff --git a/modules/losses/diff_loss.py b/modules/losses/diff_loss.py
index 50a46a24..05654992 100644
--- a/modules/losses/diff_loss.py
+++ b/modules/losses/diff_loss.py
@@ -3,6 +3,7 @@
 import torch
 
 
+from utils.hparams import hparams
 class DiffusionNoiseLoss(nn.Module):
     def __init__(self, loss_type):
         super().__init__()
@@ -30,6 +31,7 @@ def l2_rf_norm(self, x_recon, noise, timestep):
         timestep=torch.clip(timestep, 0+eps, 1-eps)
         weights = 0.398942 / timestep / (1 - timestep) * torch.exp(
             -0.5 * torch.log(timestep / (1 - timestep)) ** 2) + eps
+        weights = torch.clip(weights, hparams['loss_clip_min'],  )
         return weights[:, None, None, None] * self.loss(x_recon, noise)
 
     def _forward(self, x_recon, noise, timestep=None):