diff --git a/README.md b/README.md
index a73eead0b..6e2ae3376 100644
--- a/README.md
+++ b/README.md
@@ -77,9 +77,9 @@ There are many unknown points in FLUX.1 training, so some settings can be specif
 
 The existing `--loss_type` option may be useful for FLUX.1 training. The default is `l2`.
 
-~~In our experiments, `--timestep_sampling sigma --model_prediction_type raw --discrete_flow_shift 1.0` with `--loss_type l2` seems to work better than the default (SD3) settings. The multiplier of LoRA should be adjusted. ~~
+~~In our experiments, `--timestep_sampling sigma --model_prediction_type raw --discrete_flow_shift 1.0` with `--loss_type l2` seems to work better than the default (SD3) settings. The multiplier of LoRA should be adjusted.~~
 
-In our experiments, `--timestep_sampling shift --discrete_flow_shift 3.1582 --model_prediction_type raw --guidance_scale 1.0` with `--loss_type l2` seems to work better than other settings. 
+In our experiments, `--timestep_sampling shift --discrete_flow_shift 3.1582 --model_prediction_type raw --guidance_scale 1.0` (with the default `l2` loss_type) seems to work better. 
 
 The settings in [AI Toolkit by Ostris](https://github.com/ostris/ai-toolkit) seems to be equivalent to `--timestep_sampling sigmoid --model_prediction_type raw --guidance_scale 1.0` (with the default `l2` loss_type). 
 
@@ -92,10 +92,13 @@ Other options are described below.
 `--timestep_sampling` and `--sigmoid_scale`, `--discrete_flow_shift` adjust the distribution of timesteps. The distribution is shown in the figures below.
 
 The effect of `--discrete_flow_shift` with `--timestep_sampling shift` (when `--sigmoid_scale` is not specified, the default is 1.0):
+![Figure_2](https://github.com/user-attachments/assets/d9de42f9-f17d-40da-b88d-d964402569c6)
 
-The difference between `--timestep_sampling uniform` and `--timestep_sampling sigma`:
+The difference between `--timestep_sampling sigmoid` and `--timestep_sampling uniform` (when `--timestep_sampling sigmoid` or `uniform` is specified, `--discrete_flow_shift` is ignored):
+![Figure_3](https://github.com/user-attachments/assets/27029009-1f5d-4dc0-bb24-13d02ac4fdad)
 
 The effect of `--timestep_sampling sigmoid` and `--sigmoid_scale` (when `--timestep_sampling sigmoid` is specified, `--discrete_flow_shift` is ignored):
+![Figure_4](https://github.com/user-attachments/assets/08a2267c-e47e-48b7-826e-f9a080787cdc)
 
 #### Key Features for FLUX.1 LoRA training