Update README.md

README.md

@@ -20,7 +20,7 @@ Example chosen frame of GIF from CLIP
 
 Stage 1 (0-8k steps) The text encoder was trained along with the UNet at half precision for 15% of the total 8,000 steps (1,200 steps), and then the UNet was trained alone for the rest. I used a polynomial learning rate decay starting at 2e-6 (the default in fast-DreamBooth). "low quality" concatenated onto 1/3 of the prompts. Trained at 448x448
 
-Stage 2 (8k+) Text encoder trained 50% of steps, random choice "low quality" "lowres" "jpeg" concatenated onto 10% of prompts, starting at 1e-6 lr, trained at 384x384
+Stage 2 (8k-16k) Text encoder trained 50% of steps, random choice "low quality" "lowres" "jpeg" concatenated onto 10% of prompts, starting at 1e-6 lr, trained at 384x384
 
 ## How to use with `diffusers` library (section from [openjourney](https://huggingface.co/openjourney/openjourney))