Update README.md

README.md

@@ -47,7 +47,7 @@ large dataset of SCC brightfield images.
 The results of these models were pretty impressive, but still needed many images.
 Hence, this dataset was created to test the capabilities of dreambooth on brightfield microscopy image generation.
 I'm testing several configurations:
-- Diffusion Model Architectures (SD-1.5, SD-2.1, SDXL 1.0)
+- Diffusion Model Architectures (SD-1.5(, SD-2.1, SDXL 1.0)) -- The last two had to be discontinued due to time, and compute constraints
 - Training Data Size (10, 20, 30, 50)
 - 4 Concepts are trained in parallel (cell, cell rug, well edge, debris)
 - With and without subject class images for class-specific prior preservation loss impact assessment
@@ -59,7 +59,7 @@ The dataset consists of several classes:
 - Generated images from SDXL 1.0, one class for each concept
 
 These classes are used in the concepts for the dreambooth model training,
-resulting in 24 models trained to assess the usability of dreambooth in this domain.
+resulting in 8 models trained to assess the usability of dreambooth in this domain.
 Unfortunately, due to time constraints, I'm not able to test many hyperparameter configurations for each model, nor play around
 a lot with prompt engineering.
-This research serves as a base others (or me) can work upon.
+This research serves as a base thath others (or me) can work upon.