Update README.md

README.md

@@ -6,8 +6,28 @@ tags:
 library_name: diffusers
 ---
 
-Diffusion model trained on thousands of public images from [image data resource](https://idr.openmicroscopy.org/cell/) to create highly detailed accurate depictions of flourescent and super-resolution cell images. 
+Diffusion model trained on a public dataset of images from [image data resource](https://idr.openmicroscopy.org/cell/) to create highly detailed accurate depictions of flourescent and super-resolution cell images. 
 ![image](samples/0049.png)
 
 # Ground-truth image data obtained from idr:
-![realsamples](samples/real_samples.png)
+![realsamples](samples/real_samples.png)
+
+
+The role of generative AI in the science is a new discussion and the merits of it have yet to be evaluated. Whilst current image-to-image and text-to-image models make it easier than ever to create stunning images, they lack the specific training sets to replicate accurate and detailed images found in flourescent cell microscopy. 
+We propose ddpm-IRIS, a difusion network leveraging Google's [Diffusion Model](https://arxiv.org/abs/2006.11239) to generate visual depitctions of cell features with more detail than traditional models.
+  
+Hyperparameters:
+   - image_size = 256  
+   - train_batch_size = 16
+   - eval_batch_size = 16 
+   - num_epochs = 50
+   - gradient_accumulation_steps = 1
+   - learning_rate = 1e-4
+   - lr_warmup_steps = 500
+   - save_image_epochs = 10
+   - save_model_epochs = 30
+   - mixed_precision = 'fp16' 
+
+
+trained on 1 Nvidia A100 40GB GPU over 50 epochs for 2.5 hours. 
+