diff --git a/Reports/Thesis/verslag 13.synctex.gz b/Reports/Thesis/verslag 13.synctex.gz
index 0f652b3..d3fbabf 100644
Binary files a/Reports/Thesis/verslag 13.synctex.gz and b/Reports/Thesis/verslag 13.synctex.gz differ
diff --git a/Reports/Thesis/verslag 16.synctex.gz b/Reports/Thesis/verslag 16.synctex.gz
index 8125637..d3fbabf 100644
Binary files a/Reports/Thesis/verslag 16.synctex.gz and b/Reports/Thesis/verslag 16.synctex.gz differ
diff --git a/Reports/Thesis/verslag 17.synctex.gz b/Reports/Thesis/verslag 17.synctex.gz
index 8c7d715..d3fbabf 100644
Binary files a/Reports/Thesis/verslag 17.synctex.gz and b/Reports/Thesis/verslag 17.synctex.gz differ
diff --git a/src/training_scripts/diffusion_training.py b/src/training_scripts/diffusion_training.py
index 3f91dca..7a60569 100644
--- a/src/training_scripts/diffusion_training.py
+++ b/src/training_scripts/diffusion_training.py
@@ -2,7 +2,7 @@ from src.utils.clearml import ClearMLHelper
 
 clearml_helper = ClearMLHelper(project_name="Thesis/NrvForecast")
 task = clearml_helper.get_task(
-    task_name="Diffusion Training (GRUs): hidden_sizes=[1024, 1024] (300 steps), lr=0.0001, time_dim=8 + NRV + L + W + PV + NP",
+    task_name="Diffusion Training (GRU - 2048): hidden_sizes=[512, 512] (300 steps), lr=0.0001, time_dim=8 + NRV + L + W + PV + NP",
 )
 task.execute_remotely(queue_name="default", exit_process=True)
 
@@ -42,7 +42,7 @@ print("Input dim: ", inputDim)
 model_parameters = {
     "epochs": 15000,
     "learning_rate": 0.0001,
-    "hidden_sizes": [1024, 1024],
+    "hidden_sizes": [512, 512],
     "time_dim": 8,
 }
 
@@ -61,7 +61,7 @@ model = GRUDiffusionModel(
     model_parameters["hidden_sizes"],
     other_inputs_dim=inputDim[2],
     time_dim=model_parameters["time_dim"],
-    gru_hidden_size=512,
+    gru_hidden_size=2048,
 )
 
 ### Policy Evaluator ###