Manual/Modules/Neural-Network-Training.md

@@ -33,11 +33,7 @@ The script implements an early stopping mechanism based on validation loss to pr
 
 ### Evaluation and Results Logging
 
-The script evaluates the trained model on the validation dataset, calculates the R2 score, and logs relevant information. The results, including training metadata, are serialized into a JSON file.
-
-### Conclusion
-
-The module provides a comprehensive and flexible approach to training PyTorch neural networks on DAQ data. It can be configured through command-line arguments and a YAML configuration file, making it adaptable to different datasets and training scenarios. The logging and result-saving functionalities contribute to its usability and transparency.
+The script evaluates the trained model on the validation dataset, calculates the R2 score, and logs relevant information. The results, including training metadata, are serialized into a JSON file. The model is saved as a .pth file
 
 
 ## Usage