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Low Accuracy on MNIST Dataset by CNN model built using GNN Bundles in ECL

I am working on a project using ECL and GNN bundles to train a convolutional neural network (CNN) on the MNIST dataset. The model architecture includes three convolutional layers with batch normalization and ReLU activation, followed by max-pooling layers, and ending with three dense layers. Despite normalizing and reshaping the data correctly and using categorical cross-entropy as the loss function with the Adam optimizer, I am observing very low accuracy on the test set. The training accuracy does not improve significantly beyond a certain point. I have implemented the model architecture and data preprocessing steps correctly. Any suggestions on what might be causing this issue or how to improve the model’s accuracy would be greatly appreciated.

Roxie query timeout

Exception
Reported by: WsEcl
Message: [ -6: timeout expired Target: C!:49918 -> 192.168.0.200:9876 (20), Raised in: jsocket.cpp, line 2034]