Changes to my CNN & training.

I tried to reduce overfitting on a small dataset. I increased dropout to 0.5, added L2 regularization, and simplified the architecture by removing a convolutional block. Should improve generalization.

Examining the results of training the CNN model show that there is still significant overfitting. I will need to improve this.

Performance evaluation:

• Training loss drops but val loss remains igher showing overfitting
• Training accuracy reaches very high but val acc lags behind. Shows that model is learning patterns specific to dataset.

To-Do:

• Add time-series data augmentation to increase effective dataset size
  -Reduce model capacity
• Tune regularization
  -Tune optimizer/LR