Update README.md

README.md

@@ -8,4 +8,4 @@ Implemented as a **Multi-Layer Perceptron to classify handwritten Digits (0-9)**
 
 **Model Architecture and Results**
 
-The model comprises a flattening layer and three linear layers `((128, 64) hidden dimensions)` with relus to approximate non-linearity. It achieves 90% accuracy after `10 training epochs` and `batch size = 128`. Taining and Test MNIST datasets are loaded with PyTorch [dataloaders](https://pytorch.org/tutorials/beginner/basics/data_tutorial.html).
+The model comprises a flattening layer and three linear layers `((256, 64) hidden dimensions)` with relus to approximate non-linearity. It achieves 95.6% accuracy after `15 training epochs` and `batch size = 64`. Taining and Test MNIST datasets are loaded with PyTorch [dataloaders](https://pytorch.org/tutorials/beginner/basics/data_tutorial.html).