This is a trained model for handwriting recognition using **hojjatk/mnist-dataset** dataset.

    ## Usage
    ```python
    model = torch.load("mnsit_digit_nn")
    model.eval()
    ```

    ## Training Param:
    epochs = 300
    batch_size = 64
    learning_rate = 0.001

    ## Model Architectue:
    ['(fc1): Linear(in_features=784, out_features=128, bias=True)', '(fc2): Linear(in_features=128, out_features=64, bias=True)', '(fc3): Linear(in_features=64, out_features=10, bias=True)', '(relu): ReLU()', '(dropout): Dropout(p=0.2, inplace=False)']
    
    ## Evaluation Results
    - Accuracy: 0.98
    - Precision: 0.98
    - Recall: 0.98