
# Model Card: Sudoku Net 1.0

## Model Overview

- A Neural Network that solves Sudoku puzzles

## Intended Use

- **Use Cases:** SuDoKu is a research project aimed at exploring the capabilities of Neural Networks in SuDoKu Puzzles. It serves as an experimental tool rather than a specific real-world application.

## Training Details

- Optimizer: Adam
- Learning Rate: 1e-3
- Batch Size: 64K
- Training Dataset [Sudoku Dataset](https://huggingface.co/datasets/Ritvik19/Sudoku-Dataset)

### Model Architecture

- **Model Type:** Feed Forward Neural Network
- **Architecture Details:** Consists of two Linear layers, each with 64 units, followed by 81 output branches. ReLu activation was used for hidden layers.

## Performance Metrics

- Evaluation Metric: Accuracy (determined by whether the model correctly solves a problem or not)

## Model Usage

- Users can interact with the model through this [Space](https://huggingface.co/spaces/Ritvik19/SudokuNetDemo).
{"license": "apache-2.0", "datasets": ["Ritvik19/Sudoku-Dataset"]}
dataset:Ritvik19/Sudoku-Dataset license:apache-2.0 has_space region:us