README.md

---
license: mit
metrics:
- accuracy
---
# SolveQ

Simple neural network that learns `y = 2x + 3`. Built with PyTorch.

## What it does

Trains a small network to approximate a linear function. The model has one hidden layer and learns from synthetic data.

## Setup

```bash
pip install -r requirements.txt
```

## Running

Train the model:

```bash
python src/train.py
```

This generates 200 samples, trains for 1000 epochs, shows the loss plot, and saves to `models/model.pt`.

![Training Loss](models/loss.png)

Make predictions:

```bash
python src/predict.py
```

Predicts `x = 4.0` by default. To test other values, edit the `predict()` call in `predict.py`.

## Model

- Input: 1 neuron
- Hidden: 16 neurons (ReLU)
- Output: 1 neuron

Uses Adam optimizer (lr=0.01) and MSE loss.