metadata
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
pip install -r requirements.txt
Running
Train the model:
python src/train.py
This generates 200 samples, trains for 1000 epochs, shows the loss plot, and saves to models/model.pt.
Make predictions:
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.