TriangleModel_PyTorch

A lightweight PyTorch implementation of the Triangle Model (Harm and Seidenberg, 2004).

• model.py: Gradient computation.
• dataset.py: Data utilities.
• train.py: Training utilities + ODE solver.
• benchmark.py: Runs phased training procedure. Saves losses + accuracies.
• evaluation.py: Plots behavioral results.

To run the default set of experiments,

python3 benchmaking.py -ID baseline -model_config configs/baseline/model_config.json -trainer_config configs/baseline/trainer_config.json -optimizer_config configs/baseline/opt_config.json
python3 evaluation.py -ID baseline -model_config configs/baseline/model_config.json -trainer_config configs/baseline/trainer_config.json