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keras-tuner-tutorial

Hands on tutorial for keras-tuner

This repo aims at introducing hyperparameter tuning through the Keras Tuner library. It provides a comparison of its different tuners, applied to computer vision through the CIFAR10 dataset.

This is work in progress, all feedback is welcomed.

Install the project

  • Clone the repo
  • Create a virtualenv and activate it:
virtualenv -p python3 venv
source venv/bin/activate
  • Install the requirements:
pip install requirements.txt

Results

Tasks duration was measured on an RTX 2080 GPU

Tuner Search time Best accuracy (%)
Worst Baseline 20min 63.1
Default Baseline 20min 74.5
Random Search 10h 59min 76.8
Hyperband 10h 0min 75.1

Here, the worst baseline is the worst accuracy obtained by a set of hyperparameters during random search. The default baseline is obtained by setting all hyperparameters to their default value.

Run the baseline

python baseline.py

Run the comparison

Available tuners :

  • Random Search
  • Hyperband
python tuner_comparison.py

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  • Python 100.0%