References

1. Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization: https://arxiv.org/pdf/1603.06560.pdf
2. A SYSTEM FOR MASSIVELY PARALLEL HYPERPARAMETER TUNING: https://arxiv.org/pdf/1810.05934.pdf
3. Amazon SageMaker Automatic Model Tuning now provides up to three times faster hyperparameter tuning with Hyperband: https://aws.amazon.com/blogs/machine-learning/amazon-sagemaker-automatic-model-tuning-now-provides-up-to-three-times-faster-hyperparameter-tuning-with-hyperband/
4. amazon-sagemaker-examples: https://github.com/aws/amazon-sagemaker-examples/blob/main/training/distributed_training/pytorch/model_parallel/gpt2/smp-train-gpt-simple.ipynb
5. HyperparameterTuner: https://sagemaker.readthedocs.io/en/stable/api/training/tuner.html
6. amazon-sagemaker-examples: https://github.com/aws/amazon-sagemaker-examples/blob/main/hyperparameter_tuning/analyze_results/HPO_Analyze_TuningJob_Results.ipynb