
machinable
A modular configuration system for machine learning research
deviation: 0.5
components:
- baseline_model:
learning_rate: base_learning_rate(2**-7)
distribution:
name: normal
sigma: $.deviation
mu: 0
~heavytailed:
distribution:
name: lognormal
sigma: 1.0
- biased_model^baseline_model:
distribution:
# overwrite mean to introduces some bias
mu: -0.5
control_variate: True
- +.kaggle.sota_model:
control_variate: True
experiment = Experiment().component('biased_model',
[('~heavytailed', {'learning_rate': lr})
for lr in (0.25, 0.1, 0.5)]).repeat(3)
execute(
experiment,
storage='s3://bucket/results',
engine='ray'
)