def default() -> dict:
"""The default hyperparameters.
It will have a version key and a list of candidate models.
Each model has its own search space inside.
"""
ret = {
'version': 1,
'models': {
'BertForTextPredictionBasic': {
'search_space': {
'model.backbone.name': 'google_electra_small',
'optimization.batch_size': 32,
'optimization.num_train_epochs': 4,
'optimization.lr': space.Real(1E-5, 1E-4)
}
},
},
'hpo_params': {
'search_strategy':
'random', # Can be 'random', 'bayesopt', 'skopt',
# 'hyperband', 'bayesopt_hyperband'
'search_options': None, # Extra kwargs passed to searcher
'scheduler_options': None, # Extra kwargs passed to scheduler
'time_limits': None, # The total time limit
'num_trials': 4, # The number of trials
}
}
return ret
def default() -> dict:
"""The default hyperparameters.
It will have a version key and a list of candidate models.
Each model has its own search space inside.
"""
ret = {
'version': 1,
'models': {
'BertForTextPredictionBasic': {
'search_space': {
'model.backbone.name': 'google_electra_small',
'optimization.batch_size': 32,
'optimization.num_train_epochs': 4,
'optimization.lr': space.Real(1E-5, 1E-4)
}
},
},
'hpo_params': {
'scheduler': 'fifo', # Can be 'fifo', 'hyperband'
'search_strategy': 'random', # Can be 'random', 'skopt', or 'bayesopt'
'search_options': None, # The search option
'time_limits': None, # The total time limit
'num_trials': 4, # The number of trials
'reduction_factor': 4, # The reduction factor
'grace_period': 10, # The grace period
'max_t': 50, # The max_t in the hyperband
'time_attr': 'report_idx' # The time attribute used in hyperband searcher.
# We report the validation accuracy 10 times each epoch.
}
}
return ret