Reduced default batch size to 128
@@ -253,7 +253,7 @@ class ParameterizedRatioEstimator(Estimator):
alpha=1.0,
optimizer="amsgrad",
n_epochs=50,
- batch_size=200,
+ batch_size=128,
initial_lr=0.001,
final_lr=0.0001,
nesterov_momentum=None,
@@ -302,7 +302,7 @@ class ParameterizedRatioEstimator(Estimator):
Number of epochs. Default value: 50.
batch_size : int, optional
- Batch size. Default value: 200.
+ Batch size. Default value: 128.
initial_lr : float, optional
Learning rate during the first epoch, after which it exponentially decays to final_lr. Default value:
@@ -631,7 +631,7 @@ class DoubleParameterizedRatioEstimator(Estimator):
alpha=1.0,
optimizer="amsgrad",
n_epochs=50,
- batch_size=200,
+ batch_size=128,
initial_lr=0.001,
final_lr=0.0001,
nesterov_momentum=None,
@@ -686,7 +686,7 @@ class DoubleParameterizedRatioEstimator(Estimator):
Number of epochs. Default value: 50.
batch_size : int, optional
- Batch size. Default value: 200.
+ Batch size. Default value: 128.
initial_lr : float, optional
Learning rate during the first epoch, after which it exponentially decays to final_lr. Default value:
@@ -1045,7 +1045,7 @@ class ScoreEstimator(Estimator):
t_xz,
optimizer="amsgrad",
n_epochs=50,
- batch_size=200,
+ batch_size=128,
initial_lr=0.001,
final_lr=0.0001,
nesterov_momentum=None,
@@ -1081,7 +1081,7 @@ class ScoreEstimator(Estimator):
Number of epochs. Default value: 50.
batch_size : int, optional
- Batch size. Default value: 200.
+ Batch size. Default value: 128.
initial_lr : float, optional
Learning rate during the first epoch, after which it exponentially decays to final_lr. Default value:
@@ -1539,7 +1539,7 @@ class LikelihoodEstimator(Estimator):
alpha=1.0,
optimizer="amsgrad",
n_epochs=50,
- batch_size=200,
+ batch_size=128,
initial_lr=0.001,
final_lr=0.0001,
nesterov_momentum=None,
@@ -1581,7 +1581,7 @@ class LikelihoodEstimator(Estimator):
Number of epochs. Default value: 50.
batch_size : int, optional
- Batch size. Default value: 200.
+ Batch size. Default value: 128.
initial_lr : float, optional
Learning rate during the first epoch, after which it exponentially decays to final_lr. Default value:
