NlpFixedParameters Class

Configuration of fixed parameters for all candidates of an AutoML NLP Job

Inheritance

azure.ai.ml.entities._mixins.RestTranslatableMixin

NlpFixedParameters

Constructor

NlpFixedParameters(*, gradient_accumulation_steps: int | None = None, learning_rate: float | None = None, learning_rate_scheduler: str | None = None, model_name: str | None = None, number_of_epochs: int | None = None, training_batch_size: int | None = None, validation_batch_size: int | None = None, warmup_ratio: float | None = None, weight_decay: float | None = None)

Parameters

Name	Description
gradient_accumulation_steps Required	Optional[int] number of steps over which to accumulate gradients before a backward pass. This must be a positive integer, defaults to None
learning_rate Required	Optional[float] initial learning rate. Must be a float in (0, 1), defaults to None
learning_rate_scheduler Required	Optional[str] the type of learning rate scheduler. Must choose from 'linear', 'cosine', 'cosine_with_restarts', 'polynomial', 'constant', and 'constant_with_warmup', defaults to None
model_name Required	Optional[str] the model name to use during training. Must choose from 'bert-base-cased', 'bert-base-uncased', 'bert-base-multilingual-cased', 'bert-base-german-cased', 'bert-large-cased', 'bert-large-uncased', 'distilbert-base-cased', 'distilbert-base-uncased', 'roberta-base', 'roberta-large', 'distilroberta-base', 'xlm-roberta-base', 'xlm-roberta-large', xlnet-base-cased', and 'xlnet-large-cased', defaults to None
number_of_epochs Required	Optional[int] the number of epochs to train with. Must be a positive integer, defaults to None
training_batch_size Required	Optional[int] the batch size during training. Must be a positive integer, defaults to None
validation_batch_size Required	Optional[int] the batch size during validation. Must be a positive integer, defaults to None
warmup_ratio Required	Optional[float] ratio of total training steps used for a linear warmup from 0 to learning_rate. Must be a float in [0, 1], defaults to None
weight_decay Required	Optional[float] value of weight decay when optimizer is sgd, adam, or adamw. This must be a float in the range [0, 1] defaults to None

Keyword-Only Parameters

Name	Description
gradient_accumulation_steps Required
learning_rate Required
learning_rate_scheduler Required
model_name Required
number_of_epochs Required
training_batch_size Required
validation_batch_size Required
warmup_ratio Required
weight_decay Required

Examples

creating an nlp fixed parameters

   from azure.ai.ml import automl
   from azure.ai.ml.constants import NlpLearningRateScheduler

   nlp_fixed_parameters = automl.NlpFixedParameters(
       model_name="roberta-base",
       learning_rate_scheduler=NlpLearningRateScheduler.LINEAR,
       warmup_ratio=0.1,
   )