如何修复错误 UserWarning：'evaluate_every_number_of_epochs' 的值大于 'epochs' 的值不会进行评估

问题描述

如何修复错误用户警告：'evaluate_every_number_of_epochs' 的值大于'epochs' 的值。不会进行评估。

我在运行“rasa shell”时收到此警告。

用户警告：‘evaluate_every_number_of_epochs’的值大于‘epochs’的值。不会进行评估。

有人可以帮我解决这个问题吗？

版本 rasa 2.7.1

config.yml

# Configuration for Rasa NLU.
# https://rasa.com/docs/rasa/nlu/components/
language: ru

pipeline:
 # No configuration for the NLU pipeline was provided. The following default pipeline was used to train your model.
 # If you'd like to customize it,uncomment and adjust the pipeline.
 # See https://rasa.com/docs/rasa/tuning-your-model for more information.
   - name: Whitespacetokenizer
   - name: RegexFeaturizer
   - name: LexicalSyntacticFeaturizer
   - name: CountVectorsFeaturizer
   - name: CountVectorsFeaturizer
     analyzer: char_wb
     min_ngram: 1
     max_ngram: 4
   - name: DIETClassifier
     epochs: 100
     constrain_similarities: true
     evaluate_on_number_of_examples: 0
     evaluate_every_number_of_epochs: 5
     model_confidence: linear_norm
   - name: EntitySynonymMapper
   - name: ResponseSelector
     epochs: 100
     constrain_similarities: true
     model_confidence: linear_norm
     evaluate_on_number_of_examples: 0
     evaluate_every_number_of_epochs: 5
   - name: FallbackClassifier
     threshold: 0.3
     ambiguity_threshold: 0.1

# Configuration for Rasa Core.
# https://rasa.com/docs/rasa/core/policies/
policies:
# # No configuration for policies was provided. The following default policies were used to train your model.
# # If you'd like to customize them,uncomment and adjust the policies.
# # See https://rasa.com/docs/rasa/policies for more information.
   - name: MemoizationPolicy
   - name: RulePolicy
   - name: TEDPolicy
     max_history: 5
     evaluate_on_number_of_examples: 0
     evaluate_every_number_of_epochs: 5
     epochs: 100
     constrain_similarities: true
     model_confidence: linear_norm

解决方法

我们已注意到此问题 problem，我们会尽快修复它。 同时，我建议忽略此警告。