CODEWITHSUNDEEP
rasa-nlurasarasa-core
fini
fini

Reputation: 21

How to fix the error UserWarning: the value of 'evaluate_every_number_of_epochs' is greater than the value of 'epochs'. No evaluation will occur

How to fix the error UserWarning: the value of 'evaluate_every_number_of_epochs' is greater than the value of 'epochs'. No evaluation will occur.

I get this warning when I run ‘rasa shell’.

UserWarning: the value of ‘evaluate_every_number_of_epochs’ is greater than the value of ‘epochs’. No evaluation will occur.

Can someone please help me to solve this?

version 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

Upvotes: 2

Views: 642

Answers (1)

jupyterjazz
jupyterjazz

Reputation: 31

We are aware of this problem and we'll fix it soon. In the meantime, I'd suggest ignoring this warning.

Upvotes: 1

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