I added few examples in nlu data like “1401 is report id”
when i give 1401 it is identifying the entity but when i gave 1558, failed to get the entity
pipeline used language: en
pipeline:
- name: “nlp_spacy”
- name: “tokenizer_spacy”
- name: “intent_featurizer_spacy”
- name: “intent_classifier_sklearn”
- name: “ner_crf”
- name: “ner_synonyms”
- name: “ner_spacy”
This is the lines i got on training
C:\Users\1345325\MyBot\bot>python -m rasa_nlu.train -c cip_config.yml --data cip_intents.md -o models --fixed_model_name nlu --project CIP --verbose
2019-01-22 16:11:20 INFO rasa_nlu.utils.spacy_utils - Trying to load spacy model with name ‘en’
2019-01-22 16:11:24 INFO rasa_nlu.components - Added ‘nlp_spacy’ to component cache. Key ‘nlp_spacy-en’.
2019-01-22 16:11:25 INFO rasa_nlu.training_data.loading - Training data format of cip_intents.md is md
2019-01-22 16:11:25 INFO rasa_nlu.training_data.training_data - Training data stats: - intent examples: 120 (14 distinct intents) - Found intents: ‘eforte_report’, ‘deny’, ‘greet’, ‘goodbye’, ‘affirm’, ‘prs_loh’, ‘NRSP’, ‘pos_internal_version_report’, ‘table’, ‘upload’, ‘sirval’, ‘file’, ‘corr’, ‘thankyou’ - entity examples: 79 (10 distinct entities) - found entities: ‘upload_type’, ‘db’, ‘items’, ‘hierarchy_name’, ‘db_name’, ‘upload_table’, ‘upload_file’, ‘corr_report_id’, ‘report_name’, ‘corr_schema_name’
2019-01-22 16:11:25 INFO rasa_nlu.model - Starting to train component nlp_spacy
2019-01-22 16:11:26 INFO rasa_nlu.model - Finished training component.
2019-01-22 16:11:26 INFO rasa_nlu.model - Starting to train component tokenizer_spacy
2019-01-22 16:11:26 INFO rasa_nlu.model - Finished training component.
2019-01-22 16:11:26 INFO rasa_nlu.model - Starting to train component intent_featurizer_spacy
2019-01-22 16:11:26 INFO rasa_nlu.model - Finished training component.
2019-01-22 16:11:26 INFO rasa_nlu.model - Starting to train component intent_classifier_sklearn
Fitting 2 folds for each of 6 candidates, totalling 12 fits C:\Program Files\Python36\lib\site-packages\sklearn\metrics\classification.py:1135: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no predicted samples. ‘precision’, ‘predicted’, average, warn_for)
C:\Program Files\Python36\lib\site-packages\sklearn\metrics\classification.py:1135: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no predicted samples. ‘precision’, ‘predicted’, average, warn_for)
C:\Program Files\Python36\lib\site-packages\sklearn\metrics\classification.py:1135: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no predicted samples. ‘precision’, ‘predicted’, average, warn_for)
C:\Program Files\Python36\lib\site-packages\sklearn\metrics\classification.py:1135: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no predicted samples. ‘precision’, ‘predicted’, average, warn_for)
C:\Program Files\Python36\lib\site-packages\sklearn\metrics\classification.py:1135: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no predicted samples. ‘precision’, ‘predicted’, average, warn_for)
C:\Program Files\Python36\lib\site-packages\sklearn\metrics\classification.py:1135: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no predicted samples. ‘precision’, ‘predicted’, average, warn_for)
C:\Program Files\Python36\lib\site-packages\sklearn\metrics\classification.py:1135: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no predicted samples. ‘precision’, ‘predicted’, average, warn_for)
C:\Program Files\Python36\lib\site-packages\sklearn\metrics\classification.py:1135: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no predicted samples. ‘precision’, ‘predicted’, average, warn_for)
C:\Program Files\Python36\lib\site-packages\sklearn\metrics\classification.py:1135: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no predicted samples. ‘precision’, ‘predicted’, average, warn_for)
C:\Program Files\Python36\lib\site-packages\sklearn\metrics\classification.py:1135: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no predicted samples. ‘precision’, ‘predicted’, average, warn_for)
C:\Program Files\Python36\lib\site-packages\sklearn\metrics\classification.py:1135: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no predicted samples. ‘precision’, ‘predicted’, average, warn_for)
C:\Program Files\Python36\lib\site-packages\sklearn\metrics\classification.py:1135: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no predicted samples. ‘precision’, ‘predicted’, average, warn_for)
[Parallel(n_jobs=1)]: Done 12 out of 12 | elapsed: 0.4s finished
2019-01-22 16:11:27 INFO rasa_nlu.model - Finished training component.
2019-01-22 16:11:27 INFO rasa_nlu.model - Starting to train component ner_crf
2019-01-22 16:11:27 INFO rasa_nlu.model - Finished training component.
2019-01-22 16:11:27 INFO rasa_nlu.model - Starting to train component ner_synonyms
2019-01-22 16:11:27 INFO rasa_nlu.model - Finished training component.
2019-01-22 16:11:27 INFO rasa_nlu.model - Starting to train component ner_spacy
2019-01-22 16:11:27 INFO rasa_nlu.model - Finished training component.
2019-01-22 16:11:27 INFO rasa_nlu.model - Successfully saved model into ‘C:\Users\1345325\MyBot\bot\models\CIP\nlu’
2019-01-22 16:11:27 INFO main - Finished training