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en_tenarchexp3

Text Classification

token-classification

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Feature	Description
Name	`en_tenarchexp3`
Version	`0.0.0`
spaCy	`>=3.2.4,<3.3.0`
Default Pipeline	`tok2vec`, `ner`, `textcat_multilabel`
Components	`tok2vec`, `ner`, `textcat_multilabel`
Vectors	0 keys, 0 unique vectors (0 dimensions)
Sources	n/a
License	n/a
Author	n/a

Label Scheme

View label scheme (7 labels for 2 components)

Component	Labels
`ner`	`Seniority`, `TechSkill`
`textcat_multilabel`	`SoftwareEngineer`, `SiteReliabitliyEngineer`, `ProductManager`, `DataScientist`, `Designer`

Accuracy

Type	Score
`ENTS_F`	89.76
`ENTS_P`	95.00
`ENTS_R`	85.07
`CATS_SCORE`	71.89
`CATS_MICRO_P`	47.92
`CATS_MICRO_R`	86.79
`CATS_MICRO_F`	61.74
`CATS_MACRO_P`	39.21
`CATS_MACRO_R`	55.42
`CATS_MACRO_F`	44.90
`CATS_MACRO_AUC`	71.89
`CATS_MACRO_AUC_PER_TYPE`	0.00
`TOK2VEC_LOSS`	31131.44
`NER_LOSS`	5486.16
`TEXTCAT_MULTILABEL_LOSS`	5.73

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Text Classification

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Evaluation results

NER Precision
self-reported

0.950
NER Recall
self-reported

0.851
NER F Score
self-reported

0.898

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