es_metaextract_umsa-0.2

riturralde/es_metaextract_umsa-0.2

es_metaextract_umsa-0.2 is a machine learning model from riturralde. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for spacy.

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Repo size

59.3 MB

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Hugging Face

Repo makeup

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At a glance

Library: spacy
Access: Public
Created: Feb 3, 2024
Updated: Feb 3, 2024
SHA: 6018c7cc

Model card

From the Hugging Face model README

Feature	Description
Name	`es_metaextract_umsa`
Version	`0.2`
spaCy	`>=3.7.2,<3.8.0`
Default Pipeline	`title_model`, `authors_model`, `advisors_model`, `faculty_model`, `department_model`, `year`
Components	`title_model`, `authors_model`, `advisors_model`, `faculty_model`, `department_model`, `year`
Vectors	0 keys, 0 unique vectors (0 dimensions)
Sources	n/a
License	n/a
Author	n/a

Label Scheme

<details> <summary>View label scheme (5 labels for 5 components)</summary>

Component	Labels
`title_model`	`TITLE`
`authors_model`	`AUTHOR`
`advisors_model`	`ADVISOR`
`faculty_model`	`FACULTY`
`department_model`	`DEPARTMENT`

</details>

Accuracy

For title_model

Type	Score
`ENTS_F`	0.9416342412
`ENTS_P`	0.9394409938
`ENTS_R`	0.9438377535

For authors_model

Type	Score
`ENTS_F`	0.9764624438
`ENTS_P`	0.9774774775
`ENTS_R`	0.9754495159

For advisors_model

Type	Score
`ENTS_F`	0.9489443378
`ENTS_P`	0.935654807
`ENTS_R`	0.9626168224

For faculty_model

Type	Score
`ENTS_F`	0.9956270771
`ENTS_P`	0.9926752703
`ENTS_R`	0.9985964912

For department_model

Type	Score
`ENTS_F`	0.9971537002
`ENTS_P`	0.9966808914
`ENTS_R`	0.9976269578

For year

No accuracy available

Library: spacy
Languages: es
Created: Feb 3, 2024
Updated: Feb 3, 2024