metadata
tags:
- spacy
- token-classification
language:
- en
model-index:
- name: en_xlnet_fine_tuned_ner
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.8847416707
- name: NER Recall
type: recall
value: 0.9002161737
- name: NER F Score
type: f_score
value: 0.8924118449
This is a XLNet model for Named Entity Recognition, fine-tuned on OntoNotes v5 using Spacy in coNLL-2003 format and BIO tagged. For more details: https://github.com/nicoladisabato/ner-with-transformers
Feature | Description |
---|---|
Name | en_xlnet_fine_tuned_ner |
Version | 0.0.0 |
spaCy | >=3.5.1,<3.6.0 |
Default Pipeline | transformer , ner |
Components | transformer , ner |
Vectors | 0 keys, 0 unique vectors (0 dimensions) |
Sources | n/a |
License | n/a |
Author | n/a |
Label Scheme
View label scheme (18 labels for 1 components)
Component | Labels |
---|---|
ner |
CARDINAL , DATE , EVENT , FAC , GPE , LANGUAGE , LAW , LOC , MONEY , NORP , ORDINAL , ORG , PERCENT , PERSON , PRODUCT , QUANTITY , TIME , WORK_OF_ART |
Accuracy
Type | Score |
---|---|
ENTS_F |
89.24 |
ENTS_P |
88.47 |
ENTS_R |
90.02 |
TRANSFORMER_LOSS |
124848.21 |
NER_LOSS |
196123.19 |