|
--- |
|
tags: |
|
- spacy |
|
- token-classification |
|
language: |
|
- en |
|
model-index: |
|
- name: en_adept_ner_trf |
|
results: |
|
- task: |
|
name: NER |
|
type: token-classification |
|
metrics: |
|
- name: NER Precision |
|
type: precision |
|
value: 0.9736247174 |
|
- name: NER Recall |
|
type: recall |
|
value: 0.9758308157 |
|
- name: NER F Score |
|
type: f_score |
|
value: 0.9747265183 |
|
- task: |
|
name: TAG |
|
type: token-classification |
|
metrics: |
|
- name: TAG (XPOS) Accuracy |
|
type: accuracy |
|
value: 0.0 |
|
- task: |
|
name: LEMMA |
|
type: token-classification |
|
metrics: |
|
- name: Lemma Accuracy |
|
type: accuracy |
|
value: 0.0 |
|
- task: |
|
name: UNLABELED_DEPENDENCIES |
|
type: token-classification |
|
metrics: |
|
- name: Unlabeled Attachment Score (UAS) |
|
type: f_score |
|
value: 0.0 |
|
- task: |
|
name: LABELED_DEPENDENCIES |
|
type: token-classification |
|
metrics: |
|
- name: Labeled Attachment Score (LAS) |
|
type: f_score |
|
value: 0.0 |
|
- task: |
|
name: SENTS |
|
type: token-classification |
|
metrics: |
|
- name: Sentences F-Score |
|
type: f_score |
|
value: 0.0 |
|
--- |
|
|