metadata
tags:
- spacy
- token-classification
language:
- en
model-index:
- name: en_xlnet_res_pipeline
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.6765457333
- name: NER Recall
type: recall
value: 0.7866904337
- name: NER F Score
type: f_score
value: 0.7274725275
| Feature | Description |
|---|---|
| Name | en_xlnet_res_pipeline |
| 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 (5 labels for 1 components)
| Component | Labels |
|---|---|
ner |
degree, experience, majors, publications, skills |
Accuracy
| Type | Score |
|---|---|
ENTS_F |
72.75 |
ENTS_P |
67.65 |
ENTS_R |
78.67 |
TRANSFORMER_LOSS |
226242.24 |
NER_LOSS |
5192776.38 |