metadata
tags:
- spacy
- token-classification
- ner
- named-entity-recognition
language:
- en
model-index:
- name: en_roberta_fine_tuned_ner
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.8937349752
- name: NER Recall
type: recall
value: 0.8950083522
- name: NER F Score
type: f_score
value: 0.8943712104
This is a roBERTa 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_roberta_fine_tuned_ner |
| Version | 0.0.0 |
| spaCy | >=3.5.0,<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 | Nicola Disabato |
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 |
89.44 |
ENTS_P |
89.37 |
ENTS_R |
89.50 |
TRANSFORMER_LOSS |
294822.05 |
NER_LOSS |
316133.78 |