This is ner model for task
| Feature | Description |
|---|---|
| Name | vi_task_ner |
| Version | 0.0.0 |
| spaCy | >=3.7.5,<3.8.0 |
| Default Pipeline | tok2vec, ner |
| Components | tok2vec, ner |
| Vectors | 0 keys, 0 unique vectors (0 dimensions) |
| Sources | n/a |
| License | n/a |
| Author | Chánh Hỷ |
Label Scheme
View label scheme (5 labels for 1 components)
| Component | Labels |
|---|---|
ner |
DATE, LOCATION, PERSON, TASK, TIME |
Accuracy
| Type | Score |
|---|---|
ENTS_F |
89.80 |
ENTS_P |
89.80 |
ENTS_R |
89.80 |
TOK2VEC_LOSS |
19657.96 |
NER_LOSS |
12221.95 |
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Evaluation results
- NER Precisionself-reported0.898
- NER Recallself-reported0.898
- NER F Scoreself-reported0.898
!pip install https://huggingface.co/kenkwon/vi_task_ner/resolve/main/vi_task_ner-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("vi_task_ner") # Importing as module. import vi_task_ner nlp = vi_task_ner.load()