| Feature | Description |
|---|---|
| Name | en_pipeline |
| Version | 0.0.0 |
| spaCy | >=3.7.5,<3.8.0 |
| 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 (8 labels for 1 components)
| Component | Labels |
|---|---|
ner |
B-LAW, B-VIOLATED BY, B-VIOLATED ON, B-VIOLATION, I-LAW, I-VIOLATED BY, I-VIOLATED ON, I-VIOLATION |
Accuracy
| Type | Score |
|---|---|
ENTS_F |
92.20 |
ENTS_P |
93.09 |
ENTS_R |
91.34 |
TRANSFORMER_LOSS |
16253.98 |
NER_LOSS |
13899.54 |
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Evaluation results
- NER Precisionself-reported0.931
- NER Recallself-reported0.913
- NER F Scoreself-reported0.922
!pip install https://huggingface.co/nimamegh/ner_model/resolve/main/ner_model-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("ner_model") # Importing as module. import ner_model nlp = ner_model.load()