metadata
tags:
- spacy
- token-classification
language:
- en
model-index:
- name: en_pipeline
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.9783877242
- name: NER Recall
type: recall
value: 0.9648337596
- name: NER F Score
type: f_score
value: 0.9715634725
| Feature | Description |
|---|---|
| Name | en_pipeline |
| Version | 0.0.0 |
| spaCy | >=3.7.5,<3.8.0 |
| Default Pipeline | tok2vec, ner |
| Components | tok2vec, ner |
| Vectors | 514157 keys, 514157 unique vectors (300 dimensions) |
| Sources | n/a |
| License | n/a |
| Author | n/a |
Label Scheme
View label scheme (15 labels for 1 components)
| Component | Labels |
|---|---|
ner |
AWB, COMMODITY, DESTINATION, DIMENSIONS, GROSSWEIGHT, HSNCODE, INCOTERMS, INVOICE, MODE, ORIGIN, QUANTITY, SHIPMENTDATE, TEMPERATURE, VOLUMEWEIGHT, WEIGHT |
Accuracy
| Type | Score |
|---|---|
ENTS_F |
97.16 |
ENTS_P |
97.84 |
ENTS_R |
96.48 |
TOK2VEC_LOSS |
31298.39 |
NER_LOSS |
137951.75 |