metadata
tags:
- spacy
- token-classification
- text-classification
language:
- en
model-index:
- name: en_med12_trf
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.8630460449
- name: NER Recall
type: recall
value: 0.8640661939
- name: NER F Score
type: f_score
value: 0.8635558181
| Feature | Description |
|---|---|
| Name | en_med12_trf |
| Version | 1 |
| spaCy | >=3.4.1,<3.5.0 |
| Default Pipeline | tok2vec, transformer, ner, textcat |
| Components | tok2vec, transformer, ner, textcat |
| Vectors | 0 keys, 0 unique vectors (0 dimensions) |
| Sources | n/a |
| License | n/a |
| Author | n/a |
Label Scheme
View label scheme (14 labels for 2 components)
| Component | Labels |
|---|---|
ner |
Denominator_Unit, Denominator_Value, Dose_Form, Medication_Name, NDC, Numerator_Unit, Numerator_Value, Product_Package_Type, Product_Package_Type_Value, Quantity_Factor_Unit, Quantity_Factor_Unit_Value, Quantity_Factor_Value |
textcat |
MEDICATION, OTHER |
Accuracy
| Type | Score |
|---|---|
ENTS_F |
86.36 |
ENTS_P |
86.30 |
ENTS_R |
86.41 |
CATS_SCORE |
96.85 |
CATS_MICRO_P |
93.61 |
CATS_MICRO_R |
99.64 |
CATS_MICRO_F |
96.53 |
CATS_MACRO_P |
94.24 |
CATS_MACRO_R |
99.61 |
CATS_MACRO_F |
96.85 |
CATS_MACRO_AUC |
99.68 |
CATS_MACRO_AUC_PER_TYPE |
0.00 |
TOK2VEC_LOSS |
0.00 |
TRANSFORMER_LOSS |
131016.45 |
NER_LOSS |
28078.22 |
TEXTCAT_LOSS |
1261.44 |