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: 0.8398220245
- name: NER Recall
type: recall
value: 0.8445190157
- name: NER F Score
type: f_score
value: 0.842163971
Feature | Description |
---|---|
Name | en_med12_trf |
Version | 1 |
spaCy | >=3.4.1,<3.5.0 |
Default Pipeline | transformer , ner , textcat |
Components | 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 |
OTHER , MEDICATION |
Accuracy
Type | Score |
---|---|
ENTS_F |
84.22 |
ENTS_P |
83.98 |
ENTS_R |
84.45 |
CATS_SCORE |
93.88 |
CATS_MICRO_P |
89.78 |
CATS_MICRO_R |
97.98 |
CATS_MICRO_F |
93.70 |
CATS_MACRO_P |
90.29 |
CATS_MACRO_R |
97.93 |
CATS_MACRO_F |
93.88 |
CATS_MACRO_AUC |
98.53 |
CATS_MACRO_AUC_PER_TYPE |
0.00 |
TRANSFORMER_LOSS |
152780.09 |
NER_LOSS |
69513.43 |
TEXTCAT_LOSS |
1868.30 |