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---
license: apache-2.0
base_model: bert-base-cased
tags:
- PII
- NER
- Bert
- Token Classification
datasets:
- generator
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: pii_model
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: generator
type: generator
config: default
split: train
args: default
metrics:
- name: Precision
type: precision
value: 0.954751
- name: Recall
type: recall
value: 0.965233
- name: F1
type: f1
value: 0.959964
- name: Accuracy
type: accuracy
value: 0.991199
pipeline_tag: token-classification
language:
- en
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
## Model can Detect Following Entity Group
- ACCOUNTNUMBER
- FIRSTNAME
- ACCOUNTNAME
- PHONENUMBER
- CREDITCARDCVV
- CREDITCARDISSUER
- PREFIX
- LASTNAME
- AMOUNT
- DATE
- DOB
- COMPANYNAME
- BUILDINGNUMBER
- STREET
- SECONDARYADDRESS
- STATE
- EMAIL
- CITY
- CREDITCARDNUMBER
- SSN
- URL
- USERNAME
- PASSWORD
- COUNTY
- PIN
- MIDDLENAME
- IBAN
- GENDER
- AGE
- ZIPCODE
- SEX
### Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2 |