---
base_model: klue/roberta-small
tags:
- generated_from_trainer
- korean
- klue
widget:
- text: 저는 김철수입니다. 집은 서울특별시 강남대로이고 전화번호는 010-1234-5678, 주민등록번호는 123456-1234567입니다. 메일주소는 hugging@face.com입니다. 저는 10월 25일에 출국할 예정입니다.
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: klue_roberta_small_ner_identified
  results: []
language:
- ko
pipeline_tag: token-classification
---

<!-- 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. -->

# klue-roberta-small-ner-identified

This model is a fine-tuned version of [vitus9988/klue-roberta-small-ner-identified](https://huggingface.co/vitus9988/klue-roberta-small-ner-identified) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0082
- Precision: 0.9930
- Recall: 0.9988
- F1: 0.9959
- Accuracy: 0.9988

## Model description

아래 항목에 대한 개체명 인식을 제공합니다.

- 사람이름 [PS] - 낮은 인식률
- 주소 (구 주소 및 도로명 주소) [AD]
- 카드번호 [CN]
- 계좌번호 [BN]
- 운전면허번호 [DN]
- 주민등록번호 [RN]
- 여권번호 [PN]
- 전화번호 [PH]
- 이메일 주소 [EM]
- 날짜 [DT]

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 61   | 0.0128          | 0.9871    | 0.9929 | 0.9900 | 0.9979   |
| No log        | 2.0   | 122  | 0.0098          | 0.9895    | 0.9976 | 0.9935 | 0.9987   |
| No log        | 3.0   | 183  | 0.0082          | 0.9930    | 0.9988 | 0.9959 | 0.9988   |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.3.0+cu118
- Datasets 2.19.1
- Tokenizers 0.19.1