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klue-roberta-base-ner-bio
vitus9988/klue-roberta-base-ner-bio
klue-roberta-base-ner-bio is a token classification model from vitus9988. Use it when you need labels on individual words, such as names. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Token Classification
- Library
- transformers
- Model type
- roberta
- Access
- Public
- Created
- Jun 17, 2024
- Updated
- May 16, 2025
- SHA
- a2b7b8b4
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Base models
Model card
From the Hugging Face model README
<!-- 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-base-ner-bio
This model is a fine-tuned version of klue/roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0057
- Precision: 0.9888
- Recall: 1.0
- F1: 0.9944
- Accuracy: 0.9998
Model description
간단한 의료 관련 개체명 인식을 제공합니다.
- 약물명 [DR]
- 질병명 [DS]
- 유전자/단백질 명 [GN]
- 임상 증상 [CS]
- 의료 기기 [MD]
Training procedure
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 | 30 | 0.0363 | 0.8056 | 0.8898 | 0.8456 | 0.9886 |
| No log | 2.0 | 60 | 0.0079 | 0.9888 | 1.0 | 0.9944 | 0.9998 |
| No log | 3.0 | 90 | 0.0057 | 0.9888 | 1.0 | 0.9944 | 0.9998 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.3.0+cu118
- Datasets 2.19.1
- Tokenizers 0.19.1
- Task
- Token Classification
- Library
- transformers
- Type
- roberta
- Languages
- ko
- Created
- Jun 17, 2024
- Updated
- May 16, 2025