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bert-finetuned-ner-ko
wisejiyoon/bert-finetuned-ner-ko
bert-finetuned-ner-ko is a token classification model from wisejiyoon. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as cc-by-sa-4.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Token Classification
- Library
- transformers
- License
- cc-by-sa-4.0
- Model type
- bert
- Access
- Public
- Created
- Dec 12, 2023
- Updated
- Dec 12, 2023
- SHA
- 748acd4b
Try a prompt
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. -->
bert-finetuned-ner-ko
This model is a fine-tuned version of klue/bert-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0083
- Precision: 0.9859
- Recall: 0.9913
- F1: 0.9886
- Accuracy: 0.9980
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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 |
|---|---|---|---|---|---|---|---|
| 0.0649 | 1.0 | 1250 | 0.0295 | 0.9468 | 0.9679 | 0.9572 | 0.9919 |
| 0.0275 | 2.0 | 2500 | 0.0132 | 0.9777 | 0.9870 | 0.9823 | 0.9966 |
| 0.0141 | 3.0 | 3750 | 0.0083 | 0.9859 | 0.9913 | 0.9886 | 0.9980 |
Framework versions
- Transformers 4.27.3
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.13.2
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- License
- cc-by-sa-4.0
- Created
- Dec 12, 2023
- Updated
- Dec 12, 2023