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---
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tags:
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- generated_from_trainer
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datasets:
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- klue
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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model-index:
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- name: KR-FinBert-finetuned-ner
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results:
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- task:
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name: Token Classification
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type: token-classification
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dataset:
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name: klue
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type: klue
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config: ner
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split: train
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args: ner
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metrics:
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- name: Precision
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type: precision
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value: 0.70817831734221
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- name: Recall
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type: recall
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value: 0.7610296696359683
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- name: F1
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type: f1
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value: 0.7336533910338766
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- name: Accuracy
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type: accuracy
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value: 0.9504335292160994
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# KR-FinBert-finetuned-ner
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This model is a fine-tuned version of [snunlp/KR-FinBert](https://huggingface.co/snunlp/KR-FinBert) on the klue dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1634
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- Precision: 0.7082
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- Recall: 0.7610
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- F1: 0.7337
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- Accuracy: 0.9504
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| 0.2028 | 1.0 | 1313 | 0.1852 | 0.6650 | 0.7060 | 0.6849 | 0.9406 |
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| 0.1232 | 2.0 | 2626 | 0.1627 | 0.7028 | 0.7459 | 0.7237 | 0.9487 |
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| 0.0942 | 3.0 | 3939 | 0.1634 | 0.7082 | 0.7610 | 0.7337 | 0.9504 |
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### Framework versions
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- Transformers 4.24.0
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- Pytorch 1.12.1+cu113
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- Datasets 2.7.1
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- Tokenizers 0.13.2
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