update model card README.md

README.md

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+---
+license: cc-by-sa-4.0
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: bert-finetuned-ner-ko
+  results: []
+---
+
+<!-- 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](https://huggingface.co/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