update model card README.md

README.md

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+---
+license: cc-by-sa-4.0
+tags:
+- generated_from_trainer
+datasets:
+- nsmc
+metrics:
+- accuracy
+- f1
+model-index:
+- name: klue_bert_base
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: nsmc
+      type: nsmc
+      config: default
+      split: test
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.90564
+    - name: F1
+      type: f1
+      value: 0.9056337214649489
+---
+
+<!-- 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_bert_base
+
+This model is a fine-tuned version of [klue/bert-base](https://huggingface.co/klue/bert-base) on the nsmc dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2415
+- Accuracy: 0.9056
+- F1: 0.9056
+
+## 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: 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: 2
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| 0.2742        | 1.0   | 2344 | 0.2381          | 0.9005   | 0.9005 |
+| 0.1865        | 2.0   | 4688 | 0.2415          | 0.9056   | 0.9056 |
+
+
+### Framework versions
+
+- Transformers 4.26.1
+- Pytorch 1.13.1+cu116
+- Datasets 2.9.0
+- Tokenizers 0.13.2