update model card README.md

README.md

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+---
+base_model: kykim/albert-kor-base
+tags:
+- generated_from_trainer
+datasets:
+- nsmc
+metrics:
+- accuracy
+model-index:
+- name: electra2
+  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: 0.89276
+---
+
+<!-- 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. -->
+
+# electra2
+
+This model is a fine-tuned version of [kykim/albert-kor-base](https://huggingface.co/kykim/albert-kor-base) on the nsmc dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3037
+- Accuracy: 0.8928
+
+## 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: 5e-06
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 0.2815        | 1.0   | 9375  | 0.2801          | 0.8863   |
+| 0.2329        | 2.0   | 18750 | 0.2705          | 0.8920   |
+| 0.1949        | 3.0   | 28125 | 0.3037          | 0.8928   |
+
+
+### Framework versions
+
+- Transformers 4.31.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.4
+- Tokenizers 0.13.3