update model card README.md

README.md

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+---
+tags:
+- generated_from_trainer
+datasets:
+- klue
+metrics:
+- accuracy
+model-index:
+- name: klue_nli_roberta_base_model
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: klue
+      type: klue
+      config: nli
+      split: validation
+      args: nli
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8653333333333333
+---
+
+<!-- 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_nli_roberta_base_model
+
+This model is a fine-tuned version of [klue/roberta-base](https://huggingface.co/klue/roberta-base) on the klue dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6867
+- Accuracy: 0.8653
+
+## 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: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.5988        | 1.0   | 782  | 0.4378          | 0.8363   |
+| 0.2753        | 2.0   | 1564 | 0.4169          | 0.851    |
+| 0.1735        | 3.0   | 2346 | 0.5267          | 0.8607   |
+| 0.0956        | 4.0   | 3128 | 0.6275          | 0.8683   |
+| 0.0708        | 5.0   | 3910 | 0.6867          | 0.8653   |
+
+
+### Framework versions
+
+- Transformers 4.30.2
+- Pytorch 2.0.1+cu118
+- Datasets 2.13.1
+- Tokenizers 0.13.3