End of training

README.md

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+---
+license: apache-2.0
+base_model: beomi/kcbert-base
+tags:
+- generated_from_trainer
+datasets:
+- nsmc
+metrics:
+- accuracy
+model-index:
+- name: kcbert_nsmc_tuning
+  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: 0.90134
+---
+
+<!-- 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. -->
+
+# kcbert_nsmc_tuning
+
+This model is a fine-tuned version of [beomi/kcbert-base](https://huggingface.co/beomi/kcbert-base) on the nsmc dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4492
+- Accuracy: 0.9013
+
+## 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: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.1689        | 1.0   | 2344 | 0.2717          | 0.9006   |
+| 0.0951        | 2.0   | 4688 | 0.3458          | 0.8995   |
+| 0.051         | 3.0   | 7032 | 0.4492          | 0.9013   |
+
+
+### Framework versions
+
+- Transformers 4.42.2
+- Pytorch 2.3.1+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

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