---
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
---

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# 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