---
tags:
- generated_from_trainer
datasets:
- klue
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: ko_roberta_small_model
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: klue
      type: klue
      config: ner
      split: validation
      args: ner
    metrics:
    - name: Precision
      type: precision
      value: 0.6827303934512807
    - name: Recall
      type: recall
      value: 0.7253980500806622
    - name: F1
      type: f1
      value: 0.703417786090801
    - name: Accuracy
      type: accuracy
      value: 0.9403969397937687
---

<!-- 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. -->

# ko_roberta_small_model

This model is a fine-tuned version of [hyeonseo/ko_roberta_small_model](https://huggingface.co/hyeonseo/ko_roberta_small_model) on the klue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1864
- Precision: 0.6827
- Recall: 0.7254
- F1: 0.7034
- Accuracy: 0.9404

## 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: 16
- eval_batch_size: 16
- 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 | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2341        | 1.0   | 1313 | 0.2069          | 0.6516    | 0.6999 | 0.6749 | 0.9336   |
| 0.16          | 2.0   | 2626 | 0.1864          | 0.6827    | 0.7254 | 0.7034 | 0.9404   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3