metadata
license: cc-by-sa-4.0
base_model: klue/bert-base
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: bert-base-finetuned-ynat
results: []
language:
- ko
bert-base-finetuned-ynat
This model is a fine-tuned version of klue/bert-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3745
- F1: 0.8704
Model description
뉴스 제목을 입력하면 뉴스의 카테고리를 예측
label_map = {
'LABEL_0': 'IT/과학',
'LABEL_1': '경제',
'LABEL_2': '사회',
'LABEL_3': '생활문화',
'LABEL_4': '세계',
'LABEL_5': '스포츠',
'LABEL_6': '정치'
}
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: 256
- eval_batch_size: 256
- 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 | F1 |
|---|---|---|---|---|
| No log | 1.0 | 179 | 0.3909 | 0.8655 |
| No log | 2.0 | 358 | 0.3788 | 0.8684 |
| 0.3774 | 3.0 | 537 | 0.3629 | 0.8699 |
| 0.3774 | 4.0 | 716 | 0.3776 | 0.8667 |
| 0.3774 | 5.0 | 895 | 0.3745 | 0.8704 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0