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---
license: apache-2.0
language:
- ko
metrics:
- sklearn-accuracy_score
datasets:
- kor_3i4k
pipeline_tag: text-classification
---
# intent-classification-korean
fine-tuned for 'klue/roberta-base'
used data : 'kor_3i4k'
## How to Get Started with the Model
```python
from transformers import TextClassificationPipeline
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model_path = "gg4ever/intent-classifcation-korean"
tokenizer = AutoTokenizer.from_pretrained(model_path)
model = AutoModelForSequenceClassification.from_pretrained(model_path)
text_classifier = TextClassificationPipeline(
tokenizer=tokenizer,
model=model.to('cpu'),
return_all_scores=True
)
# predict
text = "이름이 뭐에요?"
preds_list = text_classifier(text)
preds_list
```
### Training Hyperparameters
|hyperparameters|values|
|-----------------------------|-------|
|predict_with_generate|True|
|evaluation_strategy|"steps"|
|per_device_train_batch_size|32|
|per_device_eval_batch_size|32|
|num_train_epochs|3|
|learning_rate|4e-5|
|warmup_steps|1000| |