README.md

---
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|