metadata
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
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 |