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