readme: ### Model information
    * language : Korean
    * fine tuning data : [klue-tc (a.k.a. YNAT) ](https://klue-benchmark.com/tasks/66/overview/description)
    * License : CC-BY-SA 4.0
    * Base model : [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased)
    * input : news headline
    * output : topic
  
  ----
  ### Train information
   * train_runtime: 1477.3876 
   * train_steps_per_second: 2.416 
   * train_loss: 0.3722160959110207 
   * epoch: 5.0
   
  ----
  ### How to use
  ```
  from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
  tokenizer = AutoTokenizer.from_pretrained (
  "seongju/klue-tc-bert-base-multilingual-cased"
  )
  
  model = AutoModelForSequenceClassification.from_pretrained (
  "seongju/klue-tc-bert-base-multilingual-cased"
  )
  mapping = {0: 'IT과학', 1: '경제', 2: '사회', 
  3: '생활문화', 4: '세계', 5: '스포츠', 6: '정치'}
  inputs = tokenizer(
  "백신 회피 가능성? 남미에서 새로운 변이 바이러스 급속 확산 ",
   padding=True, truncation=True, max_length=128, return_tensors="pt"
   )
  outputs = model(**inputs)
  probs = outputs[0].softmax(1)
  output = mapping[probs.argmax().item()]
  ```