readme: ---
  license: apache-2.0
  language:
  - tr
  pipeline_tag: text-classification
  tags:
  - job advertisement
  - turkish bert
  - bert-based
  - StratifiedKFold
  ---
  
  ---
  language:
  - tr
  tags:
  - translation
  license: apache-2.0
  ---
  
  ## About the model
  It has been trained with 15451 real job advertisement data.
  
  Included classes;
  
  - Uygun İlan
  - Is Ilani Degil
  - Mustehcen
  - Cift Pozisyon
  
  
  Accordingly, the success rates in education are as follows;
  
  - **Model is Turkish bert-based.**
  - **Used StratifiedKFold(5) for validation.**
  - results [0.806858621805241, 0.8912621359223301, 0.9440129449838188, 0.9750809061488673, 0.9851132686084142]
    
  Mean-Precision: 0.9204655754937342
  
  
  |        | Uygun İlan | Is Ilani Degil | Mustehcen | Cift Pozisyon | 
  | ------ | ------  | ------ | ------  | ------ |
  | Precision | 0.986 | 0.996 | 0.966 | 0.970 |
  | Recall  | 0.992 | 0.986 | 0.966 | 0.959 |
  | F1 Score | 0.989 | 0.991 | 0.966 | 0.965 |
  Accuracy : 0.975
  
  ## Example
  
  **!IMPORTANT_HINT: The sentence given to pipe must not contain Turkish characters.**
  
  ```sh
  from transformers import AutoTokenizer, TextClassificationPipeline, AutoModelForSequenceClassification
  
  tokenizer = AutoTokenizer.from_pretrained("nanelimon/bert-base-turkish-job-advertisement")
  model = AutoModelForSequenceClassification.from_pretrained("nanelimon/bert-base-turkish-job-advertisement")
  pipe = TextClassificationPipeline(model=model, tokenizer=tokenizer)
  
  
  def set_sentence(sentence: str):
      result = sentence.lower().replace('ö', 'o').replace('ı', 'i').replace('ü', 'u').replace('ç', 'c').replace('ğ', 'g').replace('ş', 's')
      return result
  
  
  print(pipe(set_sentence('Fiziği düzgün 17 yaş kızlar aranıyor')))
  
  ```
  Result;
  ```sh
  output: [{'label': 'Mustehcen', 'score': 0.9992677569389343}]
  ```
  - label= It shows which class the sent Turkish text belongs to according to the model.
  - score= It shows the compliance rate of the Turkish text sent to the label found.
  
  ## Authors
  - Seyma SARIGIL: seymasargil@gmail.com
  - Murat KOKLU: mkoklu@selcuk.edu.tr
  
  
  ## License
  
  apache-2.0
  
  **Free Software, Hell Yeah!**