readme: ---
  language: 
  - tr
  tags:
  - roberta
  license: cc-by-nc-sa-4.0
  ---
  
  # RoBERTweetTurkCovid (uncased)
  
  Pretrained model on Turkish language using a masked language modeling (MLM) objective. The model is uncased. 
  The pretrained corpus is a Turkish tweets collection related to COVID-19. 
  
  Model architecture is similar to RoBERTa-base (12 layers, 12 heads, and 768 hidden size). Tokenization algorithm is WordPiece. Vocabulary size is 30k. 
  
  The details of pretraining can be found at this paper: 
  ```bibtex
  @InProceedings{clef-checkthat:2022:task1:oguzhan,
  author = {Cagri Toraman and Oguzhan Ozcelik and Furkan Şahinuç and Umitcan Sahin},
  title = "{ARC-NLP at CheckThat! 2022:} Contradiction for Harmful Tweet Detection",
  year = {2022},
  booktitle = "Working Notes of {CLEF} 2022 - Conference and Labs of the Evaluation Forum",
  editor = {Faggioli, Guglielmo andd Ferro, Nicola and Hanbury, Allan and Potthast, Martin},
  series = {CLEF~'2022},
  address = {Bologna, Italy},
  }
  ```
  
  The following code can be used for model loading and tokenization, example max length (768) can be changed:
  ```
  	model = AutoModel.from_pretrained([model_path])
  	#for sequence classification:
  	#model = AutoModelForSequenceClassification.from_pretrained([model_path], num_labels=[num_classes])
  
  	tokenizer = PreTrainedTokenizerFast(tokenizer_file=[file_path])
  	tokenizer.mask_token = "[MASK]"
  	tokenizer.cls_token = "[CLS]"
  	tokenizer.sep_token = "[SEP]"
  	tokenizer.pad_token = "[PAD]"
  	tokenizer.unk_token = "[UNK]"
  	tokenizer.bos_token = "[CLS]"
  	tokenizer.eos_token = "[SEP]"
  	tokenizer.model_max_length = 768
  ```
  
  ### BibTeX entry and citation info
  ```bibtex
  @InProceedings{clef-checkthat:2022:task1:oguzhan,
  author = {Cagri Toraman and Oguzhan Ozcelik and Furkan Şahinuç and Umitcan Sahin},
  title = "{ARC-NLP at CheckThat! 2022:} Contradiction for Harmful Tweet Detection",
  year = {2022},
  booktitle = "Working Notes of {CLEF} 2022 - Conference and Labs of the Evaluation Forum",
  editor = {Faggioli, Guglielmo andd Ferro, Nicola and Hanbury, Allan and Potthast, Martin},
  series = {CLEF~'2022},
  address = {Bologna, Italy},
  }
  ```
  