readme: Hugging Face's logo
  ---
  language: sw
  datasets:
  
  ---
  # xlm-roberta-base-finetuned-swahili
  ## Model description
  **xlm-roberta-base-finetuned-swahili** is a **Swahili RoBERTa** model obtained by fine-tuning **xlm-roberta-base** model on Swahili language texts.  It provides **better performance** than the XLM-RoBERTa on text classification and named entity recognition datasets.  
  
  Specifically, this model is a *xlm-roberta-base* model that was fine-tuned on Swahili corpus. 
  ## Intended uses & limitations
  #### How to use
  You can use this model with Transformers *pipeline* for masked token prediction.
  ```python
  >>> from transformers import pipeline
  >>> unmasker = pipeline('fill-mask', model='Davlan/xlm-roberta-base-finetuned-swahili')
  >>> unmasker("Jumatatu, Bwana Kagame alielezea shirika la France24 huko <mask> kwamba hakuna uhalifu ulitendwa")
                      
  [{'sequence': 'Jumatatu, Bwana Kagame alielezea shirika la France24 huko Ufaransa kwamba hakuna uhalifu ulitendwa', 
  'score': 0.5077782273292542, 
  'token': 190096, 
  'token_str': 'Ufaransa'}, 
  {'sequence': 'Jumatatu, Bwana Kagame alielezea shirika la France24 huko Paris kwamba hakuna uhalifu ulitendwa', 
  'score': 0.3657738268375397, 
  'token': 7270, 
  'token_str': 'Paris'}, 
  {'sequence': 'Jumatatu, Bwana Kagame alielezea shirika la France24 huko Gabon kwamba hakuna uhalifu ulitendwa', 
  'score': 0.01592041552066803, 
  'token': 176392, 
  'token_str': 'Gabon'}, 
  {'sequence': 'Jumatatu, Bwana Kagame alielezea shirika la France24 huko France kwamba hakuna uhalifu ulitendwa', 
  'score': 0.010881908237934113, 
  'token': 9942, 
  'token_str': 'France'}, 
  {'sequence': 'Jumatatu, Bwana Kagame alielezea shirika la France24 huko Marseille kwamba hakuna uhalifu ulitendwa', 
  'score': 0.009554869495332241, 
  'token': 185918, 
  'token_str': 'Marseille'}]
  
  
  ```
  #### Limitations and bias
  This model is limited by its training dataset of entity-annotated news articles from a specific span of time. This may not generalize well for all use cases in different domains. 
  ## Training data
  This model was fine-tuned on [Swahili CC-100](http://data.statmt.org/cc-100/)
  
  ## Training procedure
  This model was trained on a single NVIDIA V100 GPU
  
  ## Eval results on Test set (F-score, average over 5 runs)
  Dataset| XLM-R F1 | sw_roberta F1
  -|-|-
  [MasakhaNER](https://github.com/masakhane-io/masakhane-ner) | 87.55 | 89.46
  
  ### BibTeX entry and citation info
  By David Adelani
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  ```
  
  
  