readme: ---
  language: 
  - multilingual
  - af
  - ar
  - bg
  - bn
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  language_bcp47:
  - fa-IR
  ---
  
  # XLM-R + NER
  
  This model is a fine-tuned  [XLM-Roberta-base](https://arxiv.org/abs/1911.02116) over the 40 languages proposed in [XTREME](https://github.com/google-research/xtreme) from [Wikiann](https://aclweb.org/anthology/P17-1178). This is still an on-going work and the results will be updated everytime an improvement is reached. 
  
  The covered labels are:
  ```
  LOC
  ORG
  PER
  O
  ```
  
  ## Metrics on evaluation set:
  ### Average over the 40 languages
  Number of documents: 262300
  ```
             precision    recall  f1-score   support
  
        ORG       0.81      0.81      0.81    102452
        PER       0.90      0.91      0.91    108978
        LOC       0.86      0.89      0.87    121868
  
  micro avg       0.86      0.87      0.87    333298
  macro avg       0.86      0.87      0.87    333298
  ```
  
  ### Afrikaans
  Number of documents: 1000
  ```
             precision    recall  f1-score   support
  
        ORG       0.89      0.88      0.88       582
        PER       0.89      0.97      0.93       369
        LOC       0.84      0.90      0.86       518
  
  micro avg       0.87      0.91      0.89      1469
  macro avg       0.87      0.91      0.89      1469
  ``` 
  
  ### Arabic
  Number of documents: 10000
  ```
             precision    recall  f1-score   support
  
        ORG       0.83      0.84      0.84      3507
        PER       0.90      0.91      0.91      3643
        LOC       0.88      0.89      0.88      3604
  
  micro avg       0.87      0.88      0.88     10754
  macro avg       0.87      0.88      0.88     10754
  ```
  
  ### Basque
  Number of documents: 10000
  ```
             precision    recall  f1-score   support
  
        LOC       0.88      0.93      0.91      5228
        ORG       0.86      0.81      0.83      3654
        PER       0.91      0.91      0.91      4072
  
  micro avg       0.89      0.89      0.89     12954
  macro avg       0.89      0.89      0.89     12954
  ```
  
  ### Bengali
  Number of documents: 1000
  ```
             precision    recall  f1-score   support
  
        ORG       0.86      0.89      0.87       325
        LOC       0.91      0.91      0.91       406
        PER       0.96      0.95      0.95       364
  
  micro avg       0.91      0.92      0.91      1095
  macro avg       0.91      0.92      0.91      1095
  ```
  
  ### Bulgarian
  Number of documents: 1000
  ```
             precision    recall  f1-score   support
  
        ORG       0.86      0.83      0.84      3661
        PER       0.92      0.95      0.94      4006
        LOC       0.92      0.95      0.94      6449
  
  micro avg       0.91      0.92      0.91     14116
  macro avg       0.91      0.92      0.91     14116
  ```
  
  ### Burmese
  Number of documents: 100
  ```
             precision    recall  f1-score   support
  
        LOC       0.60      0.86      0.71        37
        ORG       0.68      0.63      0.66        30
        PER       0.44      0.44      0.44        36
  
  micro avg       0.57      0.65      0.61       103
  macro avg       0.57      0.65      0.60       103
  ```
  
  ### Chinese
  Number of documents: 10000
  ```
             precision    recall  f1-score   support
  
        ORG       0.70      0.69      0.70      4022
        LOC       0.76      0.81      0.78      3830
        PER       0.84      0.84      0.84      3706
  
  micro avg       0.76      0.78      0.77     11558
  macro avg       0.76      0.78      0.77     11558
  ```
  
  ### Dutch
  Number of documents: 10000
  ```
             precision    recall  f1-score   support
  
        ORG       0.87      0.87      0.87      3930
        PER       0.95      0.95      0.95      4377
        LOC       0.91      0.92      0.91      4813
  
  micro avg       0.91      0.92      0.91     13120
  macro avg       0.91      0.92      0.91     13120
  ```
  
  ### English
  Number of documents: 10000
  ```
             precision    recall  f1-score   support
  
        LOC       0.83      0.84      0.84      4781
        PER       0.89      0.90      0.89      4559
        ORG       0.75      0.75      0.75      4633
  
  micro avg       0.82      0.83      0.83     13973
  macro avg       0.82      0.83      0.83     13973
  ```
  
  ### Estonian
  Number of documents: 10000
  ```
             precision    recall  f1-score   support
  
        LOC       0.89      0.92      0.91      5654
        ORG       0.85      0.85      0.85      3878
        PER       0.94      0.94      0.94      4026
  
  micro avg       0.90      0.91      0.90     13558
  macro avg       0.90      0.91      0.90     13558
  ```
  
  ### Finnish
  Number of documents: 10000
  ```
             precision    recall  f1-score   support
  
        ORG       0.84      0.83      0.84      4104
        LOC       0.88      0.90      0.89      5307
        PER       0.95      0.94      0.94      4519
  
  micro avg       0.89      0.89      0.89     13930
  macro avg       0.89      0.89      0.89     13930
  ```
  
  ### French
  Number of documents: 1