readme: ---
  language:
    - multilingual
  
  datasets:
    - squad
    - arcd
    - xquad
  ---
  
  # Multilingual BERT fine-tuned on SQuADv1.1
  
  [**WandB run link**](https://wandb.ai/salti/mBERT_QA/runs/wkqzhrp2)
  
  **GPU**: Tesla P100-PCIE-16GB
  
  ## Training Arguments
  
  ```python
  max_seq_length              = 512
  doc_stride                  = 256
  max_answer_length           = 64
  bacth_size                  = 16
  gradient_accumulation_steps = 2
  learning_rate               = 5e-5
  weight_decay                = 3e-7
  num_train_epochs            = 3
  warmup_ratio                = 0.1
  fp16                        = True
  fp16_opt_level              = "O1"
  seed                        = 0
  ```
  
  ## Results
  
  |   EM   |   F1   |
  | :----: | :----: |
  | 81.731 | 89.009 |
  
  ## Zero-shot performance
  
  ### on ARCD
  
  |   EM   |   F1   |
  | :----: | :----: |
  | 20.655 | 48.051 |
  
  ### on XQuAD
  
  |  Language  |   EM   |   F1   |
  | :--------: | :----: | :----: |
  |   Arabic   | 42.185 | 57.803 |
  |  English   | 73.529 | 85.01  |
  |   German   | 55.882 | 72.555 |
  |   Greek    | 45.21  | 62.207 |
  |  Spanish   | 58.067 | 76.406 |
  |   Hindi    | 40.588 | 55.29  |
  |  Russian   | 55.126 | 71.617 |
  |    Thai    | 26.891 | 39.965 |
  |  Turkish   | 34.874 | 51.138 |
  | Vietnamese | 47.983 | 68.125 |
  |  Chinese   | 47.395 | 58.928 |
  