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---
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 |
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