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---
language: italian
widget:
- text: "Quando nacque D'Annunzio?"
context: "D'Annunzio nacque nel 1863"
---
# Italian Bert Base Uncased on Squad-it
## Model description
This model is the uncased base version of the italian BERT trained by `dbmdz`, which you may find at `dbmdz/bert-base-italian-uncased`.
#### How to use
```python
from transformers import pipeline
nlp = pipeline('question-answering', model='antoniocappiello/bert-base-italian-uncased-squad-it')
# nlp(context="D'Annunzio nacque nel 1863", question="Quando nacque D'Annunzio?")
# {'score': 0.9990354180335999, 'start': 22, 'end': 25, 'answer': '1863'}
```
## Training data
It has been trained on the question answering task using [SQuAD-it](http://sag.art.uniroma2.it/demo-software/squadit/), derived from the original SQuAD dataset and obtained through the semi-automatic translation of the SQuAD dataset in Italian.
## Training procedure
```bash
python ./examples/run_squad.py \
--model_type bert \
--model_name_or_path ./bert-base-italian-uncased/ \
--do_train \
--do_eval \
--train_file ./squad_it_uncased/train-v1.1.json \
--predict_file ./squad_it_uncased/dev-v1.1.json \
--learning_rate 3e-5 \
--num_train_epochs 2 \
--max_seq_length 384 \
--doc_stride 128 \
--output_dir ./models/bert-base-italian-uncased-squad-it/ \
--per_gpu_eval_batch_size=3 \
--per_gpu_train_batch_size=3 \
--do_lower_case \
```
## Eval results
| Model | batch | EM | F1 |
| ------------- |:-----:|:-----:| -----:|
| BERT base uncased | 3 | **63.8** | **75.30** | |