readme: ---
  language: it
  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 (which you may find at `dbmdz/bert-base-italian-uncased`) trained on the question answering task.
  
  #### 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 dbmdz/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
  
  | Metric | # Value   |
  | ------ | --------- |
  | **EM** | **63.8** |
  | **F1** | **75.30** |
  
  ## Comparison
  
  | Model                                                                                                                            | EM        | F1 score  |
  | -------------------------------------------------------------------------------------------------------------------------------- | --------- | --------- |
  | [DrQA-it trained on SQuAD-it](https://github.com/crux82/squad-it/blob/master/README.md#evaluating-a-neural-model-over-squad-it)  | 56.1      | 65.9      |
  | This one                                                                                                                         | **63.8** | **75.30** |