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
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, derived from the original SQuAD dataset and obtained through the semi-automatic translation of the SQuAD dataset in Italian.
Training procedure
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 | 56.1 | 65.9 |
| This one | 63.8 | 75.30 |