Edit model card

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
Downloads last month
475
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.