BERT-Small fine-tuned on CORD-19 QA dataset
bert-small-cord19-squad model fine-tuned on the CORD-19 QA dataset.
CORD-19 QA dataset
The CORD-19 QA dataset is a SQuAD 2.0 formatted list of question, context, answer combinations covering the CORD-19 dataset.
Building the model
python run_squad.py \
--model_type bert \
--model_name_or_path bert-small-cord19-squad \
--do_train \
--do_lower_case \
--version_2_with_negative \
--train_file cord19-qa.json \
--per_gpu_train_batch_size 8 \
--learning_rate 5e-5 \
--num_train_epochs 10.0 \
--max_seq_length 384 \
--doc_stride 128 \
--output_dir bert-small-cord19qa \
--save_steps 0 \
--threads 8 \
--overwrite_cache \
--overwrite_output_dir
Testing the model
Example usage below:
from transformers import pipeline
qa = pipeline(
"question-answering",
model="NeuML/bert-small-cord19qa",
tokenizer="NeuML/bert-small-cord19qa"
)
qa({
"question": "What is the median incubation period?",
"context": "The incubation period is around 5 days (range: 4-7 days) with a maximum of 12-13 day"
})
qa({
"question": "What is the incubation period range?",
"context": "The incubation period is around 5 days (range: 4-7 days) with a maximum of 12-13 day"
})
qa({
"question": "What type of surfaces does it persist?",
"context": "The virus can survive on surfaces for up to 72 hours such as plastic and stainless steel ."
})
{"score": 0.5970273583242793, "start": 32, "end": 38, "answer": "5 days"}
{"score": 0.999555868193891, "start": 39, "end": 56, "answer": "(range: 4-7 days)"}
{"score": 0.9992726505196998, "start": 61, "end": 88, "answer": "plastic and stainless steel"}