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BERT L-10 H-512 CORD-19 (2020/06/16) fine-tuned on SQuAD v2.0

BERT model with 10 Transformer layers and hidden embedding of size 512, referenced in Well-Read Students Learn Better: On the Importance of Pre-training Compact Models, fine-tuned for MLM on CORD-19 dataset (as released on 2020/06/16) and fine-tuned for QA on SQuAD v2.0.

Training the model

python run_squad.py
    --model_type bert
    --model_name_or_path aodiniz/bert_uncased_L-10_H-512_A-8_cord19-200616
    --train_file 'train-v2.0.json'
    --predict_file 'dev-v2.0.json'
    --max_seq_length 384
    --per_gpu_train_batch_size 10
    --learning_rate 3e-5
    --num_train_epochs 2
    --output_dir bert_uncased_L-10_H-512_A-8_cord19-200616_squad2
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Dataset used to train aodiniz/bert_uncased_L-10_H-512_A-8_cord19-200616_squad2