This model is [Distilbert base uncased](https://huggingface.co/distilbert-base-uncased) trained on SQuAD v2 as: ``` export SQUAD_DIR=../../squad2 python3 run_squad.py --model_type distilbert --model_name_or_path distilbert-base-uncased --do_train --do_eval --overwrite_cache --do_lower_case --version_2_with_negative --save_steps 100000 --train_file $SQUAD_DIR/train-v2.0.json --predict_file $SQUAD_DIR/dev-v2.0.json --per_gpu_train_batch_size 8 --num_train_epochs 3 --learning_rate 3e-5 --max_seq_length 384 --doc_stride 128 --output_dir ./tmp/distilbert_fine_tuned/ ``` Performance on a dev subset is close to the original paper: ``` Results: { 'exact': 64.88976637051661, 'f1': 68.1776176526635, 'total': 6078, 'HasAns_exact': 69.7594501718213, 'HasAns_f1': 76.62665295288285, 'HasAns_total': 2910, 'NoAns_exact': 60.416666666666664, 'NoAns_f1': 60.416666666666664, 'NoAns_total': 3168, 'best_exact': 64.88976637051661, 'best_exact_thresh': 0.0, 'best_f1': 68.17761765266337, 'best_f1_thresh': 0.0 } ``` We are hopeful this might save you time, energy, and compute. Cheers!