This model is developed with transformers v4.10.3. # Train ```bash #!/usr/bin/env bash export CUDA_VISIBLE_DEVICES=0 OUTDIR=bert-base-uncased-squad WORKDIR=transformers/examples/pytorch/question-answering cd $WORKDIR nohup python run_qa.py \ --model_name_or_path bert-base-uncased \ --dataset_name squad \ --do_eval \ --do_train \ --per_device_train_batch_size 16 \ --per_device_eval_batch_size 16 \ --doc_stride 128 \ --max_seq_length 384 \ --learning_rate 3e-5 \ --num_train_epochs 2 \ --eval_steps 250 \ --save_steps 2500 \ --logging_steps 1 \ --overwrite_output_dir \ --output_dir $OUTDIR 2>&1 | tee $OUTDIR/run.log & ``` # Eval ```bash export CUDA_VISIBLE_DEVICES=0 OUTDIR=eval-bert-base-uncased-squad WORKDIR=transformers/examples/pytorch/question-answering cd $WORKDIR nohup python run_qa.py \ --model_name_or_path vuiseng9/bert-base-uncased-squad \ --dataset_name squad \ --do_eval \ --per_device_eval_batch_size 16 \ --max_seq_length 384 \ --doc_stride 128 \ --overwrite_output_dir \ --output_dir $OUTDIR 2>&1 | tee $OUTDIR/run.log & ```