single_gpu_training.pbs

#PBS -S /bin/bash
#PBS -N squad_train_single
#PBS -j oe
#PBS -l walltime=02:00:00
#PBS -l select=1:ncpus=12:ngpus=1:mem=20gb
#PBS -q gpuq
##PBS -q isiaq
#PBS -P isia

# Go to the current directory 
cd $PBS_O_WORKDIR

# Load the same modules as for compilation 
module load anaconda3/5.3.1
source activate transformers_env

# Path to dataset
export SQUAD_DIR=/gpfs/opt/data/squad/1.1
#export SQUAD_DIR=/gpfs/opt/data/squad/2.0

# Run code
python ./transformers/examples/run_squad.py \
  --model_type bert \
  --model_name_or_path bert-base-cased \
  --do_train \
  --do_eval \
  --do_lower_case \
  --train_file $SQUAD_DIR/train-v1.1.json \
  --predict_file $SQUAD_DIR/dev-v1.1.json \
  --per_gpu_train_batch_size 12 \
  --learning_rate 3e-5 \
  --num_train_epochs 2.0 \
  --max_seq_length 384 \
  --doc_stride 128 \
  --output_dir ./debug_squad_$PBS_JOBID/