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#SBATCH --job-name=zen1_tnews # create a short name for your job | |
#SBATCH --nodes=1 # node count | |
#SBATCH --ntasks=1 # total number of tasks across all nodes | |
#SBATCH --cpus-per-task=30 # cpu-cores per task (>1 if multi-threaded tasks) | |
#SBATCH --gres=gpu:1 # number of gpus per node | |
#SBATCH --mail-type=ALL # send email when job begins, ends or failed etc. | |
#SBATCH -o %x-%j.log # output and error file name (%x=job name, %j=job id) | |
export CUDA_VISIBLE_DEVICES='1' | |
export CUDA_LAUNCH_BLOCKING=1 | |
export TORCH_EXTENSIONS_DIR=/cognitive_comp/ganruyi/tmp/torch_extendsions | |
MODEL_NAME=zen1 | |
TASK=tnews | |
ZERO_STAGE=1 | |
STRATEGY=deepspeed_stage_${ZERO_STAGE} | |
ROOT_DIR=/cognitive_comp/ganruyi/experiments/classification_finetune/${MODEL_NAME}_${TASK} | |
if [ ! -d ${ROOT_DIR} ];then | |
mkdir -p ${ROOT_DIR} | |
echo ${ROOT_DIR} created!!!!!!!!!!!!!! | |
else | |
echo ${ROOT_DIR} exist!!!!!!!!!!!!!!! | |
fi | |
DATA_DIR=/cognitive_comp/yangping/data/ChineseCLUE_DATA/${TASK}_public/ | |
PRETRAINED_MODEL_PATH=/cognitive_comp/ganruyi/hf_models/zen/ZEN_pretrain_base_v0.1.0 | |
PRETRAINED_MODEL_PATH=IDEA-CCNL/Erlangshen-ZEN1-224M-Chinese | |
CHECKPOINT_PATH=${ROOT_DIR}/ckpt/ | |
OUTPUT_PATH=${ROOT_DIR}/predict.json | |
DATA_ARGS="\ | |
--data_dir $DATA_DIR \ | |
--train_data train.json \ | |
--valid_data dev.json \ | |
--test_data test1.1.json \ | |
--train_batchsize 32 \ | |
--valid_batchsize 16 \ | |
--max_seq_length 128 \ | |
--texta_name sentence \ | |
--label_name label \ | |
--id_name id \ | |
--task_name tnews \ | |
" | |
MODEL_ARGS="\ | |
--learning_rate 2e-5 \ | |
--weight_decay 0.01 \ | |
--warmup_ratio 0.01 \ | |
--num_labels 15 \ | |
" | |
MODEL_CHECKPOINT_ARGS="\ | |
--monitor val_acc \ | |
--save_top_k 3 \ | |
--mode max \ | |
--every_n_train_steps 400 \ | |
--save_weights_only True \ | |
--dirpath $CHECKPOINT_PATH \ | |
--filename model-{epoch:02d}-{val_acc:.4f} \ | |
" | |
TRAINER_ARGS="\ | |
--max_epochs 10 \ | |
--gpus 1 \ | |
--check_val_every_n_epoch 1 \ | |
--val_check_interval 400 \ | |
--default_root_dir $ROOT_DIR \ | |
" | |
options=" \ | |
--pretrained_model_path $PRETRAINED_MODEL_PATH \ | |
--vocab_file $PRETRAINED_MODEL_PATH/vocab.txt \ | |
--do_lower_case \ | |
--output_save_path $OUTPUT_PATH \ | |
$DATA_ARGS \ | |
$MODEL_ARGS \ | |
$MODEL_CHECKPOINT_ARGS \ | |
$TRAINER_ARGS \ | |
" | |
SCRIPT_PATH=/cognitive_comp/ganruyi/Fengshenbang-LM/fengshen/examples/zen1_finetune/fengshen_sequence_level_ft_task.py | |
/home/ganruyi/anaconda3/bin/python $SCRIPT_PATH $options | |
# SINGULARITY_PATH=/cognitive_comp/ganruyi/pytorch21_06_py3_docker_image_v2.sif | |
# python3 $SCRIPT_PATH $options | |
# source activate base | |
# singularity exec --nv -B /cognitive_comp/:/cognitive_comp/ $SINGULARITY_PATH /home/ganruyi/anaconda3/bin/python $SCRIPT_PATH $options | |
# /home/ganruyi/anaconda3/bin/python $SCRIPT_PATH $options | |