File size: 2,867 Bytes
8ebda9e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 |
#!/bin/bash
#SBATCH --job-name=zen2_base_cmnli # 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='4'
export TORCH_EXTENSIONS_DIR=/cognitive_comp/ganruyi/tmp/torch_extendsions
MODEL_NAME=zen2_base
TASK=cmnli
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 ${ROOT_DIR} exist!!!!!!!!!!!!!!!
fi
DATA_DIR=/cognitive_comp/yangping/data/ChineseCLUE_DATA/cmnli_public/${TASK}_public/
PRETRAINED_MODEL_PATH=/cognitive_comp/ganruyi/hf_models/zen/zh_zen_base_2.0
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 test.json \
--train_batchsize 64 \
--valid_batchsize 32 \
--max_seq_length 128 \
--texta_name sentence \
--label_name label \
--id_name id \
--task_name cmnli \
"
MODEL_ARGS="\
--learning_rate 2e-5 \
--weight_decay 0.1 \
--warmup_ratio 0.01 \
--num_labels 3 \
"
MODEL_CHECKPOINT_ARGS="\
--monitor val_acc \
--save_top_k 3 \
--mode max \
--every_n_train_steps 100 \
--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 100 \
--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/zen2_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
|