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#!/bin/bash
#SBATCH --job-name=second_lm_balanced_prompted # job name
#SBATCH --partition=gpu_p2l # partition with 8 32GB gpu nodes
#SBATCH --qos=qos_gpu-t4 # t4 enables 100H trainings
#SBATCH --ntasks=1 # number of MP tasks
#SBATCH --gres=gpu:8 # number of GPUs per node
#SBATCH --cpus-per-task=6 # number of cores per tasks
#SBATCH --hint=nomultithread # we get physical cores not logical
#SBATCH --time=50:00:00 # maximum execution time (HH:MM:SS)
#SBATCH --output=%x-%j.out # output file name
#SBATCH --error=%x-%j.err # error file name
#SBATCH --account=ajs@gpu
#SBATCH --mail-type=ALL
set -x -e
module load cuda/10.2
DATASET=wiki_bk_prompted
SERIALIZATION_DIR=${ALL_CCFRSCRATCH}/experiments/second_lm_balanced_prompted
source ~/.bashrc
conda activate smallexps
export TOKENIZERS_PARALLELISM=false
export PYTHONUNBUFFERED=true
export HF_DATASETS_OFFLINE=1
export TRANSFORMERS_OFFLINE=1
deepspeed ${WORK}/jay-z/scripts/run_clm_prompted.py \
--deepspeed ${WORK}/jay-z/configs/deepspeed/ds_zero2.json \
--model_name_or_path gpt2-medium \
--tokenizer_name gpt2 \
--dataset_name ${ALL_CCFRSCRATCH}/datasets/${DATASET} --block_size 1024 \
--preprocessing_num_workers 31 \
--group_by_length --length_column_name length \
--cache_dir ${CACHE_DIR} \
--do_train --do_eval \
--max_steps 15000 \
--max_train_samples 10000000 \
--per_device_train_batch_size 4 --gradient_accumulation_steps 16 \
--per_device_eval_batch_size 8 \
--output_dir ${SERIALIZATION_DIR} --overwrite_output_dir \
--report_to tensorboard \
--logging_strategy steps --logging_first_step --logging_dir tb --logging_steps 20 \
--eval_steps 250 --evaluation_strategy steps \
--save_strategy steps --save_steps 500 --save_total_limit 31
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