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run_finetune_with_custom_optim.sh
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#!/bin/bash
# Please run this script under ${project_id} in project directory of
# https://github.com/shizhediao/llm-ft
# COMMIT: d5fecf30ba8011067b10cf51fede53a5ab6574e4
# Parses arguments
model_name_or_path=gpt2
dataset_path=data/alpaca/train_conversation
# Other optional arguments that can improve memory saving
gradient_checkpointing=True
use_flash_attention=0
gradient_accumulation_steps=1
batch_size=1
block_size=256
per_device_train_batch_size=1
conversation_template=llama2
optim=dummy
# Select an optimizer from the following options:
# - 'adamw_torch'
# - 'adafactor'
# - 'sgd'
# - 'lion_8bit'
# - 'lion_32bit'
# - 'rmsprop'
# Additional optimizers are shown below
learning_rate=1e-5
lr_schedule=cosine
beta1=0.9
beta2=0.999
beta3=0.99
weight_decay=0
momentum=0
num_epoch=0.01
use_deepspeed=1
seed=42
# Safety related arguments
trust_remote_code=0
# Enable model parallelism for multiple gpus, modify this if you prefer
# customized deepspeed zero-redundancy optimization settings
num_gpu=$(python -c "import torch; print(torch.cuda.device_count())")
ds_config_file=configs/ds_config_zero0_no_offload.json
if [[ ${num_gpu} -ge 2 ]]; then
ds_config_file=configs/ds_config_zero2_no_offload.json
fi
while [[ $# -ge 1 ]]; do
key="$1"
case ${key} in
-m|--model_name_or_path)
model_name_or_path="$2"
shift
;;
-d|--dataset_path)
dataset_path="$2"
shift
;;
-o|--output_model_path)
output_dir="$2"
shift
;;
--lisa_activated_layers)
lisa_activated_layers="$2"
shift
;;
--lisa_interval_steps)
lisa_interval_steps="$2"
shift
;;
--gradient_checkpointing)
gradient_checkpointing="$2"
shift
;;
--deepspeed)
ds_config_file="$2"
shift
;;
--use_flash_attention)
use_flash_attention="$2"
shift
;;
--gradient_accumulation_steps)
gradient_accumulation_steps="$2"
shift
;;
--block_size)
block_size="$2"
shift
;;
--conversation_template)
conversation_template="$2"
shift
;;
--per_device_train_batch_size|--batch_size)
per_device_train_batch_size="$2"
batch_size="$2"
shift
;;
--trust_remote_code)
trust_remote_code="$2"
shift
;;
--run_name)
run_name="$2"
shift
;;
--optim)
optim="$2"
shift
;;
--lr)
learning_rate="$2"
shift
;;
--beta1)
beta1="$2"
shift
;;
--beta2)
beta2="$2"
shift
;;
--beta3)
beta3="$2"
shift
;;
--weight_decay)
weight_decay="$2"
shift
;;
--momentum)
momentum="$2"
shift
;;
-n|--num_epoch)
num_epoch="$2"
shift
;;
--lr_schedule)
lr_schedule="$2"
shift
;;
--use_deepspeed)
use_deepspeed="$2"
shift
;;
--seed)
seed="$2"
shift
;;
*)
echo "error: unknown option \"${key}\"" 1>&2
exit 1
esac
shift
done
deepspeed_args="--master_port=1103 --hostfile configs/hostfile"
optim_suffix_args=""
if [ "${optim}" == "dummy" ]; then
optim_suffix_args="--use_customized_optim 1"
optim_suffix_args+=" --customized_optim ${optim}"
optim_suffix_args+=" --optim_dummy_beta1 ${beta1}"
optim_suffix_args+=" --optim_dummy_beta2 ${beta2}"
elif [ "${optim}" == "adabelief" ]; then
optim_suffix_args="--use_customized_optim 1"
optim_suffix_args+=" --customized_optim ${optim}"
optim_suffix_args+=" --optim_beta1 ${beta1}"
optim_suffix_args+=" --optim_beta2 ${beta2}"
optim_suffix_args+=" --optim_weight_decay ${weight_decay}"
elif [ "${optim}" == "adabound" ]; then
optim_suffix_args="--use_customized_optim 1"
optim_suffix_args+=" --customized_optim ${optim}"
optim_suffix_args+=" --optim_beta1 ${beta1}"
optim_suffix_args+=" --optim_beta2 ${beta2}"
optim_suffix_args+=" --optim_weight_decay ${weight_decay}"
elif [ "${optim}" == "lars" ]; then
optim_suffix_args="--use_customized_optim 1"
optim_suffix_args+=" --customized_optim ${optim}"
optim_suffix_args+=" --optim_momentum ${momentum}"
optim_suffix_args+=" --optim_weight_decay ${weight_decay}"
elif [ "${optim}" == "lamb" ]; then
optim_suffix_args="--use_customized_optim 1"
optim_suffix_args+=" --customized_optim ${optim}"
optim_suffix_args+=" --optim_beta1 ${beta1}"
optim_suffix_args+=" --optim_beta2 ${beta2}"
optim_suffix_args+=" --optim_weight_decay ${weight_decay}"
elif [ "${optim}" == "adamax" ]; then
optim_suffix_args="--use_customized_optim 1"
optim_suffix_args+=" --customized_optim ${optim}"
optim_suffix_args+=" --optim_beta1 ${beta1}"
optim_suffix_args+=" --optim_beta2 ${beta2}"
optim_suffix_args+=" --optim_weight_decay ${weight_decay}"
elif [ "${optim}" == "nadam" ]; then
optim_suffix_args="--use_customized_optim 1"
optim_suffix_args+=" --customized_optim ${optim}"
optim_suffix_args+=" --optim_beta1 ${beta1}"
optim_suffix_args+=" --optim_beta2 ${beta2}"
optim_suffix_args+=" --optim_weight_decay ${weight_decay}"
elif [ "${optim}" == "radam" ]; then
optim_suffix_args="--use_customized_optim 1"
optim_suffix_args+=" --customized_optim ${optim}"
optim_suffix_args+=" --optim_beta1 ${beta1}"
optim_suffix_args+=" --optim_beta2 ${beta2}"
optim_suffix_args+=" --optim_weight_decay ${weight_decay}"
elif [ "${optim}" == "adamp" ]; then
optim_suffix_args="--use_customized_optim 1"
optim_suffix_args+=" --customized_optim ${optim}"
optim_suffix_args+=" --optim_beta1 ${beta1}"
optim_suffix_args+=" --optim_beta2 ${beta2}"
optim_suffix_args+=" --optim_weight_decay ${weight_decay}"
elif [ "${optim}" == "sgdp" ]; then
optim_suffix_args="--use_customized_optim 1"
optim_suffix_args+=" --customized_optim ${optim}"
optim_suffix_args+=" --optim_momentum ${momentum}"
optim_suffix_args+=" --optim_weight_decay ${weight_decay}"
elif [ "${optim}" == "yogi" ]; then
optim_suffix_args="--use_customized_optim 1"
optim_suffix_args+=" --customized_optim ${optim}"
optim_suffix_args+=" --optim_beta1 ${beta1}"
optim_suffix_args+=" --optim_beta2 ${beta2}"
optim_suffix_args+=" --optim_weight_decay ${weight_decay}"
elif [ "${optim}" == "sophia" ]; then
optim_suffix_args="--use_customized_optim 1"
optim_suffix_args+=" --customized_optim ${optim}"
optim_suffix_args+=" --optim_beta1 ${beta1}"
optim_suffix_args+=" --optim_beta2 ${beta2}"
optim_suffix_args+=" --optim_weight_decay ${weight_decay}"
elif [ "${optim}" == "adan" ]; then
optim_suffix_args="--use_customized_optim 1"
optim_suffix_args+=" --customized_optim ${optim}"
optim_suffix_args+=" --optim_beta1 ${beta1}"
optim_suffix_args+=" --optim_beta2 ${beta2}"
optim_suffix_args+=" --optim_beta3 ${beta3}"
optim_suffix_args+=" --optim_weight_decay ${weight_decay}"
elif [ "${optim}" == "adam" ]; then
optim_suffix_args="--use_customized_optim 1"
optim_suffix_args+=" --customized_optim ${optim}"
optim_suffix_args+=" --optim_beta1 ${beta1}"
optim_suffix_args+=" --optim_beta2 ${beta2}"
elif [ "${optim}" == "novograd" ]; then
optim_suffix_args="--use_customized_optim 1"
optim_suffix_args+=" --customized_optim ${optim}"
optim_suffix_args+=" --optim_beta1 ${beta1}"
optim_suffix_args+=" --optim_beta2 ${beta2}"
optim_suffix_args+=" --optim_weight_decay ${weight_decay}"
elif [ "${optim}" == "adadelta" ]; then
optim_suffix_args="--use_customized_optim 1"
optim_suffix_args+=" --customized_optim ${optim}"
elif [ "${optim}" == "adagrad" ]; then
optim_suffix_args="--use_customized_optim 1"
optim_suffix_args+=" --customized_optim ${optim}"
elif [ "${optim}" == "muon" ]; then
optim_suffix_args="--use_customized_optim 1"
optim_suffix_args+=" --optim_beta1 ${beta1}"
optim_suffix_args+=" --optim_beta2 ${beta2}"
optim_suffix_args+=" --optim_weight_decay ${weight_decay}"
optim_suffix_args+=" --customized_optim ${optim}"
elif [ "${optim}" == "adamw_schedule_free" ]; then
optim_suffix_args="--use_customized_optim 1"
optim_suffix_args+=" --customized_optim ${optim}"
optim_suffix_args+=" --optim_beta1 ${beta1}"
optim_suffix_args+=" --optim_beta2 ${beta2}"
optim_suffix_args+=" --optim_weight_decay ${weight_decay}"
elif [ "${optim}" == "sgd_schedule_free" ]; then
optim_suffix_args="--use_customized_optim 1"
optim_suffix_args+=" --customized_optim ${optim}"
optim_suffix_args+=" --optim_momentum ${momentum}"
optim_suffix_args+=" --optim_weight_decay ${weight_decay}"
else
optim_suffix_args="--optim ${optim}"
optim_suffix_args+=" --adam_beta1 ${beta1}"
optim_suffix_args+=" --adam_beta2 ${beta2}"
fi
# Finetune
exp_id=alpaca_${optim}_lr-${learning_rate}_beta1-${beta1}_beta2-${beta2}_lr-sched-${lr_schedule}_model-$(basename ${model_name_or_path})_batch-size-${batch_size}x${gradient_accumulation_steps}_seed-${seed}
echo "$(date): ${exp_id}..."
tmp_dir=tmp
mkdir -p ${tmp_dir}
prefix=${exp_id}
if [ -f ${tmp_dir}/${prefix}.mark ]; then
exit 0
fi
trap "rm -f ${tmp_dir}/${prefix}.mark" SIGINT SIGTERM SIGKILL
touch ${tmp_dir}/${prefix}.mark
project_dir=$(cd "$(dirname $0)"/..; pwd)
log_dir=${project_dir}/log/${exp_id}
output_dir=output_models/${exp_id}
mkdir -p ${output_dir} ${log_dir}
exe="deepspeed ${deepspeed_args}"
if [[ ${use_deepspeed} -eq 0 ]]; then
exe=python
fi
${exe} examples/finetune.py \
--model_name_or_path ${model_name_or_path} \
--trust_remote_code ${trust_remote_code} \
--dataset_path ${dataset_path} \
--output_dir ${output_dir} --overwrite_output_dir \
--conversation_template ${conversation_template} \
--num_train_epochs ${num_epoch} \
--learning_rate ${learning_rate} \
--lr_scheduler_type ${lr_schedule} \
--disable_group_texts 1 \
--block_size ${block_size} \
--per_device_train_batch_size ${per_device_train_batch_size} \
--bf16 \
--deepspeed configs/ds_config_zero2_no_offload.json \
--torch_dtype bfloat16 \
--run_name ${exp_id} \
--validation_split_percentage 0 \
--logging_steps 1 \
--do_train \
--ddp_timeout 72000 \
--save_steps 5000 \
--dataloader_num_workers 1 \
--gradient_checkpointing ${gradient_checkpointing} \
--use_flash_attention ${use_flash_attention} \
--gradient_accumulation_steps ${gradient_accumulation_steps} \
--seed ${seed} \
${optim_suffix_args} \
| tee ${log_dir}/train.log \
2> ${log_dir}/train.err
if [[ $? -ne 0 ]]; then
echo "$(date): failed"
rm -f ${tmp_dir}/${prefix}.mark
fi