You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
ColossalAI/applications/ColossalChat/examples/training_scripts/train_dpo.sh

63 lines
2.0 KiB

[ColossalChat] Update RLHF V2 (#5286) * Add dpo. Fix sft, ppo, lora. Refactor all * fix and tested ppo * 2 nd round refactor * add ci tests * fix ci * fix ci * fix readme, style * fix readme style * fix style, fix benchmark * reproduce benchmark result, remove useless files * rename to ColossalChat * use new image * fix ci workflow * fix ci * use local model/tokenizer for ci tests * fix ci * fix ci * fix ci * fix ci timeout * fix rm progress bar. fix ci timeout * fix ci * fix ci typo * remove 3d plugin from ci temporary * test environment * cannot save optimizer * support chat template * fix readme * fix path * test ci locally * restore build_or_pr * fix ci data path * fix benchmark * fix ci, move ci tests to 3080, disable fast tokenizer * move ci to 85 * support flash attention 2 * add all-in-one data preparation script. Fix colossal-llama2-chat chat template * add hardware requirements * move ci test data * fix save_model, add unwrap * fix missing bos * fix missing bos; support grad accumulation with gemini * fix ci * fix ci * fix ci * fix llama2 chat template config * debug sft * debug sft * fix colossalai version requirement * fix ci * add sanity check to prevent NaN loss * fix requirements * add dummy data generation script * add dummy data generation script * add dummy data generation script * add dummy data generation script * update readme * update readme * update readme and ignore * fix logger bug * support parallel_output * modify data preparation logic * fix tokenization * update lr * fix inference * run pre-commit --------- Co-authored-by: Tong Li <tong.li352711588@gmail.com>
8 months ago
#!/bin/bash
set_n_least_used_CUDA_VISIBLE_DEVICES() {
local n=${1:-"9999"}
echo "GPU Memory Usage:"
local FIRST_N_GPU_IDS=$(nvidia-smi --query-gpu=memory.used --format=csv |
tail -n +2 |
nl -v 0 |
tee /dev/tty |
sort -g -k 2 |
awk '{print $1}' |
head -n $n)
export CUDA_VISIBLE_DEVICES=$(echo $FIRST_N_GPU_IDS | sed 's/ /,/g')
echo "Now CUDA_VISIBLE_DEVICES is set to:"
echo "CUDA_VISIBLE_DEVICES=$CUDA_VISIBLE_DEVICES"
}
set_n_least_used_CUDA_VISIBLE_DEVICES 8
# export CUDA_VISIBLE_DEVICES=6
PROJECT_NAME="dpo"
PARENT_SAVE_DIR="" # Path to a folder to save checkpoints
PARENT_TENSORBOARD_DIR="" # Path to a folder to save logs
PARENT_CONFIG_FILE="" # Path to a folder to save training config logs
PRETRAINED_MODEL_PATH="" # huggingface or local model path
PRETRAINED_TOKENIZER_PATH="" # huggingface or local tokenizer path
declare -a dataset=(
YOUR/DATA/DIR/arrow/part-00000
YOUR/DATA/DIR/arrow/part-00001
YOUR/DATA/DIR/arrow/part-00002
YOUR/DATA/DIR/arrow/part-00003
YOUR/DATA/DIR/arrow/part-00004
YOUR/DATA/DIR/arrow/part-00005
YOUR/DATA/DIR/arrow/part-00006
YOUR/DATA/DIR/arrow/part-00007
YOUR/DATA/DIR/arrow/part-00008
YOUR/DATA/DIR/arrow/part-00009
)
TIMESTAMP=$(date +%Y-%m-%d-%H-%M-%S)
FULL_PROJECT_NAME="${PROJECT_NAME}-${TIMESTAMP}"
SAVE_DIR="${PARENT_SAVE_DIR}${FULL_PROJECT_NAME}"
CONFIG_FILE="${PARENT_CONFIG_FILE}-${FULL_PROJECT_NAME}.json"
colossalai run --nproc_per_node 8 --hostfile hostfile --master_port 31312 train_dpo.py \
--pretrain $PRETRAINED_MODEL_PATH \
--checkpoint_path $PRETRAINED_MODEL_PATH \
--tokenizer_dir $PRETRAINED_TOKENIZER_PATH \
--dataset ${dataset[@]} \
--plugin "zero2" \
--save_interval 1000 \
--save_dir $SAVE_DIR \
--config_file $CONFIG_FILE \
--max_epochs 1 \
--accumulation_steps 4 \
--batch_size 2 \
--lr 1e-6 \
--mixed_precision "bf16" \
--grad_clip 1.0 \
--weight_decay 0.01 \
--warmup_steps 100 \
--grad_checkpoint \
--use_wandb