SFT-300 / script.sh
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#!/usr/bin/env bash
#
# Copyright 2023-2024 PKU-Alignment Team. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
if [ -z "${BASH_VERSION}" ]; then
echo "Please use bash to run this script." >&2
exit 1
fi
set -x
SCRIPT_DIR="$(cd "$(dirname "$0")" &>/dev/null && pwd)"
ROOT_DIR="$(dirname "${SCRIPT_DIR}")"
export PYTHONPATH="${ROOT_DIR}${PYTHONPATH:+:${PYTHONPATH}}"
export LOGLEVEL="${LOGLEVEL:-WARNING}"
export WANDB_MODE=online
export WANDB_ENTITY="alelab"
MODEL_NAME_OR_PATH="huggyllama/llama-7b"
timestamp="$(date +%Y%m%d-%H%M%S)"
unset HOSTFILE
ZERO_STAGE=0
OFFLOAD="none"
SAFE_SFT=False
# GRIDSEARCH PARAMS
SAFETY_RATIO_TOL=10
RESILIENT_COEFF=1
LEARNING_RATE=1e-4
NUM_SAFETY_SAMPLES="100"
while [[ "$#" -gt 0 ]]; do
arg="$1"
shift
case "${arg}" in
--model_name_or_path)
MODEL_NAME_OR_PATH="$1"
shift
;;
--model_name_or_path=*)
MODEL_NAME_OR_PATH="${arg#*=}"
;;
--output_dir)
OUTPUT_DIR="$1"
shift
;;
--output_dir=*)
OUTPUT_DIR="${arg#*=}"
;;
--hostfile)
HOSTFILE="$1"
shift
;;
--hostfile=*)
HOSTFILE="${arg#*=}"
;;
--zero_stage)
ZERO_STAGE="$1"
shift
;;
--zero_stage=*)
ZERO_STAGE="${arg#*=}"
;;
--offload)
OFFLOAD="$1"
shift
;;
--offload=*)
OFFLOAD="${arg#*=}"
;;
--safety_ratio_tol)
SAFETY_RATIO_TOL="$1"
shift
;;
--safety_ratio_tol=*)
SAFETY_RATIO_TOL="${arg#*=}"
;;
--resilient_coeff)
RESILIENT_COEFF="$1"
shift
;;
--resilient_coeff=*)
RESILIENT_COEFF="${arg#*=}"
;;
--learning_rate)
LEARNING_RATE="$1"
shift
;;
--learning_rate=*)
LEARNING_RATE="${arg#*=}"
;;
--safe_sft)
SAFE_SFT="$1"
shift
;;
--safe_sft=*)
SAFE_SFT="${arg#*=}"
;;
--num_safety_samples)
NUM_SAFETY_SAMPLES="$1"
shift
;;
--num_safety_samples=*)
NUM_SAFETY_SAMPLES="${arg#*=}"
;;
*)
echo "Unknown parameter passed: '${arg}'" >&2
exit 1
;;
esac
done
OUTPUT_DIR="${ROOT_DIR}/output/sft-safe/${NUM_SAFETY_SAMPLES}/run-${SAFE_SFT}-${NUM_SAFETY_SAMPLES}-${RESILIENT_COEFF}-${SAFETY_RATIO_TOL}"
mkdir -p "${OUTPUT_DIR}"
OUTPUT_DIR="$(cd "${OUTPUT_DIR}" &>/dev/null && pwd)"
if [[ ! -f "${OUTPUT_DIR}/.gitignore" ]]; then
echo '*' >"${OUTPUT_DIR}/.gitignore"
fi
cp -f "$0" "${OUTPUT_DIR}/script.sh"
export WANDB_API_KEY="6a71e7fad84fe1aa8f6ccaa01e4e02fcf4c7ffb4"
if [[ -z "${WANDB_API_KEY}" ]]; then
export WANDB_MODE="offline"
fi
MASTER_PORT_START=10000
MASTER_PORT_END=65535
MASTER_PORT="$(
comm -23 \
<(seq "${MASTER_PORT_START}" "${MASTER_PORT_END}" | sort) \
<(ss -Htan | awk '{ print $4 }' | awk -F ':' '{ print $NF }' | sort -u) |
shuf | head -n 1
)"
DEEPSPEED_ARGS=()
if [[ -n "${HOSTFILE+x}" ]]; then
DEEPSPEED_ARGS+=("--hostfile" "${HOSTFILE}")
fi
DEEPSPEED_ARGS+=("--master_port" "${MASTER_PORT}")
exec 1> >(tee "${OUTPUT_DIR}/stdout.log" >&1) 2> >(tee "${OUTPUT_DIR}/stderr.log" >&2)
echo "--------- Environment sanity check ---------"
echo "shell: $0 running under bash $BASH_VERSION"
echo "conda env: ${CONDA_DEFAULT_ENV:-<none>}"
echo "python: $(which python)"
python - <<'PY'
import sys, os
print("sys.executable :", sys.executable)
print("python version :", sys.version.split()[0])
print("CONDA_PREFIX :", os.environ.get("CONDA_PREFIX"))
PY
echo "deepspeed: $(command -v deepspeed)"
echo "--------------------------------------------"
CUDA_VISIBLE_DEVICES=0,1 deepspeed "${DEEPSPEED_ARGS[@]}" \
--module safe_rlhf.algorithms.safe_ft \
--train_datasets "SAFE-ALPACA/${NUM_SAFETY_SAMPLES}" \
--model_name_or_path "${MODEL_NAME_OR_PATH}" \
--cache_dir "${ROOT_DIR}/cache/sft-${NUM_SAFETY_SAMPLES}" \
--safe_sft "${SAFE_SFT}" \
--max_length 1024 \
--trust_remote_code True \
--epochs 6 \
--per_device_train_batch_size 4 \
--per_device_eval_batch_size 4 \
--gradient_accumulation_steps 32 \
--gradient_checkpointing \
--learning_rate "${LEARNING_RATE}" \
--lr_scheduler_type cosine \
--lr_warmup_ratio 0.03 \
--weight_decay 0.0 \
--seed 42 \
--output_dir "${OUTPUT_DIR}" \
--log_type wandb \
--log_project SAFE-SFT-v3 \
--zero_stage "${ZERO_STAGE}" \
--offload "${OFFLOAD}" \
--safety_ratio_tol "${SAFETY_RATIO_TOL}" \
--resilient_coeff "${RESILIENT_COEFF}" \
--lora_r "4" \
--lora_alpha "16" \
--lora_dropout "0.05" \
--bf16 False \
--fp16 True \
--tf32 True