#!/bin/bash
export CUDA_DEVICE_MAX_CONNECTIONS=1
NPUS_PER_NODE=8
MASTER_ADDR=localhost
MASTER_PORT=6024
NNODES=1
NODE_RANK=0
WORLD_SIZE=$(($NPUS_PER_NODE*$NNODES))
CKPT_SAVE_DIR="your model save ckpt path"
DATA_PATH="your data path"
CKPT_LOAD_DIR="your model ckpt path"
TOKENIZER_MODEL="your tokenizer path"
TP=1
PP=8
DISTRIBUTED_ARGS="
--master_addr $MASTER_ADDR \
--node_rank $NODE_RANK \
--worker_num $WORLD_SIZE \
--local_worker_num $NPUS_PER_NODE \
--master_port $MASTER_PORT \
--log_dir=msrun_log \
--join=False \
--cluster_time_out=300 \
--bind_core=True \
"
GPT_ARGS="
--tensor-model-parallel-size ${TP} \
--pipeline-model-parallel-size ${PP} \
--use-mcore-models \
--micro-batch-size 1 \
--global-batch-size 8 \
--sequence-parallel \
--use-flash-attn \
--prompt-type llama3 \
--variable-seq-lengths \
--use-rotary-position-embeddings \
--rope-scaling-type llama3 \
--rope-scaling-factor 8.0 \
--rotary-percent 1.0 \
--low-freq-factor 1.0 \
--high-freq-factor 4.0 \
--original-max-position-embeddings 8192 \
--tokenizer-type PretrainedFromHF \
--tokenizer-name-or-path ${TOKENIZER_MODEL} \
--tokenizer-not-use-fast \
--num-layers 32 \
--hidden-size 4096 \
--ffn-hidden-size 14336 \
--num-attention-heads 32 \
--group-query-attention \
--num-query-groups 8 \
--seq-length 8192 \
--max-position-embeddings 8192 \
--make-vocab-size-divisible-by 1 \
--padded-vocab-size 128256 \
--untie-embeddings-and-output-weights \
--disable-bias-linear \
--attention-dropout 0.0 \
--init-method-std 0.02 \
--hidden-dropout 0.0 \
--position-embedding-type rope \
--rotary-base 500000 \
--normalization RMSNorm \
--norm-epsilon 1e-5 \
--swiglu \
--no-masked-softmax-fusion \
--attention-softmax-in-fp32 \
--lr 1e-6 \
--train-iters 2000 \
--lr-decay-style cosine \
--weight-decay 0.0 \
--clip-grad 1.0 \
--adam-beta1 0.9 \
--adam-beta2 0.999 \
--initial-loss-scale 4096 \
--finetune \
--stage sft \
--is-instruction-dataset \
--no-gradient-accumulation-fusion \
--no-load-optim \
--no-load-rng \
--bf16 \
--seed 42 \
--vocab-size 128256 \
"
FINETUNE_ARGS="
--lora-r 8 \
--lora-alpha 16 \
--lora-fusion \
--lora-target-modules linear_qkv linear_proj linear_fc1 linear_fc2 \
"
DATA_ARGS="
--data-path $DATA_PATH \
--split 100,0,0 \
"
OUTPUT_ARGS="
--log-interval 1 \
--save-interval 2000 \
--eval-interval 2000 \
--eval-iters 10 \
--load ${CKPT_LOAD_DIR} \
--save ${CKPT_SAVE_DIR} \
"
msrun $DISTRIBUTED_ARGS posttrain_gpt.py \
$GPT_ARGS \
$DATA_ARGS \
$FINETUNE_ARGS \
$OUTPUT_ARGS \
--distributed-backend nccl \
--ai-framework mindspore \
| tee logs/tune_llama31_8b_lora_ptd.log