run-7b-sft-lora-single.sh

#!/bin/bash
export MIOPEN_FIND_MODE=3
export GPU_MAX_HW_QUEUES=16
lrank=$OMPI_COMM_WORLD_LOCAL_RANK
comm_rank=$OMPI_COMM_WORLD_RANK
comm_size=$OMPI_COMM_WORLD_SIZE
export LOCAL_RANK=$OMPI_COMM_WORLD_LOCAL_RANK
export RANK=$comm_rank
export WORLD_SIZE=$comm_size
export NCCL_IB_HCA=mlx5
export NCCL_SOCKET_IFNAME=ib0 
export HIP_DIRECT_DISPATCH=0


APP="python3 ../src/train_bash.py --stage sft \
    --model_name_or_path ../../baichuan-7b-base \
    --do_train \
    --template default \
    --dataset alpaca_gpt4_en \
    --finetuning_type lora \
    --lora_rank 16 \
    --lora_target W_pack,o_proj,gate_proj,down_proj,up_proj \
    --output_dir out/baichuan-7b-lora-test7 \
    --per_device_train_batch_size 1 \
    --per_device_eval_batch_size 1 \
    --gradient_accumulation_steps 1 \
    --preprocessing_num_workers 8 \
    --lr_scheduler_type cosine \
    --logging_steps 10 \
    --save_steps 2 \
    --eval_steps 2 \
    --learning_rate 1e-4 \
    --max_grad_norm 0.5 \
    --num_train_epochs 1.0 \
    --val_size 0.001 \
    --evaluation_strategy steps \
    --load_best_model_at_end \
    --plot_loss \
    --fp16 \
    --deepspeed deepspeed.json
"

case ${lrank} in
[0])
  export HIP_VISIBLE_DEVICES=0,1,2,3
  export UCX_NET_DEVICES=mlx5_0:1
  export UCX_IB_PCI_BW=mlx5_0:50Gbs
  numactl --cpunodebind=0 --membind=0 ${APP}
  ;;
[1])
  export HIP_VISIBLE_DEVICES=0,1,2,3
  export UCX_NET_DEVICES=mlx5_1:1
  export UCX_IB_PCI_BW=mlx5_1:50Gbs
  numactl --cpunodebind=1 --membind=1 ${APP}
  ;;
[2])
  export HIP_VISIBLE_DEVICES=0,1,2,3
  export UCX_NET_DEVICES=mlx5_2:1
  export UCX_IB_PCI_BW=mlx5_2:50Gbs
  numactl --cpunodebind=2 --membind=2 ${APP}
  ;;
[3])
  export HIP_VISIBLE_DEVICES=0,1,2,3
  export UCX_NET_DEVICES=mlx5_3:1
  export UCX_IB_PCI_BW=mlx5_3:50Gbs
  numactl --cpunodebind=3 --membind=3 ${APP}
  ;;
esac