out of memory when fine-tune the ICX2.5

[cool-xuan]

Following your fine-tune instruction, my finetune.sh is as

#!/bin/bash
export CUDA_DEVICE_MAX_CONNECTIONS=1
DIR=`pwd`

export MODEL="./ckpt/internlm-xcomposer2d5-7b"
# export DATA="path of data"
export DATA="data.txt"

GPUS_PER_NODE=4
NNODES=1
NODE_RANK=0
MASTER_ADDR=localhost
MASTER_PORT=6001

DISTRIBUTED_ARGS="
    --nproc_per_node $GPUS_PER_NODE \
    --nnodes $NNODES \
    --node_rank $NODE_RANK \
    --master_addr $MASTER_ADDR \
    --master_port $MASTER_PORT
"

torchrun $DISTRIBUTED_ARGS ./finetune/finetune.py \
    --model_name_or_path $MODEL \
    --data_path $DATA \
    --given_num True \
    --bf16 True \
    --fix_vit True \
    --fix_sampler False \
    --use_lora False \
    --hd_num 18 \
    --output_dir output/0724/paired_data_ft_fixVIT_bz16 \
    --num_train_epochs 1 \
    --batch_size 1 \
    --per_device_train_batch_size 1 \
    --per_device_eval_batch_size 1 \
    --gradient_accumulation_steps 1 \
    --evaluation_strategy "no" \
    --save_strategy "epoch" \
    --save_total_limit 1 \
    --learning_rate 1e-5 \
    --weight_decay 0.1 \
    --adam_beta2 0.95 \
    --warmup_ratio 0.01 \
    --lr_scheduler_type "cosine" \
    --logging_steps 1 \
    --report_to "none" \
    --max_length 16384 \
    --deepspeed ./finetune/ds_config_zero2.json \
    --gradient_checkpointing True

All batch sizes are set to 1 and only two images are encoded for each conversation. I run this shell on 4 A100 with 80G GPU memory, with out of memory in the first iteration.

All packages are same with your env docs/install.md, except torch=2.10 and cuda=12.1.

Any advice for this wired OOD?

[yuhangzang]

You may

• try LoRA
• decrease the value of --max_length, e.g., --max_length=4096
• decrease the value of --hd_num

[cool-xuan]

You may

• try LoRA
• decrease the value of --max_length, e.g., --max_length=4096
• decrease the value of --hd_num

Thanks for your reply. Fine tuning by LoRA solves the OOD error. However, even when I reduce max_length=4096 and hd_num=4, full parameters tuning still encounter OOD. Maybe some other advice to try for full parameters tuning?

[FUJIsyu0515]

@yuhangzang @cool-xuan The methods you provided are very useful for avoiding OOM at startup. I have tried them. However, now it always suddenly appears OOM after running dozens of steps. I have no idea what parameter configuration is really effective.

[yuhangzang]

Do not forget to install the flash-attention 2.

You may need 8 A100 80G GPUs for full parameters tuning.

If you use LoRA fine-tuning, you can also decrease the value of lora_r and lora_alpha to avoid the OOM problem.