wehub-resource-sync
55 lines
1.9 KiB
Bash
55 lines
1.9 KiB
Bash
export OMP_NUM_THREADS=8
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export NCCL_IB_DISABLE=0
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export NCCL_IB_GID_INDEX=3
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export NCCL_SOCKET_IFNAME=eth0
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export NCCL_DEBUG=INFO
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LLM_VERSION="Qwen/Qwen2-7B-Instruct"
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LLM_VERSION_CLEAN="${LLM_VERSION//\//_}"
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VISION_MODEL_VERSION="openai/clip-vit-large-patch14-336"
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VISION_MODEL_VERSION_CLEAN="${VISION_MODEL_VERSION//\//_}"
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############### Pretrain ################
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PROMPT_VERSION=plain
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BASE_RUN_NAME="llavanext-${VISION_MODEL_VERSION_CLEAN}-${LLM_VERSION_CLEAN}-mlp2x_gelu-pretrain_blip558k_plain"
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echo "BASE_RUN_NAME: ${BASE_RUN_NAME}"
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ACCELERATE_CPU_AFFINITY=1 torchrun --nproc_per_node="${NUM_GPUS}" --nnodes="${NNODES}" --node_rank="${RANK}" --master_addr="${ADDR}" --master_port="${PORT}" \
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llava/train/train_mem.py \
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--deepspeed scripts/zero3.json \
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--model_name_or_path ${LLM_VERSION} \
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--version ${PROMPT_VERSION} \
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--data_path /blip_558k/blip_558k_plain.json \
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--image_folder /blip_558k/images \
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--vision_tower ${VISION_MODEL_VERSION} \
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--mm_tunable_parts="mm_mlp_adapter" \
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--mm_vision_select_layer -2 \
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--mm_projector_type mlp2x_gelu \
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--mm_use_im_start_end False \
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--mm_use_im_patch_token False \
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--bf16 True \
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--output_dir /checkpoints/projectors/${BASE_RUN_NAME} \
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--num_train_epochs 1 \
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--per_device_train_batch_size 16 \
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--per_device_eval_batch_size 4 \
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--gradient_accumulation_steps 1 \
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--evaluation_strategy "no" \
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--save_strategy "no" \
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--save_steps 50000 \
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--learning_rate 1e-3 \
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--weight_decay 0. \
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--warmup_ratio 0.03 \
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--lr_scheduler_type "cosine" \
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--logging_steps 1 \
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--tf32 True \
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--model_max_length 8192 \
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--gradient_checkpointing True \
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--dataloader_num_workers 16 \
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--lazy_preprocess True \
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--report_to wandb \
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--run_name $BASE_RUN_NAME \
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--attn_implementation sdpa
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# You can delete the sdpa attn_implementation if you want to use flash attn |