hanluzhi0429@gmail.com
75 lines
2.4 KiB
Bash
75 lines
2.4 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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VISION_MODEL_VERSION="google/siglip-so400m-patch14-384"
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VISION_MODEL_VERSION_CLEAN="${VISION_MODEL_VERSION//\//_}"
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############### Pretrain ################
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BASE_RUN_NAME="llavanext-google_siglip-so400m-patch14-384-Qwen_Qwen2-7B-Instruct-mlp2x_gelu-pretrain_blip558k_plain"
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echo "BASE_RUN_NAME: ${BASE_RUN_NAME}"
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############### Finetune ################
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MIXTURE="qwen"
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# Stage 2
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PROMPT_VERSION="qwen_vla"
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RUN_NAME="llava-openvla-${MIXTURE}"
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PREV_STAGE_CHECKPOINT="/mnt/d/temp/huggingface/hub/llava_qwen_vla"
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# PREV_STAGE_CHECKPOINT="/mnt/d/ckpt/llava-openvla-qwen"
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echo "PREV_STAGE_CHECKPOINT: ${PREV_STAGE_CHECKPOINT}"
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echo "MID_RUN_NAME: ${RUN_NAME}"
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NUM_GPUS=1
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NNODES=1
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ACCELERATE_CPU_AFFINITY=1 torchrun --nproc_per_node="${NUM_GPUS}" --nnodes="${NNODES}" \
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llava/train/train_mem.py \
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--deepspeed scripts/zero2.json \
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--model_name_or_path $PREV_STAGE_CHECKPOINT \
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--version $PROMPT_VERSION \
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--data_path /root/code/openvla-llava/LLaVA-Next/scripts/train/vla.yaml \
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--image_folder /root/code/openvla-llava/LLaVA-Next/images \
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--mm_tunable_parts="mm_language_model" \
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--mm_vision_tower_lr=2e-6 \
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--vision_tower google/siglip-so400m-patch14-384 \
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--mm_projector_type mlp2x_gelu \
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--mm_vision_select_layer -2 \
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--mm_use_im_start_end False \
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--mm_use_im_patch_token False \
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--group_by_modality_length True \
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--image_aspect_ratio anyres_max_9 \
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--image_grid_pinpoints "(1x1),...,(6x6)" \
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--mm_patch_merge_type spatial_unpad \
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--bf16 True \
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--run_name $RUN_NAME \
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--output_dir /mnt/d/ckpt_3_28/$RUN_NAME \
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--num_train_epochs 5 \
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--per_device_train_batch_size 8 \
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--per_device_eval_batch_size 100 \
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--gradient_accumulation_steps 2 \
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--evaluation_strategy "no" \
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--save_strategy "steps" \
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--save_steps 900 \
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--save_total_limit 2 \
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--learning_rate 1e-4 \
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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 4096 \
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--gradient_checkpointing True \
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--dataloader_num_workers 1 \
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--lazy_preprocess True \
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--report_to wandb \
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--torch_compile True \
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--torch_compile_backend "inductor" \
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--dataloader_drop_last True \
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--frames_upbound 1
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exit 0;
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# You can delete the sdpa attn_implementation if you want to use flash attn
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