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e2e_training1.sh
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# export TORCH_DISTRIBUTED_DEBUG=DETAIL
# export DEEPSPEED_LOG_LEVEL=DEBUG
# export OMPI_MCA_btl_base_verbose=1
# export NCCL_DEBUG=INFO
# export NCCL_DEBUG_SUBSYS=ALL
# export TORCH_CPP_LOG_LEVEL=INFO
OUTPUT_DIR=./checkpoints_new/llava-lora_debug #
# max_model_length=2048 # 2048 + 576 * 4 = 2048 + 2304 = 4352
# LR=0.001
# EPOCH=1
# PRBATCH=32
# gradient_accumulation_steps=1
# --lora_enable True --lora_r 128 --lora_alpha 256 --mm_projector_lr 2e-5 \
deepspeed \
--master_port=12322 \
--include localhost:0 \
llava/train/llava_uhd/train_mem.py \
--deepspeed ./scripts/zero2.json \
--model_name_or_path /home/guozonghao/pretrained_models/vicuna-13b-v1.5 \
--version plain \
--data_path ./playground/data/LLaVA-Pretrain/blip_laion_cc_sbu_558k.json \
--image_folder ./playground/data/LLaVA-Pretrain/images \
--vision_tower /home/guozonghao/pretrained_models/clip-vit-large-patch14-336 \
--mm_projector_type mlp2x_gelu \
--tune_mm_mlp_adapter True \
--mm_vision_select_layer -2 \
--mm_use_im_start_end False \
--mm_use_im_patch_token False \
--bf16 True \
--output_dir $OUTPUT_DIR \
--num_train_epochs 1 \
--per_device_train_batch_size 2 \
--per_device_eval_batch_size 4 \
--gradient_accumulation_steps 1 \
--evaluation_strategy "no" \
--save_strategy "steps" \
--save_steps 24000 \
--save_total_limit 1 \
--learning_rate 1e-3 \
--weight_decay 0. \
--warmup_ratio 0.03 \
--lr_scheduler_type "cosine" \
--logging_steps 1 \
--tf32 True \
--model_max_length 2048 \
--gradient_checkpointing True \
--dataloader_num_workers 4 \
--lazy_preprocess True \
--report_to wandb
# OUTPUT_DIR=./checkpoints_new/llava-uhd_adapt_1_schema_split_resample #
# max_model_length=2048 # 2048 + 576 * 4 = 2048 + 2304 = 4352
# LR=0.001
# EPOCH=1
# PRBATCH=32
# gradient_accumulation_steps=1
# deepspeed \
# --master_port=12322 \
# llava/train/llava_uhd/train_mem.py \
# --deepspeed ./scripts/zero2.json \
# --model_name_or_path /home/guozonghao/pretrained_models/vicuna-13b-v1.5 \
# --version plain \
# --data_path ./playground/data/LLaVA-Pretrain/blip_laion_cc_sbu_558k.json \
# --image_folder ./playground/data/LLaVA-Pretrain/images \
# --vision_tower /home/guozonghao/pretrained_models/clip-vit-large-patch14-336 \
# --mm_projector_type mlp2x_gelu \
# --tune_mm_mlp_adapter True \
# --mm_vision_select_layer -2 \
# --mm_use_im_start_end False \
# --mm_use_im_patch_token False \
# --bf16 True \
# --output_dir $OUTPUT_DIR \
# --num_train_epochs 1 \
# --per_device_train_batch_size 32 \
# --per_device_eval_batch_size 4 \
# --gradient_accumulation_steps 1 \
# --evaluation_strategy "no" \
# --save_strategy "steps" \
# --save_steps 24000 \
# --save_total_limit 1 \
# --learning_rate 1e-3 \
# --weight_decay 0. \
# --warmup_ratio 0.03 \
# --lr_scheduler_type "cosine" \
# --logging_steps 1 \
# --tf32 True \
# --model_max_length 2048 \
# --gradient_checkpointing True \
# --dataloader_num_workers 4 \
# --lazy_preprocess True \
# --report_to wandb
# # --include localhost:7 \
# # # # --include localhost:1,2,3,4,5,6,7 \
# # --data_path ./playground/data/llava_v1_5_mix665k.json \
# deepspeed \
# --master_port=12302 \
# llava/train/llava_uhd/train_mem.py \
# --deepspeed ./scripts/zero3.json \
# --model_name_or_path /home/guozonghao/pretrained_models/vicuna-13b-v1.5 \
# --version v1 \
# --data_path ./playground/data/llava_v1_5_mix665k.json \
# --image_folder ./playground/data \
# --vision_tower /home/guozonghao/pretrained_models/clip-vit-large-patch14-336 \
# --pretrain_mm_mlp_adapter $OUTPUT_DIR/mm_projector.bin \
# --mm_projector_type mlp2x_gelu \
# --mm_vision_select_layer -2 \
# --mm_use_im_start_end False \
# --mm_use_im_patch_token False \
# --image_aspect_ratio pad \
# --group_by_modality_length True \
# --bf16 True \
# --output_dir $OUTPUT_DIR \
# --num_train_epochs 1 \
# --per_device_train_batch_size 16 \
# --per_device_eval_batch_size 4 \
# --gradient_accumulation_steps 1 \
# --evaluation_strategy "no" \
# --save_strategy "steps" \
# --save_steps 50000 \
# --save_total_limit 1 \
# --learning_rate 2e-5 \
# --weight_decay 0. \
# --warmup_ratio 0.03 \
# --lr_scheduler_type "cosine" \
# --logging_steps 1 \
# --tf32 True \
# --model_max_length 2048 \
# --gradient_checkpointing True \
# --dataloader_num_workers 4 \
# --lazy_preprocess True \
# --report_to wandb
# # fix144query QWenSampler 0.0002 5ep plain adapt
# OUTPUT_DIR=./checkpoints_new/llava-v1.5-13b-pretrain_fix144_QWsampler_5ep0002_uhd_adpat #
# mm_projector_type=tokenizerQW
# process_mode=anyres
# max_model_length=2048 # 2048 + 576 * 4 = 2048 + 2304 = 4352
# LR=0.0002
# EPOCH=5
# PRBATCH=32
# gradient_accumulation_steps=1
# deepspeed \
# --master_port=12302 \
# llava/train/train_mem.py \
# --deepspeed ./scripts/zero2.json \
# --model_name_or_path /home/guozonghao/pretrained_models/vicuna-13b-v1.5 \
# --version plain \
# --data_path ./playground/data/LLaVA-Pretrain/blip_laion_cc_sbu_558k.json \
# --image_folder ./playground/data/LLaVA-Pretrain/images \
# --vision_tower /home/guozonghao/pretrained_models/clip-vit-large-patch14-336 \
# --mm_projector_type $mm_projector_type \
# --tune_mm_mlp_adapter True \
# --mm_vision_select_layer -2 \
# --mm_use_im_start_end False \
# --mm_use_im_patch_token False \
# --image_aspect_ratio $process_mode \
# --bf16 True \
# --output_dir $OUTPUT_DIR \
# --num_train_epochs $EPOCH \
# --per_device_train_batch_size $PRBATCH \
# --per_device_eval_batch_size 4 \
# --gradient_accumulation_steps $gradient_accumulation_steps \
# --evaluation_strategy "no" \
# --save_strategy "steps" \
# --save_steps 24000 \
# --save_total_limit 1 \
# --learning_rate $LR \
# --weight_decay 0. \
# --warmup_ratio 0.03 \
# --lr_scheduler_type "cosine" \
# --logging_steps 1 \
# --tf32 True \
# --model_max_length $max_model_length \
# --report_to wandb \
# --gradient_checkpointing True \
# --dataloader_num_workers 4 \
# --lazy_preprocess True \
# --crop_image_size 336 \
# --num_query 144 \
# --spatial_cross False \
# --adapt True
# # # fix144query QWenSampler 0.0002 5ep plain adapt sft
# # OUTPUT_DIR=./checkpoints_new/llava-v1.5-13b-pretrain_fix144_QWsampler_5ep0002_multi_spatial_cross #
# LR=0.00002
# EPOCH=1
# FTBATCH=16
# max_model_length=2048 # 2048 + 4 * 256
# gradient_accumulation_steps=1
# deepspeed \
# --include localhost:1 \
# --master_port=12302 \
# llava/train/train_mem.py \
# --deepspeed ./scripts/zero3.json \
# --lora_enable True --lora_r 128 --lora_alpha 256 --mm_projector_lr 2e-5 \
# --model_name_or_path /home/guozonghao/pretrained_models/vicuna-13b-v1.5 \
# --version v1 \
# --data_path ./playground/data/llava_v1_5_mix665k.json \
# --image_folder ./playground/data \
# --vision_tower /home/guozonghao/pretrained_models/clip-vit-large-patch14-336 \
# --pretrain_mm_mlp_adapter $OUTPUT_DIR/mm_projector.bin \
# --mm_projector_type $mm_projector_type \
# --mm_vision_select_layer -2 \
# --mm_use_im_start_end False \
# --mm_use_im_patch_token False \
# --image_aspect_ratio $process_mode \
# --group_by_modality_length True \
# --bf16 True \
# --output_dir $OUTPUT_DIR \
# --num_train_epochs $EPOCH \
# --per_device_train_batch_size $FTBATCH \
# --per_device_eval_batch_size 4 \
# --gradient_accumulation_steps $gradient_accumulation_steps \
# --evaluation_strategy "no" \
# --save_strategy "steps" \
# --save_steps 10000 \
# --save_total_limit 1 \
# --learning_rate $LR \
# --weight_decay 0. \
# --warmup_ratio 0.03 \
# --lr_scheduler_type "cosine" \
# --logging_steps 1 \
# --tf32 True \
# --model_max_length $max_model_length \
# --gradient_checkpointing True \
# --dataloader_num_workers 4 \
# --lazy_preprocess True \
# --crop_image_size 336 \
# --num_query 144 \
# --spatial_cross False \
# --adapt True
# # # fix144query QWenSampler 0.001 1ep spatial cross
# OUTPUT_DIR=./checkpoints_new/llava-v1.5-13b-pretrain_fix144_QWsampler_1ep001_spatial_cross #
# mm_projector_type=tokenizerQW
# max_model_length=2048 # 2048 + 576 * 4 = 2048 + 2304 = 4352
# LR=0.001
# EPOCH=1
# PRBATCH=32
# gradient_accumulation_steps=1
# deepspeed \
# --master_port=12302 \
# llava/train/train_mem.py \
# --deepspeed ./scripts/zero2.json \
# --model_name_or_path /home/guozonghao/pretrained_models/vicuna-13b-v1.5 \
# --version plain \
# --data_path ./playground/data/LLaVA-Pretrain/blip_laion_cc_sbu_558k.json \
# --image_folder ./playground/data/LLaVA-Pretrain/images \
# --vision_tower /home/guozonghao/pretrained_models/clip-vit-large-patch14-336 \
# --mm_projector_type $mm_projector_type \
# --tune_mm_mlp_adapter True \
# --mm_vision_select_layer -2 \
# --mm_use_im_start_end False \
# --mm_use_im_patch_token False \
# --bf16 True \
# --output_dir $OUTPUT_DIR \
# --num_train_epochs $EPOCH \
# --per_device_train_batch_size $PRBATCH \
# --per_device_eval_batch_size 4 \
# --gradient_accumulation_steps $gradient_accumulation_steps \
# --evaluation_strategy "no" \
# --save_strategy "steps" \
# --save_steps 24000 \
# --save_total_limit 1 \
# --learning_rate $LR \
# --weight_decay 0. \
# --warmup_ratio 0.03 \
# --lr_scheduler_type "cosine" \
# --logging_steps 1 \
# --tf32 True \
# --model_max_length $max_model_length \
# --report_to wandb \
# --gradient_checkpointing True \
# --dataloader_num_workers 4 \
# --lazy_preprocess True \
# --crop_image_size 336 \
# --num_query 144 \
# --spatial_cross True \
# --ratio "2"
# # # qw sampler fix 144 sft 0.001 1ep spatial cross
# # OUTPUT_DIR=./checkpoints_new/llava-v1.5-13b-pretrain_fix144_QWsampler_5ep0002_multi_spatial_cross #
# LR=0.00002
# EPOCH=1
# FTBATCH=16
# max_model_length=2048 # 2048 + 4 * 256
# gradient_accumulation_steps=1
# mm_projector_type=tokenizerQW
# deepspeed \
# --master_port=12302 \
# llava/train/train_mem.py \
# --deepspeed ./scripts/zero3.json \
# --model_name_or_path /home/guozonghao/pretrained_models/vicuna-13b-v1.5 \
# --version v1 \
# --data_path ./playground/data/llava_v1_5_mix665k.json \
# --image_folder ./playground/data \
# --vision_tower /home/guozonghao/pretrained_models/clip-vit-large-patch14-336 \
# --pretrain_mm_mlp_adapter $OUTPUT_DIR/mm_projector.bin \
# --mm_projector_type $mm_projector_type \
# --mm_vision_select_layer -2 \
# --mm_use_im_start_end False \
# --mm_use_im_patch_token False \
# --image_aspect_ratio pad \
# --group_by_modality_length True \
# --bf16 True \
# --output_dir $OUTPUT_DIR \
# --num_train_epochs $EPOCH \
# --per_device_train_batch_size $FTBATCH \
# --per_device_eval_batch_size 4 \
# --gradient_accumulation_steps $gradient_accumulation_steps \
# --evaluation_strategy "no" \
# --save_strategy "steps" \
# --save_steps 10000 \
# --save_total_limit 1 \
# --learning_rate $LR \
# --weight_decay 0. \
# --warmup_ratio 0.03 \
# --lr_scheduler_type "cosine" \
# --logging_steps 1 \
# --tf32 True \
# --model_max_length $max_model_length \
# --gradient_checkpointing True \
# --dataloader_num_workers 4 \
# --lazy_preprocess True \
# --crop_image_size 336 \
# --num_query 144 \
# --spatial_cross True \
# --ratio "2"
# # # fix144query QWenSampler 0.0005 2ep spatial cross
# OUTPUT_DIR=./checkpoints_new/llava-v1.5-13b-pretrain_fix144_QWsampler_2ep0005_spatial_cross #
# mm_projector_type=tokenizerQW
# max_model_length=2048 # 2048 + 576 * 4 = 2048 + 2304 = 4352
# LR=0.0005
# EPOCH=2
# PRBATCH=32
# gradient_accumulation_steps=1
# deepspeed \
# --master_port=12302 \
# llava/train/train_mem.py \
# --deepspeed ./scripts/zero2.json \
# --model_name_or_path /home/guozonghao/pretrained_models/vicuna-13b-v1.5 \
# --version plain \
# --data_path ./playground/data/LLaVA-Pretrain/blip_laion_cc_sbu_558k.json \
# --image_folder ./playground/data/LLaVA-Pretrain/images \
# --vision_tower /home/guozonghao/pretrained_models/clip-vit-large-patch14-336 \
# --mm_projector_type $mm_projector_type \
# --tune_mm_mlp_adapter True \
# --mm_vision_select_layer -2 \
# --mm_use_im_start_end False \
# --mm_use_im_patch_token False \
# --bf16 True \
# --output_dir $OUTPUT_DIR \
# --num_train_epochs $EPOCH \
# --per_device_train_batch_size $PRBATCH \
# --per_device_eval_batch_size 4 \
# --gradient_accumulation_steps $gradient_accumulation_steps \
# --evaluation_strategy "no" \
# --save_strategy "steps" \
# --save_steps 24000 \
# --save_total_limit 1 \
# --learning_rate $LR \
# --weight_decay 0. \
# --warmup_ratio 0.03 \
# --lr_scheduler_type "cosine" \
# --logging_steps 1 \
# --tf32 True \
# --model_max_length $max_model_length \
# --report_to wandb \
# --gradient_checkpointing True \
# --dataloader_num_workers 4 \
# --lazy_preprocess True \
# --crop_image_size 336 \
# --num_query 144 \
# --spatial_cross True \
# --ratio "2"
# # # qw sampler fix 144 sft 0.001 1ep spatial cross
# # OUTPUT_DIR=./checkpoints_new/llava-v1.5-13b-pretrain_fix144_QWsampler_5ep0002_multi_spatial_cross #
# LR=0.00002
# EPOCH=1
# FTBATCH=16
# max_model_length=2048 # 2048 + 4 * 256
# gradient_accumulation_steps=1
# mm_projector_type=tokenizerQW
# deepspeed \
# --master_port=12302 \
# llava/train/train_mem.py \
# --deepspeed ./scripts/zero3.json \
# --model_name_or_path /home/guozonghao/pretrained_models/vicuna-13b-v1.5 \
# --version v1 \
# --data_path ./playground/data/llava_v1_5_mix665k.json \
# --image_folder ./playground/data \
# --vision_tower /home/guozonghao/pretrained_models/clip-vit-large-patch14-336 \
# --pretrain_mm_mlp_adapter $OUTPUT_DIR/mm_projector.bin \
# --mm_projector_type $mm_projector_type \
# --mm_vision_select_layer -2 \
# --mm_use_im_start_end False \
# --mm_use_im_patch_token False \
# --image_aspect_ratio pad \
# --group_by_modality_length True \
# --bf16 True \
# --output_dir $OUTPUT_DIR \
# --num_train_epochs $EPOCH \
# --per_device_train_batch_size $FTBATCH \
# --per_device_eval_batch_size 4 \
# --gradient_accumulation_steps $gradient_accumulation_steps \
# --evaluation_strategy "no" \
# --save_strategy "steps" \
# --save_steps 10000 \
# --save_total_limit 1 \
# --learning_rate $LR \
# --weight_decay 0. \
# --warmup_ratio 0.03 \
# --lr_scheduler_type "cosine" \
# --logging_steps 1 \
# --tf32 True \
# --model_max_length $max_model_length \
# --gradient_checkpointing True \
# --dataloader_num_workers 4 \
# --lazy_preprocess True \
# --crop_image_size 336 \
# --num_query 144 \
# --spatial_cross True \
# --ratio "2"