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Starting
on
A10G
Starting
on
A10G
# Uncomment and set the following variables correspondingly to run this script: | |
################## VICUNA ################## | |
# PROMPT_VERSION=v1 | |
# MODEL_VERSION="vicuna-v1-3-7b" | |
################## VICUNA ################## | |
################## LLaMA-2 ################## | |
# PROMPT_VERSION="llava_llama_2" | |
# MODEL_VERSION="llama-2-7b-chat" | |
################## LLaMA-2 ################## | |
deepspeed llava/train/train_mem.py \ | |
--deepspeed ./scripts/zero2.json \ | |
--model_name_or_path ./checkpoints/$MODEL_VERSION \ | |
--version $PROMPT_VERSION \ | |
--data_path ./playground/data/llava_instruct_80k.json \ | |
--image_folder /path/to/coco/train2017 \ | |
--vision_tower openai/clip-vit-large-patch14 \ | |
--pretrain_mm_mlp_adapter ./checkpoints/llava-$MODEL_VERSION-pretrain/mm_projector.bin \ | |
--mm_vision_select_layer -2 \ | |
--mm_use_im_start_end False \ | |
--mm_use_im_patch_token False \ | |
--bf16 True \ | |
--output_dir ./checkpoints/llava-$MODEL_VERSION-finetune \ | |
--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 | |