Video-LLaVA / scripts /finetune_qlora.sh
LinB203
m
5244231
#!/bin/bash
# IMPORTANT: this is the training script for the original LLaVA, NOT FOR LLaVA V1.5!
# 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 \
--lora_enable True \
--bits 4 \
--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_lora \
--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 \
--lazy_preprocess True \
--dataloader_num_workers 4 \
--report_to wandb