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#!/bin/bash
# IMPORTANT: this is the training script for the original LLaVA, NOT FOR LLaVA V1.5!
deepspeed llava/train/train_mem.py \
--deepspeed ./scripts/zero2.json \
--model_name_or_path lmsys/vicuna-13b-v1.3 \
--version $PROMPT_VERSION \
--data_path /Data/ScienceQA/data/scienceqa/llava_train_QCM-LEA.json \
--image_folder /Data/ScienceQA/data/scienceqa/images/train \
--vision_tower openai/clip-vit-large-patch14 \
--pretrain_mm_mlp_adapter ./checkpoints/huggingface/liuhaotian/llava-pretrain-vicuna-13b-v1.3/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-vicuna-13b-v1.3-pretrain_lcs558k_plain-ScienceQA_QCM_LEA-12e \
--num_train_epochs 12 \
--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
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