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| export LLAVA_DEFAULT_CONVERSATION="conv_vicuna_v1" | |
| # run | |
| export LOGDIR=logs/ | |
| export out_dir="${LOGDIR}/llava-plus/llava_plus_v1.3_7b" | |
| mkdir -p $out_dir | |
| echo ${out_dir}/loginfo.txt | |
| # Note: Our scripts support multi-source data and image folders. Seperate each item with `,`. Note that it may cause problems if multiple folders have images with the same name. | |
| deepspeed llava/train/train_mem.py \ | |
| --deepspeed scripts/zero2.json \ | |
| --model_name_or_path path/to/LLAVA/vicuna-7b-v1.3 \ | |
| --pretrain_mm_mlp_adapter path/to/llava-pretrain-vicuna-7b-v1.3 \ | |
| --version v1 \ | |
| --data_path path/to/llava-150k-tool-aug.json,path/to/llava-plus-v1-117k-tool-merge.json \ | |
| --image_folder /path/to/coco/train2017/,/path/to/hiertext/train,/path/to/infoseek/infoseek_images,/path/to/instruct-pix2pix/clip-filtered-dataset,/path/to/goldg/vg_mdetr/images \ | |
| --vision_tower openai/clip-vit-large-patch14 \ | |
| --mm_vision_select_layer -2 \ | |
| --mm_use_im_start_end False \ | |
| --mm_use_im_patch_token False \ | |
| --bf16 True \ | |
| --output_dir $out_dir \ | |
| --num_train_epochs 3 \ | |
| --per_device_train_batch_size 16 \ | |
| --per_device_eval_batch_size 4 \ | |
| --gradient_accumulation_steps 2 \ | |
| --evaluation_strategy "no" \ | |
| --save_strategy "steps" \ | |
| --save_steps 1000 \ | |
| --save_total_limit 8 \ | |
| --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 \ | |
| >> ${out_dir}/loginfo.txt 2>&1 |