tuanio/ft-llava-qwen1.5-0.5b-vista_llava-2ep

• Merged LoRA
• Training script

#!/bin/bash

PRETRAIN_CKPT_PATH=checkpoints/llava-qwen1.5-0.5b-pretrain-vista_description-3ep
BASE_MODEL=Qwen/Qwen1.5-0.5B
ROOT_DATA=data/llm_data

WANDB_PROJECT=chart-vision-llm CUDA_VISIBLE_DEVICES=0,1,2,3,4  deepspeed moellava/train/train_mem.py \
    --lora_enable True --lora_r 128 --lora_alpha 256 --mm_projector_lr 0.00000125 \
    --deepspeed ./scripts/zero2.json \
    --model_name_or_path $BASE_MODEL \
    --version qwen \
    --data_path $ROOT_DATA/json_files/vista_llava.json \
    --image_folder ${ROOT_DATA}/coco2017/train2017 \
    --image_tower google/siglip-base-patch16-256-multilingual \
    --image_projector_type mlp2x_gelu \
    --pretrain_mm_mlp_adapter $PRETRAIN_CKPT_PATH/mm_projector.bin \
    --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 pad \
    --group_by_modality_length True \
    --bf16 True \
    --output_dir ./checkpoints/ft-llava-qwen1.5-0.5b-vista_llava-lora-2ep \
    --num_train_epochs 2 \
    --per_device_train_batch_size 8 \
    --per_device_eval_batch_size 2 \
    --gradient_accumulation_steps 2 \
    --evaluation_strategy "no" \
    --save_strategy "steps" \
    --save_steps 5000 \
    --save_total_limit 1 \
    --learning_rate 2e-5 \
    --weight_decay 0. \
    --warmup_ratio 0.03 \
    --lr_scheduler_type "cosine" \
    --logging_steps 10 \
    --tf32 True \
    --model_max_length 2048 \
    --gradient_checkpointing True \
    --dataloader_num_workers 4 \
    --lazy_preprocess True \
    --report_to wandb \
    --push_to_hub True \
    --cache_dir cache_dir \
    --run_name ft-llava-qwen1.5-0.5b-vista_llava-lora-2ep