37 lines
1.3 KiB
Bash
37 lines
1.3 KiB
Bash
#!/bin/bash
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# IMPORTANT: this is the training script for the original LLaVA, NOT FOR LLaVA V1.5!
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deepspeed llava/train/train_mem.py \
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--deepspeed ./scripts/zero2.json \
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--model_name_or_path lmsys/vicuna-13b-v1.3 \
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--version $PROMPT_VERSION \
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--data_path /Data/ScienceQA/data/scienceqa/llava_train_QCM-LEA.json \
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--image_folder /Data/ScienceQA/data/scienceqa/images/train \
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--vision_tower openai/clip-vit-large-patch14 \
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--pretrain_mm_mlp_adapter ./checkpoints/huggingface/liuhaotian/llava-pretrain-vicuna-13b-v1.3/mm_projector.bin \
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--mm_vision_select_layer -2 \
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--mm_use_im_start_end False \
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--mm_use_im_patch_token False \
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--bf16 True \
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--output_dir ./checkpoints/llava-vicuna-13b-v1.3-pretrain_lcs558k_plain-ScienceQA_QCM_LEA-12e \
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--num_train_epochs 12 \
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--per_device_train_batch_size 16 \
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--per_device_eval_batch_size 4 \
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--gradient_accumulation_steps 1 \
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--evaluation_strategy "no" \
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--save_strategy "steps" \
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--save_steps 50000 \
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--save_total_limit 1 \
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--learning_rate 2e-5 \
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--weight_decay 0. \
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--warmup_ratio 0.03 \
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--lr_scheduler_type "cosine" \
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--logging_steps 1 \
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--tf32 True \
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--model_max_length 2048 \
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--gradient_checkpointing True \
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--dataloader_num_workers 4 \
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--lazy_preprocess True \
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--report_to wandb
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