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35 lines
1.0 KiB
Bash
35 lines
1.0 KiB
Bash
#!/bin/bash
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CUDA_VISIBLE_DEVICES=0 python src/train_bash.py \
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--stage sft_mm \
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--do_train \
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--model_name_or_path /home/LAB/fengzc/LLM/checkpoints/Salesforce/blip2-opt-2.7b \
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--dataset llava_instruct_100 \
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--dataset_dir data \
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--template default \
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--finetuning_type lora \
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--lora_target q_proj,k_proj \
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--output_dir saves/blip2-opt-2.7b/lora/sft \
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--overwrite_cache \
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--overwrite_output_dir \
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--cutoff_len 1024 \
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--preprocessing_num_workers 16 \
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--per_device_train_batch_size 1 \
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--per_device_eval_batch_size 1 \
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--gradient_accumulation_steps 8 \
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--lr_scheduler_type cosine \
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--logging_steps 1 \
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--warmup_steps 20 \
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--save_steps 100 \
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--eval_steps 100 \
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--evaluation_strategy steps \
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--load_best_model_at_end \
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--learning_rate 5e-5 \
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--num_train_epochs 3.0 \
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--max_samples 3000 \
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--val_size 0.1 \
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--plot_loss \
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--quantization_bit 8 \
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--image_path /home/LAB/fengzc/LLM/checkpoints/liuhaotian/LLaVA-Instruct-150K/images/coco/train2017
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