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run_training.sh
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run_training.sh
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# base
CUDA_VISIBLE_DEVICES=0 python main_central.py \
--data_root data/ScienceQA/data \
--caption_file data/instruct_captions.json \
--model declare-lab/flan-alpaca-base \
--user_msg rationale --img_type vit \
--bs 8 --eval_bs 8 --epoch 20 --lr 8e-5 --output_len 512 \
--use_caption --use_generate --final_eval --prompt_format QCM-E \
--output_dir experiments0620
CUDA_VISIBLE_DEVICES=0 python main_central.py \
--data_root data/ScienceQA/data \
--caption_file data/instruct_captions.json \
--model declare-lab/flan-alpaca-base \
--user_msg rationale --img_type vit \
--bs 8 --eval_bs 8 --epoch 20 --lr 8e-5 --output_len 64 \
--use_caption --use_generate --prompt_format QCMG-A \
--output_dir experiments0620 \
--eval_le experiments/rationale_declare-lab-flan-alpaca-base_vit_QCM-E_lr8e-05_bs8_op512_ep20/predictions_ans_eval.json \
--test_le experiments/rationale_declare-lab-flan-alpaca-base_vit_QCM-E_lr8e-05_bs8_op512_ep20/predictions_ans_test.json
# large
# rationale generation
CUDA_VISIBLE_DEVICES=0,1,2,3 python main.py \
--data_root data/ScienceQA/data \
--caption_file data/instruct_captions.json \
--model declare-lab/flan-alpaca-large \
--user_msg rationale --img_type vit \
--bs 2 --eval_bs 4 --epoch 50 --lr 5e-5 --output_len 512 \
--use_caption --use_generate --prompt_format QCM-E \
--output_dir experiments
# answer inference
CUDA_VISIBLE_DEVICES=0,1,2,3 python main_central.py \
--data_root data/ScienceQA/data \
--caption_file data/instruct_captions.json \
--model declare-lab/flan-alpaca-large \
--user_msg answer --img_type vit \
--bs 4 --eval_bs 8 --epoch 50 --lr 5e-5 --output_len 64 \
--use_caption --use_generate --prompt_format QCMG-A \
--output_dir experiments \
--eval_le experiments/rationale_declare-lab-flan-alpaca-large_vit_QCM-E_lr5e-05_bs8_op512_ep50/predictions_ans_eval.json \
--test_le experiments/rationale_declare-lab-flan-alpaca-large_vit_QCM-E_lr5e-05_bs8_op512_ep50/predictions_ans_test.json