pllava-34b-demo / scripts /train_pllava.sh
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echo "PYTHONPATH: ${PYTHONPATH}"
which_python=$(which python)
echo "which python: ${which_python}"
export PYTHONPATH=${PYTHONPATH}:${which_python}
export PYTHONPATH=${PYTHONPATH}:.
echo "PYTHONPATH: ${PYTHONPATH}"
OUTPUT_DIR=./pllava_video_outputs/test_train_7b_reconstruct
# # Naive Env
# rm -rf ${OUTPUT_DIR}
pooling_shape=(16,12,12)
accelerate launch --main_process_port 6876 --config_file scripts/accel_config_multigpu.yaml tasks/train/train_pllava_nframe_accel.py \
tasks/train/config_pllava_nframe.py \
output_dir ${OUTPUT_DIR} \
train_corpus videochat2_video \
save_steps 10000 \
num_workers 8 \
num_frames 16 \
model.pooling_method avg \
model.repo_id llava-hf/llava-v1.6-vicuna-7b-hf \
model.use_lora True \
model.pooling_shape $pooling_shape \
optimizer.lr 2e-5 \
scheduler.epochs 3 \
scheduler.warmup_ratio 0.2 \
scheduler.min_lr_multi 0.25 \
scheduler.is_videochat2_custom True \
preprocess.mm_alone False \
preprocess.random_shuffle False \
preprocess.add_second_msg False \
train_corpus videochat2_instruction_debug