| echo "PYTHONPATH: ${PYTHONPATH}" | |
| which_python=$(which python) | |
| echo "which python: ${which_python}" | |
| export PYTHONPATH=${PYTHONPATH}:${which_python} | |
| export PYTHONPATH=${PYTHONPATH}:. | |
| echo "PYTHONPATH: ${PYTHONPATH}" | |
| OUTPUT_DIR=./pllava_video_outputs/test_train_7b_reconstruct | |
| pooling_shape=(16,12,12) | |
| num_save_samples=80000 | |
| num_gpus=8 | |
| full_batch_size=128 | |
| batch_size=8 | |
| save_steps=$[$num_save_samples/($batch_size*$num_gpus)] | |
| ckpt_steps=$[$save_steps/10] | |
| gradient_accumulation_steps=$[$full_batch_size/($batch_size*$num_gpus)] | |
| echo $batch_size | |
| echo $gradient_accumulation_steps | |
| repo_id=llava-hf/llava-v1.6-vicuna-7b-hf | |
| 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_instruction_debug \ | |
| save_steps $save_steps \ | |
| ckpt_steps $ckpt_steps \ | |
| num_workers 8 \ | |
| num_frames 16 \ | |
| gradient_accumulation_steps $gradient_accumulation_steps \ | |
| batch_size $batch_size \ | |
| model.pooling_method avg \ | |
| model.use_lora True \ | |
| model.use_pooling True \ | |
| model.repo_id $repo_id \ | |
| gradient_checkpointing True \ | |
| preprocess.center_pad False \ | |
| preprocess.clip_transform False \ | |
| optimizer.lr 2e-5 \ | |
| scheduler.epochs 3 \ | |
| scheduler.warmup_ratio 0.2 \ | |
| scheduler.min_lr_multi 0.25 \ | |
| model.pooling_shape $pooling_shape \ | |
| scheduler.is_videochat2_custom True \ | |
| preprocess.mm_alone False \ | |
| preprocess.random_shuffle False \ | |
| preprocess.add_second_msg False | |