|
|
|
|
|
|
|
|
RANK=1 |
|
|
MASTER_PORT=29571 |
|
|
|
|
|
|
|
|
LOCAL_BATCH_SIZE=4 |
|
|
GRADIENT_ACCUMULATION_STEPS=1 |
|
|
|
|
|
|
|
|
export TRANSFORMERS_OFFLINE=1 |
|
|
export WANDB_PROJECT=vtimellm |
|
|
MODEL_VERSION=vicuna-v1-5-7b |
|
|
OUTPUT_DIR=./outputs/ |
|
|
|
|
|
RUN_NAME=vtimellm-$MODEL_VERSION-activitynet-stage4 |
|
|
deepspeed --include localhost:$RANK --master_port $MASTER_PORT vtimellm/train/train_mem.py \ |
|
|
--deepspeed ./scripts/zero2.json \ |
|
|
--lora_enable True \ |
|
|
--training_stage 3 --finetuning True \ |
|
|
--model_name_or_path ./checkpoints/vtimellm/vicuna-7b-v1.5 \ |
|
|
--version v1 \ |
|
|
--data_path ./data/activitynet/cotasks-train.json \ |
|
|
--feat_folder ./data/activitynet/clipvitl14-vtimellm.pth \ |
|
|
--pretrain_mm_mlp_adapter ./checkpoints/vtimellm/vtimellm-$MODEL_VERSION-stage1/mm_projector.bin \ |
|
|
--stage2_path ./checkpoints/vtimellm/vtimellm-$MODEL_VERSION-stage2 \ |
|
|
--stage3_path ./checkpoints/vtimellm/vtimellm-$MODEL_VERSION-stage3 \ |
|
|
--output_dir $OUTPUT_DIR/${RUN_NAME} \ |
|
|
--bf16 True \ |
|
|
--num_train_epochs 1 \ |
|
|
--per_device_train_batch_size $LOCAL_BATCH_SIZE \ |
|
|
--gradient_accumulation_steps $GRADIENT_ACCUMULATION_STEPS \ |
|
|
--evaluation_strategy "no" \ |
|
|
--save_strategy "no" \ |
|
|
--save_steps 50000 \ |
|
|
--save_total_limit 10 \ |
|
|
--learning_rate 2e-5 \ |
|
|
--freeze_mm_mlp_adapter True \ |
|
|
--lora_r 64 --lora_alpha 128 --weight_decay 0. --warmup_ratio 0.03 \ |
|
|
--lr_scheduler_type "cosine" \ |
|
|
--logging_steps 1 \ |
|
|
--tf32 True \ |
|
|
--model_max_length 2048 \ |
|
|
--gradient_checkpointing True \ |
|
|
--dataloader_num_workers 4 \ |
|
|
--lazy_preprocess True \ |
|
|
--report_to wandb \ |
|
|
--run_name $RUN_NAME |
