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finetune_all_stage3_next.sh

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+#!/bin/bash
+
+# Pretrain a multimodal model.
+export OMP_NUM_THREADS=8
+export NCCL_IB_DISABLE=0
+export NCCL_IB_GID_INDEX=3
+export NCCL_SOCKET_IFNAME=eth0
+export NCCL_DEBUG=INFO
+export NCCL_IB_SL=1
+export CUDA_DEVICE_MAX_CONNECTIONS=1
+export NCCL_BLOCKING_WAIT=1
+export NCCL_ASYNC_ERROR_HANDLING=1
+export NCCL_TIMEOUT=500
+export TORCH_DISTRIBUTED_DEBUG=DETAIL
+export NCCL_SOCKET_FAMILY=AF_INET6
+export NCCL_NET_PLUGIN=libnccl-net-gcp-fastrak.so
+
+DATETIME=`date +'%y-%m-%d-%H-%M-%S'`
+
+# Setting for multi nodes training.
+ports=(`echo $METIS_WORKER_0_PORT | tr ',' ' '`)
+port=${ports[0]}
+
+echo "total workers: ${ARNOLD_WORKER_NUM}"
+echo "cur worker id: ${ARNOLD_ID}"
+echo "gpus per worker: ${ARNOLD_WORKER_GPU}"
+echo "master ip: ${METIS_WORKER_0_HOST}"
+echo "master port: ${port}"
+
+source /mnt/bn/tns-algo-video-public-my2/wangpeng.an/environment/anaconda3/bin/activate vicuna16k
+
+cd /mnt/bn/tns-algo-video-public-my2/wangpeng.an/model/OmniFusion-vicuna16k
+
+# Install necessary packages
+pip3 install requests
+pip3 install attrs
+pip3 install aiofiles
+pip3 install pynvml
+
+
+# Print Python executable path, torchrun, deepspeed and PYTHONPATH
+echo "Python executable: $(which python)"
+echo "torchrun executable: $(which torchrun)"
+echo "deepspeed executable: $(which deepspeed)"
+echo "PYTHONPATH before torchrun: $PYTHONPATH"
+
+sudo chmod 777 /var/lib/fastrak -R
+
+# Launch training with DeepSpeed and torchrun
+ACCELERATE_CPU_AFFINITY=1 torchrun --nproc_per_node=$ARNOLD_WORKER_GPU --nnodes=$ARNOLD_WORKER_NUM --node_rank=$ARNOLD_ID --master_addr=$METIS_WORKER_0_HOST --master_port=$port \
+    llava/train/train_mem.py \
+    --deepspeed ./scripts/zero2.json \
+    --model_name_or_path /mnt/bn/tns-algo-video-public-my2/wangpeng.an/model/vicuna-7b-v1.5-16k \
+    --version plain \
+    --data_path /mnt/bn/tns-algo-video-public-my2/wangpeng.an/data/stage3/video_image_asr_caption_stage3_1225_next.json \
+    --audio_asr_folder /mnt/bn/tns-algo-video-public-my2/wangpeng.an/data \
+    --audio_caption_folder /mnt/bn/tns-algo-video-public-my2/wangpeng.an/data/audio_caption \
+    --video_folder /mnt/bn/tns-algo-video-public-my2/wangpeng.an/data/video \
+    --image_folder /mnt/bn/tns-algo-video-public-my2/wangpeng.an/data/video/Video-LLaVA \
+    --X "Audio_asr" "Audio_caption" "Video" "Image" \
+    --audio_tower /mnt/bn/tns-algo-video-public-my2/wangpeng.an/model/LanguageBind_Audio_Asr \
+    --audio_caption_tower /mnt/bn/tns-algo-video-public-my2/wangpeng.an/model/pretrained_model/LanguageBind_Audio \
+    --video_tower /mnt/bn/tns-algo-video-public-my2/wangpeng.an/model/pretrained_model/LanguageBind_Video_merge \
+    --image_tower /mnt/bn/tns-algo-video-public-my2/wangpeng.an/model/pretrained_model/LanguageBind_Image \
+    --pretrain_mm_mlp_adapter /mnt/bn/tns-algo-video-public-my2/wangpeng.an/model/OmniFusion-vicuna16k/checkpoints/Video-LLaVA-Pretrain-7B-0106/mm_projector.bin \
+    --mm_projector_type mlp2x_gelu \
+    --mm_vision_select_layer -2 \
+    --mm_use_x_start_end False \
+    --mm_use_x_patch_token False \
+    --image_aspect_ratio pad \
+    --group_by_modality_length True \
+    --bf16 True \
+    --output_dir ./checkpoints/OmniFusion-vicuna-stage3-0106-next \
+    --num_train_epochs 1 \
+    --per_device_train_batch_size 4 \
+    --per_device_eval_batch_size 4 \
+    --gradient_accumulation_steps 1 \
+    --evaluation_strategy "no" \
+    --save_strategy "steps" \
+    --save_steps 3000 \
+    --save_total_limit 4 \
+    --learning_rate 2e-5 \
+    --weight_decay 0. \
+    --warmup_ratio 0.03 \
+    --lr_scheduler_type "cosine" \
+    --logging_steps 1 \
+    --tf32 True \
+    --model_max_length 2048 \
+    --tokenizer_model_max_length 3072 \
+    --gradient_checkpointing True \
+    --dataloader_num_workers 8 \
+    --lazy_preprocess True \
+    --report_to none \
+    --cache_dir "./cache_dir"