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52 lines
1.6 KiB
52 lines
1.6 KiB
#!/bin/bash
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set_n_least_used_CUDA_VISIBLE_DEVICES() {
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local n=${1:-"9999"}
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echo "GPU Memory Usage:"
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local FIRST_N_GPU_IDS=$(nvidia-smi --query-gpu=memory.used --format=csv |
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tail -n +2 |
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nl -v 0 |
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tee /dev/tty |
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sort -g -k 2 |
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awk '{print $1}' |
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head -n $n)
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export CUDA_VISIBLE_DEVICES=$(echo $FIRST_N_GPU_IDS | sed 's/ /,/g')
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echo "Now CUDA_VISIBLE_DEVICES is set to:"
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echo "CUDA_VISIBLE_DEVICES=$CUDA_VISIBLE_DEVICES"
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}
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set_n_least_used_CUDA_VISIBLE_DEVICES 2
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PROJECT_NAME="orpo"
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PARENT_CONFIG_FILE="./benchmark_config" # Path to a folder to save training config logs
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PRETRAINED_MODEL_PATH="" # huggingface or local model path
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PRETRAINED_TOKENIZER_PATH="" # huggingface or local tokenizer path
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BENCHMARK_DATA_DIR="./temp/orpo" # Path to benchmark data
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DATASET_SIZE=160
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TIMESTAMP=$(date +%Y-%m-%d-%H-%M-%S)
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FULL_PROJECT_NAME="${PROJECT_NAME}-${TIMESTAMP}"
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declare -a dataset=(
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$BENCHMARK_DATA_DIR/arrow/part-0
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)
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# Generate dummy test data
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python prepare_dummy_test_dataset.py --data_dir $BENCHMARK_DATA_DIR --dataset_size $DATASET_SIZE --max_length 2048 --data_type preference
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colossalai run --nproc_per_node 2 --master_port 31313 ../examples/training_scripts/train_orpo.py \
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--pretrain $PRETRAINED_MODEL_PATH \
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--tokenizer_dir $PRETRAINED_TOKENIZER_PATH \
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--dataset ${dataset[@]} \
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--plugin "zero2" \
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--max_epochs 1 \
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--accumulation_steps 1 \
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--batch_size 4 \
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--lr 8e-6 \
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--lam 0.5 \
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--mixed_precision "bf16" \
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--grad_clip 1.0 \
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--max_length 2048 \
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--weight_decay 0.01 \
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--warmup_steps 60 \
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--grad_checkpoint \
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--use_flash_attn
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