53 lines
1.3 KiB
Bash
53 lines
1.3 KiB
Bash
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run_type = $1
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model = $2
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gpu_cnt = $3
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max_steps = $4
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current_datetime=$(date +%Y%m%d%H%M%S)
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if [ "${run_type}" = "lora_sft" ]; then
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run_name="${run_type}_${model}_${gpu_cnt}_gpu_${max_steps}_step_${current_datetime}"
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else
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run_name="${run_type}_${model}_${gpu_cnt}_gpu_${current_datetime}"
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fi
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output_dir ="./results/${run_name}"
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if [ ! -d "$output_dir" ]; then
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mkdir -p "$output_dir"
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echo "路径不存在，已创建: $output_dir"
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else
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echo "路径已存在: $output_dir"
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fi
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echo "${run_type} ${model} ${gpu_cnt} ${max_steps} ${run_name} ${output_dir}"
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python prepare_yaml_file.py ${run_type} ${model} ${max_steps} ${run_name} ${output_dir}
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# export USE_MODELSCOPE_HUB=1
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# # 0 means not printing gpu status
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# python gpu_status.py ${output_dir} 0 &
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# gpu_status_pid=$!
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# echo "Start recording gpu status "
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# if [ "${gpu_cnt}" = "1" ]; then
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# ASCEND_RT_VISIBLE_DEVICES=0 llamafactory-cli train ${output_dir}/${run_name}.yml \
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# | tee ${output_dir}/log.txt" &
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# train_pid=$!
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# echo "Start train"
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# else
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# FORCE_TORCHRUN=1 llamafactory-cli train ${output_dir}/${run_name}.yml \
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# | tee ${output_dir}/log.txt" &
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# train_pid=$!
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# echo "Start train"
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# fi
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# wait $train_pid
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# echo "Train ended"
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# sleep 90
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# kill $gpu_status_pid
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# echo "Gpu status ended"
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