83 lines
2.3 KiB
Markdown
83 lines
2.3 KiB
Markdown
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# Lora 训练
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## lora 训练脚本
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``` shell
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#! /bin/bash
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#!/bin/bash
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#SBATCH --partition=gpu3
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#SBATCH --nodes=1
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#SBATCH --nodelist=g3005
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#SBATCH --ntasks-per-node=4
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#SBATCH --gres=gpu:4
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#SBATCH --cpus-per-task=4
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#SBATCH --mem=512GB
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export MASTER_ADDR="localhost"
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export MASTER_PORT=12347
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CPM_PATH="/home/wangxvjia/CPM-onlyllama"
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EXP_PATH=/home/wangxvjia/9g_models/cpm_fin_new_1e4
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MODEL_NAME="9g-finance-sft"
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OPTS=""
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OPTS+=" --vocab /home/wangxvjia/9g_models/vocab.txt"
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OPTS+=" --model-config /home/wangxvjia/9g_models/config.json"
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OPTS+=" --train-iters 695"
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OPTS+=" --inspect-iters 2000"
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OPTS+=" --warmup-iters 20"
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OPTS+=" --lr-decay-style cosine"
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OPTS+=" --weight-decay 0.01"
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OPTS+=" --clip-grad 1.0"
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OPTS+=" --loss-scale 1048576"
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OPTS+=" --max-loss-scale 33554432"
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OPTS+=" --min-loss-scale 1"
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OPTS+=" --loss-scale-steps 32"
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OPTS+=" --offload"
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OPTS+=" --batch-size 2"
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OPTS+=" --max-length 4096"
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OPTS+=" --lr 3e-4"
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OPTS+=" --start-step 0"
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OPTS+=" --epoch 4"
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OPTS+=" --load /data/groups/QY_LLM_Other/anrongqiao/UltraEval/caterpillar_8b_checkpoint-22000-float16.pt"
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OPTS+=" --dataset /home/wangxvjia/molora/data_process/fin_9g/train_data_30000"
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# TODO 这些 /data 在启元机器上需要改成 /home 下的路径
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OPTS+=" --save ${EXP_PATH}/checkpoints"
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OPTS+=" --save-name ${MODEL_NAME}"
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OPTS+=" --delta-tuning"
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OPTS+=" --delta-type lora"
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OPTS+=" --lora-r 64" # 常用的lora 参数
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OPTS+=" --lora-dropout 0.05"
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OPTS+=" --lora-alpha 64" # 常用的lora alpha 参数
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OPTS+=" --lora-layer project_q project_v project_k w_0 w_1 w_out"
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OPTS+=" --save-origin-model"
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OPTS+=" $@"
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CMD="torchrun --nnodes=1 --nproc_per_node=2 --rdzv_id=1 --rdzv_backend=c10d --rdzv_endpoint=${MASTER_ADDR}:${MASTER_PORT} ${CPM_PATH}/apps/cpm9g/sft_cpm9g.py ${OPTS}"
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echo "${CMD}"
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$CMD
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```
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## 合并模型
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训练好的lora delta model一般有两种方式
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- 在直接含有lora的推理代码进行推理
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- 将lora delta model参数和original model merge在一起 作为新的模型，但是模型的参数数量并没有增多
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python merge_lora_delta.py --base_path cpm9g-8b-sft.pt --delta_path cpm9g-lora.pt --merge_path cpm9g-8b-sft_with_lora.pt
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# lora 推理
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合并后的lora模型可以直接采用基础模型推理代码
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见[quick start](https://www.osredm.com/jiuyuan/CPM-9G-8B/tree/master/quick_start_clean/readmes/README_ALL.md)
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