{"id":119740,"date":"2026-10-30T08:48:41","date_gmt":"2026-10-30T00:48:41","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/119740.html"},"modified":"2026-10-30T08:48:41","modified_gmt":"2026-10-30T00:48:41","slug":"%e5%a4%a7%e6%a8%a1%e5%9e%8b%e5%be%ae%e8%b0%83%e5%a4%8d%e7%8e%b0%e5%ae%9e%e9%aa%8c%e5%88%86%e6%9e%90%e6%8a%a5%e5%91%8a-%e5%9f%ba%e4%ba%8e%e5%8d%95%e5%8d%a1-gpu-%e6%9c%8d%e5%8a%a1","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/119740.html","title":{"rendered":"\u5927\u6a21\u578b\u5fae\u8c03\u590d\u73b0\u5b9e\u9a8c\u5206\u6790\u62a5\u544a\u2014\u2014 \u57fa\u4e8e\u5355\u5361 GPU \u670d\u52a1\u5668\u7684\u8bad\u7ec3\u73af\u5883\u9002\u914d\u4e0e\u95ee\u9898\u6392\u67e5"},"content":{"rendered":"

\u5927\u6a21\u578b\u5fae\u8c03\u590d\u73b0\u5b9e\u9a8c\u5206\u6790\u62a5\u544a<\/span><\/p>\n

\u2014\u2014 <\/span>\u57fa\u4e8e\u5355\u5361<\/span> GPU <\/span>\u670d\u52a1\u5668\u7684\u8bad\u7ec3\u73af\u5883\u9002\u914d\u4e0e\u95ee\u9898\u6392\u67e5<\/span><\/p>\n\n\n\n\n\n\n\n
\n

\u9879\u76ee<\/span><\/p>\n<\/td>\n

\n

\u8bf4\u660e<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

\u5b9e\u9a8c\u4e3b\u9898<\/span><\/p>\n<\/td>\n

\n

\u4f2a\u4ee3\u7801\u89c4\u8303\u5316\u6a21\u578b\u5fae\u8c03\u4efb\u52a1\u590d\u73b0（<\/span>LLaMA-Factory <\/span>\u5168\u53c2<\/span> SFT<\/span>）<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

\u8bad\u7ec3\u6846\u67b6<\/span><\/p>\n<\/td>\n

\n

LLaMA-Factory<\/span>（<\/span>llamafactory-cli<\/span>）<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

\u786c\u4ef6\u73af\u5883<\/span><\/p>\n<\/td>\n

\n

\u5355\u5361<\/span> GPU <\/span>\u670d\u52a1\u5668，\u663e\u5b58<\/span> 31.73 GiB<\/span>（<\/span>32 GB <\/span>\u7ea7）<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

\u6838\u5fc3\u95ee\u9898<\/span><\/p>\n<\/td>\n

\n

\u6df7\u5408\u7cbe\u5ea6\u4e0d\u517c\u5bb9\u3001\u5206\u5e03\u5f0f\u542f\u52a8\u65b9\u5f0f\u4e0d\u5339\u914d\u3001\u6a21\u578b\u4e0b\u8f7d\u53d7\u9650\u3001\u663e\u5b58\u6ea2\u51fa<\/span><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u4e00\u3001\u5b9e\u9a8c\u6458\u8981<\/span><\/p>\n

\u672c\u5b9e\u9a8c\u5728\u5355\u5361<\/span> GPU <\/span>\u670d\u52a1\u5668\u4e0a，\u57fa\u4e8e<\/span> LLaMA-Factory <\/span>\u6846\u67b6\u5bf9\u4f2a\u4ee3\u7801\u89c4\u8303\u5316（<\/span>pseudo2norm<\/span>）\u4efb\u52a1\u8fdb\u884c\u5168\u53c2\u6570\u76d1\u7763\u5fae\u8c03（<\/span>SFT<\/span>）\u590d\u73b0\u3002\u590d\u73b0\u8fc7\u7a0b\u5e76\u975e\u4e00\u5e06\u98ce\u987a，\u5148\u540e\u906d\u9047\u56db\u7c7b\u5178\u578b\u95ee\u9898：<\/span><\/p>\n

\u2460<\/span>\u8bad\u7ec3\u786c\u4ef6\u4e0d\u652f\u6301<\/span> bf16 <\/span>\u6df7\u5408\u7cbe\u5ea6；<\/span><\/p>\n

\u2461DeepSpeed <\/span>\u5206\u5e03\u5f0f\u542f\u52a8\u65b9\u5f0f\u4e0e\u5355\u5361\u73af\u5883\u4e0d\u5339\u914d；<\/span><\/p>\n

\u2462<\/span>\u6a21\u578b\u4e0e\u4f9d\u8d56\u4e0b\u8f7d\u53d7\u7f51\u7edc\u9650\u5236；<\/span><\/p>\n

\u2463<\/span>\u5168\u53c2\u5fae\u8c03\u89e6\u53d1<\/span> CUDA <\/span>\u663e\u5b58\u6ea2\u51fa\u3002<\/span><\/p>\n

\u9488\u5bf9\u4e0a\u8ff0\u95ee\u9898，\u5b9e\u9a8c\u91c7\u53d6<\/span>\u201c<\/span>\u9010\u5c42\u5b9a\u4f4d\u3001\u9010\u9879\u9002\u914d<\/span>\u201d<\/span>\u7684\u6392\u67e5\u601d\u8def，\u4f9d\u6b21\u901a\u8fc7<\/span>\u201cbf16 <\/span>\u6539<\/span> fp16<\/span>\u3001\u5173\u95ed<\/span> DeepSpeed<\/span>\u3001\u914d\u7f6e<\/span> HF <\/span>\u955c\u50cf\u7aef\u70b9\u3001\u538b\u7f29\u5355\u6b65\u6279\u5927\u5c0f\u5e76\u653e\u5927\u68af\u5ea6\u7d2f\u79ef<\/span>\u201d<\/span>\u56db\u9879\u63aa\u65bd\u5b8c\u6210\u73af\u5883\u4e0e\u914d\u7f6e\u7684\u672c\u5730\u5316\u9002\u914d，\u6700\u7ec8\u4ee5<\/span> nohup <\/span>\u540e\u53f0\u65b9\u5f0f\u7a33\u5b9a\u62c9\u8d77\u957f\u65f6\u8bad\u7ec3\u3002\u6574\u4e2a\u6392\u67e5\u94fe\u8def\u8986\u76d6\u4e86\u4ece\u4f9d\u8d56\u5b89\u88c5\u3001\u7cbe\u5ea6\u9009\u578b\u3001\u5206\u5e03\u5f0f\u7b56\u7565\u5230\u8d44\u6e90\u9884\u7b97\u7684\u5b8c\u6574\u5de5\u7a0b\u73af\u8282，\u5bf9\u540c\u7c7b<\/span>\u201c<\/span>\u5355\u5361\u590d\u73b0\u591a\u5361\u8bad\u7ec3\u914d\u7f6e<\/span>\u201d<\/span>\u7684\u573a\u666f\u5177\u6709\u8f83\u5f3a\u7684\u53c2\u8003\u4ef7\u503c\u3002<\/span><\/p>\n

\u4e8c\u3001\u5b9e\u9a8c\u73af\u5883\u4e0e\u6574\u4f53\u6392\u67e5\u6d41\u7a0b<\/span><\/p>\n

2.1 <\/span>\u8f6f\u4ef6\u73af\u5883<\/span><\/p>\n

\u8bad\u7ec3\u4f9d\u8d56\u4ee5\u4e0b\u6838\u5fc3\u5e93，\u7248\u672c\u4e4b\u95f4\u9700\u4e25\u683c\u5339\u914d<\/span>：<\/span><\/p>\n\n\n\n\n\n\n\n\n
\n

\u7ec4\u4ef6<\/span><\/p>\n<\/td>\n

\n

\u7248\u672c<\/span><\/p>\n<\/td>\n

\n

\u4f5c\u7528<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

accelerate<\/span><\/p>\n<\/td>\n

\n

1.3.0<\/span><\/p>\n<\/td>\n

\n

\u8bad\u7ec3\u52a0\u901f\u4e0e\u8bbe\u5907\u8c03\u5ea6<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

peft<\/span><\/p>\n<\/td>\n

\n

0.14.0<\/span><\/p>\n<\/td>\n

\n

\u53c2\u6570\u9ad8\u6548\u5fae\u8c03\u652f\u6301<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

transformers<\/span><\/p>\n<\/td>\n

\n

4.49.0<\/span><\/p>\n<\/td>\n

\n

\u6a21\u578b\u4e0e\u8bad\u7ec3\u6838\u5fc3\u5e93<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

trl<\/span><\/p>\n<\/td>\n

\n

0.8.6<\/span><\/p>\n<\/td>\n

\n

\u8bad\u7ec3\u6d41\u7a0b\u6269\u5c55（<\/span>SFT <\/span>\u7b49）<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

LLaMA-Factory<\/span><\/p>\n<\/td>\n

\n

\u6e90\u7801\u90e8\u7f72<\/span><\/p>\n<\/td>\n

\n

\u7edf\u4e00\u8bad\u7ec3\u5165\u53e3<\/span><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

2.2 <\/span>\u6574\u4f53\u6392\u67e5\u6d41\u7a0b<\/span><\/p>\n

\u590d\u73b0\u5de5\u4f5c\u6309\u7167<\/span>\u201c<\/span>\u73af\u5883\u642d\u5efa<\/span> \u2192 <\/span>\u542f\u52a8\u914d\u7f6e<\/span> \u2192 <\/span>\u8d44\u6e90\u9002\u914d<\/span> \u2192 <\/span>\u540e\u53f0\u8fd0\u884c<\/span>\u201d<\/span>\u56db\u4e2a\u9636\u6bb5\u63a8\u8fdb，\u6bcf\u4e2a\u9636\u6bb5\u5747\u4ee5\u4e00\u6b21\u62a5\u9519\u6216\u74f6\u9888\u4e3a\u9a71\u52a8\u5b8c\u6210\u4e00\u8f6e\u4fee\u590d，\u6574\u4f53\u6d41\u7a0b\u5982\u56fe<\/span> 1 <\/span>\u6240\u793a\u3002<\/span><\/p>\n

\"\"<\/p>\n

\u56fe<\/span> 1\u00a0 <\/span>\u8bad\u7ec3\u73af\u5883\u9002\u914d\u95ee\u9898\u6392\u67e5\u4e0e\u89e3\u51b3\u6d41\u7a0b<\/span><\/p>\n

2.3 <\/span>\u5e38\u7528\u73af\u5883\u51c6\u5907\u547d\u4ee4<\/span><\/p>\n

# <\/span>\u6bcf\u6b21\u8fdb\u5165<\/span> conda <\/span>\u73af\u5883\u524d\u9700\u5148\u521d\u59cb\u5316<\/span> shell<\/span><\/span><\/p>\n

# <\/span>\u6a21\u578b\u4e0e\u6570\u636e\u96c6\u4e0b\u8f7d\u8d70\u56fd\u5185\u955c\u50cf，\u907f\u514d\u5883\u5916\u6e90\u8d85\u65f6<\/span><\/span><\/p>\n

\u4e09\u3001\u95ee\u9898\u73b0\u8c61\u3001\u6839\u56e0\u4e0e\u89e3\u51b3\u65b9\u6848<\/span><\/p>\n

\u56db\u7c7b\u95ee\u9898\u7684<\/span>\u201c<\/span>\u73b0\u8c61<\/span>\u2014<\/span>\u6839\u56e0<\/span>\u2014<\/span>\u5bf9\u7b56<\/span>\u201d<\/span>\u5bf9\u5e94\u5173\u7cfb\u6c47\u603b\u5982\u56fe<\/span> 2 <\/span>\u6240\u793a，\u4ee5\u4e0b\u5206\u5c0f\u8282\u5c55\u5f00\u5206\u6790\u3002<\/span><\/p>\n

\"\"<\/p>\n

\u56fe<\/span> 2\u00a0 <\/span>\u56db\u7c7b\u95ee\u9898<\/span>\u201c<\/span>\u73b0\u8c61<\/span>\u2014<\/span>\u6839\u56e0<\/span>\u2014<\/span>\u5bf9\u7b56<\/span>\u201d<\/span>\u5f52\u56e0\u77e9\u9635<\/span><\/p>\n

3.1 <\/span>\u6df7\u5408\u7cbe\u5ea6\u4e0d\u517c\u5bb9：<\/span>bf16 <\/span>\u4e0d\u53d7\u786c\u4ef6\u652f\u6301<\/span><\/p>\n

\u9996\u6b21\u542f\u52a8\u8bad\u7ec3\u5373\u5728\u53c2\u6570\u89e3\u6790\u9636\u6bb5\u629b\u51fa\u5f02\u5e38：<\/span><\/p>\n

\u8be5\u62a5\u9519\u6765\u81ea<\/span> transformers <\/span>\u7684<\/span> TrainingArguments <\/span>\u6821\u9a8c\u903b\u8f91：<\/span>bf16 <\/span>\u6df7\u5408\u7cbe\u5ea6\u8981\u6c42<\/span> GPU <\/span>\u5177\u5907<\/span> Ampere<\/span>（\u5b89\u57f9）\u53ca\u4ee5\u4e0a\u67b6\u6784\u5e76\u914d\u5408<\/span> CUDA 11.0+<\/span>\u3002\u672c\u5b9e\u9a8c\u6240\u7528<\/span> GPU <\/span>\u4e3a\u4e0a\u4e00\u4ee3\u67b6\u6784，\u4ec5\u652f\u6301<\/span> fp16 <\/span>\u534a\u7cbe\u5ea6，\u56e0\u6b64\u8bad\u7ec3\u914d\u7f6e\u4e2d\u76f4\u63a5\u542f\u7528<\/span> bf16 <\/span>\u4f1a\u89e6\u53d1\u786c\u6027\u6821\u9a8c\u5931\u8d25\u3002<\/span><\/p>\n

\u89e3\u51b3\u65b9\u6848\u662f\u5c06\u8bad\u7ec3<\/span> YAML <\/span>\u914d\u7f6e\u4e2d\u7684\u7cbe\u5ea6\u5f00\u5173\u7531<\/span> bf16 <\/span>\u5207\u6362\u4e3a<\/span> fp16<\/span>：<\/span><\/p>\n

# <\/span>\u539f\u914d\u7f6e（\u542f\u7528<\/span> bf16<\/span>，\u5f53\u524d<\/span> GPU <\/span>\u4e0d\u652f\u6301）<\/span><\/span><\/p>\n

bf16: true<\/span><\/span><\/p>\n

# <\/span>\u4fee\u6539\u4e3a（\u5173\u95ed<\/span> bf16<\/span>，\u542f\u7528<\/span> fp16<\/span>）<\/span><\/span><\/p>\n

bf16: false<\/span><\/span><\/p>\n

fp16: true<\/span><\/span><\/p>\n

\u9700\u8981\u6ce8\u610f，<\/span>fp16 <\/span>\u52a8\u6001\u8303\u56f4\u5c0f\u4e8e<\/span> bf16<\/span>，\u8bad\u7ec3\u6846\u67b6\u4f1a\u81ea\u52a8\u5f15\u5165\u635f\u5931\u7f29\u653e（<\/span>loss scaling<\/span>）\u4ee5\u7f13\u89e3\u68af\u5ea6\u4e0b\u6ea2；\u82e5\u540e\u7eed\u8bad\u7ec3\u51fa\u73b0\u635f\u5931\u9707\u8361，\u53ef\u91cd\u70b9\u5173\u6ce8\u8be5\u56e0\u7d20\u3002<\/span><\/p>\n

3.2 <\/span>\u5206\u5e03\u5f0f\u542f\u52a8\u65b9\u5f0f\u4e0d\u5339\u914d：<\/span>DeepSpeed <\/span>\u4e0e\u5355\u5361\u73af\u5883\u51b2\u7a81<\/span><\/p>\n

\u4fee\u590d\u7cbe\u5ea6\u95ee\u9898\u540e\u518d\u6b21\u542f\u52a8，\u51fa\u73b0\u7b2c\u4e8c\u4e2a\u963b\u65ad\u6027\u62a5\u9519：<\/span><\/p>\n

\u539f\u4ed3\u5e93\u8bad\u7ec3\u914d\u7f6e<\/span>\u65b9\u6848\u9762\u5411\u591a\u5361\u96c6\u7fa4，\u8981\u6c42\u901a\u8fc7<\/span> torchrun <\/span>\u5206\u5e03\u5f0f\u65b9\u5f0f\u62c9\u8d77\u8fdb\u7a0b\u3002\u800c\u5f53\u524d\u670d\u52a1\u5668\u4ec5\u6709\u4e00\u5f20<\/span> GPU<\/span>，\u65e2\u65e0\u5fc5\u8981\u4e5f\u65e0\u6761\u4ef6\u542f\u7528\u5206\u5e03\u5f0f\u8bad\u7ec3\u3002<\/span><\/p>\n

\n

\u56fe<\/span> 3\u00a0 <\/span>\u5173\u952e\u914d\u7f6e\u9009\u578b\u5bf9\u6bd4：\u6df7\u5408\u7cbe\u5ea6\u4e0e\u8bad\u7ec3\u62c9\u8d77\u65b9\u5f0f<\/span><\/p>\n

\u89e3\u51b3\u65b9\u6848\u6709\u4e24\u6761\u8def\u5f84：\u5176\u4e00，\u6309\u62a5\u9519\u63d0\u793a\u6539\u7528<\/span> FORCE_TORCHRUN=1 <\/span>\u62c9\u8d77（\u9002\u5408\u591a\u5361）；\u5176\u4e8c，\u9488\u5bf9\u5355\u5361\u73af\u5883\u76f4\u63a5\u5173\u95ed<\/span> DeepSpeed<\/span>\u3002\u672c\u5b9e\u9a8c\u9009\u62e9\u540e\u8005：<\/span><\/p>\n

3.3 <\/span>\u6a21\u578b\u4e0e\u4f9d\u8d56\u4e0b\u8f7d\u53d7\u9650：\u914d\u7f6e\u56fd\u5185\u955c\u50cf<\/span><\/p>\n

\u73af\u5883\u51c6\u5907\u9636\u6bb5\u8fd8\u53d1\u73b0<\/span> Hugging Face <\/span>\u5b98\u65b9\u6e90\u8bbf\u95ee\u7f13\u6162\u3001\u6613\u8d85\u65f6，\u5bfc\u81f4\u6a21\u578b\u6743\u91cd\u4e0e\u6570\u636e\u96c6\u4e0b\u8f7d\u53cd\u590d\u4e2d\u65ad\u3002\u901a\u8fc7\u8bbe\u7f6e\u955c\u50cf\u7aef\u70b9\u73af\u5883\u53d8\u91cf\u89e3\u51b3：<\/span><\/p>\n

\u8be5\u53d8\u91cf\u4f1a\u5c06\u88ab<\/span> Hugging Face <\/span>\u7cfb\u5de5\u5177\u8bc6\u522b\u7684\u4e0b\u8f7d\u6e90\u6574\u4f53\u5207\u6362\u81f3\u56fd\u5185\u955c\u50cf\u7ad9\u70b9，\u5c5e\u4e8e\u4e00\u6b21\u914d\u7f6e\u3001\u5168\u7a0b\u751f\u6548\u7684\u4f4e\u6210\u672c\u4f18\u5316\u3002<\/span><\/p>\n

3.4 <\/span>\u663e\u5b58\u6ea2\u51fa：<\/span>CUDA OOM <\/span>\u7684\u91cf\u5316\u5206\u6790\u4e0e\u53c2\u6570\u518d\u5e73\u8861<\/span><\/p>\n

\u4e0a\u8ff0\u914d\u7f6e\u4fee\u6b63\u540e\u8bad\u7ec3\u5f97\u4ee5\u542f\u52a8，\u4f46\u5f88\u5feb\u5728\u6ce8\u610f\u529b\u8ba1\u7b97（<\/span>softmax<\/span>）\u9636\u6bb5\u5d29\u6e83，\u62a5\u9519\u4fe1\u606f\u7ed9\u51fa\u4e86\u5b8c\u6574\u7684\u663e\u5b58\u8d26\u672c：<\/span><\/p>\n

\u4ece\u62a5\u9519\u6570\u636e\u770b：\u5168\u53c2\u5fae\u8c03\u672c\u8eab\u5df2\u5360\u7528\u7ea6<\/span> 27.81 GiB<\/span>（\u6a21\u578b\u6743\u91cd\u3001\u4f18\u5316\u5668\u72b6\u6001\u4e0e\u6fc0\u6d3b\u503c），\u52a0\u4e0a\u6846\u67b6\u4e0e\u4e0a\u4e0b\u6587\u5f00\u9500\u540e\u8fdb\u7a0b\u603b\u5360\u7528\u8fbe<\/span> 30.30 GiB<\/span>，\u4ec5\u5269<\/span> 1.43 GiB <\/span>\u53ef\u7528；\u800c\u5355\u4e2a\u6ce8\u610f\u529b\u5c42\u7684<\/span> softmax <\/span>\u6fc0\u6d3b\u5c31\u9700\u8981<\/span> 1.79 GiB<\/span>，\u7f3a\u53e3\u7ea6<\/span> 0.36 GiB<\/span>，\u76f4\u63a5\u89e6\u53d1<\/span> OOM<\/span>\u3002\u5404\u663e\u5b58\u5206\u91cf\u7684\u5bf9\u6bd4\u89c1\u56fe<\/span> 4(a)<\/span>\u3002<\/span><\/p>\n

\n

\u56fe<\/span> 4\u00a0 <\/span>\u663e\u5b58\u74f6\u9888\u5206\u6790\u4e0e\u8bad\u7ec3\u6279\u53c2\u6570\u8c03\u6574<\/span><\/p>\n

\u89e3\u51b3\u601d\u8def\u662f<\/span>\u201c<\/span>\u4ee5\u65f6\u95f4\u6362\u7a7a\u95f4<\/span>\u201d<\/span>：\u5c06\u5355\u6b65\u6279\u5927\u5c0f\u4ece<\/span> 8 <\/span>\u964d\u81f3<\/span> 1<\/span>，\u540c\u65f6\u628a\u68af\u5ea6\u7d2f\u79ef\u6b65\u6570\u4ece<\/span> 8 <\/span>\u63d0\u5347\u81f3<\/span> 16<\/span>，\u5728\u51e0\u4e4e\u4e0d\u6539\u53d8\u8bad\u7ec3\u8bed\u4e49\u7684\u524d\u63d0\u4e0b\u5927\u5e45\u538b\u7f29\u6fc0\u6d3b\u663e\u5b58\u5cf0\u503c（\u89c1\u56fe<\/span> 4(b)<\/span>）\u3002\u540c\u65f6\u5c06\u5b66\u4e60\u7387\u56fa\u5b9a\u4e3a<\/span> 3.0e-6<\/span>\u3001\u8bad\u7ec3<\/span> 2 <\/span>\u4e2a<\/span> epoch<\/span>，\u5e76\u91c7\u7528\u5e26\u6700\u5c0f\u5b66\u4e60\u7387\u4e0b\u9650\u7684\u4f59\u5f26\u8c03\u5ea6\u5668\u3002\u76f8\u5173\u914d\u7f6e\u4fee\u6539\u5982\u4e0b：<\/span><\/p>\n

\u9700\u8981\u6307\u51fa，\u8c03\u6574\u540e\u6709\u6548\u6279\u5927\u5c0f\u7531<\/span> 8\u00d78=64 <\/span>\u53d8\u4e3a<\/span> 1\u00d716=16<\/span>，\u7b49\u6548\u4e8e\u8bad\u7ec3\u566a\u58f0\u76f8\u5bf9\u589e\u5927；\u82e5\u540e\u7eed\u6307\u6807\u4e0d\u7406\u60f3，\u53ef\u7ee7\u7eed\u589e\u5927\u68af\u5ea6\u7d2f\u79ef\u6b65\u6570\u4ee5\u903c\u8fd1\u539f\u59cb\u6709\u6548\u6279\u5927\u5c0f，\u4ee3\u4ef7\u662f\u5355\u8f6e\u8bad\u7ec3\u65f6\u95f4\u8fdb\u4e00\u6b65\u62c9\u957f\u3002<\/span><\/p>\n

3.5 <\/span>\u957f\u65f6\u8bad\u7ec3\u5b88\u62a4：\u540e\u53f0\u5316\u4e0e\u65e5\u5fd7\u7559\u5b58<\/span><\/p>\n

\u5fae\u8c03\u4efb\u52a1\u901a\u5e38\u8fd0\u884c\u6570\u5c0f\u65f6\u4ee5\u4e0a，\u4e3a\u907f\u514d<\/span> SSH <\/span>\u4f1a\u8bdd\u4e2d\u65ad\u5bfc\u81f4\u8bad\u7ec3\u7ec8\u6b62，\u6700\u7ec8\u91c7\u7528<\/span> nohup <\/span>\u540e\u53f0\u8fd0\u884c\u5e76\u5c06\u5168\u90e8\u8f93\u51fa\u91cd\u5b9a\u5411\u5230\u65e5\u5fd7\u6587\u4ef6：<\/span><\/p>\n

\u65e5\u5fd7\u91cd\u5b9a\u5411\u4fdd\u7559\u4e86\u5b8c\u6574\u7684\u8fdb\u5ea6\u6761\u4e0e\u62a5\u9519\u4e0a\u4e0b\u6587，\u4e3a\u4e8b\u540e\u56de\u6eaf\u8bad\u7ec3\u66f2\u7ebf\u3001\u5b9a\u4f4d\u4e2d\u65ad\u539f\u56e0\u63d0\u4f9b\u4e86\u539f\u59cb\u4f9d\u636e\u3002<\/span><\/p>\n

\u56db\u3001\u6700\u7ec8\u8bad\u7ec3\u65b9\u6848\u6c47\u603b<\/span><\/p>\n\n\n\n\n\n\n\n\n\n\n
\n

\u914d\u7f6e\u9879<\/span><\/p>\n<\/td>\n

\n

\u539f\u914d\u7f6e<\/span><\/p>\n<\/td>\n

\n

\u6700\u7ec8\u914d\u7f6e<\/span><\/p>\n<\/td>\n

\n

\u4fee\u6539\u52a8\u56e0<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

\u6df7\u5408\u7cbe\u5ea6<\/span><\/p>\n<\/td>\n

\n

bf16: true<\/span><\/p>\n<\/td>\n

\n

bf16: false \/ fp16: true<\/span><\/p>\n<\/td>\n

\n

GPU <\/span>\u67b6\u6784\u4e0d\u652f\u6301<\/span> bf16<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

\u5206\u5e03\u5f0f\u7b56\u7565<\/span><\/p>\n<\/td>\n

\n

DeepSpeed ZeRO-2<\/span><\/p>\n<\/td>\n

\n

deepspeed: false<\/span><\/p>\n<\/td>\n

\n

\u5355\u5361\u73af\u5883\u65e0\u9700\u5206\u5e03\u5f0f<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

\u542f\u52a8\u65b9\u5f0f<\/span><\/p>\n<\/td>\n

\n

\u591a\u5361<\/span> torchrun <\/span>\u62c9\u8d77<\/span><\/p>\n<\/td>\n

\n

\u76f4\u63a5\u542f\u52a8<\/span> + nohup <\/span>\u540e\u53f0<\/span><\/p>\n<\/td>\n

\n

\u5355\u5361<\/span> + <\/span>\u4f1a\u8bdd\u4fdd\u6d3b<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

\u5355\u6b65\u6279\u5927\u5c0f<\/span><\/p>\n<\/td>\n

\n

8<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

\u538b\u7f29\u6fc0\u6d3b\u663e\u5b58\u5cf0\u503c<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

\u68af\u5ea6\u7d2f\u79ef\u6b65\u6570<\/span><\/p>\n<\/td>\n

\n

8<\/span><\/p>\n<\/td>\n

\n

16<\/span><\/p>\n<\/td>\n

\n

\u7ef4\u6301\u8bad\u7ec3\u541e\u5410\u4e0e\u7a33\u5b9a\u6027<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

\u5b66\u4e60\u7387<\/span><\/p>\n<\/td>\n

\n

3.0e-6<\/span><\/p>\n<\/td>\n

\n

3.0e-6<\/span>（\u4fdd\u6301）<\/span><\/p>\n<\/td>\n

\n

\u4e0e\u539f\u4ed3\u5e93\u5bf9\u9f50<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

\u8bad\u7ec3\u8f6e\u6570<\/span><\/p>\n<\/td>\n

\n

2.0<\/span><\/p>\n<\/td>\n

\n

2.0<\/span>（\u4fdd\u6301）<\/span><\/p>\n<\/td>\n

\n

\u4e0e\u539f\u4ed3\u5e93\u5bf9\u9f50<\/span><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u4e94\u3001\u7ed3\u8bba\u4e0e\u540e\u7eed\u5efa\u8bae<\/span><\/p>\n

5.1 <\/span>\u4e3b\u8981\u7ed3\u8bba<\/span><\/p>\n

（<\/span>1<\/span>）\u590d\u73b0\u5931\u8d25\u7684\u4e3b\u8981\u539f\u56e0\u5e76\u975e\u6a21\u578b\u6216\u6570\u636e\u95ee\u9898，\u800c\u662f<\/span>\u201c<\/span>\u8bad\u7ec3\u914d\u7f6e\u4e0e\u672c\u5730\u786c\u4ef6\u73af\u5883\u7684\u9519\u914d<\/span>\u201d<\/span>：\u7cbe\u5ea6\u683c\u5f0f\u3001\u5206\u5e03\u5f0f\u7b56\u7565\u3001\u6279\u5927\u5c0f\u4e09\u9879\u914d\u7f6e\u5747\u9700\u6309\u5355\u5361<\/span> 32GB <\/span>\u7ea7\u73af\u5883\u91cd\u65b0\u9002\u914d\u3002<\/span><\/p>\n

（<\/span>2<\/span>）<\/span>\u201c<\/span>\u62a5\u9519\u4fe1\u606f<\/span> \u2192 <\/span>\u9010\u5c42\u5b9a\u4f4d<\/span> \u2192 <\/span>\u6700\u5c0f\u6539\u52a8\u4fee\u590d<\/span>\u201d<\/span>\u7684\u6392\u67e5\u8def\u5f84\u6548\u7387\u8f83\u9ad8，\u56db\u7c7b\u95ee\u9898\u5747\u5728\u4fdd\u6301\u8bad\u7ec3\u8bed\u4e49\u57fa\u672c\u4e0d\u53d8\u7684\u524d\u63d0\u4e0b\u5f97\u5230\u89e3\u51b3，\u672a\u5f15\u5165\u989d\u5916\u7684\u8bad\u7ec3\u8d85\u53c2\u6570\u6539\u52a8\u3002<\/span><\/p>\n

（<\/span>3<\/span>）\u663e\u5b58\u9884\u7b97\u5e94\u63d0\u524d\u6d4b\u7b97：\u5168\u53c2\u5fae\u8c03\u7684\u663e\u5b58\u5360\u7528<\/span> = <\/span>\u6a21\u578b\u6743\u91cd<\/span> + <\/span>\u4f18\u5316\u5668\u72b6\u6001<\/span> + <\/span>\u68af\u5ea6<\/span> + <\/span>\u6fc0\u6d3b\u503c，\u5728\u5927\u6279\u914d\u7f6e\u4e0b\u6fc0\u6d3b\u503c\u662f\u9996\u8981\u74f6\u9888，<\/span>batch <\/span>\u4e0e\u68af\u5ea6\u7d2f\u79ef\u7684\u7ec4\u5408\u8c03\u8282\u662f\u6700\u76f4\u63a5\u7684\u964d\u538b\u624b\u6bb5\u3002<\/span><\/p>\n

5.2 <\/span>\u540e\u7eed\u5efa\u8bae<\/span><\/p>\n

（<\/span>1<\/span>）\u7cbe\u5ea6\u76d1\u63a7：<\/span>fp16 <\/span>\u6570\u503c\u8303\u56f4\u8f83\u7a84，\u5efa\u8bae\u5728\u8bad\u7ec3\u65e5\u5fd7\u4e2d\u6301\u7eed\u89c2\u5bdf<\/span> loss <\/span>\u662f\u5426\u51fa\u73b0<\/span> NaN <\/span>\u6216\u9707\u8361，\u5fc5\u8981\u65f6\u4e0b\u8c03\u5b66\u4e60\u7387\u6216\u6539\u7528\u68af\u5ea6\u88c1\u526a\u3002<\/span><\/p>\n

（<\/span>2<\/span>）\u6709\u6548\u6279\u5927\u5c0f\u5bf9\u9f50：\u5f53\u524d\u6709\u6548\u6279\u5927\u5c0f（<\/span>16<\/span>）\u4f4e\u4e8e\u539f\u914d\u7f6e（<\/span>64<\/span>），\u590d\u73b0\u6307\u6807\u51fa\u73b0\u504f\u5dee\u65f6\u53ef\u4f18\u5148\u589e\u5927\u68af\u5ea6\u7d2f\u79ef\u6b65\u6570\u518d\u8bc4\u4f30\u3002<\/span><\/p>\n

（<\/span>3<\/span>）\u663e\u5b58\u4f59\u91cf\u7559\u767d：\u5efa\u8bae\u8bad\u7ec3\u914d\u7f6e\u9884\u7559<\/span> 10%~15% <\/span>\u663e\u5b58\u4f59\u91cf，\u907f\u514d\u5e8f\u5217\u957f\u5ea6\u6ce2\u52a8（\u957f\u6837\u672c\u6279\u6b21）\u518d\u6b21\u89e6\u53d1<\/span> OOM<\/span>\u3002<\/span><\/p>\n

（<\/span>4<\/span>）\u73af\u5883\u56fa\u5316：\u5c06\u9a8c\u8bc1\u901a\u8fc7\u7684\u4f9d\u8d56\u7248\u672c（<\/span>accelerate 1.3.0 \/ peft 0.14.0 \/ transformers 4.49.0 \/ trl 0.8.6<\/span>）\u4e0e\u955c\u50cf\u914d\u7f6e\u5199\u5165\u73af\u5883\u811a\u672c，\u4fbf\u4e8e\u56e2\u961f\u590d\u7528\u4e0e\u4e8c\u6b21\u590d\u73b0\u3002<\/span><\/p>\n

（<\/span>5<\/span>）\u914d\u7f6e\u6a21\u677f\u5206\u5c42：\u53ef\u6574\u7406\u51fa<\/span>\u201c<\/span>\u591a\u5361\u96c6\u7fa4\u7248<\/span>\u201d<\/span>\u4e0e<\/span>\u201c<\/span>\u5355\u5361\u9002\u914d\u7248<\/span>\u201d<\/span>\u4e24\u5957<\/span> YAML <\/span>\u6a21\u677f，\u964d\u4f4e\u540e\u7eed\u5728\u4e0d\u540c\u786c\u4ef6\u95f4\u8fc1\u79fb\u7684\u8bd5\u9519\u6210\u672c\u3002<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

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