{"id":89647,"date":"2026-08-03T12:00:57","date_gmt":"2026-08-03T04:00:57","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/89647.html"},"modified":"2026-08-03T12:00:57","modified_gmt":"2026-08-03T04:00:57","slug":"%e5%a4%a7%e6%a8%a1%e5%9e%8b%e5%be%ae%e8%b0%83%e5%ae%9e%e6%88%98%ef%bc%9alora%e4%b8%8eqlora%e4%bb%8e%e5%85%a5%e9%97%a8%e5%88%b0%e7%b2%be%e9%80%9a%e7%9a%84%e5%ae%8c%e6%95%b4%e6%8c%87%e5%8d%97","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/89647.html","title":{"rendered":"\u5927\u6a21\u578b\u5fae\u8c03\u5b9e\u6218\uff1aLoRA\u4e0eQLoRA\u4ece\u5165\u95e8\u5230\u7cbe\u901a\u7684\u5b8c\u6574\u6307\u5357"},"content":{"rendered":"

\u5927\u6a21\u578b\u5fae\u8c03\u5b9e\u6218：LoRA\u4e0eQLoRA\u4ece\u5165\u95e8\u5230\u7cbe\u901a\u7684\u5b8c\u6574\u6307\u5357<\/h2>\n

\u5f15\u8a00<\/h3>\n

\u5fae\u8c03\u6210\u672c\u4ece10\u4e07\u964d\u52301000\u5143，\u8fd9\u542c\u8d77\u6765\u50cf\u662f\u8425\u9500\u8bdd\u672f，\u4f46\u5b83\u662f2026\u5e74\u771f\u5b9e\u53d1\u751f\u7684\u4e8b\u60c5\u30022023\u5e74，\u5168\u53c2\u6570\u5fae\u8c03\u4e00\u4e2a7B\u6a21\u578b\u9700\u8981\u7ea680GB\u663e\u5b58，\u4f9d\u8d56A100\u96c6\u7fa4，\u8bad\u7ec33-5\u5929，\u4e91\u8d44\u6e90\u8d39\u52a0\u4eba\u529b\u8c03\u8bd5\u7ea68-12\u4e07\u5143\u3002\u52302026\u5e74，QLoRA\u914d\u5408\u68af\u5ea6\u68c0\u67e5\u70b9\u548c\u5206\u9875\u4f18\u5316\u5668，\u5c06\u663e\u5b58\u538b\u81f316-24GB，\u5355\u5f20RTX 4090\u8dd12-4\u5c0f\u65f6\u5373\u53ef\u5b8c\u6210，\u786c\u4ef6\u52a0\u7b97\u529b\u6210\u672c\u53ef\u63a7\u5236\u5728800-1500\u5143\u3002\u6210\u672c\u4e0b\u964d\u4e86\u4e24\u4e2a\u6570\u91cf\u7ea7，\u5fae\u8c03\u4e0d\u518d\u662f\u5c11\u6570\u5927\u516c\u53f8\u7684\u4e13\u5229\u3002<\/p>\n

\u672c\u6587\u5c06\u6df1\u5165\u8bb2\u89e3LoRA\u548cQLoRA\u7684\u6838\u5fc3\u539f\u7406\u3001\u914d\u7f6e\u6280\u5de7\u548c\u5b9e\u6218\u7ecf\u9a8c，\u5e2e\u52a9\u4f60\u7528\u6700\u4f4e\u7684\u6210\u672c\u8ba9\u901a\u7528\u5927\u6a21\u578b\u5728\u5782\u76f4\u9886\u57df\u8868\u73b0\u51fa\u8272\u3002<\/p>\n

\u4e00\u3001\u4e3a\u4ec0\u4e48\u8981\u5fae\u8c03：Prompt\u4e0eRAG\u4e0d\u591f\u7528\u7684\u65f6\u5019<\/h3>\n

\u5728\u51b3\u5b9a\u5fae\u8c03\u4e4b\u524d，\u4f60\u9700\u8981\u5148\u56de\u7b54\u4e00\u4e2a\u95ee\u9898：Prompt\u5de5\u7a0b\u548cRAG\u662f\u5426\u5df2\u7ecf\u65e0\u6cd5\u6ee1\u8db3\u9700\u6c42？<\/p>\n

Prompt\u5de5\u7a0b\u662f\u6210\u672c\u6700\u4f4e\u7684\u65b9\u6848，\u9002\u5408\u5feb\u901f\u9a8c\u8bc1\u548c\u7b80\u5355\u4efb\u52a1\u3002\u5982\u679c\u4f60\u7684\u9700\u6c42\u662f"\u8ba9\u6a21\u578b\u4ee5\u7279\u5b9a\u683c\u5f0f\u8f93\u51fa"\u6216"\u5f15\u5bfc\u6a21\u578b\u9075\u5faa\u7279\u5b9a\u6307\u4ee4"，\u4f18\u5316Prompt\u901a\u5e38\u5c31\u80fd\u89e3\u51b3\u3002RAG\u9002\u5408\u9700\u8981\u52a8\u6001\u77e5\u8bc6\u66f4\u65b0\u7684\u573a\u666f，\u5982\u4f01\u4e1a\u77e5\u8bc6\u5e93\u95ee\u7b54\u3001\u5b9e\u65f6\u4fe1\u606f\u67e5\u8be2\u3002RAG\u4e0d\u6539\u53d8\u6a21\u578b\u7684\u884c\u4e3a\u6a21\u5f0f，\u800c\u662f\u901a\u8fc7\u5916\u90e8\u77e5\u8bc6\u6ce8\u5165\u6765\u63d0\u5347\u56de\u7b54\u8d28\u91cf\u3002<\/p>\n

\u5fae\u8c03\u9002\u7528\u4e8e\u4ee5\u4e0b\u573a\u666f：\u9886\u57df\u77e5\u8bc6\u5185\u5316（\u6a21\u578b\u9700\u8981"\u61c2\u884c"，\u5982\u533b\u7597\u8bca\u65ad\u3001\u6cd5\u5f8b\u54a8\u8be2）\u3001\u56fa\u5b9a\u8f93\u51fa\u98ce\u683c（\u6a21\u578b\u9700\u8981\u4ee5\u7279\u5b9a\u8bed\u6c14\u3001\u683c\u5f0f\u548c\u98ce\u683c\u56de\u590d）\u3001\u590d\u6742\u6307\u4ee4\u9075\u5faa（Prompt\u5de5\u7a0b\u65e0\u6cd5\u53ef\u9760\u5b9e\u73b0\u7684\u590d\u6742\u7ea6\u675f）\u3001\u79bb\u7ebf\u90e8\u7f72（\u9700\u8981\u5728\u65e0\u7f51\u7edc\u73af\u5883\u4e2d\u8fd0\u884c，\u4e0d\u80fd\u4f9d\u8d56RAG）\u3002<\/p>\n

\u4e00\u4e2a\u5b9e\u7528\u7684\u51b3\u7b56\u6846\u67b6：\u77e5\u8bc6\u9700\u8981\u5b9e\u65f6\u66f4\u65b0\u2192\u4e0aRAG；\u53ea\u9700\u89c4\u8303\u8f93\u51fa\u683c\u5f0f\u2192\u4f18\u5316Prompt；\u9700\u8981\u6a21\u578b"\u50cf\u4e13\u5bb6\u4e00\u6837\u8bf4\u8bdd"\u6216"\u6df1\u5ea6\u7406\u89e3\u9886\u57df\u77e5\u8bc6"\u2192\u5fae\u8c03\u3002\u4e09\u8005\u4e0d\u662f\u4e92\u65a5\u7684，\u53ef\u4ee5\u7ec4\u5408\u4f7f\u7528\u2014\u2014\u5fae\u8c03\u540e\u7684\u6a21\u578b\u7ed3\u5408RAG，\u6548\u679c\u5f80\u5f80\u66f4\u597d\u3002<\/p>\n

\u4e8c\u3001LoRA：\u53c2\u6570\u9ad8\u6548\u5fae\u8c03\u7684\u9769\u547d\u6027\u7a81\u7834<\/h3>\n

LoRA（Low-Rank Adaptation）\u662f2026\u5e74\u6700\u4e3b\u6d41\u7684\u5fae\u8c03\u65b9\u6cd5\u3002\u5b83\u7684\u6838\u5fc3\u601d\u60f3\u6781\u5176\u4f18\u96c5：\u6a21\u578b\u6743\u91cd\u7684\u66f4\u65b0\u53ef\u4ee5\u7528\u4f4e\u79e9\u5206\u89e3\u6765\u8fd1\u4f3c\u3002<\/p>\n

\u5bf9\u4e8e\u539f\u59cb\u6743\u91cd\u77e9\u9635W（\u7ef4\u5ea6d\u00d7k），LoRA\u4e0d\u76f4\u63a5\u66f4\u65b0W，\u800c\u662f\u5f15\u5165\u4e24\u4e2a\u5c0f\u77e9\u9635B（d\u00d7r）\u548cA（r\u00d7k），\u5176\u4e2dr\u8fdc\u5c0f\u4e8ed\u548ck\u3002\u6700\u7ec8\u7684\u6743\u91cd\u66f4\u65b0\u4e3a\u0394W = B \u00d7 A\u3002\u5178\u578b\u7684r=8\u621616，\u800cd\u548ck\u901a\u5e38\u662f4096\u3002\u8fd9\u610f\u5473\u7740\u53c2\u6570\u91cf\u4ece4096\u00b2\u964d\u52304096\u00d716\u00d72\u2248131K，\u51cf\u5c11\u4e8699.8%\u3002<\/p>\n

\u4e3a\u4ec0\u4e48\u8fd9\u4e2a\u8fd1\u4f3c\u6709\u6548？\u56e0\u4e3a\u6a21\u578b\u5728\u5fae\u8c03\u65f6，\u6743\u91cd\u66f4\u65b0\u7684"\u6709\u6548\u81ea\u7531\u5ea6"\u8fdc\u4f4e\u4e8e\u6743\u91cd\u7684\u7ef4\u5ea6\u3002\u5927\u591a\u6570\u6743\u91cd\u51e0\u4e4e\u4e0d\u53d8，\u53ea\u6709\u5c11\u6570\u65b9\u5411\u7684\u66f4\u65b0\u5bf9\u4efb\u52a1\u6709\u663e\u8457\u5f71\u54cd\u3002LoRA\u901a\u8fc7\u4f4e\u79e9\u5206\u89e3\u6355\u6349\u4e86\u8fd9\u4e9b\u5173\u952e\u7684\u66f4\u65b0\u65b9\u5411\u3002<\/p>\n

LoRA\u7684\u914d\u7f6e\u57282026\u5e74\u5df2\u7ecf\u5f62\u6210\u4e86\u660e\u786e\u7684\u6700\u4f73\u5b9e\u8df5\u3002\u9996\u5148\u662ftarget_modules\u7684\u9009\u62e9\u3002\u5bf9\u4e8eLLaMA\/Qwen\u7b49\u4e3b\u6d41\u67b6\u6784，\u5efa\u8bae\u5728\u6240\u6709Attention\u5c42\u7684Q\u3001K\u3001V\u3001O\u6295\u5f71\u90fd\u52a0LoRA\u3002\u662f\u5426\u5bf9FFN\u5c42（gate_proj\u3001up_proj\u3001down_proj）\u52a0LoRA\u53d6\u51b3\u4e8e\u4efb\u52a1\u7c7b\u578b：\u77e5\u8bc6\u5bc6\u96c6\u578b\u4efb\u52a1（\u5982\u6cd5\u5f8b\u3001\u533b\u7597）\u5efa\u8bae\u52a0FFN\u5c42，\u56e0\u4e3a\u9700\u8981\u66f4\u591a\u53ef\u8bad\u7ec3\u53c2\u6570\u6765\u5b66\u4e60\u65b0\u77e5\u8bc6；\u683c\u5f0f\/\u98ce\u683c\u8f6c\u6362\u4efb\u52a1\u53ea\u9700\u52a0Attention\u5c42，\u56e0\u4e3a\u53ea\u9700\u8981\u8c03\u6574\u8f93\u51fa\u6a21\u5f0f\u3002<\/p>\n

r（\u79e9）\u7684\u9009\u62e9\u662f\u4e00\u4e2a\u5de5\u7a0b\u6743\u8861\u3002r\u8d8a\u5927，\u53ef\u8bad\u7ec3\u53c2\u6570\u8d8a\u591a，\u6a21\u578b\u5bb9\u91cf\u8d8a\u5927，\u4f46\u8bad\u7ec3\u8d8a\u6162，\u8fc7\u62df\u5408\u98ce\u9669\u8d8a\u9ad8\u3002r=16\u662f\u5927\u591a\u6570\u573a\u666f\u7684\u5408\u7406\u9009\u62e9\u3002\u5bf9\u4e8e\u683c\u5f0f\u8f6c\u6362\u7b49\u7b80\u5355\u4efb\u52a1，r=8\u8db3\u591f；\u5bf9\u4e8e\u77e5\u8bc6\u6ce8\u5165\u7b49\u590d\u6742\u4efb\u52a1，r=32\u751a\u81f364\u53ef\u80fd\u66f4\u597d\u3002<\/p>\n

lora_alpha\u662f\u7f29\u653e\u56e0\u5b50，\u901a\u5e38\u8bbe\u4e3ar\u76842\u500d（\u5982r=16\u65f6alpha=32）\u3002\u5b83\u63a7\u5236LoRA\u66f4\u65b0\u5bf9\u539f\u59cb\u6743\u91cd\u7684\u5f71\u54cd\u7a0b\u5ea6\u3002lora_dropout\u8bbe\u4e3a0.05-0.1\u53ef\u4ee5\u9632\u6b62\u8fc7\u62df\u5408，\u5728\u6570\u636e\u91cf\u8f83\u5c11\u65f6\u5c24\u5176\u91cd\u8981\u3002<\/p>\n

\u4ee5\u4e0b\u662f\u63a8\u8350\u7684LoRA\u914d\u7f6e\u4ee3\u7801：<\/p>\n

from<\/span> peft import<\/span> LoraConfig,<\/span> get_peft_model<\/p>\n

lora_config =<\/span> LoraConfig(<\/span>
\n r=<\/span>16<\/span>,<\/span>
\n lora_alpha=<\/span>32<\/span>,<\/span>
\n target_modules=<\/span>[<\/span>
\n "q_proj"<\/span>,<\/span> "k_proj"<\/span>,<\/span> "v_proj"<\/span>,<\/span> "o_proj"<\/span>,<\/span>
\n "gate_proj"<\/span>,<\/span> "up_proj"<\/span>,<\/span> "down_proj"<\/span> # FFN\u5c42，\u77e5\u8bc6\u5bc6\u96c6\u578b\u4efb\u52a1\u52a0<\/span>
\n ]<\/span>,<\/span>
\n lora_dropout=<\/span>0.05<\/span>,<\/span>
\n task_type=<\/span>"CAUSAL_LM"<\/span>
\n)<\/span><\/p>\n

model =<\/span> get_peft_model(<\/span>base_model,<\/span> lora_config)<\/span><\/p>\n

\u4e09\u3001QLoRA：\u628a\u663e\u5b58\u538b\u5230\u6781\u81f4<\/h3>\n

QLoRA\u5728LoRA\u7684\u57fa\u7840\u4e0a\u589e\u52a0\u4e864-bit\u91cf\u5316，\u5c06\u663e\u5b58\u9700\u6c42\u8fdb\u4e00\u6b65\u538b\u7f29\u5230\u6781\u81f4\u3002\u5b83\u7684\u6838\u5fc3\u521b\u65b0\u662fNF4（NormalFloat4）\u91cf\u5316\u683c\u5f0f\u548c\u53cc\u91cd\u91cf\u5316（Double Quantization）\u3002<\/p>\n

NF4\u662f\u4e00\u79cd\u4e13\u95e8\u4e3a\u6b63\u6001\u5206\u5e03\u6570\u636e\u8bbe\u8ba1\u76844-bit\u91cf\u5316\u683c\u5f0f\u3002\u6a21\u578b\u6743\u91cd\u901a\u5e38\u670d\u4ece\u6b63\u6001\u5206\u5e03，NF4\u901a\u8fc7\u975e\u5747\u5300\u7684\u91cf\u5316\u533a\u95f4，\u5728\u6743\u91cd\u5206\u5e03\u5bc6\u96c6\u7684\u533a\u57df\u4f7f\u7528\u66f4\u7ec6\u7684\u91cf\u5316\u7c92\u5ea6，\u5728\u7a00\u758f\u533a\u57df\u4f7f\u7528\u66f4\u7c97\u7684\u7c92\u5ea6，\u4ece\u800c\u57284-bit\u7cbe\u5ea6\u4e0b\u6700\u5927\u5316\u4fe1\u606f\u4fdd\u7559\u3002<\/p>\n

\u53cc\u91cd\u91cf\u5316\u662f\u5bf9\u91cf\u5316\u5e38\u6570\u7684\u4e8c\u6b21\u91cf\u5316\u3002\u5728\u6807\u51c6\u91cf\u5316\u4e2d，\u6bcf\u4e2a\u91cf\u5316\u5757\u9700\u8981\u4e00\u4e2a32-bit\u7684\u91cf\u5316\u5e38\u6570\u3002\u53cc\u91cd\u91cf\u5316\u5c06\u8fd9\u4e9b\u91cf\u5316\u5e38\u6570\u518d\u8fdb\u884c\u4e00\u6b218-bit\u91cf\u5316，\u5c06\u989d\u5916\u5b58\u50a8\u5f00\u9500\u4ece\u6bcf64\u4e2a\u53c2\u657032-bit\u964d\u4f4e\u5230\u6bcf256\u4e2a\u53c2\u65708-bit，\u51cf\u5c11\u4e86\u7ea60.4 bits per parameter\u7684\u5b58\u50a8\u5f00\u9500\u3002<\/p>\n

QLoRA\u7684\u914d\u7f6e\u4e0eLoRA\u57fa\u672c\u4e00\u81f4，\u53ea\u9700\u5728\u52a0\u8f7d\u6a21\u578b\u65f6\u6307\u5b9a\u91cf\u5316\u53c2\u6570：<\/p>\n

from<\/span> transformers import<\/span> BitsAndBytesConfig<\/p>\n

bnb_config =<\/span> BitsAndBytesConfig(<\/span>
\n load_in_4bit=<\/span>True<\/span>,<\/span>
\n bnb_4bit_quant_type=<\/span>"nf4"<\/span>,<\/span>
\n bnb_4bit_compute_dtype=<\/span>torch.<\/span>bfloat16,<\/span>
\n bnb_4bit_use_double_quant=<\/span>True<\/span>
\n)<\/span><\/p>\n

model =<\/span> AutoModelForCausalLM.<\/span>from_pretrained(<\/span>
\n "Qwen\/Qwen2.5-7B"<\/span>,<\/span>
\n quantization_config=<\/span>bnb_config,<\/span>
\n device_map=<\/span>"auto"<\/span>
\n)<\/span><\/p>\n

QLoRA\u7684\u663e\u5b58\u8282\u7701\u6548\u679c\u662f\u663e\u8457\u7684\u3002\u4ee57B\u6a21\u578b\u4e3a\u4f8b，\u5168\u53c2\u6570\u5fae\u8c03\u9700\u8981\u7ea680GB\u663e\u5b58，LoRA\u9700\u8981\u7ea624GB，QLoRA\u53ea\u9700\u8981\u7ea616GB\u3002\u8fd9\u610f\u5473\u7740\u5728\u5355\u5f20RTX 4090（24GB）\u4e0a\u5c31\u53ef\u4ee5\u5b8c\u6210QLoRA\u5fae\u8c03，\u5728RTX 4070（12GB）\u4e0a\u4e5f\u53ef\u4ee5\u8fd0\u884c7B\u6a21\u578b\u7684QLoRA\u5fae\u8c03\u3002<\/p>\n

\u56db\u3001\u5fae\u8c03\u6570\u636e\u51c6\u5907：\u8d28\u91cf\u6bd4\u6570\u91cf\u91cd\u8981\u4e00\u767e\u500d<\/h3>\n

\u6570\u636e\u662f\u5fae\u8c03\u7684\u7075\u9b42\u3002500\u6761\u9ad8\u8d28\u91cf\u6837\u672c\u7684\u6548\u679c\u901a\u5e38\u4f18\u4e8e5000\u6761\u4f4e\u8d28\u91cf\u6837\u672c\u3002\u6570\u636e\u51c6\u5907\u662f\u5fae\u8c03\u4e2d\u6700\u8017\u65f6\u4f46\u4e5f\u6700\u5173\u952e\u7684\u73af\u8282\u3002<\/p>\n

\u6570\u636e\u683c\u5f0f\u63a8\u8350\u4f7f\u7528Alpaca\u683c\u5f0f\u6216ShareGPT\u683c\u5f0f\u3002Alpaca\u683c\u5f0f\u5305\u542binstruction（\u6307\u4ee4）\u3001input（\u8f93\u5165，\u53ef\u9009）\u3001output（\u671f\u671b\u8f93\u51fa）\u4e09\u4e2a\u5b57\u6bb5\u3002ShareGPT\u683c\u5f0f\u662f\u5bf9\u8bdd\u683c\u5f0f，\u5305\u542b\u591a\u8f6e\u5bf9\u8bdd\u7684messages\u5217\u8868\u3002\u9009\u62e9\u54ea\u79cd\u683c\u5f0f\u53d6\u51b3\u4e8e\u4f60\u7684\u4efb\u52a1\u7c7b\u578b\u2014\u2014\u5355\u8f6e\u6307\u4ee4\u9075\u5faa\u7528Alpaca，\u591a\u8f6e\u5bf9\u8bdd\u7528ShareGPT\u3002<\/p>\n

\u6570\u636e\u8d28\u91cf\u8981\u6c42\u5305\u62ec：\u51c6\u786e\u6027（output\u5fc5\u987b\u6b63\u786e，\u4e0d\u80fd\u6709\u4e8b\u5b9e\u9519\u8bef）\u3001\u4e00\u81f4\u6027（\u540c\u7c7b\u578b\u95ee\u9898\u7684output\u683c\u5f0f\u548c\u98ce\u683c\u4e00\u81f4）\u3001\u591a\u6837\u6027（\u8986\u76d6\u4e0d\u540c\u7684\u573a\u666f\u548c\u8f93\u5165\u53d8\u5316）\u3001\u4ee3\u8868\u6027（\u6570\u636e\u5206\u5e03\u5e94\u53cd\u6620\u5b9e\u9645\u4f7f\u7528\u573a\u666f\u7684\u5206\u5e03）\u3002<\/p>\n

\u6570\u636e\u6e05\u6d17\u662f\u5fc5\u4e0d\u53ef\u5c11\u7684\u6b65\u9aa4\u3002\u5e38\u89c1\u7684\u6e05\u6d17\u64cd\u4f5c\u5305\u62ec：\u53bb\u91cd（\u79fb\u9664\u5185\u5bb9\u91cd\u590d\u7684\u6837\u672c）\u3001\u53bb\u566a（\u4fee\u6b63\u683c\u5f0f\u9519\u8bef\u548c\u62fc\u5199\u9519\u8bef）\u3001\u8fc7\u6ee4（\u79fb\u9664\u8d28\u91cf\u4e0d\u8fbe\u6807\u7684\u6837\u672c）\u3001\u5e73\u8861（\u786e\u4fdd\u5404\u7c7b\u522b\u6837\u672c\u6570\u91cf\u5747\u8861）\u3002<\/p>\n

\u6570\u636e\u91cf\u5efa\u8bae：\u5bf9\u4e8e\u683c\u5f0f\/\u98ce\u683c\u8f6c\u6362\u4efb\u52a1，200-500\u6761\u9ad8\u8d28\u91cf\u6837\u672c\u901a\u5e38\u8db3\u591f；\u5bf9\u4e8e\u9886\u57df\u77e5\u8bc6\u6ce8\u5165\u4efb\u52a1，\u9700\u89811000-5000\u6761\u6837\u672c；\u5bf9\u4e8e\u590d\u6742\u6307\u4ee4\u9075\u5faa\u4efb\u52a1，\u9700\u89815000-10000\u6761\u6837\u672c\u3002\u6ce8\u610f，\u6570\u636e\u91cf\u8d85\u8fc7\u4e00\u5b9a\u9608\u503c\u540e，\u8fb9\u9645\u6536\u76ca\u6025\u5267\u4e0b\u964d\u2014\u2014\u4ece5000\u6761\u589e\u52a0\u523010000\u6761，\u6548\u679c\u63d0\u5347\u901a\u5e38\u4e0d\u52305%\u3002<\/p>\n

\u4e94\u3001\u8bad\u7ec3\u8d85\u53c2\u6570\u8c03\u4f18\u6307\u5357<\/h3>\n

\u8bad\u7ec3\u8d85\u53c2\u6570\u7684\u8bbe\u7f6e\u76f4\u63a5\u5f71\u54cd\u5fae\u8c03\u6548\u679c\u3002\u4ee5\u4e0b\u662f2026\u5e74\u7684\u6700\u4f73\u5b9e\u8df5\u5efa\u8bae\u3002<\/p>\n

\u5b66\u4e60\u7387（Learning Rate）\u662f\u5f71\u54cd\u6700\u5927\u7684\u8d85\u53c2\u6570\u3002LoRA\u5fae\u8c03\u7684\u5b66\u4e60\u7387\u901a\u5e38\u6bd4\u5168\u53c2\u6570\u5fae\u8c03\u9ad8\u4e00\u4e2a\u6570\u91cf\u7ea7，\u8303\u56f4\u57281e-4\u52305e-4\u4e4b\u95f4\u3002\u5efa\u8bae\u4ece2e-4\u5f00\u59cb，\u6839\u636e\u9a8c\u8bc1\u635f\u5931\u8c03\u6574\u3002\u5982\u679c\u635f\u5931\u9707\u8361，\u964d\u4f4e\u5b66\u4e60\u7387；\u5982\u679c\u635f\u5931\u4e0b\u964d\u7f13\u6162，\u63d0\u9ad8\u5b66\u4e60\u7387\u3002<\/p>\n

\u8bad\u7ec3\u8f6e\u6570（Epochs）\u901a\u5e38\u8bbe\u4e3a1-3\u8f6e\u3002\u5bf9\u4e8e\u5c0f\u6570\u636e\u96c6（<1000\u6761），\u53ef\u4ee5\u8bad\u7ec33-5\u8f6e，\u4f46\u8981\u6ce8\u610f\u8fc7\u62df\u5408\u3002\u5bf9\u4e8e\u5927\u6570\u636e\u96c6（>5000\u6761），1-2\u8f6e\u901a\u5e38\u8db3\u591f\u3002\u5efa\u8bae\u6bcf\u4e2aepoch\u540e\u4fdd\u5b58\u68c0\u67e5\u70b9，\u5728\u9a8c\u8bc1\u96c6\u4e0a\u8bc4\u4f30，\u9009\u62e9\u6700\u4f18\u7684\u68c0\u67e5\u70b9\u3002<\/p>\n

\u6279\u6b21\u5927\u5c0f（Batch Size）\u53d7\u663e\u5b58\u9650\u5236\u3002\u5728QLoRA\u4e0b，7B\u6a21\u578b\u901a\u5e38\u53ef\u4ee5\u8bbe\u7f6ebatch_size=4-8，\u914d\u5408gradient_accumulation_steps=4-8，\u5b9e\u73b0\u6709\u6548\u7684\u6279\u6b21\u5927\u5c0f16-64\u3002\u68af\u5ea6\u7d2f\u79ef\u8ba9\u4f60\u5728\u663e\u5b58\u53d7\u9650\u7684\u60c5\u51b5\u4e0b\u6a21\u62df\u66f4\u5927\u7684\u6279\u6b21\u5927\u5c0f\u3002<\/p>\n

\u5b66\u4e60\u7387\u8c03\u5ea6\u65b9\u9762，\u4f59\u5f26\u9000\u706b（Cosine Annealing）\u914d\u5408\u7ebf\u6027\u9884\u70ed（Linear Warmup）\u662f\u6700\u63a8\u8350\u7684\u7ec4\u5408\u3002\u9884\u70ed\u6b65\u6570\u901a\u5e38\u8bbe\u4e3a\u603b\u6b65\u6570\u768410%，\u5e2e\u52a9\u6a21\u578b\u5728\u8bad\u7ec3\u521d\u671f\u7a33\u5b9a\u6536\u655b\u3002<\/p>\n

\u516d\u3001\u8bc4\u4f30\u4e0e\u8fed\u4ee3<\/h3>\n

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\u81ea\u52a8\u5316\u8bc4\u4f30\u4f7f\u7528\u6807\u51c6\u57fa\u51c6\u6d4b\u8bd5\u96c6\u8bc4\u4f30\u6a21\u578b\u5728\u7279\u5b9a\u4efb\u52a1\u4e0a\u7684\u8868\u73b0\u3002\u5bf9\u4e8e\u4e2d\u6587\u573a\u666f，\u63a8\u8350\u4f7f\u7528C-Eval\u3001CMMLU\u3001SuperCLUE\u7b49\u57fa\u51c6\u3002\u4f46\u81ea\u52a8\u5316\u8bc4\u4f30\u53ea\u80fd\u53cd\u6620\u6a21\u578b\u5728\u6807\u51c6\u5316\u4efb\u52a1\u4e0a\u7684\u80fd\u529b，\u4e0d\u80fd\u5b8c\u5168\u4ee3\u8868\u5b9e\u9645\u4f7f\u7528\u6548\u679c\u3002<\/p>\n

\u4eba\u5de5\u8bc4\u4f30\u662f\u6700\u53ef\u9760\u7684\u8bc4\u4f30\u65b9\u5f0f\u3002\u9080\u8bf7\u9886\u57df\u4e13\u5bb6\u5bf9\u6a21\u578b\u8f93\u51fa\u8fdb\u884c\u6253\u5206，\u8bc4\u4f30\u7ef4\u5ea6\u5305\u62ec\u51c6\u786e\u6027\u3001\u76f8\u5173\u6027\u3001\u5b8c\u6574\u6027\u3001\u98ce\u683c\u5339\u914d\u5ea6\u3002\u4eba\u5de5\u8bc4\u4f30\u7684\u6210\u672c\u8f83\u9ad8，\u4f46\u80fd\u53d1\u73b0\u81ea\u52a8\u5316\u8bc4\u4f30\u65e0\u6cd5\u6355\u6349\u7684\u95ee\u9898\u3002<\/p>\n

A\/B\u6d4b\u8bd5\u662f\u5c06\u5fae\u8c03\u6a21\u578b\u90e8\u7f72\u5230\u751f\u4ea7\u73af\u5883\u540e，\u4e0e\u5c0f\u6d41\u91cf\u7528\u6237\u8fdb\u884c\u5bf9\u6bd4\u5b9e\u9a8c\u3002\u6bd4\u8f83\u5fae\u8c03\u6a21\u578b\u548c\u57fa\u5ea7\u6a21\u578b\u5728\u7528\u6237\u6ee1\u610f\u5ea6\u3001\u4efb\u52a1\u5b8c\u6210\u7387\u3001\u5e73\u5747\u5bf9\u8bdd\u8f6e\u6570\u7b49\u4e1a\u52a1\u6307\u6807\u4e0a\u7684\u5dee\u5f02\u3002<\/p>\n

\u8fed\u4ee3\u4f18\u5316\u662f\u6301\u7eed\u63d0\u5347\u6a21\u578b\u6548\u679c\u7684\u5173\u952e\u3002\u57fa\u4e8e\u8bc4\u4f30\u7ed3\u679c，\u5206\u6790bad case，\u627e\u51fa\u6a21\u578b\u7684\u8584\u5f31\u73af\u8282，\u9488\u5bf9\u6027\u5730\u8865\u5145\u8bad\u7ec3\u6570\u636e\u3001\u8c03\u6574\u8d85\u53c2\u6570\u3001\u4f18\u5316\u8bad\u7ec3\u7b56\u7565\u3002\u5fae\u8c03\u4e0d\u662f\u4e00\u6b21\u6027\u7684\u5de5\u4f5c，\u800c\u662f\u6301\u7eed\u8fed\u4ee3\u7684\u8fc7\u7a0b\u3002<\/p>\n

\u4e03\u3001\u5e38\u89c1\u95ee\u9898\u4e0e\u907f\u5751\u6307\u5357<\/h3>\n

\u707e\u96be\u6027\u9057\u5fd8：\u6a21\u578b\u5728\u9886\u57df\u6570\u636e\u4e0a\u8fc7\u5ea6\u8bad\u7ec3，\u5fd8\u8bb0\u4e86\u901a\u7528\u80fd\u529b\u3002\u89e3\u51b3\u65b9\u6848：\u6df7\u5408\u901a\u7528\u6570\u636e\u548c\u9886\u57df\u6570\u636e（\u6bd4\u4f8b\u5efa\u8bae7:3）\u3001\u964d\u4f4e\u5b66\u4e60\u7387\u3001\u51cf\u5c11\u8bad\u7ec3\u8f6e\u6570\u3001\u4f7f\u7528\u66f4\u5c0f\u7684r\u503c\u3002<\/p>\n

\u8fc7\u62df\u5408：\u6a21\u578b\u5728\u8bad\u7ec3\u6570\u636e\u4e0a\u8868\u73b0\u5f88\u597d，\u4f46\u5728\u65b0\u6570\u636e\u4e0a\u8868\u73b0\u5dee\u3002\u89e3\u51b3\u65b9\u6848：\u589e\u52a0\u6570\u636e\u591a\u6837\u6027\u3001\u589e\u52a0dropout\u3001\u51cf\u5c11\u8bad\u7ec3\u8f6e\u6570\u3001\u4f7f\u7528\u66f4\u5c0f\u7684r\u503c\u3002<\/p>\n

\u6570\u636e\u6cc4\u9732：\u8bad\u7ec3\u6570\u636e\u4e2d\u5305\u542b\u4e86\u6d4b\u8bd5\u6570\u636e\u7684\u4fe1\u606f，\u5bfc\u81f4\u8bc4\u4f30\u7ed3\u679c\u865a\u9ad8\u3002\u89e3\u51b3\u65b9\u6848：\u4e25\u683c\u5206\u79bb\u8bad\u7ec3\u96c6\u548c\u6d4b\u8bd5\u96c6\u3001\u4f7f\u7528\u8bad\u7ec3\u6570\u636e\u4e2d\u4e0d\u5305\u542b\u7684\u65b0\u573a\u666f\u8fdb\u884c\u8bc4\u4f30\u3002<\/p>\n

\u8bad\u7ec3\u4e0d\u7a33\u5b9a：\u635f\u5931\u51fd\u6570\u9707\u8361，\u65e0\u6cd5\u6536\u655b\u3002\u89e3\u51b3\u65b9\u6848：\u964d\u4f4e\u5b66\u4e60\u7387\u3001\u589e\u52a0\u9884\u70ed\u6b65\u6570\u3001\u68c0\u67e5\u6570\u636e\u8d28\u91cf\u3001\u4f7f\u7528\u68af\u5ea6\u88c1\u526a\u3002<\/p>\n

\u7ed3\u8bed<\/h3>\n

LoRA\u548cQLoRA\u8ba9\u5927\u6a21\u578b\u5fae\u8c03\u4ece"\u8d35\u65cf\u8fd0\u52a8"\u53d8\u6210\u4e86"\u5e73\u6c11\u6280\u80fd"\u3002\u4f46\u6280\u672f\u95e8\u69db\u7684\u964d\u4f4e\u5e76\u4e0d\u610f\u5473\u7740\u8d28\u91cf\u7684\u964d\u4f4e\u2014\u2014\u6570\u636e\u8d28\u91cf\u3001\u8d85\u53c2\u6570\u8c03\u4f18\u3001\u8bc4\u4f30\u8fed\u4ee3\u4ecd\u7136\u662f\u51b3\u5b9a\u5fae\u8c03\u6548\u679c\u7684\u5173\u952e\u56e0\u7d20\u3002\u638c\u63e1\u4e86\u672c\u6587\u7684\u65b9\u6cd5\u8bba，\u4f60\u5c31\u80fd\u7528\u6700\u5c0f\u7684\u6210\u672c，\u8ba9\u901a\u7528\u5927\u6a21\u578b\u5728\u5782\u76f4\u9886\u57df\u7115\u53d1\u51fa\u4e13\u4e1a\u7ea7\u7684\u8868\u73b0\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"

\u5927\u6a21\u578b\u5fae\u8c03\u5b9e\u6218：LoRA\u4e0eQLoRA\u4ece\u5165\u95e8\u5230\u7cbe\u901a\u7684\u5b8c\u6574\u6307\u5357
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