{"id":29656,"date":"2024-10-28T01:55:56","date_gmt":"2024-10-28T01:55:56","guid":{"rendered":"http:\/\/atmokpo.com\/w\/?p=29656"},"modified":"2024-11-26T06:51:51","modified_gmt":"2024-11-26T06:51:51","slug":"%ed%97%88%ea%b9%85%ed%8e%98%ec%9d%b4%ec%8a%a4-%ed%8a%b8%eb%a0%8c%ec%8a%a4%ed%8f%ac%eb%a8%b8-%ed%99%9c%ec%9a%a9%ea%b0%95%ec%a2%8c-%eb%8d%b0%ec%9d%b4%ed%84%b0%ec%84%b8%ed%8a%b8-%ed%81%b4%eb%9e%98","status":"publish","type":"post","link":"https:\/\/atmokpo.com\/w\/29656\/","title":{"rendered":"\ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub80c\uc2a4\ud3ec\uba38 \ud65c\uc6a9\uac15\uc88c, \ub370\uc774\ud130\uc138\ud2b8 \ud074\ub798\uc2a4 \uc0dd\uc131"},"content":{"rendered":"

<\/p>\n

\uc774\ubc88 \uac15\uc88c\uc5d0\uc11c\ub294 \ud5c8\uae45\ud398\uc774\uc2a4(Hugging Face)<\/strong>\uc758 \ud2b8\ub79c\uc2a4\ud3ec\uba38(Transformers)<\/strong> \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \ud65c\uc6a9\ud558\uc5ec \ub370\uc774\ud130\uc138\ud2b8 \ud074\ub798\uc2a4\ub97c \uc0dd\uc131\ud558\ub294 \ubc29\ubc95\uc5d0 \ub300\ud574 \ub2e4\ub8f0 \uac83\uc785\ub2c8\ub2e4. \ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub79c\uc2a4\ud3ec\uba38\ub294 \uc790\uc5f0\uc5b4 \ucc98\ub9ac(NLP) \uc791\uc5c5\uc744 \uc704\ud55c \ud544\uc218 \ub3c4\uad6c \uc911 \ud558\ub098\ub85c, \ub2e4\uc591\ud55c \uc0ac\uc804 \ud6c8\ub828\ub41c \ubaa8\ub378\uacfc \ub370\uc774\ud130\uc14b\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4. \uc774\ub7ec\ud55c \ubaa8\ub378\uc744 \ud6a8\uacfc\uc801\uc73c\ub85c \ud65c\uc6a9\ud558\uae30 \uc704\ud574\uc11c\ub294 \uc0ac\uc6a9\uc790 \uc815\uc758 \ub370\uc774\ud130\uc138\ud2b8\ub97c \uc0dd\uc131\ud558\ub294 \uac83\uc774 \uc911\uc694\ud569\ub2c8\ub2e4.<\/p>\n

1. \ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub79c\uc2a4\ud3ec\uba38\ub780?<\/h2>\n

\ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub79c\uc2a4\ud3ec\uba38 \ub77c\uc774\ube0c\ub7ec\ub9ac\ub294 \uba38\uc2e0\ub7ec\ub2dd\uc758 \uc790\uc5f0\uc5b4 \ucc98\ub9ac \ubd84\uc57c\uc5d0\uc11c \uac00\uc7a5 \ub9ce\uc774 \uc0ac\uc6a9\ub418\ub294 \ub77c\uc774\ube0c\ub7ec\ub9ac \uc911 \ud558\ub098\ub85c, BERT, GPT-2, T5\uc640 \uac19\uc740 \ucd5c\uc2e0 \ubaa8\ub378\uc744 \ud3ec\ud568\ud558\uace0 \uc788\uc2b5\ub2c8\ub2e4. \uc774 \ub77c\uc774\ube0c\ub7ec\ub9ac\ub294 \ubaa8\ub378\uc758 \ud6c8\ub828, \ubbf8\uc138 \uc870\uc815(fine-tuning), \uc608\uce21 \ub4f1\uc744 \uac04\ud3b8\ud558\uac8c \uad6c\ud604\ud560 \uc218 \uc788\ub3c4\ub85d \ub3c4\uc640\uc90d\ub2c8\ub2e4.<\/p>\n

2. \ub370\uc774\ud130\uc14b \ud074\ub798\uc2a4\ub780?<\/h2>\n

\ub370\uc774\ud130\uc14b \ud074\ub798\uc2a4\ub294 \ubaa8\ub378 \ud6c8\ub828 \ubc0f \ud3c9\uac00\uc5d0 \uc0ac\uc6a9\ub420 \ub370\uc774\ud130\uc758 \uad6c\uc870\ub97c \uc815\uc758\ud558\ub294 \ud074\ub798\uc2a4\uc785\ub2c8\ub2e4. \ub370\uc774\ud130\uc14b \ud074\ub798\uc2a4\ub97c \uc0ac\uc6a9\ud558\uba74 \uc0ac\uc6a9\uc790 \uc815\uc758 \ub370\uc774\ud130\ub97c \uc27d\uac8c \ub85c\ub4dc\ud558\uace0 \uc804\ucc98\ub9ac\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub79c\uc2a4\ud3ec\uba38\uc5d0\uc11c\ub294 datasets<\/strong> \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \ud1b5\ud574 \ub370\uc774\ud130\ub97c \uc27d\uac8c \ub2e4\ub8f0 \uc218 \uc788\ub294 \uae30\ub2a5\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4.<\/p>\n

3. \ub370\uc774\ud130\uc14b \ud074\ub798\uc2a4 \uc0dd\uc131 \ubc29\ubc95<\/h2>\n

\uc774\ubc88 \uc139\uc158\uc5d0\uc11c\ub294 Python\uc744 \uc0ac\uc6a9\ud558\uc5ec \ub370\uc774\ud130\uc14b \ud074\ub798\uc2a4\ub97c \uc0dd\uc131\ud558\ub294 \ubc29\ubc95\uc744 \ub2e4\ub8e8\uaca0\uc2b5\ub2c8\ub2e4. \uad6c\uccb4\uc801\uc73c\ub85c\ub294 torch.utils.data.Dataset<\/code> \ud074\ub798\uc2a4\ub97c \uc0c1\uc18d\ubc1b\uc544 \uc0ac\uc6a9\uc790 \uc815\uc758 \ub370\uc774\ud130\uc14b \ud074\ub798\uc2a4\ub97c \ub9cc\ub4e4\uace0 \uc774\ub97c \ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub79c\uc2a4\ud3ec\uba38\uc640 \ud1b5\ud569\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud558\uaca0\uc2b5\ub2c8\ub2e4.<\/p>\n

3.1 \uc900\ube44\ud558\uae30<\/h3>\n

\uba3c\uc800, \ud544\uc694\ud55c \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc124\uce58\ud558\uace0 \uc784\ud3ec\ud2b8\ud569\ub2c8\ub2e4. \uc544\ub798\uc758 \ucf54\ub4dc\ub97c \uc0ac\uc6a9\ud558\uc5ec transformers<\/strong>\uc640 datasets<\/strong> \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc124\uce58\ud569\ub2c8\ub2e4.<\/p>\n

!pip install transformers datasets torch<\/code><\/pre>\n
3.2 \uc0ac\uc6a9\uc790 \uc815\uc758 \ub370\uc774\ud130\uc14b \ud074\ub798\uc2a4 \ub9cc\ub4e4\uae30<\/h3>\n
\uc5ec\uae30\uc5d0\uc11c \ub370\uc774\ud130\uc14b \ud074\ub798\uc2a4\ub97c \uc0dd\uc131\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\ub4dc\ub9ac\uaca0\uc2b5\ub2c8\ub2e4.<\/p>\n
import torch\nfrom torch.utils.data import Dataset\n\nclass MyDataset(Dataset):\n    def __init__(self, texts, labels, tokenizer, max_length=512):\n        self.texts = texts\n        self.labels = labels\n        self.tokenizer = tokenizer\n        self.max_length = max_length\n\n    def __len__(self):\n        return len(self.texts)\n\n    def __getitem__(self, idx):\n        text = self.texts[idx]\n        label = self.labels[idx]\n\n        # \ud1a0\ud070\ud654 \ubc0f \uc778\ub371\uc2a4 \ubcc0\ud658\n        encoding = self.tokenizer.encode_plus(\n            text,\n            add_special_tokens=True,\n            max_length=self.max_length,\n            return_token_type_ids=False,\n            padding='max_length',\n            truncation=True,\n            return_attention_mask=True,\n            return_tensors='pt'\n        )\n\n        return {\n            'input_ids': encoding['input_ids'].flatten(),\n            'attention_mask': encoding['attention_mask'].flatten(),\n            'labels': torch.tensor(label, dtype=torch.long)\n        }<\/code><\/pre>\n
\uc704\uc758 \ud074\ub798\uc2a4\ub294 \ud14d\uc2a4\ud2b8\uc640 \ub77c\ubca8\uc744 \uc785\ub825\uc73c\ub85c \ubc1b\uc544\uc11c \ud574\ub2f9 \ud14d\uc2a4\ud2b8\ub97c \ud1a0\ud070\ud654 \ud558\uace0 \ub77c\ubca8\uc744 \ud150\uc11c\ub85c \ubc18\ud658\ud558\ub294 \ub370\uc774\ud130\uc14b\uc785\ub2c8\ub2e4. torch.utils.data.Dataset<\/code> \ud074\ub798\uc2a4\ub97c \uc0c1\uc18d\ubc1b\uc544 __len__<\/code>\uacfc __getitem__<\/code> \uba54\uc18c\ub4dc\ub97c \uad6c\ud604\ud558\uc600\uc2b5\ub2c8\ub2e4.<\/p>\n
3.3 \ub370\uc774\ud130\uc14b \uc0ac\uc6a9\ud558\uae30<\/h4>\n
\uc774\uc81c \uc0ac\uc6a9\uc790 \uc815\uc758 \ub370\uc774\ud130\uc14b\uc744 \uc5b4\ub5bb\uac8c \uc0ac\uc6a9\ud560 \uc218 \uc788\ub294\uc9c0 \uc0b4\ud3b4\ubd05\uc2dc\ub2e4. \ub370\uc774\ud130\ub97c \uc900\ube44\ud558\uace0 \ub370\uc774\ud130\ub85c\ub354\ub97c \uc0dd\uc131\ud558\ub294 \uc608\ub294 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4.<\/p>\n
from transformers import AutoTokenizer\n\n# \ud1a0\ud06c\ub098\uc774\uc800 \uc900\ube44\ntokenizer = AutoTokenizer.from_pretrained('bert-base-uncased')\n\n# \ub370\uc774\ud130 \uc900\ube44\ntexts = [\"Hello, how are you?\", \"I am fine, thank you.\"]\nlabels = [0, 1] # \uc608\uc2dc \ub77c\ubca8\n\n# \ub370\uc774\ud130\uc14b \uc778\uc2a4\ud134\uc2a4 \uc0dd\uc131\ndataset = MyDataset(texts, labels, tokenizer)\n\n# \ub370\uc774\ud130 \ub85c\ub354 \uc0dd\uc131\nfrom torch.utils.data import DataLoader\n\ndataloader = DataLoader(dataset, batch_size=2, shuffle=True)\n\nfor batch in dataloader:\n    print(batch)\n<\/code><\/pre>\n
\uc704 \ucf54\ub4dc\ub294 \uc791\uc740 \ub370\uc774\ud130\uc14b\uc744 \ub9cc\ub4e0 \ud6c4\uc5d0 \ub370\uc774\ud130\ub85c\ub354\ub97c \uc0dd\uc131\ud558\uc5ec \ubc30\uce58 \ub2e8\uc704\ub85c \ub370\uc774\ud130\ub97c \ubc18\ud658\ud558\ub294 \uc608\uc785\ub2c8\ub2e4. \ub370\uc774\ud130 \ub85c\ub354\ub294 \ud6c8\ub828 \uc911 \ub370\uc774\ud130 \uc0d8\ud50c\uc744 \ubb34\uc791\uc704\ub85c \uc120\ud0dd\ud558\uc5ec \ubc30\uce58 \ub2e8\uc704\ub85c \ubc18\ud658\ud560 \uc218 \uc788\uac8c \ud574\uc90d\ub2c8\ub2e4.<\/p>\n
4. \ub370\uc774\ud130\uc14b \ud074\ub798\uc2a4 \ud655\uc7a5<\/h2>\n
\uc774\uc81c \uc0ac\uc6a9\uc790 \uc815\uc758 \ub370\uc774\ud130\uc14b \ud074\ub798\uc2a4\ub97c \ud655\uc7a5\ud558\uc5ec \uc5ec\ub7ec \uae30\ub2a5\uc744 \ucd94\uac00\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\ub4dc\ub9ac\uaca0\uc2b5\ub2c8\ub2e4. \uc608\ub97c \ub4e4\uc5b4, \ub370\uc774\ud130 \uc804\ucc98\ub9ac \uacfc\uc815 \ucd94\uac00, \uc5ec\ub7ec \ud615\uc2dd\uc758 \uc785\ub825\uc744 \ucc98\ub9ac\ud558\uae30 \ub4f1 \ub2e4\uc591\ud55c \uae30\ub2a5\uc744 \ud3ec\ud568\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
4.1 \ub370\uc774\ud130 \uc804\ucc98\ub9ac<\/h3>\n
\ub370\uc774\ud130 \uc804\ucc98\ub9ac\ub294 \ubaa8\ub378\uc758 \uc131\ub2a5\uc744 \ub192\uc774\ub294 \uc911\uc694\ud55c \ub2e8\uacc4\uc785\ub2c8\ub2e4. \ud544\uc694\ud55c \uacbd\uc6b0, __init__<\/code> \uba54\uc18c\ub4dc\uc5d0 \uc804\ucc98\ub9ac \uae30\ub2a5\uc744 \uad6c\ud604\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
def preprocess(self, text):\n        # \uc5ec\uae30\uc5d0 \uc804\ucc98\ub9ac \ub85c\uc9c1\uc744 \ucd94\uac00\ud558\uc138\uc694\n        return text.lower().strip()\n<\/code><\/pre>\n
\uc774 \uba54\uc18c\ub4dc\ub97c __getitem__<\/code>\uc5d0\uc11c \ud638\ucd9c\ud558\uc5ec \ub370\uc774\ud130\ub97c \ubc18\ud658\ud558\uae30 \uc804\uc5d0 \uc804\ucc98\ub9ac\ub97c \uc218\ud589\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
4.2 \uc5ec\ub7ec \ud615\uc2dd\uc758 \uc785\ub825 \ucc98\ub9ac<\/h3>\n
\ub370\uc774\ud130\uc14b\uc774 \ub2e4\uc591\ud55c \uc785\ub825 \ud615\uc2dd\uc744 \ucc98\ub9ac\ud574\uc57c \ud560 \uacbd\uc6b0 \uc870\uac74\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec \ub2e4\ub974\uac8c \ucc98\ub9ac\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc785\ub825 \ud14d\uc2a4\ud2b8\uc758 \ud615\uc2dd\uc5d0 \ub530\ub77c \uc870\uac74\uc744 \ucd94\uac00\ud558\uba74 \ub429\ub2c8\ub2e4.<\/p>\n
if isinstance(text, list):\n    text = \" \".join(text)  # \ub9ac\uc2a4\ud2b8 \ud14d\uc2a4\ud2b8 \ud569\uce58\uae30\n<\/code><\/pre>\n
5. \uacb0\ub860<\/h2>\n
\uc774\ubc88 \uac15\uc88c\uc5d0\uc11c\ub294 \ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub79c\uc2a4\ud3ec\uba38\uc758 \ub370\uc774\ud130\uc14b \ud074\ub798\uc2a4\ub97c \uc0dd\uc131\ud558\uace0 \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc744 \uc54c\uc544\ubcf4\uc558\uc2b5\ub2c8\ub2e4. \uc0ac\uc6a9\uc790 \uc815\uc758 \ub370\uc774\ud130\uc14b\uc740 \ubaa8\ub378 \ud6c8\ub828 \ubc0f \ud3c9\uac00\uc5d0 \uc788\uc5b4 \ub9e4\uc6b0 \uc911\uc694\ud55c \uc694\uc18c\uc785\ub2c8\ub2e4. \uc774\ub97c \ud1b5\ud574 \uc6b0\ub9ac\ub294 \ub2e4\uc591\ud55c \ud615\uc2dd\uc758 \ub370\uc774\ud130\ub97c \ud6a8\uc728\uc801\uc73c\ub85c \ucc98\ub9ac\ud558\uace0, \uc6d0\ud558\ub294 \ubc29\uc2dd\uc73c\ub85c \ubaa8\ub378\uc744 \ud6c8\ub828\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
\uc55e\uc73c\ub85c \ub354 \ub9ce\uc740 \uc790\uc5f0\uc5b4 \ucc98\ub9ac \ubb38\uc81c\ub97c \ud574\uacb0\ud558\uae30 \uc704\ud574 \ud5c8\uae45\ud398\uc774\uc2a4\ub97c \ud65c\uc6a9\ud574 \ubcf4\uc138\uc694. \uadf8\ub9ac\uace0 \uc790\uc2e0\ub9cc\uc758 \ub370\uc774\ud130\uc14b \ud074\ub798\uc2a4\ub97c \ub9cc\ub4e4\uc5b4 \ubcf4\uba70 \uc2e4\ub825\uc744 \uc313\uc544\ubcf4\uc2dc\uae30 \ubc14\ub78d\ub2c8\ub2e4. \uac10\uc0ac\ud569\ub2c8\ub2e4!<\/p>\n
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\uc774\ubc88 \uac15\uc88c\uc5d0\uc11c\ub294 \ud5c8\uae45\ud398\uc774\uc2a4(Hugging Face)\uc758 \ud2b8\ub79c\uc2a4\ud3ec\uba38(Transformers) \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \ud65c\uc6a9\ud558\uc5ec \ub370\uc774\ud130\uc138\ud2b8 \ud074\ub798\uc2a4\ub97c \uc0dd\uc131\ud558\ub294 \ubc29\ubc95\uc5d0 \ub300\ud574 \ub2e4\ub8f0 \uac83\uc785\ub2c8\ub2e4. \ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub79c\uc2a4\ud3ec\uba38\ub294 \uc790\uc5f0\uc5b4 \ucc98\ub9ac(NLP) \uc791\uc5c5\uc744 \uc704\ud55c \ud544\uc218 \ub3c4\uad6c \uc911 \ud558\ub098\ub85c, \ub2e4\uc591\ud55c \uc0ac\uc804 \ud6c8\ub828\ub41c \ubaa8\ub378\uacfc \ub370\uc774\ud130\uc14b\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4. \uc774\ub7ec\ud55c \ubaa8\ub378\uc744 \ud6a8\uacfc\uc801\uc73c\ub85c \ud65c\uc6a9\ud558\uae30 \uc704\ud574\uc11c\ub294 \uc0ac\uc6a9\uc790 \uc815\uc758 \ub370\uc774\ud130\uc138\ud2b8\ub97c \uc0dd\uc131\ud558\ub294 \uac83\uc774 \uc911\uc694\ud569\ub2c8\ub2e4. 1. \ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub79c\uc2a4\ud3ec\uba38\ub780? \ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub79c\uc2a4\ud3ec\uba38 \ub77c\uc774\ube0c\ub7ec\ub9ac\ub294 \uba38\uc2e0\ub7ec\ub2dd\uc758 \uc790\uc5f0\uc5b4 \ucc98\ub9ac \ubd84\uc57c\uc5d0\uc11c \uac00\uc7a5 \ub9ce\uc774 \uc0ac\uc6a9\ub418\ub294 \ub77c\uc774\ube0c\ub7ec\ub9ac … \ub354 \ubcf4\uae30 “\ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub80c\uc2a4\ud3ec\uba38 \ud65c\uc6a9\uac15\uc88c, \ub370\uc774\ud130\uc138\ud2b8 \ud074\ub798\uc2a4 \uc0dd\uc131”<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[30],"tags":[],"class_list":["post-29656","post","type-post","status-publish","format-standard","hentry","category-30"],"yoast_head":"\n\ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub80c\uc2a4\ud3ec\uba38 \ud65c\uc6a9\uac15\uc88c, \ub370\uc774\ud130\uc138\ud2b8 \ud074\ub798\uc2a4 \uc0dd\uc131 - 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