\n1. \uc11c\ub860<\/h2>\n
\n \ucd5c\uadfc \uc790\uc5f0\uc5b4 \ucc98\ub9ac(NLP) \ubd84\uc57c\uc5d0\uc11c\ub294 \uc0ac\uc804 \ud6c8\ub828\ub41c \ubaa8\ub378\uc744 \ud65c\uc6a9\ud558\uc5ec \ub2e4\uc591\ud55c \ud0dc\uc2a4\ud06c\uc5d0\uc11c \ub6f0\uc5b4\ub09c \uc131\ub2a5\uc744 \ubcf4\uc5ec\uc8fc\uace0 \uc788\uc2b5\ub2c8\ub2e4. \uadf8 \uc911\uc5d0\uc11c\ub3c4 ALBERT<\/b>(A Lite BERT)\ub294 \uad6c\uae00\uc5d0\uc11c \uc81c\uc548\ud55c \uacbd\ub7c9\ud654\ub41c BERT \ubaa8\ub378\uc785\ub2c8\ub2e4. ALBERT\ub294 \ud30c\ub77c\ubbf8\ud130 \uacf5\uc720 \ubc0f \ub9e4\ud2b8\ub9ad\uc2a4 \ubd84\ud574 \uae30\ubc95\uc744 \ud1b5\ud574 \ubaa8\ub378 \ud06c\uae30\ub97c \uc904\uc774\uba70, \uc774\ub7ec\ud55c \ud2b9\uc131 \ub355\ubd84\uc5d0 \ub354 \uc801\uc740 \uc790\uc6d0\uc73c\ub85c\ub3c4 \ub192\uc740 \uc131\ub2a5\uc744 \ubc1c\ud718\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ubcf8 \uac15\uc88c\uc5d0\uc11c\ub294 Hugging Face\uc758 Transformers<\/b> \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \ud65c\uc6a9\ud558\uc5ec ALBERT\ub97c \ub85c\ub529\ud558\uace0, Masked Language Modeling(MLM) \ud30c\uc774\ud504\ub77c\uc778\uc744 \uc124\uc815\ud558\ub294 \ubc29\ubc95\uc5d0 \ub300\ud574 \uc2ec\ub3c4 \uc788\uac8c \ub2e4\ub904\ubcf4\uaca0\uc2b5\ub2c8\ub2e4.\n <\/p>\n<\/section>\n\n2. ALBERT \uac1c\uc694<\/h2>\n
\n ALBERT\ub294 BERT\uc758 \uad6c\uc870\ub97c \uae30\ubc18\uc73c\ub85c \ud55c \ubaa8\ub378\ub85c, \ub2e4\uc74c\uacfc \uac19\uc740 \uc8fc\uc694 \ud2b9\uc9d5\uc744 \uac00\uc9c0\uace0 \uc788\uc2b5\ub2c8\ub2e4:\n <\/p>\n
\n- \ud30c\ub77c\ubbf8\ud130 \uacf5\uc720<\/b>: \ub808\uc774\uc5b4 \uac04 \uc804\uccb4 \ud30c\ub77c\ubbf8\ud130\ub97c \uacf5\uc720\ud558\uc5ec \ubaa8\ub378 \ud06c\uae30\ub97c \uc904\uc785\ub2c8\ub2e4.<\/li>\n
- \ub9e4\ud2b8\ub9ad\uc2a4 \ubd84\ud574<\/b>: \ud070 \uc784\ubca0\ub529 \ub9e4\ud2b8\ub9ad\uc2a4\ub97c \ub450 \uac1c\uc758 \uc791\uc740 \ub9e4\ud2b8\ub9ad\uc2a4\ub85c \ubd84\ud574\ud558\uc5ec \uba54\ubaa8\ub9ac \uc0ac\uc6a9\ub7c9\uc744 \uc904\uc785\ub2c8\ub2e4.<\/li>\n
- \ub354 \uae4a\uc740 \ubaa8\ub378<\/b>: \ub354 \uae4a\uc740 \uc544\ud0a4\ud14d\ucc98\ub97c \uc0ac\uc6a9\ud560 \uc218 \uc788\ub3c4\ub85d \ud558\uc5ec \uc131\ub2a5\uc744 \ud5a5\uc0c1\uc2dc\ud0b5\ub2c8\ub2e4.<\/li>\n<\/ul>\n
\n ALBERT\ub294 \ub2e4\uc591\ud55c \uc790\uc5f0\uc5b4 \ucc98\ub9ac \ud0dc\uc2a4\ud06c\uc5d0\uc11c BERT\ubcf4\ub2e4 \ub354 \ub6f0\uc5b4\ub09c \uc131\ub2a5\uc744 \ubcf4\uc5ec\uc8fc\uba70, \ud2b9\ud788 \ud30c\ub77c\ubbf8\ud130 \uc218\ub97c \uc904\uc600\uc74c\uc5d0\ub3c4 \ubd88\uad6c\ud558\uace0 \ub180\ub77c\uc6b4 \uacb0\uacfc\ub97c \ub0a8\uae30\uace4 \ud569\ub2c8\ub2e4.\n <\/p>\n<\/section>\n\n3. \ud658\uacbd \uc124\uc815<\/h2>\n
\n ALBERT\ub97c \ud65c\uc6a9\ud558\uae30 \uc704\ud574\uc11c\ub294 \uba3c\uc800 Hugging Face\uc758 Transformers \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc124\uce58\ud574\uc57c \ud569\ub2c8\ub2e4. \uc774\ub294 NLP \ubaa8\ub378\uc758 \ub85c\ub529\uacfc \uc0ac\uc6a9\uc744 \ub9e4\uc6b0 \uac04\ud3b8\ud558\uac8c \ud574\uc8fc\ub294 \ub77c\uc774\ube0c\ub7ec\ub9ac\uc785\ub2c8\ub2e4. \uc544\ub798\uc758 \uba85\ub839\uc5b4\ub97c \ud1b5\ud574 Transformers\uc640 torch\ub97c \uc124\uce58\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4:\n <\/p>\n
\n !pip install transformers torch<\/code>\n <\/pre>\n\n \uc124\uce58\uac00 \uc644\ub8cc\ub41c \ud6c4, \ud544\uc694\ud55c \ub77c\uc774\ube0c\ub7ec\ub9ac\ub4e4\uc744 \uc784\ud3ec\ud2b8\ud569\ub2c8\ub2e4.\n <\/p>\n
\n \nimport torch\nfrom transformers import AlbertTokenizer, AlbertForMaskedLM\n <\/code>\n <\/pre>\n<\/section>\n\n4. ALBERT \ubaa8\ub378 \ubc0f \ud1a0\ud06c\ub098\uc774\uc800 \ub85c\ub529<\/h2>\n
\n ALBERT \ubaa8\ub378\uc740 \uc0ac\uc804 \ud6c8\ub828\ub41c \ud615\ud0dc\ub85c \uc81c\uacf5\ub418\uba70, \uc774\ub97c \uc27d\uac8c \ub85c\ub529\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ub2e4\uc74c \ub2e8\uacc4\uc5d0\uc11c\ub294 ALBERT\uc758 \ud1a0\ud06c\ub098\uc774\uc800\uc640 MLM \ubaa8\ub378\uc744 \ub85c\ub529\ud558\ub294 \uacfc\uc815\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.\n <\/p>\n
\n \n# ALBERT \ubaa8\ub378\uacfc \ud1a0\ud06c\ub098\uc774\uc800 \ub85c\ub529\nmodel_name = 'albert-base-v2'\ntokenizer = AlbertTokenizer.from_pretrained(model_name)\nmodel = AlbertForMaskedLM.from_pretrained(model_name)\n <\/code>\n <\/pre>\n\n \uc704 \ucf54\ub4dc\ub97c \uc2e4\ud589\ud558\uba74, Hugging Face\uc758 \ubaa8\ub378 \ud5c8\ube0c\uc5d0\uc11c ALBERT \ubaa8\ub378\uacfc \uadf8\uc5d0 \ub9de\ub294 \ud1a0\ud06c\ub098\uc774\uc800\uac00 \uc790\ub3d9\uc73c\ub85c \ub2e4\uc6b4\ub85c\ub4dc\ub418\uc5b4 \ub85c\ub529\ub429\ub2c8\ub2e4.\n <\/p>\n<\/section>\n\n5. Masked Language Modeling(MLM) \uac1c\uc694<\/h2>\n
\n Masked Language Modeling\uc740 \ud14d\uc2a4\ud2b8\uc5d0\uc11c \uc77c\ubd80 \ub2e8\uc5b4\ub97c \ub9c8\uc2a4\ud0b9\ud55c \uc0c1\ud0dc\uc5d0\uc11c, \ud574\ub2f9 \ub9c8\uc2a4\ud0b9\ub41c \ub2e8\uc5b4\ub97c \uc608\uce21\ud558\ub294 \ud0dc\uc2a4\ud06c\uc785\ub2c8\ub2e4. ALBERT\ub294\uc774 \ud0dc\uc2a4\ud06c\ub97c \ud6a8\uacfc\uc801\uc73c\ub85c \uc218\ud589\ud558\uae30 \uc704\ud574 \uc124\uacc4\ub418\uc5c8\uc2b5\ub2c8\ub2e4. MLM\uc744 \ud1b5\ud574 \ubaa8\ub378\uc740 \ub300\ub7c9\uc758 \uc5b8\uc5b4 \ub370\uc774\ud130\ub97c \ud559\uc2b5\ud558\uba70 \uad6c\ubb38 \ubc0f \uc758\ubbf8\uc801 \ud328\ud134\uc744 \uc774\ud574\ud558\uac8c \ub429\ub2c8\ub2e4.\n <\/p>\n<\/section>\n\n6. MLM \ud30c\uc774\ud504\ub77c\uc778 \uad6c\ucd95<\/h2>\n
\n MLM\uc744 \uc218\ud589\ud558\uae30 \uc704\ud55c \ud30c\uc774\ud504\ub77c\uc778\uc740 \ub2e4\uc74c\uacfc \uac19\uc740 \ub2e8\uacc4\ub97c \ud3ec\ud568\ud569\ub2c8\ub2e4:\n <\/p>\n
\n- \uc785\ub825 \ubb38\uc7a5 \uc804\ucc98\ub9ac<\/li>\n
- \ubb38\uc7a5 \ub0b4 \ub2e8\uc5b4 \ub9c8\uc2a4\ud0b9<\/li>\n
- \ubaa8\ub378\uc744 \ud1b5\ud55c \uc608\uce21 \uc218\ud589<\/li>\n
- \uacb0\uacfc \ubd84\uc11d<\/li>\n<\/ul>\n
\uc544\ub798\uc5d0\uc11c \uc774 \uacfc\uc815\uc744 \uc790\uc138\ud788 \uc0b4\ud3b4\ubcf4\uaca0\uc2b5\ub2c8\ub2e4.<\/p>\n
6.1 \uc785\ub825 \ubb38\uc7a5 \uc804\ucc98\ub9ac<\/h3>\n
\n \uba3c\uc800, \ubaa8\ub378\uc5d0 \uc785\ub825\ub420 \ubb38\uc7a5\uc744 \uc815\uc758\ud558\uace0 \uadf8 \ubb38\uc7a5\uc744 ALBERT \ubaa8\ub378\uc5d0 \ub9de\uac8c \ud1a0\ud070\ud654\ud569\ub2c8\ub2e4. \ud1a0\ud06c\ub098\uc774\uc800\ub294 \ubb38\uc7a5\uc744 \ud1a0\ud070 \ub2e8\uc704\ub85c \ubd84\ub9ac\ud558\uace0, \uc774\ub97c \uc815\uc218 \uc778\ub371\uc2a4\ub85c \ubcc0\ud658\ud569\ub2c8\ub2e4. \uc544\ub798\ub294 \uc785\ub825 \ubb38\uc7a5\uc744 \uc804\ucc98\ub9ac\ud558\ub294 \uacfc\uc815\uc785\ub2c8\ub2e4.\n <\/p>\n
\n \n# \uc785\ub825 \ubb38\uc7a5 \uc815\uc758\ninput_sentence = \"Hugging Face\ub294 NLP\uc758 \ubbf8\ub798\ub97c \uc5f4\uc5b4\uac00\uace0 \uc788\uc2b5\ub2c8\ub2e4.\"\n\n# \ubb38\uc7a5 \ud1a0\ud070\ud654\ninput_ids = tokenizer.encode(input_sentence, return_tensors='pt')\nprint(\"Input IDs:\", input_ids)\n <\/code>\n <\/pre>\n6.2 \ubb38\uc7a5 \ub0b4 \ub2e8\uc5b4 \ub9c8\uc2a4\ud0b9<\/h3>\n
\n MLM\uc744 \uc704\ud574 \ubb38\uc7a5 \ub0b4 \uc77c\ubd80 \ub2e8\uc5b4\ub97c \ub9c8\uc2a4\ud0b9\ud569\ub2c8\ub2e4. \uc774\ub54c \ub9c8\uc2a4\ud0b9 \ub300\uc0c1\uc740 \ub79c\ub364\ud558\uac8c \uc120\ud0dd\ub429\ub2c8\ub2e4. \uc544\ub798\uc758 \ucf54\ub4dc\ub97c \ud1b5\ud574 \ub79c\ub364\ud558\uac8c \ud558\ub098\uc758 \ud1a0\ud070\uc744 \ub9c8\uc2a4\ud0b9\ud569\ub2c8\ub2e4.\n <\/p>\n
\n \nimport random\n\n# \ub79c\ub364\ud558\uac8c \ud558\ub098\uc758 \ud1a0\ud070\uc744 \ub9c8\uc2a4\ud0b9\nmasked_index = random.randint(1, input_ids.size(1)-1) # 0\uc740 [CLS] \ud1a0\ud070\uc774\ubbc0\ub85c \uc81c\uc678\nmasked_input_ids = input_ids.clone()\nmasked_input_ids[0, masked_index] = tokenizer.mask_token_id\n\nprint(\"Masked Input IDs:\", masked_input_ids)\n <\/code>\n <\/pre>\n6.3 \ubaa8\ub378\uc744 \ud1b5\ud55c \uc608\uce21 \uc218\ud589<\/h3>\n
\n \ubaa8\ub378\uc5d0 \ub9c8\uc2a4\ud0b9\ub41c \ubb38\uc7a5\uc744 \uc785\ub825\ud558\uc5ec, \ub9c8\uc2a4\ud0b9\ub41c \ud1a0\ud070\uc744 \uc608\uce21\ud569\ub2c8\ub2e4. \uc774\ub97c \uc704\ud574 \ubaa8\ub378\uc744 \ud1b5\uacfc\uc2dc\ud0a4\uace0, \uacb0\uacfc\ub97c \ucd94\ucd9c\ud569\ub2c8\ub2e4.\n <\/p>\n
\n \n# \ubaa8\ub378\uc744 \ud1b5\ud55c \uc608\uce21\nwith torch.no_grad():\n outputs = model(masked_input_ids)\n \npredictions = outputs[0]\npredicted_index = torch.argmax(predictions[0, masked_index]).item()\npredicted_token = tokenizer.decode(predicted_index)\n\nprint(\"Predicted Token:\", predicted_token)\n <\/code>\n <\/pre>\n6.4 \uacb0\uacfc \ubd84\uc11d<\/h3>\n
\n \uc608\uce21\ub41c \ud1a0\ud070\uc744 \uc6d0\ub798 \ubb38\uc7a5\uc5d0 \uc0bd\uc785\ud558\uc5ec \uacb0\uacfc\ub97c \ud655\uc778\ud569\ub2c8\ub2e4.\n <\/p>\n
\n \n# \uc608\uce21\ub41c \ud1a0\ud070\uc73c\ub85c \ub9c8\uc2a4\ud0b9\ub41c \ud1a0\ud070 \ub300\uccb4\ninput_tokens = tokenizer.convert_ids_to_tokens(input_ids[0])\ninput_tokens[masked_index] = predicted_token\n\noutput_sentence = tokenizer.convert_tokens_to_string(input_tokens)\nprint(\"Output Sentence:\", output_sentence)\n <\/code>\n <\/pre>\n<\/section>\n\n7. \ub9c8\uce58\uba70<\/h2>\n
\n ALBERT\uc640 \uac19\uc740 \ud601\uc2e0\uc801\uc778 \ubaa8\ub378\uc744 \ud65c\uc6a9\ud558\uc5ec Masked Language Modeling\uc744 \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc5d0 \ub300\ud574 \uc54c\uc544\ubcf4\uc558\uc2b5\ub2c8\ub2e4. Hugging Face\uc758 Transformers \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \ud1b5\ud574 \uac04\ud3b8\ud558\uac8c \ubaa8\ub378\uc744 \ub85c\ub529\ud558\uace0 \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc744 \ubc30\uc6e0\uc73c\uba70, \uae30\ubcf8 \uac1c\ub150\ubd80\ud130 \uc751\uc6a9 \ubc29\ubc95\uae4c\uc9c0 \uccb4\uacc4\uc801\uc73c\ub85c \ud559\uc2b5\ud560 \uc218 \uc788\uc5c8\uc2b5\ub2c8\ub2e4. \uc774\ub7ec\ud55c \uae30\uc220\uc744 \ud1b5\ud574 \uc790\uc5f0\uc5b4 \ucc98\ub9ac \ubd84\uc57c\uc5d0\uc11c \ub354\uc6b1 \ubc1c\uc804\ub41c \uc751\uc6a9 \ud504\ub85c\uadf8\ub7a8\uc744 \uac1c\ubc1c\ud558\ub294 \ub370 \uae30\uc5ec\ud560 \uc218 \uc788\uc744 \uac83\uc785\ub2c8\ub2e4.\n <\/p>\n<\/section>\n
<\/body><\/p>\n","protected":false},"excerpt":{"rendered":"
1. \uc11c\ub860 \ucd5c\uadfc \uc790\uc5f0\uc5b4 \ucc98\ub9ac(NLP) \ubd84\uc57c\uc5d0\uc11c\ub294 \uc0ac\uc804 \ud6c8\ub828\ub41c \ubaa8\ub378\uc744 \ud65c\uc6a9\ud558\uc5ec \ub2e4\uc591\ud55c \ud0dc\uc2a4\ud06c\uc5d0\uc11c \ub6f0\uc5b4\ub09c \uc131\ub2a5\uc744 \ubcf4\uc5ec\uc8fc\uace0 \uc788\uc2b5\ub2c8\ub2e4. \uadf8 \uc911\uc5d0\uc11c\ub3c4 ALBERT(A Lite BERT)\ub294 \uad6c\uae00\uc5d0\uc11c \uc81c\uc548\ud55c \uacbd\ub7c9\ud654\ub41c BERT \ubaa8\ub378\uc785\ub2c8\ub2e4. ALBERT\ub294 \ud30c\ub77c\ubbf8\ud130 \uacf5\uc720 \ubc0f \ub9e4\ud2b8\ub9ad\uc2a4 \ubd84\ud574 \uae30\ubc95\uc744 \ud1b5\ud574 \ubaa8\ub378 \ud06c\uae30\ub97c \uc904\uc774\uba70, \uc774\ub7ec\ud55c \ud2b9\uc131 \ub355\ubd84\uc5d0 \ub354 \uc801\uc740 \uc790\uc6d0\uc73c\ub85c\ub3c4 \ub192\uc740 \uc131\ub2a5\uc744 \ubc1c\ud718\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ubcf8 \uac15\uc88c\uc5d0\uc11c\ub294 Hugging Face\uc758 Transformers \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \ud65c\uc6a9\ud558\uc5ec … \ub354 \ubcf4\uae30 “\ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub80c\uc2a4\ud3ec\uba38 \ud65c\uc6a9\uac15\uc88c, ALBERT \ub85c\ub529 MLM \ud30c\uc774\ud504\ub77c\uc778”<\/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-29518","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, ALBERT \ub85c\ub529 MLM \ud30c\uc774\ud504\ub77c\uc778 - \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/atmokpo.com\/w\/29518\/\" \/>\n<meta property=\"og:locale\" content=\"ko_KR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub80c\uc2a4\ud3ec\uba38 \ud65c\uc6a9\uac15\uc88c, ALBERT \ub85c\ub529 MLM \ud30c\uc774\ud504\ub77c\uc778 - \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8\" \/>\n<meta property=\"og:description\" content=\"1. \uc11c\ub860 \ucd5c\uadfc \uc790\uc5f0\uc5b4 \ucc98\ub9ac(NLP) \ubd84\uc57c\uc5d0\uc11c\ub294 \uc0ac\uc804 \ud6c8\ub828\ub41c \ubaa8\ub378\uc744 \ud65c\uc6a9\ud558\uc5ec \ub2e4\uc591\ud55c \ud0dc\uc2a4\ud06c\uc5d0\uc11c \ub6f0\uc5b4\ub09c \uc131\ub2a5\uc744 \ubcf4\uc5ec\uc8fc\uace0 \uc788\uc2b5\ub2c8\ub2e4. \uadf8 \uc911\uc5d0\uc11c\ub3c4 ALBERT(A Lite BERT)\ub294 \uad6c\uae00\uc5d0\uc11c \uc81c\uc548\ud55c \uacbd\ub7c9\ud654\ub41c BERT \ubaa8\ub378\uc785\ub2c8\ub2e4. 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