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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"#!pip install bertopic\n",
"\n",
"# bertopicのmodelを作るscript"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/user/miniconda3/envs/ft/lib/python3.11/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
" from .autonotebook import tqdm as notebook_tqdm\n"
]
}
],
"source": [
"from bertopic import BERTopic"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"from datasets import load_dataset\n",
"streaming=True\n",
"dataset_list =[\n",
" load_dataset('mc4', 'ja', split='train',streaming=streaming),\n",
" load_dataset('oscar', 'unshuffled_deduplicated_ja', split='train',streaming=streaming),\n",
" load_dataset('cc100', lang='ja', split='train',streaming=streaming),\n",
" load_dataset(\"augmxnt/shisa-pretrain-en-ja-v1\",split=\"train\",streaming=streaming),\n",
" load_dataset(\"hpprc/wikipedia-20240101\", split=\"train\",streaming=streaming),\n",
"]"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"10000it [00:20, 482.63it/s]\n",
"10000it [00:19, 524.44it/s]\n",
"10000it [00:12, 778.96it/s]\n",
"10000it [00:25, 386.40it/s]\n",
"10000it [00:58, 171.79it/s]\n"
]
}
],
"source": [
"from tqdm import tqdm\n",
"docs=[]\n",
"#prepare data for training model\n",
"for dataset in dataset_list:\n",
" cnt=0\n",
" for record in tqdm(dataset):\n",
" text=record[\"text\"]\n",
" docs.append(text)\n",
" cnt+=1\n",
"\n",
" if cnt>10000:\n",
" break\n"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"2024-03-12 08:37:19,823 - BERTopic - Embedding - Transforming documents to embeddings.\n",
"Batches: 100%|██████████| 1563/1563 [00:50<00:00, 30.79it/s] \n",
"2024-03-12 08:38:20,622 - BERTopic - Embedding - Completed ✓\n",
"2024-03-12 08:38:20,622 - BERTopic - Dimensionality - Fitting the dimensionality reduction algorithm\n",
"2024-03-12 08:38:59,566 - BERTopic - Dimensionality - Completed ✓\n",
"2024-03-12 08:38:59,567 - BERTopic - Cluster - Start clustering the reduced embeddings\n",
"huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n",
"To disable this warning, you can either:\n",
"\t- Avoid using `tokenizers` before the fork if possible\n",
"\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n",
"huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n",
"To disable this warning, you can either:\n",
"\t- Avoid using `tokenizers` before the fork if possible\n",
"\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n",
"huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n",
"To disable this warning, you can either:\n",
"\t- Avoid using `tokenizers` before the fork if possible\n",
"\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n",
"huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n",
"To disable this warning, you can either:\n",
"\t- Avoid using `tokenizers` before the fork if possible\n",
"\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n",
"huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n",
"To disable this warning, you can either:\n",
"\t- Avoid using `tokenizers` before the fork if possible\n",
"\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n",
"2024-03-12 08:46:25,241 - BERTopic - Cluster - Completed ✓\n",
"2024-03-12 08:46:25,242 - BERTopic - Representation - Extracting topics from clusters using representation models.\n",
"2024-03-12 08:47:25,876 - BERTopic - Representation - Completed ✓\n",
"2024-03-12 08:47:25,952 - BERTopic - Topic reduction - Reducing number of topics\n",
"2024-03-12 08:48:28,300 - BERTopic - Topic reduction - Reduced number of topics from 435 to 342\n"
]
}
],
"source": [
"\n",
"model_path=\"data/topic_model.bin\"\n",
"topic_model = BERTopic(language=\"japanese\", calculate_probabilities=True, verbose=True, nr_topics=\"20\")\n",
"topics, probs = topic_model.fit_transform(docs)\n",
"\n",
"\n",
"#topic_model=BERTopic.load(model_path)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"2024-03-12 08:48:42,599 - BERTopic - WARNING: When you use `pickle` to save/load a BERTopic model,please make sure that the environments in which you saveand load the model are **exactly** the same. The version of BERTopic,its dependencies, and python need to remain the same.\n",
"/home/user/miniconda3/envs/ft/lib/python3.11/site-packages/scipy/sparse/_index.py:143: SparseEfficiencyWarning: Changing the sparsity structure of a csr_matrix is expensive. lil_matrix is more efficient.\n",
" self._set_arrayXarray(i, j, x)\n"
]
}
],
"source": [
"topic_model.save(model_path)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
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" <td>[it's ok with me 意味\\t9\\n英語で「It's okay.（イッツオーケー...</td>\n",
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" <td>[スピリチュアルカウンセリングは、魂の向上を目的とした、至高神からのヒーリングで魂を整えて頂...</td>\n",
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" <td>[オアフ島（ホノルル） 福岡発 ◎今だけ無料で海の見える部屋へアップグレード！◎シェラトン・...</td>\n",
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" <td>[冊子の「契約内容のお知らせ」ページをめくると、登録情報の変更シートがあります。\\n, 今回...</td>\n",
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" <td>[ S8 PlusとS9 Plus - bajatyoutube.com\\n2019/0...</td>\n",
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" Topic Count Name \\\n",
"0 -1 22559 -1_the_and_to_of \n",
"1 0 1585 0_送料無料_サマータイヤ_代引不可_中古 \n",
"2 1 1209 1_としあき_無念_name_投稿日 \n",
"3 2 801 2_ワンピース_5cm_レディース_着丈 \n",
"4 3 799 3_ベンジャミン_フランクリン_passion_thee \n",
".. ... ... ... \n",
"337 336 11 336_abuse_you_counselling_emotional \n",
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"\n",
" Representation \\\n",
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"1 [送料無料, サマータイヤ, 代引不可, 中古, ブラック, diy, レディース, 工具,... \n",
"2 [としあき, 無念, name, 投稿日, id, 16, 名前, 柳宗理, no, 11] \n",
"3 [ワンピース, 5cm, レディース, 着丈, 肩幅, 素材, 格安通販, シューズ, 袖丈... \n",
"4 [ベンジャミン, フランクリン, passion, thee, nベンジャミン, 全業種, ... \n",
".. ... \n",
"337 [abuse, you, counselling, emotional, addiction... \n",
"338 [京都の道, snorkeling, その１, 中の池, k7, silfra, 今だけ特別... \n",
"339 [実印, いつ使う, 件のレビュー例えば, いつ使うは, しっかりした会社, 印鑑, 実印の... \n",
"340 [galaxy, s7, samsung, edge, i9195i, s8, 3i9200... \n",
"341 [ﾟдﾟ, 対価, 労働, 産業別組合, 工会, 約款, union, 契約書, 規約, 労... \n",
"\n",
" Representative_Docs \n",
"0 [Створення сайту - Сторінка 419 - Форум\\nЧетве... \n",
"1 [上品なスタイル 【5/1(土)クーポン&ワンダフルデー 4本1台分!!】 215/45R1... \n",
"2 [ハニーセレクト日曜昼の部テンプレセット髪型全然使ってなかったけど - ふたろぐばこ−二次元... \n",
"3 [非売品 入学式 セレモニー 秋冬 秋 他と被らない 冬 小さいサイズ スカート セット 卒... \n",
"4 [it's ok with me 意味\\t9\\n英語で「It's okay.（イッツオーケー... \n",
".. ... \n",
"337 [スピリチュアルカウンセリングは、魂の向上を目的とした、至高神からのヒーリングで魂を整えて頂... \n",
"338 [オアフ島（ホノルル） 福岡発 ◎今だけ無料で海の見える部屋へアップグレード！◎シェラトン・... \n",
"339 [冊子の「契約内容のお知らせ」ページをめくると、登録情報の変更シートがあります。\\n, 今回... \n",
"340 [ S8 PlusとS9 Plus - bajatyoutube.com\\n2019/0... \n",
"341 [ただし、中小企業の事業主等、労働者以外でも業務の実態や災害の発生状況からみて、労働者に準じ... \n",
"\n",
"[342 rows x 5 columns]"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"topic_model.get_topic_info()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
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